Jianghuanglian is one of the representative processed products of Coptidis Rhizoma for treating cold syndrome with drugs of heat nature， and ginger is used to restrict the bitter cold of Coptidis Rhizoma， which can be traced back to Bojifang， and it is suitable for stagnation of damp-heat in middle-jiao， cold-heat mutual knots and other symptoms. Jianghuanglian retains the alkaloids， phenylpropanoids and flavonoids of Coptidis Rhizoma， and also introduces gingerol components such as 6-gingerol in ginger， which has pharmacological activities such as anti-inflammatory， antibacterial， anti-tumor， and improving gastrointestinal function. The 2020 edition of Chinese Pharmacopoeia and many local processing specifications have included the traditional processing process and quality standards of Jianghuanglian， but the specific process parameters and quality standards are incomplete， which limits the production and clinical application of this processed product. By summarizing the processing history， process research， quality evaluation， pharmacodynamic and medicinal property changes and application of Jianghuanglian in the past 20 years， there are differences in the processing methods and standards in various provinces and cities， which are mainly reflected in the preparation method， dosage， processing process and quantitative standards of ginger juice. In addition， there are also certain differences in the changes of the main components of Jianghuanglian prepared from ginger or dried ginger， as well as their efficacy and medicinal properties. The research on the processing process of Jianghuanglian plays an important role in improving its quality standards， and this review can provide a reference for improving the quality evaluation system of Jianghuanglian.

The chemical constituents in dried roots of Atractylodes macrocephala were investigated in this study. Through utilizing normal-phase silica gel and ODS column chromatography, TLC, and semi-preparative HPLC, 4 new sesquiterpenoids were purified from the ethyl acetate extract of A. macrocephala. By various spectroscopic techniques, such as 1D and 2D NMR, HR-ESI-MS, IR, UV, and CD, their structures were identified as atractylmacron A (1), 9β-hydroxyasterolide (2), atractylenolide H (3), atractylenolide J (4). Compound 1 possesses a rare 6/7 bicyclic skeleton.

Disorders of consciousness (DOC) are pathological conditions characterized by severely suppressed brain function and the persistent interruption or loss of consciousness. Accurate diagnosis and evaluation of DOC are prerequisites for precise treatment. Traditional assessment methods are primarily based on behavioral scales, which are inherently subjective and rely on observable behaviors. Moreover, traditional methods have a high misdiagnosis rate, particularly in distinguishing minimally conscious state (MCS) from vegetative state/unresponsive wakefulness syndrome (VS/UWS). This diagnostic uncertainty has driven the exploration of objective, reliable, and efficient assessment tools. Among these tools, electroencephalography (EEG) has garnered significant attention for its non-invasive nature, portability, and ability to capture real-time neurodynamics. This paper systematically reviews the application of EEG biomarkers in DOC assessment. These biomarkers are categorized into 3 main types: resting-state EEG features, task-related EEG features, and features derived from transcranial magnetic stimulation-EEG (TMS-EEG). Resting-state EEG biomarkers include features based on spectrum, microstates, nonlinear dynamics, and brain network metrics. These biomarkers provide baseline representations of brain activity in DOC patients. Studies have shown their ability to distinguish different levels of consciousness and predict clinical outcomes. However, because they are not task-specific, they are challenging to directly associate with specific brain functions or cognitive processes. Strengthening the correlation between resting-state EEG features and consciousness-related networks could offer more direct evidence for the pathophysiological mechanisms of DOC. Task-related EEG features include event-related potentials, event-related spectral modulations, and phase-related features. These features reveal the brain’s responses to external stimuli and provide dynamic information about residual cognitive functions, reflecting neurophysiological changes associated with specific cognitive, sensory, or behavioral tasks. Although these biomarkers demonstrate substantial value, their effectiveness rely on patient cooperation and task design. Developing experimental paradigms that are more effective at eliciting specific EEG features or creating composite paradigms capable of simultaneously inducing multiple features may more effectively capture the brain activity characteristics of DOC patients, thereby supporting clinical applications. TMS-EEG is a technique for probing the neurodynamics within thalamocortical networks without involving sensory, motor, or cognitive functions. Parameters such as the perturbational complexity index (PCI) have been proposed as reliable indicators of consciousness, providing objective quantification of cortical dynamics. However, despite its high sensitivity and objectivity compared to traditional EEG methods, TMS-EEG is constrained by physiological artifacts, operational complexity, and variability in stimulation parameters and targets across individuals. Future research should aim to standardize experimental protocols, optimize stimulation parameters, and develop automated analysis techniques to improve the feasibility of TMS-EEG in clinical applications. Our analysis suggests that no single EEG biomarker currently achieves an ideal balance between accuracy, robustness, and generalizability. Progress is constrained by inconsistencies in analysis methods, parameter settings, and experimental conditions. Additionally, the heterogeneity of DOC etiologies and dynamic changes in brain function add to the complexity of assessment. Future research should focus on the standardization of EEG biomarker research, integrating features from resting-state, task-related, and TMS-EEG paradigms to construct multimodal diagnostic models that enhance evaluation efficiency and accuracy. Multimodal data integration (e.g., combining EEG with functional near-infrared spectroscopy) and advancements in source localization algorithms can further improve the spatial precision of biomarkers. Leveraging machine learning and artificial intelligence technologies to develop intelligent diagnostic tools will accelerate the clinical adoption of EEG biomarkers in DOC diagnosis and prognosis, allowing for more precise evaluations of consciousness states and personalized treatment strategies.

RNA-binding proteins (RBPs) are ubiquitous components within cells, fulfilling essential functions in a myriad of biological processes. These proteins interact with RNA molecules to regulate gene expression at various levels, including transcription, splicing, transport, localization, translation, and degradation. Understanding the intricate network of RBP-RNA interactions is crucial for deciphering the complex regulatory mechanisms that govern cellular function and organismal development. Ultravidet (UV) cross-linking and immunoprecipitation (CLIP) stands out as a powerful approach designed to map the precise locations where RBPs bind to RNA. By using UV light to create covalent bonds between proteins and RNA, followed by immunoprecipitation to isolate the protein-RNA complexes, researchers can identify the direct targets of specific RBPs. The advent of high-throughput sequencing technologies has revolutionized CLIP, enabling the identification of not only the types but also the exact sequences of RNA bound by RBPs on a genome-wide scale. The evolution of CLIP has led to the development of specialized variants, each with unique features that address specific challenges and expand the scope of what can be studied. High-throughput sequencing CLIP (HITS-CLIP) was one of the first advancements, significantly increasing the throughput and resolution of RNA-protein interaction mapping. Photoactivatable-ribonucleoside-enhanced CLIP (PAR-CLIP) introduced the use of photoactivatable ribonucleosides to enhance cross-linking efficiency and specificity, reducing background noise and improving the detection of low-abundance RNA-protein interactions. Individual-nucleotide resolution CLIP (iCLIP) further refined the technique, achieving unprecedented precision by resolving individual nucleotides involved in RBP binding, which is particularly valuable for studying the fine details of RNA structure and function. Despite the remarkable progress, there remains room for improvement in CLIP technology. Researchers continue to seek methods to increase sensitivity, reduce technical variability, and improve the reproducibility of results. Advances in sample preparation, data analysis algorithms, and computational tools are critical for addressing these challenges. Moreover, the application of CLIP to more diverse biological systems, including non-model organisms and clinical samples, requires the development of tailored protocols and the optimization of existing ones. Looking forward, the field of RNA biology is poised to benefit greatly from ongoing innovations in CLIP technology. The exploration of non-canonical RNA-protein interactions, such as those involving long non-coding RNAs (lncRNAs) and circular RNAs (circRNAs), promises to reveal new layers of cellular regulation and may lead to the discovery of novel therapeutic targets. Furthermore, integrating CLIP data with other omics approaches, such as proteomics and metabolomics, will provide a more comprehensive understanding of the dynamic interplay between RNA and its binding partners within the cell. In conclusion, the continuous refinement and expansion of CLIP techniques have not only deepened our knowledge of RNA biology but have also opened up new avenues for investigating the molecular underpinnings of health and disease. As the technology matures, it is expected to play an increasingly pivotal role in both basic and applied research, contributing to the advancement of medical science and biotechnology.

BackgroundGraduate students frequently face life events， many of which may adversely affect their mental well-being. However， the interaction between life events and the development of depression， anxiety， and somatic symptoms remains unclear. ObjectiveTo explore the relationship between life events and the development of depressive， anxiety and somatic symptoms in graduate students， thereby informing prevention strategies for these conditions. MethodsA sample of 6 722 newly enrolled graduate students at a comprehensive university in Southwest China from September to November 2018 was selected. The assessment was conducted using the Adolescent Self-rating Life Events Checklist （ASLEC）， the 7-item Generalized Anxiety Disorder scale-7 item （GAD-7）， the Patient Health Questionnaire Depression Scale-9 item （PHQ-9）， and the Patient Health Questionnaire-15 （PHQ-15）. Network analysis was implemented by using the bootnet and qgraph packages in the R software （version 4.2.3）， with centrality indices calculated to identify core and bridge symptoms within the network. ResultsThe study encompassed a total of 6 171 graduate students， representing 91.80% of the target population. The prevalence rates of anxiety， depressive， and somatic symptoms among graduate students were 12.59% （777/6 171）， 16.63% （1 026/6 171）， and 27.66% （1 707/6 171）， respectively. Network analysis revealed that 'academic stress' was the core symptom with the highest strength and expected influence （both values=1.207）， while 'feeling down， depressed， or hopeless' was the bridge symptom with the highest bridge strength and bridge expected influence （both values=0.454）. There was no significant difference in global network strength and edge weight between women and men （P>0.05）. ConclusionAcademic stress， emerging as the core symptom， assumes a dominant position within the symptom network and exhibits strong interactions with other negative affective states. There was no gender difference in the network structure.

Secondary metabolites of medicinal plants are extremely important to human health because of their special pharmacological activities or efficacy. They are the main source of drugs, health care products, and cosmetics. As human beings continue to pursue health and longevity, the demand in the pharmaceutical market continues to grow. It becomes especially important to improve the production and quality of secondary metabolites of medicinal plants. Plant secondary metabolites are a kind of adaptation of plants to their environment and are the result of the interaction between plants and biotic and abiotic factors during the long-term evolution process. The production and accumulation of secondary metabolites in medicinal plants are mainly affected by plant genetic factors and environmental factors. Among them, light environment is extremely important for their synthesis. Therefore, light regulation has long been a research focus for many scholars in China and abroad. In this article, we the recent research progress on the effects of light regulation on the secondary metabolites of medicinal plants were reviewed, mainly focusing on the effects of light quality, light intensity and photoperiod, in order to provide theoretical basis and practical guidance for the efficient production of secondary metabolites with important pharmacological activities.

The assessment of adverse drug events is an important basis for clinical safety evaluation and post-marketing risk control of drugs,and its causality assessment is gaining increasing attention.The existing methods for assessing the causal relationship between drugs and the occurrence of adverse reactions can be broadly classified into three categories:global introspective methods,standardized methods,and probabilistic methods.At present,there is no systematic introduction of the operational details of the various methods in the domestic literature.This paper compares representative causality assessment methods in terms of definition and concept,methodological steps,industry evaluation and advantages and disadvantages,clarifies the basic process of determining the causality of adverse drug reactions,and discusses how to further improve the adverse drug reaction monitoring and evaluation system,with a view to providing a reference for drug development and pharmacovigilance work in China.

Objective To observe the efficacy and safety of Morinda officinalis oligosaccharides in the continuation treatment of mild and moderate depression.Methods An open,single-arm,multi-center design was adopted in our study.Adult patients with mild and moderate depression who had received acute treatment of Morinda officinalis oligosaccharides were enrolled and continue to receive Morinda officinalis oligosaccharides capsules for 24 weeks,the dose remained unchanged during continuation treatment.The remission rate,recurrence rate,recurrence time,and the change from baseline to endpoint of Hamilton Depression Scale(HAMD),Hamilton Anxiety Scale(HAMA),Clinical Global Impression-Severity(CGI-S)and Arizona Sexual Experience Scale(ASEX)were evaluated.The incidence of treatment-related adverse events was reported.Results The scores of HAMD-17 at baseline and after treatment were 6.60±1.87 and 5.85±4.18,scores of HAMA were 6.36±3.02 and 4.93±3.09,scores of CGI-S were 1.49±0.56 and 1.29±0.81,scores of ASEX were 15.92±4.72 and 15.57±5.26,with significant difference(P＜0.05).After continuation treatment,the remission rate was 54.59％(202 cases/370 cases),and the recurrence rate was 6.49％(24 cases/370 cases),the recurrence time was(64.67±42.47)days.The incidence of treatment-related adverse events was 15.35％(64 cases/417 cases).Conclusion Morinda officinalis oligosaccharides capsules can be effectively used for the continuation treatment of mild and moderate depression,and are well tolerated and safe.

Objective To explore the toxicity of Polygonum multiflorum alcohol extract on 3D hepatospheres.Methods Variations in culture conditions and cell ratios were implemented,followed by the assessment of cell sphere diameter,density,and roundness,aiming to explore the optimal culture conditions.The 3D hepatocyte spheres were divided into control group and experimental-L,-M,-H groups.The experimental-L,-M,-H groups were treated with 0.25,1.00 and 2.50 mg·mL-1 Polygounm multiforum alcohol extract,and the control group was given the same amount of culture medium.The cell viability of the cell spheroids was tested by CellTiter-Glo reagent,the expression level of liver function related genes was detected by fluorescent quantitative polymerase chain reaction(RT-qRCR).The toxicity of cell spheres was detected by double fluorescent staining of living and dead cells.Results The ideal culture condition of cell sphere was 500 cells per micropore,and the cell ratio was HepG2-Huvec-LX-2=8∶1∶1.It displayed the values of 0.91±0.07 for circularity,0.91±0.02 for firmness,1.12±0.14 for aspect ratio,and(170.97±14.79)μm for diameter.On the 3rd,7th,10th and 14th days,the expression levels of albumin(ALB)mRNA were 1.00±0.02,0.96±0.02,0.54±0.07,0.52±0.07,and the expression levels of cytochrome P450 1A2(CYP1A2)mRNA were 1.00±0.10,2.15±0.16,2.45±0.33,1.30±0.03,respectively.The expression levels of multidrug resistance protein 2(MPR2)in the control group and the experimental-L,-M,-H groups were 1.00±0.31,1.38±0.24,1.48±0.06 and 1.90±0.08,respectively;spheroid viability were(98.19±0.49)％,(88.53±0.90)％,(71.60±2.91)％and(56.65±5.41)％.There were statistically significant differences in the above indexes between the experimental-L,-M,-H groups and the control group(all P＜0.05).Conclusion The established hepatocyte sphere co-culture model showed varying degrees of expression of phase Ⅰ/Ⅱ drug metabolism enzymes,transporters,and liver cell specific marker molecule albumin and can be used to evaluate the toxicity of multiflorum multiflorum,which provides further reference for the clinical application of multiflorum multiflorum.

BACKGROUND:The preoperative planning of traditional X-ray films is often inaccurate,which can lead to some intraoperative and postoperative complications,increase the operation time and intraoperative blood loss,and to some extent affect the surgical outcome of total hip arthroplasty. OBJECTIVE:To investigate the accuracy and effectiveness of artificial intelligence preoperative planning in total hip arthroplasty. METHODS:Sixty patients who underwent primary total hip arthroplasty on the affected side were selected.30 of them used artificial intelligence 3D preoperative planning(trial group)and 30 used conventional X-ray film 2D preoperative planning(control group),and there were no statistically significant differences between the two groups in terms of gender,age,condition and other general data(P>0.05).The actual intraoperative prosthesis placement and preoperative planning prosthesis matching,intraoperative operation time,intraoperative blood loss,bilateral femoral eccentric distance difference,bilateral joint eccentric distance difference and bilateral lower limb length difference,and Harris score at 3 months after operation were compared between the two groups,and the accuracy and application effect of the two preoperative plans were analyzed. RESULTS AND CONCLUSION:(1)Patients in both groups were followed up for 4-6 months postoperatively.One patient in the control group had a posterior dislocation of the prosthesis at 5 days postoperatively,which recovered after performing manual repositioning without re-dislodgement.The rest of the patients did not have postoperative complications or postoperative death.(2)Complete matching rate of the prosthesis on the acetabular side and femoral side was significantly better in the trial group than that in the control group(P<0.05).(3)Operation time and intraoperative blood loss were significantly less in the trial group than those in the control group(P<0.05).(4)The difference in bilateral lower limb length between the two groups was statistically significant(P<0.05),and the difference in bilateral femoral eccentric distance and bilateral joint eccentric distance was not statistically significant(P>0.05).(5)Harris score of patients in the trial group was significantly higher than that in the control group 3 months after operation(P<0.05).(6)These results confirm that compared with traditional film planning,artificial intelligence preoperative planning can predict the prosthesis type more accurately,shorten the operation time,reduce intraoperative blood loss,diminish the occurrence of postoperative bilateral lower limb inequality,and accelerate postoperative recovery.