ObjectiveTo define hyaluronidase treatment parameters that efficiently remove the extracellular matrix from zygotes without impairing embryo development， thereby providing a basis for standardized assisted reproductive procedures. MethodsMouse zygotes were treated with hyaluronidase at 40， 80， or 120 IU/mL for 60， 90， or 120 s. Following treatment， embryos were cultured in Krebs-ringer bicarbonate-based solution for organismal media （KSOM） medium， and blastocyst formation was monitored using a Time-lapse imaging system. ResultsA concentration of 40 IU/mL was insufficient for effective matrix removal， whereas 120 IU/mL markedly reduced blastocyst formation. In contrast， 80 IU/mL achieved efficient matrix clearance with minimal impact on development. Blastocyst rates were comparable between the 60 s and 90 s groups， with a slight advantage for the 60 s under the experimental conditions. ConclusionHyaluronidase treatment at 80 IU/mL for 60 s represents optimal processing conditions for mouse zygotes. These findings provide experimental basis and standardized reference for embryo handling in assisted reproductive technologies.

ObjectiveTo investigate the changes in chemical components of Gardeniae Fructus（GF） before and after being charred， providing data support for research on the material basis of GF Carbonisata（GFC）. MethodsUltra-performance liquid chromatography-quadrupole-electrostatic field orbitrap high-resolution mass spectrometry（UPLC-Q-Orbitrap MS/MS） was used to conduct a comprehensive analysis of the chemical components in GF and GFC under positive and negative ion modes with Compound Discoverer 3.3 software and online database. Then， principal component analysis and partial least squares-discriminant analysis in SIMCA14.1 software were used to analyze the MS data of each sample. Based on the principle of variable importance in the projection（VIP） value>1， differential secondary and primary metabolites before and after carbonization were screened. In addition， MetaboAnalyst website was used for pathway enrichment of Kyoto Encyclopedia of Genes and Genomes（KEGG）， so as to provide a reference for clarifying the processing mechanism. ResultsA total of 185 components were identified， including 96 secondary metabolites and 89 primary metabolites. These components were classified into nine categories， primarily including iridoid glycosides， flavonoids， and terpenoids， their fragmentation pathways were also analyzed. Simultaneously， multivariate statistical analysis was performed on the secondary and primary metabolites， identifying 70 and 59 differential metabolites， respectively. The secondary metabolites were enriched in two metabolic pathways， including C5-branched dibasic acid metabolism and flavonoid and flavonol biosynthesis， while the primary differential metabolites were enriched in seven pathways such as linoleic acid metabolism and tyrosine metabolism. ConclusionThe chemical components of GF change significantly after carbonization， with a significant decrease in the contents of iridoid glycosides and terpenoids such as hydroxyisogeniposide， crocin Ⅱ， crocetin， and jasminoside B. while the contents of 4-hydroxycoumarin， geniposidic acid， gentiopicroside， and gardenoside methyl ester increase significantly. This change is presumed to be associated with the enhanced cooling and hemostatic effects of the processed products. The identified key components provide a basis for elucidating the material basis underlying the efficacy changes before and after carbonization.

Background: Sex-based differences often influence the therapeutic efficacy and safety of medications. Semen Cuscutae is a traditional tonic botanical drug with sex-specific characteristics, traditionally indicated for conditions such as impotence (exclusive to males) and restless fetus (exclusive to pregnant females). However, most existing studies have focused on a single sex. Objective: To evaluate the sex-specific biological effects of Semen Cuscutae in rats and explore its molecular mechanisms, with the aim of uncovering its pharmacological characteristics through a multiomics approach. Methods: A traditional aqueous extract of Semen Cuscutae (SCA) was used as the experimental material. Forty adult Sprague-Dawley rats (equal numbers of males and females) were randomly divided into 4 groups: male control, male SCA treatment (240 mg/kg), female control, and female SCA treatment (240 mg/kg), with 10 rats in each group. The biological effects were comprehensively evaluated using a combination of open field test, biochemical analyses, proteomics, and gut microbiota profiling. Results: As a tonic botanical drug, SCA appeared to directly affect the mental and behavioral state of rats. It significantly altered the time spent by rats in the center area during the open field test, showing a sex-dependent reversal of behaviors. Proteomic analysis of brain tissue identified 624 differentially expressed proteins across the groups, with 10 key differentially expressed proteins related to sex differences, including fibroblast growth factor receptor 3, transcription elongation factor A protein-like 1, 40S ribosomal protein S25, neural cell adhesion molecule, and anion exchange protein 2 (SLC4A2). Enrichment analysis revealed that in male rats, SCA upregulated proteins involved in biological processes such as ribosome function and energy derivation, supporting protein synthesis and enhancing energy supply, showing an overall gain effect. In contrast, in female rats, SCA downregulated proteins associated with processes such as positive regulation of target of rapamycin (TOR) signaling and vesicle transport, suggesting suppression of neuronal signaling and material transport, indicative of a shift toward a more restrained physiological state. Furthermore, SCA reduced gut microbiota diversity in female rats but increased it in males, including the abundance of Akkermansia, which may serve as a crucial mediator. Conclusion: Overall, the biological effects of SCA differ significantly between male and female rats, with evidence suggesting greater health benefits in males. These findings help elucidate the scientific basis of its traditional applications and provide guidance for the precise application of SCA as a functional health food.

Objective To identify high-risk factors for healthcare-associated infection(HAI)in patients in inten-sive care units(ICUs),and develop a quick response(QR)code-based APP prediction tool.Methods Information of inpatients in general ICUs of three hospitals in Guizhou Province from January to December 2024 were collected.Risk factors were analyzed with a logistic regression model.QR code-based APP was constructed and validated.Results A total of 1 782 patients in general ICUs of three hospitals in Guizhou Province in 2024 were included in the analysis,out of which 410 were HAI cases,and the incidence of HAI was 23.01％.Multivariate logistic regre-ssion analysis results of HAI in ICU inpatients showed that regional gross domestic product(GDP)≥58 685 Yuan,performing pathogen culture during this hospitalization,history of diabetes mellitus,history of cancer,length of hospital stay ≥7 days before infection,and duration of persistent fever＞5 days before infection were independent risk factors for HAI in ICU patients(all P＜0.05).The discrimination of the model(area under the receiver operating characteristic curve[AUC]of 0.841),calibration(Brier score of 0.129),and clinical effectiveness(net benefit of 11.4％when the risk threshold was 5％-74％)all performed well.Conclusion The QR code-based APP prediction tool is of great significance for scientific research transformation and precise HAI control.

Objective To investigate the similarities and differences in the mechanisms of Huatan drugs and Qushi drugs in treating obesity-related polycystic ovary syndrome(PCOS)and to identify the key active components.Methods Components and targets of Huatan drugs and Qushi drugs were screened by HERB database.The OmicsCloud platform was employed for enrichment analyses of targets by Gene Ontology and Kyoto Encyclopedia of Genes and Genomes.Pathway networks were constructed by Cytoscape 3.8.0 software to visualize pathway differences.PCOS-related key targets were identified by Gene Expression Omnibus database and R 4.2.2 software.Molecular docking techniques were used to predict binding affinities between the key components and targets,followed by validation through molecular dynamics simulations.Results Huatan drugs and Qushi drugs shared 52 active components and 81 targets.Common pathways involved lipid metabolism,insulin regulation,hormonal regulation,and oocyte maturation,aligning with the pathological mechanisms of obesity-related PCOS.Huatan drugs exhibited superior efficacy in hormonal and insulin regulation,while Qushi drugs excelled in vitamin metabolism and anti-inflammatory pathways.Quercetin,β-sitosterol,and stigmasterol were identified as key components.Stigmasterol demonstrated optimal binding with PCOS-associated key targets Churchill domain-containing protein 1(CHURC1)and tumor necrosis factor ligand superfamily member 11(TNFSF11),while molecular dynamics simulations confirmed the robust stability of β-sitosterol and TNFSF11 binding.Conclusion This study elucidates potential targets and mechanisms of Huatan drugs and Qushi drugs in treating obesity-related PCOS,providing insights for identifying key active components and guiding clinical application.

Aim To investigate the effect of p-AMPK activity on autophagy in different subtypes of MDA-MB-231(triple-negative breast cancer cells)and MCF-7(estrogen receptor-positive cells)and its regulatory mechanism.Methods MDA-MB-231 cells were trea-ted with EBSS,Baf-A1,and EBSS+Baf-A1 for four hours,and MCF-7 cells for eight hours.The effects of autophagy on cell proliferation and apoptosis were ob-served,mitochondrial morphology was examined,and the expression of autophagy markers LC3B,P62,LAMP1,TOM20,AMPK,p-AMPK,ULK1,and Bec-lin1/VPS34 proteins was detected.The autophagy pathway was validated by inhibiting AMPK activity.Results Breast cancer cells underwent autophagy af-ter starvation induction(EBSS),with inconsistent au-tophagy processes observed in different subtypes of breast cancer cells.Autophagy inhibited cell prolifera-tion.In MDA-MB-231 cells,autophagy led to an in-crease in p-AMPK levels and a decrease in ULK1 lev-els,initiating autophagy through p-AMPK activation of ULK1.In MCF-7 cells,both p-AMPK and ULK1 levels decreased after autophagy,suggesting that autophagy might not be mediated by p-AMPK activation.Conclu-sions MDA-MB-231 cells primarily initiate autophagy by directly activating ULK1 by p-AMPK,independent of the MTOR pathway.In MCF-7 cells autophagy might be triggered by inhibiting MTOR through AMPK activity or directly activating MTOR through other up-stream factors.Regulating p-AMPK activity based on the autophagy pathways in different cell subtypes could enable more precise targeting and treatment of different types of breast cancer.

AIM:This study aims to investigate the role and mechanism of proprotein convertase subtilisin/kexin type 9(PCSK9)in ovarian cancer.METHODS:We compared the expression levels of PCSK9 between ovarian cancer specimens and their corresponding adjacent non-cancerous tissues,while also assessing its expression in various ovarian cancer cell lines.Using a shRNA strategy,we reduced the expression of PCSK9 in ovarian cancer cell lines cul-tured in vitro,with confirmation via Western blot.The effects of PCSK9 downregulation on the proliferation,migration,and invasion of ovarian cancer cells were evaluated through EdU,colony formation,and Transwell assays.Additionally,we analyzed the impact of PCSK9 down-regulation on the MAPK/ERK signaling pathway using Western blot analysis.RE-SULTS:PCSK9 was significantly upregulated in ovarian cancer tissues and cell lines(P＜0.01).Downregulation of PC-SK9 resulted in a significant decrease in cell proliferation,migration,and invasion(P＜0.01).Western blot analysis dem-onstrated that PCSK9 knockdown led to reduced expression levels of key molecules within the MAPK/ERK signaling path-way(P＜0.01).CONCLUSION:PCSK9 promotes the proliferation and invasion of ovarian cancer cells by activating MAPK/ERK signaling pathway.

Aim To investigate the effect of p-AMPK activity on autophagy in different subtypes of MDA-MB-231(triple-negative breast cancer cells)and MCF-7(estrogen receptor-positive cells)and its regulatory mechanism.Methods MDA-MB-231 cells were trea-ted with EBSS,Baf-A1,and EBSS+Baf-A1 for four hours,and MCF-7 cells for eight hours.The effects of autophagy on cell proliferation and apoptosis were ob-served,mitochondrial morphology was examined,and the expression of autophagy markers LC3B,P62,LAMP1,TOM20,AMPK,p-AMPK,ULK1,and Bec-lin1/VPS34 proteins was detected.The autophagy pathway was validated by inhibiting AMPK activity.Results Breast cancer cells underwent autophagy af-ter starvation induction(EBSS),with inconsistent au-tophagy processes observed in different subtypes of breast cancer cells.Autophagy inhibited cell prolifera-tion.In MDA-MB-231 cells,autophagy led to an in-crease in p-AMPK levels and a decrease in ULK1 lev-els,initiating autophagy through p-AMPK activation of ULK1.In MCF-7 cells,both p-AMPK and ULK1 levels decreased after autophagy,suggesting that autophagy might not be mediated by p-AMPK activation.Conclu-sions MDA-MB-231 cells primarily initiate autophagy by directly activating ULK1 by p-AMPK,independent of the MTOR pathway.In MCF-7 cells autophagy might be triggered by inhibiting MTOR through AMPK activity or directly activating MTOR through other up-stream factors.Regulating p-AMPK activity based on the autophagy pathways in different cell subtypes could enable more precise targeting and treatment of different types of breast cancer.

Peritoneal metastasis is a key factor in the poor prognosis of advanced gastrointestinal cancer patients. Traditional radiological diagnostic faces challenges such as insufficient sensitivity. Through technologies like radiomics and deep learning, artificial intelligence can deeply analyze the tumor heterogeneity and microenvironment features in medical images, revealing markers of peritoneal metastasis and constructing high-precision predictive models. These technologies have demonstrated advantages in tasks such as predicting peritoneal metastasis, assessing the risk of peritoneal recurrence, and identifying small metastatic foci during surgery. This paper summarizes the representative progress and application prospects of medical imaging artificial intelligence in the diagnosis and treatment of peritoneal metastasis, and discusses potential development directions such as multimodal data fusion and large model. The integration of medical imaging artificial intelligence with clinical practice is expected to advance personalized and precision medicine in the diagnosis and treatment of peritoneal metastasis in gastrointestinal cancers.

Time rhythm and the immune system play crucial roles in the pathogenesis of allergic rhinitis.Traditional Chinese medicine(TCM)believes that the circulation of qi and blood in lung meridian follows the principle of"yang during the day,yin at night",which has a defensive function to protect the body from external pathogens.Qi stagnation in lung meridian and impaired qi and blood circulation can lead to the invasion of external pathogens,exacerbating allergic reactions,especially during the active period of the lung meridian,when the immune system is most sensitive to allergens.Based on this,this paper proposes the concept of"bidirectional regulation among meridian,time rhythm,and immune system",and in combination with TCM theory of midnight-noon and ebb-flow doctrine,analyzes the fluctuations of allergic rhinitis symptoms and the temporal changes of meridian qi and blood,and reveals the rhythmic relationship between meridian activity and immune response.This paper combines existing clinical and experimental studies to support this hypothesis,integrating the time dimension into traditional TCM syndrome differentiation and treatment,offering a more individualized treatment approach.This concept not only provides novel scientific evidence for TCM treatment of allergic rhinitis,but also offers theoretical support for optimizing treatment timing and intervention strategies.