Objective To gain insights into the biological characteristics of different populations of Culex tritaeniorhynchus within and around the Yellow Sea wetland from the perspective of the occurrence of resistance, we investigated the levels of resistance to deltamethrin and kdr gene mutation in the wetland and its peripheral areas. Methods Specimens were collected from Cx. tritaeniorhynchus populations at two monitoring sites in the Rare Bird National Nature Reserve and Tiaozi Ni Wetland Scenic Area, and also from two populations in Yancheng City and the Liuhe District of Nanjing, and the resistance of these mosquitoes to deltamethrin was determined using the CDC biotest bottle method. For each concentration of deltamethrin assessed, a random subset of exposed specimens was selected for amplification of the kdr gene fragment, followed by Sanger sequencing to identify and analyze resistance-associated mutations. Results The LC50 levels of deltamethrin among mosquitoes from the four populations in Luhe, Yancheng, the Rare Bird National Nature Reserve and the Tiaozi Ni Wetland Scenic Area were 2.048 5, 7.798 2, 3.473 3, and 17.695 5 mg/mL, respectively, with corresponding concentrations of deltamethrin ranging from 0.005 to 5.000,0.050 to 50.000,0.050 to 25.000 and 0.050 to 50.000 mg/mL, respectively. Furthermore, the ranges of the KT50 values were 11.76-107.43, 67.05-216.30,29.77-107.43 and 28.40-329.51 min; the 1-h knockdown rates were 34.58%-99.15%, 9.52%-43.80%, 55.09%-73.01%, and 10.09%-68.07%; and the 24-h mortality rates were 12.15%-67.52%,9.52%-79.56%,13.17%-82.21%, and 11.01%-78.99%, respectively. With respect to kdr gene mutation, we assayed a total of 63,70,59, and 57 mosquitoes for the four populations, for which we detected L1014F mutation frequencies of 14.29%, 35.00%, 20.34%, and 31.58%, respectively, with a majority of these mutations being heterozygous for resistance. In addition, five adult mosquitoes were identified has having synonymous mutations at site 1011[i. e. , AAT(asparagine)mutation to AAC(asparagine)]. Conclusions Our findings revealed the clear resistance of Cx. tritaeniorhynchus to deltamethrin in the Yancheng region of the Yellow Sea wetland, and the resistance phenotype and kdr frequency of Cx. tritaeniorhynchus in the wetland environment were comparable to those of Cx. tritaeniorhynchus in the wetland environment, thereby indicating that the resistance of different populations of Cx. tritaeniorhynchus was homogeneous under the pressure of different insecticide selection within and around the wetland. However, the underlying mechanisms need to be further studied.

Exercise-induced muscle damage (EIMD) is a frequent form of skeletal muscle microdamage that occurs after high-intensity, prolonged, or unaccustomed exercise, especially exercise dominated by eccentric contractions. It is commonly characterized by delayed-onset muscle soreness, transient loss of muscle strength, local inflammation, structural disruption of myofibers, and delayed functional recovery. Although mild EIMD may serve as a stimulus for training adaptation, excessive or insufficiently recovered muscle damage can impair exercise performance, disturb training continuity, and reduce participation in physical activity. Therefore, clarifying the molecular mechanisms that underlie the initiation, amplification, and resolution of EIMD is important for optimizing athletic training, improving post-exercise recovery, and guiding evidence-based public fitness practice. Necroptosis is a regulated form of programmed cell death mediated primarily by the receptor-interacting protein kinase (RIPK) 1/RIPK3/mixed lineage kinase domain-like protein (MLKL) signaling axis. Recent studies have shown that necroptosis is closely involved in tissue injury, sterile inflammation, and repair remodeling. However, whether necroptosis acts as an initiating driver, a secondary damage amplifier, or an adaptive signal required for repair after EIMD remains unclear. This review aimed to summarize the potential role of necroptosis in EIMD and to establish a mechanistic framework linking regulated cell death, inflammatory amplification, immune regulation, and skeletal muscle repair. Relevant studies concerning EIMD, necroptosis, RIPK1/RIPK3/MLKL signaling, damage-associated molecular patterns (DAMPs), inflammatory responses, immune cell recruitment, extracellular matrix remodeling, and muscle regeneration were reviewed and integrated. On this basis, the possible temporal and functional involvement of necroptosis in different phases of EIMD was analyzed. The main evidence summarized in this review suggests that EIMD is not merely a consequence of primary mechanical disruption. Instead, it develops through a dynamic sequence that includes sarcolemmal instability, calcium overload, mitochondrial dysfunction, oxidative stress, inflammatory mediator production, immune cell infiltration, necrotic tissue clearance, and regeneration-associated remodeling. Necroptosis may participate in this process through at least two interconnected mechanisms. First, in the early or progressive phase of EIMD, activation of the RIPK1/RIPK3/MLKL signaling axis may promote MLKL phosphorylation and plasma membrane permeabilization, leading to the release of DAMPs such as high-mobility group box 1, ATP, mitochondrial DNA, and other intracellular components. These signals may activate innate immune pathways, amplify inflammatory cytokine production, and enhance the recruitment of neutrophils and macrophages, thereby aggravating secondary inflammation and extending muscle fiber injury. Second, during the resolution and repair phases, necroptosis-related signaling may also contribute indirectly to the formation of a regenerative microenvironment. By influencing the clearance of necrotic debris, the recruitment and phenotypic transition of immune cells, and the remodeling of extracellular matrix components, necroptosis may affect satellite cell activation, myogenic repair, and the eventual structural and functional recovery of injured skeletal muscle. Thus, the biological effect of necroptosis in EIMD may be context dependent rather than uniformly harmful. Its outcome may depend on exercise intensity, the extent of tissue damage, the timing of pathway activation, the involved cell types, inflammatory status, training background, age, and metabolic condition. In conclusion, necroptosis may represent an important molecular link between skeletal muscle injury, sterile inflammation, and tissue repair after damaging exercise. It may exert a dual role in EIMD by amplifying secondary damage while also contributing to repair coordination under appropriate temporal and microenvironmental conditions. Future studies should determine the activation pattern of RIPK1/RIPK3/MLKL signaling after different exercise protocols, identify the major cell populations undergoing necroptosis in injured skeletal muscle, and examine whether targeted modulation of necroptosis can reduce excessive inflammation without impairing necessary regenerative responses. This review provides a theoretical basis for understanding the pathogenesis of EIMD and for developing targeted strategies to improve skeletal muscle recovery after exercise-induced injury.

Electroencephalography (EEG) is a non-invasive neurophysiological monitoring technique. It records the electrical activity of the cerebral cortex using electrodes placed on the scalp surface. Owing to its high safety, portability, and millisecond-level temporal resolution, EEG has been widely utilized in a variety of fields, including clinical diagnosis, brain-computer interfaces (BCIs), and cognitive neuroscience research. However, due to its microvolt-level amplitude, EEG is highly susceptible to various artifacts, including electrooculographic (EOG), electrocardiographic (ECG), electromyographic (EMG), and power line interference (PLI). These artifacts can obscure genuine neural activity and introduce spurious electrophysiological features. Consequently, they may compromise EEG signal quality, thereby reducing the reliability of downstream analyses. To address this issue, numerous EEG artifact removal methods have been developed, including both traditional denoising techniques and deep learning-based approaches. Traditional EEG denoising methods have long served as the primary solutions for artifact removal. Representative approaches include filtering, regression, and blind source separation. Although these methods have demonstrated effectiveness in specific scenarios, they suffer from several inherent limitations. Filtering assumes that artifacts and EEG signals can be separated in the frequency domain, but many artifacts, such as EOG and EMG, overlap with EEG spectra, which may lead to the loss of valuable neural information. Regression methods require high-quality artifact references to estimate and subtract contaminations, limiting their effectiveness in reference-free scenarios. Blind source separation can remove artifacts without external references, but it typically requires the number of EEG channels to exceed the number of sources, restricting its application in single- or low-channel EEG recordings. Deep learning-based EEG denoising methods address these limitations effectively. First, they learn the nonlinear mapping between contaminated and clean EEG directly from data in an end-to-end manner. This approach does not rely on assumptions about spectral separability, thereby preserving neural activity more completely. Second, the reference information is incorporated during the training phase, allowing the trained model to perform artifact removal independently without external references. Third, deep learning models can be flexibly designed to accommodate various recording setups, achieving robust denoising for both high-density and single-channel EEG. Collectively, these advantages enable deep learning-based methods to overcome the main challenges of traditional approaches, providing more accurate and reliable EEG signal recovery. The superior denoising performance of deep learning-based EEG denoising methods has attracted increasing attention in EEG artifact removal research. As a result, many deep learning-based denoising methods have been developed and successfully applied in neural engineering areas. However, a systematic review of the techniques and applications in this field is still lacking. To address this gap, this paper reviews recent advances in deep learning-based EEG denoising from four perspectives: technical principle, benchmark dataset, denoising model, and evaluation method. Representative applications in neural signal analysis and BCI decoding are also summarized. Furthermore, the advantage, existing challenge, and future research direction of deep learning-based EEG denoising are discussed. This review aims to provide valuable theoretical insights and technical guidance for researchers. It is also expected to promote further advances and broader applications of deep learning-based EEG denoising techniques.

Consciousness, which underpins human perception, cognition, and behavioural responses, has long been a major focus of neuroscience and medicine. Alterations in consciousness occur not only during reversible processes such as sleep and anaesthesia, but also in pathological conditions, including disorders of consciousness (DOC) and brain injury. With recent advances in the synchronized acquisition and analysis of multimodal physiological signals, such as electroencephalography (EEG) and electrocardiography (ECG), the dynamic interactions between the heart and brain have become increasingly apparent. A growing body of evidence indicates that heart-brain interactions are closely associated with the maintenance and transition of consciousness states, offering a novel perspective for elucidating their underlying mechanisms and supporting relevant clinical assessments. Current approaches to heart-brain interaction analysis for consciousness-state assessment can be broadly grouped into three categories: ECG-based methods, EEG-based methods, and heart-brain coupling analysis. These approaches characterize heart-brain interactions during changes in consciousness from the complementary perspectives of autonomic regulation, cortical interoceptive processing, and cross-system information transfer, respectively. Nevertheless, this field remains at an early stage. Most studies have focused on a single experimental context or a fixed analytical method, with insufficient systematic consideration of the applicability and limitations of different approaches. Moreover, the mechanisms underlying the emergence and alteration of consciousness remain incompletely understood. Accordingly, this review examines heart-brain interaction methods employed in recent consciousness-state assessment studies in accordance with progressively deeper analytical perspectives, and systematically evaluates the advantages and limitations of these methods across distinct consciousness-related conditions. Heart rate variability (HRV) is one of the classical ECG-based indices used to investigate heart-brain interactions. It refers to fluctuations in consecutive interbeat intervals over a specified time period and is regarded as a physiological measure of autonomic nervous system regulation that may indirectly reflect the strength of heart-brain interactions. Depending on the analytical dimension, HRV analysis is commonly divided into time-domain, frequency-domain, and complexity-index analyses. These approaches characterize autonomic activity in terms of temporal fluctuations, the distribution of frequency components, and nonlinear dynamical properties, respectively. Although extensive research supports their physiological interpretation, they cannot characterize directional interactions from the heart to the brain. Among EEG-based methods for heart-brain interaction analysis, EEG activity directly related to cardiac fluctuations has received particular attention. One of the most widely used measures is the heartbeat-evoked potential (HEP). HEP-based approaches are considered to directly reflect the capacity of the cerebral cortex to process cardiac afferent signals and may be especially advantageous for characterizing rapidly changing consciousness levels, such as those observed during sleep. However, they do not comprehensively capture dynamic bidirectional information exchange between the brain and heart and are susceptible to cardiac artefacts, respiration, and variation in preprocessing procedures. Heart-brain coupling analysis quantifies functional associations between ECG and EEG through cross-system interaction measures, thereby assessing dynamic interactions between the heart and brain. It emphasizes information transfer, feedback regulation, and cross-timescale coordination between the two systems, offering a more comprehensive perspective for investigating changes in consciousness during sleep, anaesthesia, and DOC. However, the neurophysiological mechanisms and physiological interpretation of individual computational indices have not yet been fully established, and the robustness of their results and their potential for clinical generalization require further validation. Finally, this review summarizes the commonalities and differences among the three classes of methods across research domains involving different consciousness states. It further argues that heart-brain interaction research requires deeper investigation at both the mechanistic level of consciousness and the level of clinical application. Current challenges and key issues are identified, and future directions and feasible pathways for heart-brain interaction research are discussed, with the aim of providing new perspectives for researchers in related fields.

ObjectiveChemotherapy is one of the important therapeutic approaches for cancer treatment. However, the emergence of multidrug resistance and side effects significantly limit its application. To address these challenges, chemotherapy is often combined with other drugs or therapies. Among the 13 human fucosyltransferases (FUTs) identified, FUT8 (alpha-(1,6)-fucosyltransferase) is the only enzyme responsible for core fucosylation. Core fucosylation plays an important role in cancer occurrence, metastasis and chemotherapy resistance, making the suppression of FUT8 a potential strategy for reversing multidrug resistance. This study aims to evaluate the feasibility of combining the small molecule FUT8 inhibitor 2FF (2-deoxy-2-fluoro-L-fucose) with the clinical chemotherapeutic drug doxorubicin (DOX) for treating malignant tumors. MethodsThe human hepatocellular carcinoma cell line HepG2 and mouse colon cancer cell line CT26 cells were treated with 2FF, DOX or their combination and core fucosylation levels were assessed using Lectin blot. HepG2 and CT26 cells were exposed to 50 μmol/L 2FF for 72 h, followed by treatment with a gradient concentration of DOX for 24 h. Cell viability and IC₅₀ values were determined via the CCK-8 assay. Transwell invasion assays were conducted to evaluate the combined effect of 2FF and DOX on the invasion ability of HepG2 cells. Flow cytometry was performed to analyze the impact of 2FF, DOX and their combination on membrane PD-L1 expression of HepG2 cells. To assess the in vivo effect, 6- to 8-week-old female BALB/c mice (20-25 g), were subcutaneously injected with 1×10⁶ CT26 cells into the right axilla (four groups, six mice in each group). After the average tumor volume reached 100 mm³, mice were treated with DOX, 2FF, their combination, or saline (mock group) every other day. DOX was administrated intraperitoneally (2 mg/kg), 2FF intravenously (5 mg/kg), and the combination group, received the both treatment. Tumor size was measured every other day using a vernier caliper. ResultsThis study demonstrated that DOX upregulates the core fucosylation levels in HepG2 and CT26 cells,while 2FF effectively inhibits this DOX-induced effect. Furthermone, 2FF enhanced the sensitivity of HepG2 and CT26 cells to DOX. The combination of 2FF and DOX synergistically inhibited the invasion ability of HepG2 cells, and enhanced the anti-tumor efficacy of CT26 subcutaneous tumor model in BALB/c mice. However the combination treatment led to weight loss in mice. In addition, DOX increased the cell surface PD-L1 expression in HepG2 cells, which was effectively suppressed by 2FF. ConclusionThe FUT8 inhibitor 2FF effectively suppresses DOX-induced upregulation of core fucosylation and PD-L1 levels in tumor cells, and 2FF synergistically enhances the anticancer efficacy of DOX.

OBJECTIVE To investigate the effects of ertugliflozin on pharmacokinetic of sorafenib and donafenib in rats and explore the mechanism. METHODS Twenty-four male SD rats were randomly divided into four groups， with 6 rats in each group. Groups A and B were respectively gavaged with 0.5% sodium carboxymethyl cellulose solution and ertugliflozin （1.5 mg/kg） for 7 consecutive days， and both were given sorafenib （100 mg/kg） on the 7th day. Groups C and D were administered intragastrically in the same way as those in Groups A and B， respectively， for the first 7 days； after the drug administration on the 7th day， all rats in Groups C and D were further gavaged with donafenib （40 mg/kg）. Blood samples were collected at different time points before and after administration of sorafenib or donafenib， the concentrations of sorafenib in plasma of rats in groups A and B and donafenib in groups C and D were determined by UPLC-MS/MS method. The pharmacokinetic parameters were calculated by DAS 2.1.1 software. Six additional rats were randomly divided into blank control group and ertugliflozin group， with three rats in each group. Blank control group was given 0.5% sodium carboxymethyl cellulose intragastrically， while rats in ertugliflozin group were given ertugliflozin （1.5 mg/kg） once a day for 7 consecutive days. After the last administration， the mRNA expression levels of uridine diphosphate glucuronosyl transferase 1A7 （UGT1A7）， breast cancer resistance protein （BCRP）， and P-glycoprotein （P-gp） in the liver and small intestine tissues of the rats were detected. RESULTS Compared with group A， the AUC0-t， AUC0-∞， cmax， tmax， MRT0-t and MRT0-∞ of sorafenib in group B were decreased significantly， while CL and V were increased significantly. Compared with group C， the AUC0-t， AUC0-∞ ， tmax， cmax and MRT0-t of Δ donafenib in group D were decreased significantly， while V and CL were increased significantly （P＜0.05）. mRNA expression of UGT1A7， P-gp and BCRP in the liver tissue and small intestine of rats were not significantly affected after intragastric administration of ertugliflozin for 7 consecutive days. CONCLUSIONS Ertugliflozin can affect the pharmacokinetics of sorafenib and donafenib in rats and decrease the plasma exposure of them significantly. However， its mechanism of action may not be through the regulation of related metabolic enzymes and transporters. When using drugs in combination clinically， one should be vigilant about the potential for disease progression due to poor therapeutic effects.

Objective: Huntington’s disease (HD) is characterized by motor, cognitive, and neuropsychiatric symptoms. Oculomotor impairments and gait variability have been independently considered as potential markers in HD. However, an integrated analysis of eye movement and gait is lacking. We performed multiple examinations of eye movement and gait variability in HTT mutation carriers, analyzed the consistency between these parameters and clinical severity, and then examined the associations between oculomotor impairments and gait deficits. Methods: We included 7 patients with pre-HD, 30 patients with HD and 30 age-matched controls. We collected demographic data and assessed the Unified Huntington’s Disease Rating Scale (UHDRS) score. Examinations, including saccades, smooth pursuit tests, and optokinetic (OPK) tests, were performed to evaluate eye movement function. The parameters of gait include stride length, walking velocity, step deviation, step length, and gait phase. Results: HD patients have significant impairments in the latency and velocity of saccades, the gain of smooth pursuit, and the gain and slow phase velocities of OPK tests. Only the speed of saccades significantly differed between pre-HD patients and controls. There are significant impairments in stride length, walking velocity, step length, and gait phase in HD patients. The parameters of eye movement and gait variability in HD patients were consistent with the UHDRS scores. There were significant correlations between eye movement and gait parameters. Conclusion Our results show that eye movement and gait are impaired in HD patients and that the speed of saccades is impaired early in pre-HD. Eye movement and gait abnormalities in HD patients are significantly correlated with clinical disease severity.

Objective: Huntington’s disease (HD) is characterized by motor, cognitive, and neuropsychiatric symptoms. Oculomotor impairments and gait variability have been independently considered as potential markers in HD. However, an integrated analysis of eye movement and gait is lacking. We performed multiple examinations of eye movement and gait variability in HTT mutation carriers, analyzed the consistency between these parameters and clinical severity, and then examined the associations between oculomotor impairments and gait deficits. Methods: We included 7 patients with pre-HD, 30 patients with HD and 30 age-matched controls. We collected demographic data and assessed the Unified Huntington’s Disease Rating Scale (UHDRS) score. Examinations, including saccades, smooth pursuit tests, and optokinetic (OPK) tests, were performed to evaluate eye movement function. The parameters of gait include stride length, walking velocity, step deviation, step length, and gait phase. Results: HD patients have significant impairments in the latency and velocity of saccades, the gain of smooth pursuit, and the gain and slow phase velocities of OPK tests. Only the speed of saccades significantly differed between pre-HD patients and controls. There are significant impairments in stride length, walking velocity, step length, and gait phase in HD patients. The parameters of eye movement and gait variability in HD patients were consistent with the UHDRS scores. There were significant correlations between eye movement and gait parameters. Conclusion Our results show that eye movement and gait are impaired in HD patients and that the speed of saccades is impaired early in pre-HD. Eye movement and gait abnormalities in HD patients are significantly correlated with clinical disease severity.

ObjectiveThe proteome of biological evidence contains rich genetic information, namely single amino acid polymorphisms (SAPs) in protein sequences. However, due to the lack of efficient and convenient analysis tools, the application of SAP in public security still faces many challenges. This paper aims to meet the application requirements of SAP analysis for forensic biological evidence’s proteome data. MethodsThe software is divided into three modules. First, based on a built-in database of common non-synonymous single nucleotide polymorphisms (nsSNPs) and SAPs in East Asian populations, the software integrates and annotates newly identified exonic nsSNPs as SAPs, thereby constructing a customized SAP protein sequence database. It then utilizes a pre-installed search engine—either pFind or MaxQuant—to perform analysis and output SAP typing results, identifying both reference and variant types, along with their corresponding imputed nsSNPs. Finally, SAPTyper compares the proteome-based typing results with the individual’s exome-derived nsSNP profile and outputs the comparison report. ResultsSAPTyper accepts proteomic DDA mass spectrometry raw data (DDA acquisition mode) and exome sequencing results of nsSNPs as input and outputs the report of SAPs result. The pFind and Maxquant search engines were used to test the proteome data of 2 hair shafts of2 individuals, and both obtained SAP results. It was found that the results of the Maxquant search engine were slightly less than those of pFind. This result shows that SAPTyper can achieve SAP fingding function. Moreover, the pFind search engine was used to test the proteome data of 3 hair shafts from 1 European person and 1 African person in the literature. Among the sites fully matched by the literature method, sites detected by SAPTyper are also included; for semi-matching sites, that is, nsSNPs are heterozygous, both literature method and SAPTyper method had the risk of missing detection for one type of the allele. Comparing the analysis results of SAPTyper with the SAP test results reported in the literature, it was found that some imputed nsSNP sites identified by the literature method but not detected by SAPTyper had a MAF of less than 0.1% in East Asian populations, and therefore they were not included in the common nsSNP database of East Asian populations constructed by this software. Since the database construction of this software is based on the genetic variation information of East Asian populations, it is currently unable to effectively identify representative unique common variation sites in European or African populations, but it can still identify SAP sites shared by these populations and East Asian populations. ConclusionAn automated SAP analysis algorithm was developed for East Asian populations, and the software named SAPTyper was developed. This software provides a convenient and efficient analysis tool for the research and application of forensic proteomic SAP and has important application prospects in individual identification and phenotypic inference based on SAP.

Objective: Huntington’s disease (HD) is characterized by motor, cognitive, and neuropsychiatric symptoms. Oculomotor impairments and gait variability have been independently considered as potential markers in HD. However, an integrated analysis of eye movement and gait is lacking. We performed multiple examinations of eye movement and gait variability in HTT mutation carriers, analyzed the consistency between these parameters and clinical severity, and then examined the associations between oculomotor impairments and gait deficits. Methods: We included 7 patients with pre-HD, 30 patients with HD and 30 age-matched controls. We collected demographic data and assessed the Unified Huntington’s Disease Rating Scale (UHDRS) score. Examinations, including saccades, smooth pursuit tests, and optokinetic (OPK) tests, were performed to evaluate eye movement function. The parameters of gait include stride length, walking velocity, step deviation, step length, and gait phase. Results: HD patients have significant impairments in the latency and velocity of saccades, the gain of smooth pursuit, and the gain and slow phase velocities of OPK tests. Only the speed of saccades significantly differed between pre-HD patients and controls. There are significant impairments in stride length, walking velocity, step length, and gait phase in HD patients. The parameters of eye movement and gait variability in HD patients were consistent with the UHDRS scores. There were significant correlations between eye movement and gait parameters. Conclusion Our results show that eye movement and gait are impaired in HD patients and that the speed of saccades is impaired early in pre-HD. Eye movement and gait abnormalities in HD patients are significantly correlated with clinical disease severity.