OBJECTIVE To investigate the effects of borneol on pharmacodynamic and pharmacokinetic effects of Corydalis saxicola total alkaloids in depression model rats. METHODS Thirty male SD rats were divided into blank control group， negative control group， positive control group （fluoxetine 10 mg/kg， i.g.）， single drug group （C. saxicola total alkaloids 210 mg/kg， i.g.） and combined drug group （C. saxicola total alkaloids 210 mg/kg+borneol 50 mg/kg， i.g.） according to the random number table method， with 6 rats in each group. By lipopolysaccharide （LPS） induction modeling， except blank control group （no model and no administration） received intraperitoneal injection of the same amount of normal saline， the rats in the other groups were intraperitoneally injected with LPS once a day to establish a rat model of depression. After 1 week of modeling， each administration group was given relevant drug intragastrically according to the corresponding dose， and blank control group and negative control group （without drug treatment） were administered intragastrically with an equal volume of solvent to dissolve the drug； continued modeling while administering the drug. After two weeks of continuous administration， the effects of C. saxicola total alkaloids versus the combination of C. saxicola total alkaloids and borneol on the behavior of depressed rats were tested by behavioral experiments； the levels of tumor necrosis factor-α， interleukin-1β and interleukin-6 in rats were determined； the histopathological changes of the hippocampus of rats were observed. Blood sample was collected from the orbit at different time points after administration on the 15th day， and the upper plasma was obtained. Ultra-performance liquid chromatography-triple quadrupole tandem mass spectrometry was established for the simultaneous determination of dehydrocarvedine， tetrahydropalmatine， coptisine， palmatine， jatrorrhizine， berberine， berberrubine and epiberberine in rat plasma. The average plasma concentration-time curve was depicted， the area under the curve （AUC） was calculated， and the pharmacokinetic parameters were analyzed by DAS 3.2.2 software. RESULTS Compared with blank control group， the negative control group had a decrease in body mass and sugar water preference rate， a decrease in the total distance of open field， a prolonged swimming immobility time， and a increased in the expression of inflammatory factors in serum （P＜0.05）； compared with negative control group, the single drug group and the combined drug group increased the preference rate of sugar water， increased the total distance of open field， shortened the time of swimming immobility， and decreased the expression of inflammatory factors in serum （P＜0.05）. There was no significant difference in the above indicators between the single drug group and the combined drug group in rats （P＞0.05）. Pharmacokinetic results showed that compared with single drug group， AUC0-t of coptisine， AUC0-t， AUC0-∞， tmax and cmax of jatrorrhizine， AUC0-t， AUC0-∞， t1/2 and cmax of berberrubine， and AUC0-t of epiberberine， cmax of dehydrocarvedine， cmax of palmatine were significantly increased in combined drug group， but there was no significant difference， indicating that borneol didn’t have a significant effect on the efficacy of Corydalis saxicola nigra at this dose. CONCLUSIONS Both C. saxicola total alkaloids alone and in combination with borneol can improve depression-like behavior in depression model rats， reduce serum inflammatory cytokine levels， and protect hippocampal neurons. Compared with the use of Corydalis saxicola base alone， the combination with borneol do not show significant pharmacodynamic differences， bu can improve the absorption of coptisine， jatrorrhizine in model rats.

Electromagnetic fields can regulate the fundamental biological processes involved in bone remodeling. As a non-invasive physical therapy, electromagnetic fields with specific parameters have demonstrated therapeutic effects on bone remodeling diseases, such as fractures and osteoporosis. Electromagnetic fields can be generated by the movement of charged particles or induced by varying currents. Based on whether the strength and direction of the electric field change over time, electromagnetic fields can be classified into static and time-varying fields. The treatment of bone remodeling diseases with static magnetic fields primarily focuses on fractures, often using magnetic splints to immobilize the fracture site while studying the effects of static magnetic fields on bone healing. However, there has been relatively little research on the prevention and treatment of osteoporosis using static magnetic fields. Pulsed electromagnetic fields, a type of time-varying field, have been widely used in clinical studies for treating fractures, osteoporosis, and non-union. However, current clinical applications are limited to low-frequency, and research on the relationship between frequency and biological effects remains insufficient. We believe that different types of electromagnetic fields acting on bone can induce various “secondary physical quantities”, such as magnetism, force, electricity, acoustics, and thermal energy, which can stimulate bone cells either individually or simultaneously. Bone cells possess specific electromagnetic properties, and in a static magnetic field, the presence of a magnetic field gradient can exert a certain magnetism on the bone tissue, leading to observable effects. In a time-varying magnetic field, the charged particles within the bone experience varying Lorentz forces, causing vibrations and generating acoustic effects. Additionally, as the frequency of the time-varying field increases, induced currents or potentials can be generated within the bone, leading to electrical effects. When the frequency and power exceed a certain threshold, electromagnetic energy can be converted into thermal energy, producing thermal effects. In summary, external electromagnetic fields with different characteristics can generate multiple physical quantities within biological tissues, such as magnetic, electric, mechanical, acoustic, and thermal effects. These physical quantities may also interact and couple with each other, stimulating the biological tissues in a combined or composite manner, thereby producing biological effects. This understanding is key to elucidating the electromagnetic mechanisms of how electromagnetic fields influence biological tissues. In the study of electromagnetic fields for bone remodeling diseases, attention should be paid to the biological effects of bone remodeling under different electromagnetic wave characteristics. This includes exploring innovative electromagnetic source technologies applicable to bone remodeling, identifying safe and effective electromagnetic field parameters, and combining basic research with technological invention to develop scientifically grounded, advanced key technologies for innovative electromagnetic treatment devices targeting bone remodeling diseases. In conclusion, electromagnetic fields and multiple physical factors have the potential to prevent and treat bone remodeling diseases, and have significant application prospects.

ObjectiveTo combine metabolomics， proteomics， and transcriptomics to analyze the biological characteristics of damp-heat toxin accumulation syndrome and damp-heat accumulation syndrome in acute gout. MethodsBlood samples were collected from 15 patients with damp-heat toxin accumulation syndrome and 15 patients with damp-heat accumulation syndrome in acute gout in clinical practice. Metabolomics technology was applied to detect serum metabolites， and an orthogonal partial sample least squares discriminant analysis model was constructed to screen for metabolites with significant intergroup changes， and enrichment pathway analysis and receiver operating characteristic （ROC） curve analysis were performed. Astral data independence acquisition （DIA） was used to detect serum proteins， perform principal component analysis and screen differential proteins， demonstrate differential ploidy by radargram， apply subcellular localisation to analyse protein sources， and finally apply weighted gene co-expression network analysis （WGCNA） to find key proteins. Transcriptome sequencing technology was also applied to detect whole blood mRNA， screen differential genes and perform WGCNA， and construct machine learning models to screen key genes. ResultsMetabolome differential analysis revealed 62 differential metabolites in positive ion mode and 26 in negative ion mode. These differential metabolites were mainly enriched in the mTOR signaling pathway and FoxO signaling pathway， with trans-3,5-dimethoxy-4-hydroxycinnamaldehyde， guanabenz， 4-aminophenyl-1-thio-beta-d-galactopyranoside showing the highest diagnostic efficacy. The proteome differential analysis found that 55 proteins up-regulated and 20 proteins down-regulated in the samples of damp-heat toxin accumulation syndrome. Notably， myelin basic protein （MBP）， transferrin （TF）， DKFZp686N02209， and apolipoprotein B （APOB） showed the most significant differences in expression. Differential proteins were mainly enriched in pathways related to fat digestion and absorption， lipid and atherosclerosis， and cholesterol metabolism. WGCNA showed the highest correlation between damp-heat toxin accumulation syndrome and the brown module， with proteins in this module primarily enriched in the hypoxia-inducible factor 1 （HIF-1） signaling pathway and lipid and atherosclerosis. Transcriptomic differential analysis identified 252 differentially expressed genes， with WGCNA indicating the highest correlation between damp-heat toxin accumulation syndrome and the midnight blue module. The random forest （RF） model was identified as the optimal machine learning model， predicting apolipoprotein B receptor （APOBR）， far upstream element-binding protein 2 （KHSRP）， POU domain class 2 transcription factor 2 （POU2F2）， EH domain-containing protein 1 （EHD1）， and family with sequence similarity 110A （FAM110A） as key genes. Integrated multi-omics analysis suggested that damp-heat toxin accumulation syndrome in the acute phase of gout is closely associated with lipid metabolism， particularly APOB. ConclusionCompared to damp-heat accumulation syndrome in the acute phase of gout， damp-heat toxin accumulation syndrome is more closely associated with lipid metabolism， particularly APOB， and lipid metabolism disorders contribute to the development of damp-heat toxin accumulation syndrome in patients with acute gout.

Objective To investigate the new-onset conduction block after transcatheter aortic valve replacement (TAVR) and summarize the relevant experience. Methods The perioperative data of TAVR patients in the Second Hospital of Hebei Medical University from January 2016 to February 2023 were collected, and the new-onset incidence of conduction block after TAVR was analyzed retrospectively. Results Finally 352 patients were included, including 225 males and 127 females, with an average age of (67.2±5.1) years, among whom 256 patients were treated with Venus-A valves, 69 patients with Vita-Flow valves, and 27 patients with J-Valve valves. There were 38 (10.8%) patients of new-onset postoperative block. There were 6 (1.7%) patients of new-onset postoperative grade Ⅲ atrioventricular block, including 5 (2.0%) patients of Venus-A and 1 (1.4%) patient of Vita-Flow. Conduction function was restored in 2 patients within 14 days after surgery, and failed to be restored in 4 patients, who then received permanent pacemaker implantation in the Department of Cardiology. There were 27 (7.7%) patients of new left bundle branch block after surgery, including 22 (8.6%) patients of Venus-A, 4 (5.8%) patients of Vita-Flow and 1 (3.7%) patient of J-Valve; and conduction function was restored within 7 days after surgery in 23 patients, and 5 (1.4%) patients developed new right bundle branch blocks after surgery including 4 (1.5%) patients of Venus-A and 1 (1.4%) patient of Vita-Flow. Conclusion New-onset conduction block is a common complication after TAVR, and the new-onset rate of left bundle branch block is the highest, followed by the grade Ⅲ atrioventricular block. Mastering reasonable methods and applying appropriate strategies can effectively reduce the new-onset rate of postoperative conduction block and improve the overall success rate of TAVR surgery.

ObjectiveThis paper used the AGREE Ⅱ guideline evaluation tool to evaluate the quality of 14 clinical guidelines for acute myocardial infarction，aiming to provide reference for the formulation and improvement of the guidelines. MethodsClinical guidelines and expert consensus related to acute myocardial infarction were searched by web search. The search period ranges from January 1，2019 to November 1，2024 in CNKI，VIP，Wanfang Data，SinoMed，Web of Science，OVID， the International Guidelines Collaboration Network （GIN），the UK National Institute for Health and Clinical Excellence （NICE），Yimaitong， and other platforms. Three researchers independently screened the literature and used AGREE Ⅱ to score the screening results. After ensuring that the researchers have a consistent understanding of each guideline，the quality of the guidelines was evaluated. After that，the ratings were analyzed by layer according to the issuing agency，category，method of formulation，and funding situation and compared longitudinally by rating time. The clinical guidelines and expert consensus were compared in terms of content and evidence. ResultsA total of 14 guidelines and consensus were included. The results of AGREE Ⅱ in the six areas in descending order were scope and purpose （62.82%±10.43%），rigor （62.40%±12.77%），editorial independence （62.11%±22.26%），participants （61.42%±11.65%），clarity of expression （59.98%±9.62%），and application （52.94%±16.90%） . Eleven of the guidelines were at level B， and three were at level A. In the stratified analysis，the score of the guideline formulated by the Chinese Medical Doctor Association was lower. There was little difference between the scores of Chinese/Western and Western medicine guidelines. The average score of the guidelines was higher than the consensus. Funded guidelines and consensus scores were higher. In the longitudinal comparison，the highest number of guidelines were developed in 2020 and 2021，while those developed in 2023 scored the highest. In the differential comparison analysis，the content of the guidelines was more comprehensive， and the evidence level was higher，while the content of the consensus was more novel， and the evidence was less. ConclusionThe AGREE Ⅱ score of the clinical guidelines for acute myocardial infarction is generally moderate，and there is room for improvement in terms of applicability. At the same time，the content quality of expert consensus should be improved，and more efforts should be made to develop and apply Chinese medicine guidelines for complications such as heart failure and microcirculatory obstruction after acute myocardial infarction.

Objective: To establish a method for determining the molecular weight and molecular weight distribution of Poly(Lactide-co-Glycolide Acid) (PLGA) using Size Exclusion Chromatography-Refractive Index-Multiangle Laser Light Scattering (SEC-RI-MALLS) and Size Exclusion Chromatography-Refractive Index (SEC-RID), and to compare the results obtained from these two methods.
Methods: For SEC-RI-MALLS, tetrahydrofuran was used as the mobile phase, Shodex GPC KF-803L was employed as the chromatographic column with a flow rate of 1 mL·min^-1, column temperature at 30 ℃, and an injection volume of 100 μL. For SEC-RID, tetrahydrofuran was also used as the mobile phase, Agilent PLgel 5 μm MIXD-D was used as the chromatographic column with a flow rate of 1 mL·min^-1, column temperature at 30 ℃, differential detector temperature at 35 ℃, and an injection volume of 20 μL. The molecular weight and molecular weight distribution were calculated using Agilent’s GPC software. The newly established methods were validated methodologically, and the molecular weight and molecular weight distribution of 13 batches of samples were determined.
Results: The precision, accuracy, stability, and repeatability tests for SEC-RI-MALLS showed RSD values of 1.35%, 1.58%, 1.53%, and 1.26%, respectively. The SEC-RID method exhibited good linearity (r=0.999 9), with RSD values for precision, accuracy, stability, and repeatability tests (n=6) of 2.05%, 1.62%, 1.30%, and 2.97%, respectively. The results obtained from SEC-RI-MALLS were lower than those from SEC-RID, and the molecular weight distribution coefficient was smaller, but the results from the paired T-test performed with the value measured by SEC-RID method and the value measured by SEC-RI-MALLS method multiplied a conversion coefficient of 1.5 showed no significant difference between the two methods.
Conclusion: Both methods are stable and reliable, and can be used for the determination of PLGA molecular weight and molecular weight distribution based on the specific situations.

ObjectiveThe rapid advancement of bioanalytical technologies has heightened the demand for high-throughput, label-free, and real-time cellular analysis. Electrochemical impedance spectroscopy (EIS) operating in the GHz frequency range (GHz-EIS) has emerged as a promising tool for characterizing cell suspensions due to its ability to rapidly and non-invasively capture the dielectric properties of cells and their microenvironment. Although GHz-EIS enables rapid and label-free detection of cell suspensions, significant challenges remain in interpreting GHz impedance data for complex samples, limiting the broader application of this technique in cellular research. To address these challenges, this study presents a novel method that integrates GHz-EIS with deep learning algorithms, aiming to improve the precision of cell suspension concentration identification and quantification. This method provides a more efficient and accurate solution for the analysis of GHz impedance data. MethodsThe proposed method comprises two key components: dielectric property dataset construction and backpropagation (BP) neural network modeling. Yeast cell suspensions at varying concentrations were prepared and separately introduced into a coaxial sensor for impedance measurement. The dielectric properties of these suspensions were extracted using a GHz-EIS dielectric property extraction method applied to the measured impedance data. A dielectric properties dataset incorporating concentration labels was subsequently established and divided into training and testing subsets. A BP neural network model employing specific activation functions (ReLU and Leaky ReLU) was then designed. The model was trained and tested using the constructed dataset, and optimal model parameters were obtained through this process. This BP neural network enables automated extraction and analytical processing of dielectric properties, facilitating precise recognition of cell suspension concentrations through data-driven training. ResultsThrough comparative analysis with conventional centrifugal methods, the recognized concentration values of cell suspensions showed high consistency, with relative errors consistently below 5%. Notably, high-concentration samples exhibited even smaller deviations, further validating the precision and reliability of the proposed methodology. To benchmark the recognition performance against different algorithms, two typical approaches—support vector machines (SVM) and K-nearest neighbor (KNN)—were selected for comparison. The proposed method demonstrated superior performance in quantifying cell concentrations. Specifically, the BP neural network achieved a mean absolute percentage error (MAPE) of 2.06% and an R² value of 0.997 across the entire concentration range, demonstrating both high predictive accuracy and excellent model fit. ConclusionThis study demonstrates that the proposed method enables accurate and rapid determination of unknown sample concentrations. By combining GHz-EIS with BP neural network algorithms, efficient identification of cell concentrations is achieved, laying the foundation for the development of a convenient online cell analysis platform and showing significant application prospects. Compared to typical recognition approaches, the proposed method exhibits superior capabilities in recognizing cell suspension concentrations. Furthermore, this methodology not only accelerates research in cell biology and precision medicine but also paves the way for future EIS biosensors capable of intelligent, adaptive analysis in dynamic biological research.

Purpose: Erectile dysfunction (ED) is a common male sexual dysfunction. Gut microbiota plays an important role in various diseases. To investigate the effects and mechanisms of intestinal flora dysregulation induced by high-fat diet (HFD) on erectile function. Materials and Methods: Male Sprague–Dawley rats aged 8 weeks were randomly divided into the normal diet (ND) and HFD groups. After 24 weeks, a measurement of erectile function was performed. We performed 16S rRNA sequencing of stool samples. Then, we established fecal microbiota transplantation (FMT) rat models by transplanting fecal microbiota from rats of ND group and HFD group to two new groups of rats respectively. After 24 weeks, erectile function of the rats was evaluated and 16S rRNA sequencing was performed, and serum samples were collected for the untargeted metabolomics detection. Results: The erectile function of rats and the species diversity of intestinal microbiota in the HFD group was significantly lower, and the characteristics of the intestinal microbiota community structure were also significantly different between the two groups. The erectile function of rats in the HFD-FMT group was significantly lower than that of rats in the ND-FMT group. The characteristics of the intestinal microbiota community structure were significantly different. In the HFD-FMT group, 27 metabolites were significantly different and they were mainly involved in the several inflammation-related pathways. Conclusions Intestinal microbiota disorders induced by HFD can damage the intestinal barrier of rats, change the serum metabolic profile, induce low-grade inflammation and apoptosis in the corpus cavernosum of the penis, and lead to ED.

Background: The transvenous approach to the treatment of cerebral arteriovenous malformation (AVM) is difficult and requires strict blood pressure and blood flow control; however, the cure rate is very high. Appropriate blood pressure control techniques can greatly benefit these patients.Case: A 55-year-old male patient was found to have an aneurysm complicated with a cerebral AVM (length: 2.0 cm, width: 1.6 cm, height: 1.2 cm). Aneurysm embolization was considered for the first-stage surgery and transvenous AVM embolization for the second-stage surgery. Rapid ventricular pacing (RVP) provided a stable blood flow environment for the surgery, which was completed successfully. Conclusion RVP can thus provide an ideal condition for the embolization of cerebral AVM through the transvenous approach and can be a viable surgical option.

Background: s/Aims: Sarcomatoid hepatocellular carcinoma (HCC) is a rare histological subtype of HCC characterized by extremely poor prognosis; however, its molecular characterization has not been elucidated. Methods: In this study, we conducted an integrated multiomics study of whole-exome sequencing, RNA-seq, spatial transcriptome, and immunohistochemical analyses of 28 paired sarcomatoid tumor components and conventional HCC components from 10 patients with sarcomatoid HCC, in order to identify frequently altered genes, infer the tumor subclonal architectures, track the genomic evolution, and delineate the transcriptional characteristics of sarcomatoid HCCs. Results: Our results showed that the sarcomatoid HCCs had poor prognosis. The sarcomatoid tumor components and the conventional HCC components were derived from common ancestors, mostly accessing similar mutational processes. Clonal phylogenies demonstrated branched tumor evolution during sarcomatoid HCC development and progression. TP53 mutation commonly occurred at tumor initiation, whereas ARID2 mutation often occurred later. Transcriptome analyses revealed the epithelial–mesenchymal transition (EMT) and hypoxic phenotype in sarcomatoid tumor components, which were confirmed by immunohistochemical staining. Moreover, we identified ARID2 mutations in 70% (7/10) of patients with sarcomatoid HCC but only 1–5% of patients with non-sarcomatoid HCC. Biofunctional investigations revealed that inactivating mutation of ARID2 contributes to HCC growth and metastasis and induces EMT in a hypoxic microenvironment. Conclusions We offer a comprehensive description of the molecular basis for sarcomatoid HCC, and identify genomic alteration (ARID2 mutation) together with the tumor microenvironment (hypoxic microenvironment), that may contribute to the formation of the sarcomatoid tumor component through EMT, leading to sarcomatoid HCC development and progression.