The Golgi body, a core organelle in eukaryotic cells, plays a critical role in protein modification, sorting, vesicular transport, and serves as a key site for lipid synthesis and glycosylation. Glucose and lipid metabolism are central processes for cellular energy maintenance and biosynthesis, and are closely linked to Golgi function. Recent studies have revealed the extensive involvement of the Golgi body in regulating glucose and lipid metabolism, where maintaining its structural and functional homeostasis is crucial for normal physiological activity. Under various stress conditions such as acidosis, hypoxia, and nutrient deficiency, the Golgi body undergoes structural and functional disruption, leading to Golgi stress. This in turn activates specific signaling pathways, such as those mediated by the cAMP-responsive element binding protein 3 (CREB3) and proteoglycans, to alleviate Golgi stress and enhance Golgi function. Golgi stress contributes to glucose and lipid metabolic disorders by affecting the activity of insulin receptors, glucose transporters, and lipid metabolism-related enzymes. For example, Golgi stress triggers the cleavage and release of the active fragment of CREB3, which enters the nucleus and upregulates the transcription of ADP-ribosylation factor 4 (ARF4) and key gluconeogenic enzymes, including phosphoenolpyruvate carboxykinase (PEPCK) and glucose-6-phosphatase (G6Pase). ARF4 promotes vesicle retrograde transport between the Golgi and endoplasmic reticulum, maintains secretory capacity, and enhances hepatic glucose output. This pathway is particularly active under high-fat or lipotoxic stress, leading to fasting hyperglycemia. When damaged Golgi components accumulate beyond a tolerable threshold, the cell initiates an autophagic response, selectively encapsulating the damaged Golgi into autophagosomes, which then fuse with lysosomes to form autolysosomes, leading to Golgiphagy. This process results in the degradation and clearance of damaged Golgi, thereby regulating Golgi quantity, quality, and function. Golgiphagy also plays a significant role in regulating glucose and lipid metabolism. For instance, under high-glucose conditions, autophagic flux may be suppressed, impairing the timely clearance and renewal of damaged Golgi, compromising its normal function, and further exacerbating glucose metabolism disorders. Additionally, Golgiphagy may participate in lipid degradation and influence lipid synthesis and transport. Research indicates that Golgi stress and Golgiphagy play important roles in glucose and lipid metabolism-related diseases. For example, the leucine zipper protein (LZIP) under Golgi stress conditions can promote hepatic steatosis. In mouse primary cells and human tissues, LZIP induces the expression of apolipoprotein A-IV (APOA4), which increases peripheral free fatty acid uptake, resulting in lipid accumulation in the liver and contributing to the development of fatty liver disease. This review systematically outlines the structure and function of the Golgi apparatus, the molecular regulatory mechanisms of Golgi stress and Golgiphagy, and their synergistic roles. It further elaborates on how Golgi stress and Golgiphagy participate in the regulation of glucose and lipid metabolism, discusses their clinical significance in related diseases such as diabetes, fatty liver disease, and obesity, and highlights potential novel therapeutic strategies from the perspective of Golgi-targeted medicine. Finally, this article addresses the challenges and future directions in Golgi-targeted interventions, aiming to advance the clinical translation of such strategies and foster breakthroughs in the treatment of glucose and lipid metabolism-related disorders.

The Golgi body, a core organelle in eukaryotic cells, plays a critical role in protein modification, sorting, vesicular transport, and serves as a key site for lipid synthesis and glycosylation. Glucose and lipid metabolism are central processes for cellular energy maintenance and biosynthesis, and are closely linked to Golgi function. Recent studies have revealed the extensive involvement of the Golgi body in regulating glucose and lipid metabolism, where maintaining its structural and functional homeostasis is crucial for normal physiological activity. Under various stress conditions such as acidosis, hypoxia, and nutrient deficiency, the Golgi body undergoes structural and functional disruption, leading to Golgi stress. This in turn activates specific signaling pathways, such as those mediated by the cAMP-responsive element binding protein 3 (CREB3) and proteoglycans, to alleviate Golgi stress and enhance Golgi function. Golgi stress contributes to glucose and lipid metabolic disorders by affecting the activity of insulin receptors, glucose transporters, and lipid metabolism-related enzymes. For example, Golgi stress triggers the cleavage and release of the active fragment of CREB3, which enters the nucleus and upregulates the transcription of ADP-ribosylation factor 4 (ARF4) and key gluconeogenic enzymes, including phosphoenolpyruvate carboxykinase (PEPCK) and glucose-6-phosphatase (G6Pase). ARF4 promotes vesicle retrograde transport between the Golgi and endoplasmic reticulum, maintains secretory capacity, and enhances hepatic glucose output. This pathway is particularly active under high-fat or lipotoxic stress, leading to fasting hyperglycemia. When damaged Golgi components accumulate beyond a tolerable threshold, the cell initiates an autophagic response, selectively encapsulating the damaged Golgi into autophagosomes, which then fuse with lysosomes to form autolysosomes, leading to Golgiphagy. This process results in the degradation and clearance of damaged Golgi, thereby regulating Golgi quantity, quality, and function. Golgiphagy also plays a significant role in regulating glucose and lipid metabolism. For instance, under high-glucose conditions, autophagic flux may be suppressed, impairing the timely clearance and renewal of damaged Golgi, compromising its normal function, and further exacerbating glucose metabolism disorders. Additionally, Golgiphagy may participate in lipid degradation and influence lipid synthesis and transport. Research indicates that Golgi stress and Golgiphagy play important roles in glucose and lipid metabolism-related diseases. For example, the leucine zipper protein (LZIP) under Golgi stress conditions can promote hepatic steatosis. In mouse primary cells and human tissues, LZIP induces the expression of apolipoprotein A-IV (APOA4), which increases peripheral free fatty acid uptake, resulting in lipid accumulation in the liver and contributing to the development of fatty liver disease. This review systematically outlines the structure and function of the Golgi apparatus, the molecular regulatory mechanisms of Golgi stress and Golgiphagy, and their synergistic roles. It further elaborates on how Golgi stress and Golgiphagy participate in the regulation of glucose and lipid metabolism, discusses their clinical significance in related diseases such as diabetes, fatty liver disease, and obesity, and highlights potential novel therapeutic strategies from the perspective of Golgi-targeted medicine. Finally, this article addresses the challenges and future directions in Golgi-targeted interventions, aiming to advance the clinical translation of such strategies and foster breakthroughs in the treatment of glucose and lipid metabolism-related disorders.

OBJECTIVE To systematically review the current application of discrete choice experiment （DCE） in the value assessment and preference measurement of orphan medicinal product （OMP）， and to provide a reference for the standardized use of this methodology in China. METHODS The systematic search was conducted across Chinese and English databases including CNKI， Wanfang Data， VIP， CBM， PubMed， Web of Science， Medline， and Embase. Original studies that employed DCE to evaluate the value or preferences related to OMP were included. The methodological quality and reporting completeness of the included studies were assessed using the ISPOR Conjoint Analysis Checklist and the DIRECT Checklist， respectively. Respondent populations， attribute setting， and the relative importance of attributes were summarized and analyzed. RESULTS Eight eligible studies were included； all studies demonstrated high-quality reporting and methodological rigor. Respondents comprised the general public， patients/caregivers， policymakers， and other stakeholders. The number of DCE attributes ranged from 4 to 13 （median＝7.5）. Through thematic synthesis， these attributes were categorized into three dimensions， namely “disease-related” “treatment-related” and “economic/financial-related” along with 14 secondary criteria. The most frequently included secondary criteria were treatment efficacy （13 occurrences）， disease severity （9 occurrences）， safety （7 occurrences）， unmet medical need （6 occurrences）， and treatment cost （5 occurrences）. Rankings of relative importance identified treatment efficacy as the most valued criterion across most studies， followed by health insurance financing. CONCLUSIONS DCE applications in the value assessment of OMP have begun to converge on a relatively consistent core attribute framework and selection preference. Future research should further promote the use of DCE to inform attribute and criterion selection in multi-criteria decision analysis frameworks for OMP.

Multidrug-resistant (MDR) bacterial infections have emerged as a serious challenge of global public health crisis. The overuse and misuse of conventional antibiotics have dramatically accelerated the emergence, evolution and worldwide spread of drug-resistant bacterial strains, necessitating urgent exploration of novel antibacterial strategies. Bacteriophages serve as natural bacterial predators offering distinct advantages including high host specificity, autonomous self-replication capabilities and cost-effective large-scale production. However, wild-type phages present significant clinical limitations due to their narrow host ranges, susceptibility to rapid immune clearance and poor penetration of bacterial biofilms, which severely restrict their therapeutic applications. The convergence of synthetic biology, nanotechnology and advanced gene editing technologies has accelerated the development of engineered bacteriophage platforms, providing programmable, scalable and clinically translatable pathways to overcome these inherent biological constraints. Here, we systematically delineate four fundamental strategies for engineered bacteriophage development. Chemical modification utilizes reactive functional groups such as amino, carboxyl and thiol moieties on capsid proteins through esterification, amidation or click chemistry reactions to achieve precise drug conjugation and surface functionalization. In vivo editing encompasses ultraviolet or chemical mutagenesis for random mutation induction, homologous recombination for targeted genetic alterations, recombineering methodologies including electroporation-mediated bacteriophage recombination engineering, and CRISPR-Cas systems for precise genome editing to enable exact genetic reconstruction and host range reprogramming. In vitro synthesis leverages genome engineering platforms where intact phage genomes are transferred into yeast or host bacteria to facilitate highly efficient homologous recombination, enabling large DNA fragment assembly and cross-gene host range expansion without bacterial toxicity constraints. Directed evolution combines artificial selection through mutation library screening with rational design approaches involving chimeric receptor binding protein construction or site-specific mutagenesis, effectively balancing the discovery of unknown adaptive pathways with targeted host specificity modification. Moreover, we comprehensively discuss therapeutic applications across diverse clinical scenarios. Engineered bacteriophage effectively disrupt bacterial biofilms through sophisticated functionalized delivery platforms including nanozyme-conjugated phages, phage-liposome nanoconjugates and bio-responsive hydrogels, demonstrating significantly enhanced bactericidal efficiency compared to unmodified free phages. These bioengineered vectors attenuate bacterial virulence and resensitize pathogens to antibiotics by delivering CRISPR-Cas systems or base editors to disrupt critical virulence factors such as pili, capsule synthesis machineries and quorum sensing systems, or by inactivating antibiotic resistance determinants including beta-lactamase genes. As an intelligent nanomedicine delivery platform, engineered bacteriophage enable precise pathogen elimination an through photocatalytic reactive oxygen species generation, immunomodulatory interventions, or controlled release of antibacterial drugs. Furthermore, oral administration of engineered bacteriophage facilitates microbiota modulation, which selectively eliminate intestinal pathogens while preserve beneficial commensal microbiota, thereby restoring microbial community balance and preventing complications associated with dysbiosis. Finally, we critically analyze persistent challenges including host strain matching complexity, evolution of bacterial resistance mechanisms, pharmacokinetic optimization requirements, optimal administration route selection, large-scale production quality control standards and clinical dosing determination protocols. Through multidisciplinary integration of synthetic biology, infectious disease medicine and immunology, future translational medicine studies of bacteriophage should establish comprehensive technical platforms encompassing rapid phage screening, intelligent rational design, rigorous in vivo evaluation and standardized clinical validation processes, ultimately advancing engineered bacteriophage from laboratory innovations to clinically approved therapeutics for effectively combating MDR bacterial infections.

The functional realization of proteins and other biological macromolecules depends on conformational dynamics and allosteric regulation, and elucidating their molecular mechanisms is an important foundation for understanding life processes. Molecular dynamics simulations are a powerful tool for investigating conformational evolution at the atomic level. However, traditional methods are limited by simulation timescales and high free-energy barriers, making it difficult to effectively capture rare conformations and their transition pathways. As a result, the development of enhanced sampling techniques has become key to overcoming this bottleneck. As a classical enhanced sampling technique, metadynamics suffers from several shortcomings, including strong dependence on collective variables and significant errors caused by bias potential accumulation. This article reviews three major improvement strategies. The first combines stochastic resetting with metadynamics, using trajectory-resetting mechanisms to improve sampling efficiency while avoiding the difficulty of optimizing collective variables. The second, SinkMeta, employs a “sinking” bias effect to enable efficient exploration of specific regions and paths. The third, OPES-based hybrid methods, improve the stability of free-energy estimation by optimizing the target distribution or the way the bias is constructed. These methods provide new ideas for characterizing free-energy landscapes and studying conformational transitions in complex biological systems, while also promoting the continued development of enhanced sampling methodologies.

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.

Objectives: . This study aimed to investigate the regulatory functions of gamma-aminobutyric acid (GABA)ergic neural circuits from the inferior colliculus (IC) to the medial geniculate body (MGB) in salicylate-induced tinnitus. Methods: . Mice were treated with salicylate to induce tinnitus, and tinnitus-like behaviors were evaluated via gap prepulse inhibition of acoustic startle. Using combined viral tracing methodologies, we identified and mapped the pathways and connections from the IC to the MGB. Furthermore, we employed Gq-coupled human M3 designer receptors exclusively activated by designer drugs (DREADDs) and Gi-coupled human M4 DREADDs to achieve targeted excitation or suppression of GABAergic neurons in the IC and MGB. Following the administration of clozapine N-oxide, which binds to these receptors, we modulated these neural circuits to assess their impact on tinnitus severity in a mouse model. Results: . Our findings demonstrated that mice exposed to salicylate exhibited tinnitus-like behaviors. GABAergic neurons projecting retrogradely from the MGB to the IC were primarily concentrated in the external nucleus of the IC. After clozapine N-oxide administration, chemogenetic activation of IC-MGB GABAergic neurons aggravated salicylate-induced tinnitus. Additionally, activation of GABAergic neurons between the IC and MGB induced the perception of tinnitus even without salicylate. However, chemogenetic inhibition of the IC-MGB GABAergic circuit did not reverse salicylate-induced tinnitus. Conclusion . These findings suggest that activation of the IC-MGB GABAergic neural circuit may contribute to tinnitus generation through a mechanism distinct from that of salicylate-induced tinnitus. This study provides novel insights into the mechanisms underlying tinnitus.

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.

Objective To analyze mosquito species composition and prevalence of pathogens carried by mosquitoes in Jiangsu Province from 2020 to 2024 and to provide a scientific basis for the prevention and control of mosquito-borne diseases. Methods Mosquitoes were collected using CO2-baited traps. The presence of mosquito-borne pathogens including dengue virus, Japanese encephalitis virus, yellow fever virus, West Nile virus, Chikungunya virus, and Sindbis virus was tested using commercial kits for fluorescence-based quantitative PCR. Results The most prevalent mosquito species found across different regions of Jiangsu Province were Culex pipiens pallens and Cx. tritaeniorhynchus, accounting for 81.35% to 93.01% of the total, followed by Armigeres subalbatus and Anopheles sinensis, which comprised 5.89% to 15.85% of the total. The densities of other monitored mosquito species were relatively low. Pathogen detection revealed that, only Cx. tritaeniorhynchus tested positive for Japanese encephalitis virus nucleic acid, whereas the remaining four mosquito species tested negative for the nucleic acids of all other six pathogens. The overall positivity rate of Japanese encephalitis virus (JEV) in Cx. tritaeniorhynchus showed an initially increasing trend followed by a decrease and a subsequent increase. The peak detection rate occurred in 2021 (11.93%), with a much lower positive rate of 0.80% in 2023. Genotyping result revealed that all JEV strains in Jiangsu Province belonged to the G1 genotype and were genetically closest to the strain Shangdong08DY.29 (MN072875.1). Conclusions The incidence of Japanese encephalitis virus carried by mosquito, especially Cx. tritaeniorhynchus, in Jiangsu Province shows an upward trend, requiring sustained surveillance. A variety of monitoring method should be adopted to survey mosquitoes across different habitats, ensuring the accuracy and comprehensiveness of the monitoring result.

Objective To investigate the species composition, distribution, density, and pathogen-carrying status of host-seeking ticks in urban environments of Jiangsu Province, and to provide a scientific basis for the prevention and control of tick-borne diseases in urban settings. Methods From April to September 2023, a survey on host-seeking ticks was conducted in three types of habitats (city parks, residential areas, and street greenbelts) across 54 counties (cities, districts) of 13 prefecture-level cities in Jiangsu Province by using the flagging method. RStudio 4.4.3 (Windows version) was employed to perform chi-square test analysis on the species composition of ticks across different months, and Friedman test (for multiple paired samples) was applied to analyze monthly changes in the average tick density index among different habitats. Quantitative real-time PCR was performed to detect pathogens in the captured ticks. Results A total of 863 host-seeking ticks were captured from 54 habitats in 24 counties (cities, districts) of 11 prefecture-level cities (Nanjing, Wuxi, Changzhou, Suzhou, Nantong, Huai'an, Yancheng, Yangzhou, Zhenjiang, Taizhou, and Suqian) in Jiangsu Province, whereas no ticks were captured in Xuzhou and Lianyungang. The collected ticks belonged to three species, with Haemaphysalis longicornis being the dominant species (accounting for 82.62%), followed by Haemaphysalis flava and Hae. phasiana. The average density index of ticks in positive habitats was 3.20 ticks/ (flag·100 m). In terms of tick density among prefecture-level cities, Wuxi had the highest density[13.55 ticks/(flag·100 m)], whereas Nanjing and Taizhou had the lowest[both,0.20 ticks/(flag·100 m)]. With respect to the types of positive habitats,46 positive city parks,7 positive residential areas, and 1 positive street greenbelt were found, with the average tick density index being 3.46, 1.86, and 3.60 ticks/flag · 100 m, respectively. No statistically significant differences were observed in the monthly variations in the average tick density index among different habitats (P＞0.05). Pathogen detection showed no Bandavirus dabieense, Rickettsia, or Borrelia burgdorferi in the collected ticks. Conclusions Host-seeking ticks have established populations in urban environments across most prefecture-level cities in Jiangsu Province, with Hae. longicornis identified as the dominant species. City parks serve as the primary breeding habitats for these ticks. Strengthening tick surveillance and control measures in densely populated and frequently visited areas, such as city parks and residential neighborhoods, is crucial for the effective prevention and control of urban tick-borne diseases.