ObjectiveTo collate and compare the characteristics and differences in the methods for constructing animal models of different subtypes of gastroesophageal reflux disease （GERD） based on literature， providing a reference for researchers in this field regarding animal model construction. MethodsExperimental studies related to GERD including reflux esophagitis （RE）， nonerosive reflux disease （NERD） and Barrett's esophagus （BE） model construction from January 1， 2014 to January 27， 2024， were retrieved from databases such as CNKI， Wanfang， VIP， Web of Science， and Pubmed. Information on animal strains， genders， modeling methods including disease-syndrome combination models， modeling cycles were extracted； for studies with model evaluation， the methods of model evaluation were also extracted； then analyzing all those information. ResultsA total of 182 articles were included. SD rats were most frequently selected when inducing animal models of RE （88/148， 59.46%） and NERD （9/14， 64.29%）. For BE， C57BL/6 mice were most commonly used （11/20， 55.00%）. Male animals （RE： 111/135， 82.22%； NERD： 11/14， 78.57%； BE： 10/12， 83.33%） were the most common gender among the three subtypes. The key to constructing RE animal models lies in structural damage to the esophageal mucosal layer， gastric content reflux， or mixed reflux， among which forestomach ligation + incomplete pylorus ligation （42/158， 26.58%） was the most common modeling method； the key to constructing NERD animal models lies in micro-inflammation of the esophageal mucosa， visceral hypersensitivity， and emotional problems， and intraperitoneal injection of a mixed suspension of ovalbumin and aluminum hydroxide combined with acid perfusion in the lower esophagus （8/14， 57.14%） was the most common modeling method； the key to constructing BE animal models lies in long-term inflammatory stimulation of the esophageal mucosa and bile acid reflux， and constructing interleukin 2-interleukin 1β transgenic mice （7/25， 28.00%） was the most common modeling method. Adverse psychological stress was the most common method for inducing liver depression. ConclusionsThe construction key principles and methodologies for RE， NERD， and BE animal models exhibit significant differences. Researchers should select appropriate models based on subtype characteristics （e.g.， RE focusing on structural damage， NERD emphasizing visceral hypersensitivity）. Current studies show insufficient exploration of traditional Chinese medicine disease-syndrome combination models. Future research needs to optimize syndrome modeling approaches （e.g.， composite etiology simulation） and establish integrated Chinese-Western medicine evaluation systems to better support mechanistic investigations of traditional Chinese medicine.

The circadian clock is a highly conserved timekeeping system in organisms, which maintains physiological homeostasis by precisely regulating periodic fluctuations in gene expression. Substantial clinical and experimental evidence has established a close association between circadian rhythm disruption and the development of various malignancies. Research has revealed characteristic alterations in the circadian gene expression profiles in tumor tissues, primarily manifested as a dysfunction of core clock components (particularly circadian locomotor output cycles kaput (CLOCK) and brain and muscle ARNT-like 1 (BMAL1)) and the widespread dysregulation of their downstream target genes. Notably, CLOCK demonstrates non-canonical oncogenic functions, including epigenetic regulation via histone acetyltransferase activity and the circadian-independent modulation of cancer pathways. This review systematically elaborates on the oncogenic mechanisms mediated by CLOCK/BMAL1, encompassing multidimensional effects such as cell cycle control, DNA damage response, metabolic reprogramming, and tumor microenvironment (TME) remodeling. Regarding the therapeutic strategies, we focus on cutting-edge approaches such as chrononutritional interventions, chronopharmacological modulation, and treatment regimen optimization, along with a discussion of future perspectives. The research breakthroughs highlighted in this work not only deepen our understanding of the crucial role of circadian regulation in cancer biology but also provide novel insights for the development of chronotherapeutic oncology, particularly through targeting the non-canonical functions of circadian proteins to develop innovative anti-cancer strategies.
Humans ; ARNTL Transcription Factors/physiology* ; Neoplasms/therapy* ; CLOCK Proteins/physiology* ; Circadian Clocks/genetics* ; Animals ; Circadian Rhythm/genetics* ; Tumor Microenvironment ; Epigenesis, Genetic ; Gene Expression Regulation, Neoplastic

Nanocarrier-based drug delivery systems (nDDSs) present significant opportunities for improving disease treatment, offering advantages in drug encapsulation, solubilization, stability enhancement, and optimized pharmacokinetics and biodistribution. nDDSs, comprising lipid, polymeric, protein, and inorganic nanovehicles, can be guided by or respond to biological cues for precise disease treatment and management. Equipping nanocarriers with tissue/cell-targeted ligands enables effective navigation in complex environments, while functionalization with stimuli-responsive moieties facilitates site-specific controlled release. These strategies enhance drug delivery efficiency, augment therapeutic efficacy, and reduce side effects. This article reviews recent strategies and ongoing advancements in nDDSs for targeted drug delivery and controlled release, examining lesion-targeted nanomedicines through surface modification with small molecules, peptides, antibodies, carbohydrates, or cell membranes, and controlled-release nanocarriers responding to endogenous signals such as pH, redox conditions, enzymes, or external triggers like light, temperature, and magnetism. The article also discusses perspectives on future developments.
Humans ; Drug Carriers/chemistry* ; Drug Delivery Systems/methods* ; Delayed-Action Preparations/chemistry* ; Nanoparticles/chemistry* ; Animals ; Drug Liberation ; Nanomedicine

BackgroundGenetic factor plays an important role in the pathogenesis of panic disorder. Previous studies have revealed that immune system dysregulation is closely related to mental disorders such as panic disorder， while the relationship between panic disorder and immune-related gene expression remains unclear. ObjectiveTo explore the relationship between the expression of CXCL8， IL6R， JUN， PTGS2， TGFBR1， TLR2， CCR4 genes and panic disorder， providing references for the diagnosis and treatment of panic disorder. MethodsA total of 52 patients who met the diagnostic criteria for panic disorder according to the Diagnosed and Statistical Manual of Mental Disorders， fourth edition （DSM-IV） were enrolled at the Psychosomatic Medicine Center of Sichuan Provincial People's Hospital from January 2020 to March 2021. Another 72 healthy individuals matched for age and gender from Chengdu were concurrently recruited as control group. The Panic Disorder Severity Scale （PDSS） was used to assess the severity of symptoms in panic disorder patients. Quantitative real-time polymerase chain reaction （PCR） was used to detect gene expression levels in two groups. Spearman correlation analysis was adopted to determine the correlation between PDSS score and immune-related gene expression in research group. ResultsThe expression of the JUN， PTGS2 and TGFBR1 genes were significant higher in panic disorder patients than those in control group （Z=-4.172， -2.086， -3.018， P<0.05 or 0.01）. After false discovery rate （FDR） correction for multiple testing， the differential expression of JUN and TGFBR1 genes remained statistically significant between two groups （P<0.05）. There was no significant difference in the expression of CCR4， CXCL8， IL6R and TLR2 genes between two groups （P>0.05）. Correlation analysis revealed that the expression of the JUN gene in panic disorder patients was positively correlated with PDSS score （r=0.360， P<0.01）， while the CCR4， CXCL8， IL6R， PTGS2， TGFBR1 and TLR2 genes showed no statistically significant correlation with the PDSS score （P>0.05）. ConclusionThe expression of the JUN and TGFBR1 genes may be associated with panic disorder， and the expression of the JUN gene correlated with the severity of panic disorder. ［Funded by Science and Technology Plan Project of Sichuan Provincial Department of Science and Technology （number， 2021YJ0440）］

Glaucocalyxin A （GLA） is a natural diterpenoid extracted from Isodon amethystoides belonging to Labiatae. Modern pharmacological research has shown that GLA has anti-inflammatory， anti-tumor， anti-fibrotic， osteoporosis-ameliorating， and cardiovascular system-protecting activities and good biosafety. However， the low content in plants， poor solubility， high metabolic rate， and low bioavailability limit the application of GLA. To address these issues， researchers have studied the total synthesis， structural modification， and nanomedicine development of GLA. By reviewing the available studies about GLA in the past five years， we summarize the research progress in the total synthesis， pharmacological activities and mechanisms， and in vivo metabolic transformation， aiming to provide a theoretical basis for clarifying the specific mechanisms underlying the pharmacological activities of GLA and for further research， development， and clinical applications of GLA.

Background Mercury, as a global heavy metal pollutant, poses a serious threat to human health. The toxicity of mercury depends on its chemical form. Distinguishing the forms of mercury in the environment is of great significance for mercury management and reducing human mercury exposure risks. Objective To establish a non-targeted metallomics method based on synchrotron radiation X-ray fluorescence (SRXRF) spectroscopy combined with machine learning to screen inorganic mercury (IHg) or methylmercury (MeHg) exposed rice plants. Methods Rice seeds were exposed to ultra-pure water (control group), 0.1 mg·L⁻¹ IHg (IHg group) or MeHg (MeHg group) solutions, respectively. After germination, the seedlings were cultured for 21 d, and rice leaves were collected, dried, weighed, and pressed. The content of metallome in rice leaves was determined by SRXRF. Machine learning models including soft independent modeling cluster analysis (SIMCA), partial least squares discriminant analysis (PLS-DA), and logistic regression (LR) were used to classify the SRXRF full spectra of different groups and find the best model to distinguish rice exposed to IHg or MeHg. Besides, characteristic elements were selected as input parameters to optimize the model by improving computing speed and reducing model calculation. Results The SRXRF spectral intensities of the control group, IHg group, and MeHg group were different, indicating that exposure to IHg and MeHg can interfere the homeostasis of metallome in rice leaves. The results of principal component analysis (PCA) of SRXRF spectra showed that the control group could be well distinguished from the mercury exposed groups, but the IHg group and the MeHg group were mostly overlapped. The accuracy rates of the three models (PLS-DA, SIMCA, and LR) were higher than 98% for the training set, higher than 95% for the validation set, and higher than 94% for the cross-validation set. Besides, the accuracy of the LR model was higher than that of the PLS-DA model and the SIMCA model. Furthermore, the accuracy was 92.05% when using characteristic elements K, Ca, Mn, Fe, and Zn selected by LR to distinguish the IHg group and the MeHg group. Compared with the full spectra model, although the prediction accuracy of the characteristic spectral model decreased, the input parameters of the model decreased by 99.51%, and precision, recall, and F1 score were above 84.48%, indicating that the model could distinguish rice exposed to different mercury forms. Conclusion Non-targeted metallomics method based on SRXRF and machine learning can be applied for high-throughput screening of rice exposed to different forms of mercury and thus decrease the risks of people being exposed to mercury.

OBJECTIVE To optimize the processing technology of wine steamed Cnidii Fructus. METHODS The content of xanthotoxol, xanthotoxin, bergapten, isobergapten, imperatorin and osthole was used as the evaluation index. The response surface methodology combined with entropy weight method was used to investigate the adding amount of rice wine, the soaking time and the steaming time with aim to find the best processing technology. RESULTS The best processing technology for Cnidii Fructus with wine steaming was: adding 30 g of rice wine 4 mL for infiltrating 18.5 h, and steaming for 10 h. CONCLUSION The optimized wine steaming process is stable and feasible. The establishment of an HPLC analytical method for the determination of 6 components in wine steamed Cnidii Fructus is accurate and reliable, which can be used for the quality control of wine steamed Cnidii Fructus decoction pieces.

Cerebral organoids are three-dimensional nerve cultures induced by embryonic stem cells(ESCs)or induced pluripotent stem cells(iPSCs)that mimic the structure and function of human brain.With the continuous optimization of cerebral organoid culture technology and the combination with emerging technologies such as organ transplantation,gene editing and organoids-on-chip,complex brain tissue structures such as functional vascular structures and neural circuits have been produced,which provides new methods and ideas for studying human brain development and diseases.This article reviews the latest advances in brain organoid technology,describes its application in neurological diseases and advances in stroke modeling and transplantation treatment.