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.

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.

This study aims to systematically characterize the targeted effects of Quanduzhong Capsules on cartilage lesions in knee osteoarthritis by integrating spatial transcriptomics data mining and animal experiments validation, thereby elucidating the related molecular mechanisms. A knee osteoarthritis model was established using Sprague-Dawley(SD) rats, via a modified Hulth method. Hematoxylin and eosin(HE) staining was employed to detect knee osteoarthritis-associated pathological changes in knee cartilage. Candidate targets of Quanduzhong Capsules were collected from the HIT 2.0 database, followed by bioinformatics analysis of spatial transcriptomics datasets(GSE254844) from cartilage tissues in clinical knee osteoarthritis patients to identify spatially specific disease genes. Furthermore, a "formula candidate targets-spatially specific genes in cartilage lesions" interaction network was constructed to explore the effects and major mechanisms of Quanduzhong Capsules in distinct cartilage regions. Experimental validation was conducted through immunohistochemistry using animal-derived biospecimens. The results indicated that Quanduzhong Capsules effectively inhibited the degenerative changes in the cartilage of affected joints in rats, which was associated with the regulation of Quanduzhong Capsules on the thioredoxin-interacting protein(TXNIP)-NOD-like receptor family pyrin domain containing 3(NLRP3)-bone morphogenetic protein receptor type 2(BMPR2)-fibronectin 1(FN1)-matrix metallopeptidase 2(MMP2) signal axis in the articular cartilage surface and superficial zones, subsequently inhibiting cartilage matrix degradation leading to oxidative stress and inflammatory diffusion. In summary, this study clarifies the spatially specific targeted effects and protective mechanisms of Quanduzhong Capsules within pathological cartilage regions in knee osteoarthritis, providing theoretical and experimental support for the clinical application of this drug in the targeted therapy on the inflamed cartilage.
Animals ; Osteoarthritis, Knee/metabolism* ; Drugs, Chinese Herbal/administration & dosage* ; Rats, Sprague-Dawley ; Rats ; Male ; Humans ; Capsules ; Female ; Disease Models, Animal

Based on latent structure model and association rule analysis, this study investigates the prescription patterns used by professor YANG Zhong-qi in treating hypertension with traditional Chinese medicine(TCM) and infers the associated TCM syndromes, providing a reference for clinical syndrome differentiation and treatment. The observation window spanned from January 8, 2013, to June 26, 2024, during which qualified herbal decoction prescriptions meeting efficacy criteria were extracted from the outpatient medical record system of the First Affiliated Hospital of Guangzhou University of Chinese Medicine and compiled into a standardized database. Statistical analysis of high-frequency herbs included frequency counts and herbal property-channel tropism analysis. Latent structure modeling and association rule analysis were performed using R 4.3.2 and Lantern 5.0 software to identify core herbal combinations and infer TCM syndrome patterns. A total of 2 436 TCM prescriptions were included in the study, involving 263 drugs with a cumulative frequency of 29 783. High-frequency herbs comprised Uncariae Ramulus cum Uncis, Poria, Glycyrrhizae Radix et Rhizoma, Puerariae Lobatae Radix, and Alismatis Rhizoma, predominantly categorized as deficiency-tonifying, heat-clearing, and blood-activating and stasis-resolving herbs. Latent structure analysis identified 18 latent variables, 74 latent classes, 5 comprehensive clustering models, and 15 core herbal combinations, suggesting that the core syndrome clusters include liver Yang hyperactivity pattern, Yin deficiency with Yang hyperactivity pattern, phlegm-stasis intermingling pattern, and liver-kidney insufficiency pattern. Association rule analysis revealed 22 robust association rules. RESULTS:: indicate that hypertension manifests as a deficiency-rooted excess manifestation, significantly associated with functional dysregulation of the liver, lung, spleen-stomach, heart, and kidney. Key pathogenic mechanisms involve liver Yang hyperactivity, phlegm-stasis interaction, and liver-kidney insufficiency. Therapeutic strategies should prioritize liver-calming, spleen-fortifying, and deficiency-tonifying principles, supplemented by dynamic regulation of Qi-blood and Yin-Yang balance according to syndrome evolution, alongside pathogen-eliminating methods such as phlegm-resolving and stasis-dispelling. Synergistic interventions like mind-tranquilizing therapies should be tailored to individual conditions.
Hypertension/drug therapy* ; Drugs, Chinese Herbal/therapeutic use* ; Humans ; Medicine, Chinese Traditional ; Drug Prescriptions ; Latent Class Analysis

Since the promulgation of the first Drug Administration Law of the People's Republic of China 40 years ago in 1984, China has undergone four main stages in the traditional Chinese medicine(TCM) regulation: the initial establishment of TCM regulation rules(1984-1997), the formation of a modern TCM regulatory system(1998-2014), the reform of the review and approval system for new TCM drugs(2015-2018), and the construction of a scientific regulation system for TCM(2019-2024). Over the past five years, a series of milestone achievements of TCM regulation in China have been achieved in the six aspects, including its strategic objectives and the establishment of a science-based regulatory system, the reform of the review and approval system for new TCM drugs, the optimization and improvement of the TCM standard system and its formation mechanism, comprehensive enhancement of regulatory capabilities for TCM safety, international harmonization of TCM regulation and its role in promoting innovation. Looking ahead, centered on advancing TCMRS to establish a sound regulatory framework tailored to the unique characteristics of TCM, TCM regulation will evolve into new reform patterns, advancing and extending across eight critical fronts, including the legal framework and policy architecture, the review and approval system for new TCM drugs, the quality standard and management system of TCM, the comprehensive quality & safety regulation and traceability system, the research and transformation system for TCMRS, AI-driven innovations in TCM regulation, the coordination between high-quality industrial development and high-level regulation, and the leadership in international cooperation and regulatory harmonization. In this way, a unique path for the development of modern TCM regulation with Chinese characteristics will be pioneered.
Humans ; China ; Drugs, Chinese Herbal/standards* ; History, 20th Century ; History, 21st Century ; Medicine, Chinese Traditional/trends*

To improve the quality evaluation system of Hibisci Mutabilis Folium, this study established high performance liquid chromatography(HPLC) fingerprints of Hibisci Mutabilis Folium and evaluated the quality differences of medicinal materials from different places of production by chemometrics. Furthermore, a content measurement method of differential components was established based on quantitative analysis of multi-components by single-marker(QAMS). The fingerprints of 17 batches of Hibisci Mutabilis Folium from different places of production were constructed, with a total of 19 common peaks marked and seven components confirmed. The similarity between the sample fingerprints and the reference fingerprints ranged from 0.890 to 0.974. By utilizing principal component analysis(PCA), hierarchical cluster analysis(HCA), and orthogonal partial least squares-discriminant analysis(OPLS-DA), the chemical patterns of fingerprints were identified. Five components that could be used to evaluate the quality differences of Hibisci Mutabilis Folium were screened, namely peak 6(quercetin 3-O-β-robinobioside), peak 7(rutin), peak 9(kaempferol-3-O-β-robinobioside), peak 10(kaempferol-3-O-rutinoside), and peak 14(tiliroside). The relative correction factors of isoquercitrin, kaempferol-3-O-β-robinobioside, kaempferol-3-O-rutinoside, kaempferol-3-O-β-D-glucoside, and tiliroside were measured with rutin as the internal reference. The QAMS method was established for the content measurement of six flavonoids, and the results showed there was no significant difference compared to the results obtained by an external standard method. In summary, the HPLC fingerprints and QAMS method established in the study, demonstrating stability and accuracy, can provide a reference for the overall quality evaluation of Hibisci Mutabilis Folium.
Chromatography, High Pressure Liquid/methods* ; Drugs, Chinese Herbal/chemistry* ; Quality Control ; Principal Component Analysis

OBJECTIVE: To explore clinical effect of autologous osteochondral transplantation (AOT) in the treatment of recurrent anterior dislocation of the shoulder joint with glenoid cartilage defect in rabbits by establishing a model of recurrent anterior dislocation of the shoulder joint with < 20% glenoid cartilage defect in rabbits. METHODS: Twenty-four male New Zealand white rabbits, aged 6-month-old, weighed (2.69±0.17) kg were selected. The labrum of shoulder joint of rabbits was artificially destroyed to establish a model of recurrent anterior dislocation of shoulder joint with cartilage defect. They were divided into AOT surgery group and simple suture group, with 12 rabbits in each group. AOT group were underwent AOT surgery, while simple suture group was treated with simple Bankart suture for recurrent shoulder joint dislocation. At 6 and 12 weeks after operation, 6 rabbits between two groups were sacrificed for sampling. The dietary conditions, activity conditions, mental states of rabbits and healing conditions of grafts in the specimens were observed and compared between two groups. HE staining was used to observe cell creep, cell morphology, inflammatory cell infiltration, fibrochondrocytes and their arrangement. Masson staining was used to observe the formation and arrangement of collagen fibers; Safrane-green staining was used to observe the regeneration of articular cartilage, subchondral bone and bone tissue. Bone mineral density (BMD), bone volume (BV) and trabecular thickness (Tb.Th) between two groups were measured by Micro-CT to evaluate the remodeling of shoulder glenoid bone defects by autologous osteochondral cartilage. RESULTS: After different surgical interventions were carried out in both groups of rabbits, at 6 weeks after the operation, the abduction, extension, internal rotation and external rotation of the shoulder joint on the operated side showed limited range of motion compared with the contralateral side, while adduction and forward flexion showed no obvious abnormalities compared with the contralateral side. At 12 weeks after operation, the range motion of tshoulder joints in both groups of rabbits had returned to the state before modeling. The effects of HE staining, Masson staining and safrane-green staining at 12 weeks after operation in both groups were stronger than the staining results at 6 weeks after operation. Moreover, the results of HE staining, Masson staining and safranin fixation green staining in AOT group at 6 and 12 weeks after operation were all higher than those in simple suture group. Micro-CT scan results at 6 and 12 weeks after operation showed that BMD (0.427±0.014), (0.466±0.032) g·cm-3, BV(116.171±3.527), (159.327±3.500) mm3, and Tb.Th (0.230±0.006), (0.285±0.009) mm in AOT group, which were higher than those of simple suture group in BMD(0.358±0.011), (0.384±0.096) g·cm-3, BV(72.657±3.903), (118.713±3.860) mm3, and Tb.Th(0.204±0.009), (0.243±0.007) mm;and the differences were statistically significant (P<0.05). CONCLUSION AOT procedure could effectively promote osteogenesis and fibrocartilage regeneration in the cartilage defect area of the shoulder glenoid <20%, which is conducive to reshaping the structure of the shoulder glenoid.
Animals ; Rabbits ; Male ; Transplantation, Autologous ; Cartilage, Articular/injuries* ; Shoulder Dislocation/physiopathology* ; Bone Transplantation ; Shoulder Joint/surgery*

Primary ciliary dyskinesia (PCD) is a clinically rare, genetically and phenotypically heterogeneous condition characterized by chronic respiratory tract infections, male infertility, tympanitis, and laterality abnormalities. PCD is typically resulted from variants in genes encoding assembly or structural proteins that are indispensable for the movement of motile cilia. Here, we identified a novel nonsense mutation, c.466G>T, in cilia- and flagella-associated protein 300 ( CFAP300 ) resulting in a stop codon (p.Glu156*) through whole-exome sequencing (WES). The proband had a PCD phenotype with laterality defects and immotile sperm flagella displaying a combined loss of the inner dynein arm (IDA) and outer dynein arm (ODA). Bioinformatic programs predicted that the mutation is deleterious. Successful pregnancy was achieved through intracytoplasmic sperm injection (ICSI). Our results expand the spectrum of CFAP300 variants in PCD and provide reproductive guidance for infertile couples suffering from PCD caused by them.
Adult ; Female ; Humans ; Male ; Pregnancy ; China ; Ciliary Motility Disorders/genetics* ; Codon, Nonsense ; East Asian People/genetics* ; Exome Sequencing ; Homozygote ; Infertility, Male/genetics* ; Kartagener Syndrome/genetics* ; Pedigree ; Sperm Injections, Intracytoplasmic ; Cytoskeletal Proteins/genetics*

The 2024 National Education Work Conference pointed out that at the current juncture of the critical period for achieving the goals and tasks of the 14th Five-Year Plan,the implementation of the Education Powerhouse Construction Plan Outline should be taken as the main line of work,and building first-class disciplines is an crucial task for a higher education powerhouse.In 2022,forensic medicine was officially listed as a first-level discipline under the medical category,presenting an un-precedented historical opportunity for the development of forensic medicine.The forensic medicine dis-cipline of Southern Medical University comprehensively improves the quality of talent cultivation and facilitates the construction of first-class disciplines as its main direction.It aims to initiate and imple-ment a high-level faculty team building plan featuring"combining recruitment and cultivation,inter-disciplinary integration";make vigorous efforts to establish a first-level doctoral program,refine advan-tageous second-level disciplines and research directions;and establish an innovative research platform from a high starting point with deep integration.The discipline adheres to moral cultivation and the Five Domains of Education simultaneous development,to build a high-quality talent joint training model.Guided by the construction of the national legal system and industry needs,the discipline will enhance social service capabilities.The forensic medicine construction in our university will continue to contribute to the rule of law in China and educational power.