ObjectiveTo investigate the migration and distribution characteristics of chemical constituents in blood and hippocampal tissues before and after vinegar processing of Citri Reticulatae Pericarpium Viride（CRPV）， and to explore the potential material basis and mechanisms underlying their regulatory effects on emotional disorders by comparing the effects of raw and vinegar-processed products of CRPV. MethodsUltra-performance liquid chromatography-quadrupole-time-of-flight mass spectrometry（UPLC-Q-TOF-MS/MS） was employed to characterize and identify the chemical constituents of raw and vinegar-processed products of CRPV extracts， as well as their migrating components in blood and hippocampal tissues after oral administration. Reference standards， databases， and relevant literature were utilized for compound annotation， with data processing performed using PeakView 1.2 software. Seventy male C57BL/6 mice were randomly divided into seven groups， including the blank group， model group， diazepam group（2.5 mg·kg^-1）， raw CRPV low/high dose groups（0.6， 1.2 g·kg^-1）， and vinegar-processed CRPV low/high dose groups（0.6， 1.2 g·kg^-1）， with 10 mice per group. Except for the blank group， all other groups underwent chronic restraint stress（2 h·d^-1） for 20 d. Each drug-treated group received oral administration at the predetermined dose starting 10 d after modeling， with a total treatment duration of 10 d. Following model-based drug administration， mice underwent open-field， forced swimming， and elevated plus maze tests. After anesthesia with isoflurane， whole brains were collected from each group of mice， and hippocampi were dissected. Reactive oxygen species（ROS） level in hippocampal tissues was quantified by enzyme-linked immunosorbent assay（ELISA）. Hematoxylin-eosin（HE） staining was used to observe hippocampal tissue morphology. Immunofluorescence was performed to detect neuronal nuclei（NeuN） and peroxisome proliferator-activated receptor alpha（PPARα） expressions in hippocampal tissue. Then， pharmacodynamic evaluations were conducted to assess the effects of raw and vinegar-processed CRPV on mood disorders， exploring the potential mechanisms. ResultsVinegar processing caused significant changes in the chemical composition of CRPV， with 18 components showing increased relative content and 35 components showing decreased relative content. The primary changes occurred in flavonoid compounds， including 20 flavonoids， 20 flavonoid glycosides， 3 triterpenes， 3 phenolic acids， 1 alkaloid， and 6 other compounds. Twenty-one components were detected in blood（15 methoxyflavones， 4 flavonoid glycosides， and 2 phenolic acids）， with 17 shared between raw and vinegar-processed CRPV. Seven components reached hippocampal tissues（all common to both forms）. In regulating emotional disorders， Vinegar-processed CRPV exhibited superior antidepressant-like effects compared to raw products. HE staining revealed that both treatments improved hippocampal neuronal morphology， particularly in the damaged CA1 and CA3 regions. Immunofluorescence and ELISA analyses demonstrated that both raw and vinegar-processed CRPV significantly modulated NeuN and PPARα expressions in hippocampal tissue while alleviating oxidative stress induced by excessive ROS（P<0.05）. ConclusionThe chemical composition of CRPV undergoes changes after vinegar processing， but the migrating components in blood and hippocampus are primarily methoxyflavonoids. These components may serve as the potential material basis for activating the PPARα pathway， thereby negatively regulating ROS generation in the hippocampus， reducing oxidative stress， and promoting the development of NeuN-positive neurons. These findings provide experimental evidence for enhancing quality standards， pharmacodynamic material research， and active drug development of raw and vinegar-processed CRPV.

ObjectiveIn traditional Chinese medicine (TCM), the foundational doctrine that the eyes reflect the essence of the internal viscera establishes ocular observation as a cornerstone of diagnostic practice. Specifically, the morphological characteristics and coloration variations of the scleral microvasculature serve as critical clinical indicators for assessing the dynamic balance of Qi and Blood, as well as the pathological status of internal organs. Historically, however, TCM eye diagnosis has relied predominantly on the subjective clinical experience and visual acuity of individual practitioners, leading to inherent challenges in standardization and reproducibility. While automated computer-aided diagnostic systems offer a promising solution, existing vessel segmentation algorithms encounter significant domain-specific bottlenecks when applied to scleral imagery. These challenges primarily stem from the highly reflective and moist nature of the ocular surface, which generates severe reflective interference. Furthermore, the inherent low contrast of fine capillary networks against complex background textures, compounded by non-uniform illumination, frequently results in high false-positive rates, misdetections, and severe vessel fragmentation. To address these critical limitations and advance the objective quantification of TCM diagnostics, this paper proposes a novel, highly robust sclera vessel segmentation framework that innovatively integrates Frangi-Sato dual-filter adaptive enhancement with pixel-level reflection detection. MethodsThe proposed methodology systematically addresses the segmentation pipeline through three synergistic stages. First, to overcome the structural limitations of single-filter approaches, a multi-scale weighted fusion strategy is meticulously designed to harness the complementary extraction capabilities of both Frangi and Sato filters. This adaptive enhancement optimally balances the preservation of main vessel trunk continuity with the heightened sensitivity required for delineating delicate, low-contrast peripheral capillaries. Second, to tackle the persistent issue of reflective highlights, a sophisticated multi-feature synergistic reflection detection module is introduced. By jointly analyzing local information entropy, gradient field variations, and intensity statistical distributions, this module achieves precise, pixel-level identification and elimination of reflective artifacts without compromising the underlying vascular structures. Finally, a dual-level adaptive thresholding strategy, featuring an innovative “core protection” mechanism, is implemented. This critical step effectively suppresses complex background noise while rigorously preserving the structural and topological integrity of the intricate vessel network, preventing the structural breaks often seen in conventional binarization methods. ResultsThe efficacy of the proposed framework was rigorously evaluated using both self-constructed clinical datasets specifically acquired for TCM research and standardized public datasets. Extensive experimental results demonstrate that the proposed method consistently outperforms state-of-the-art traditional approaches and contemporary deep learning models. Specifically, the proposed method achieves a Dice similarity coefficient of approximately 0.71 on the private clinical dataset, and secures the best performance across the majority of quantitative metrics on both datasets. Notably, the framework exhibits exceptional robustness and generalization capabilities in highly challenging scenarios characterized by intense reflective interference, low signal-to-noise ratios, and cross-domain image variations. ConclusionThis study successfully realizes the high-integrity, automated segmentation of scleral vessel networks under complex clinical imaging conditions. By overcoming the fundamental algorithmic challenges of reflection interference and micro-vessel loss, the proposed methodology provides potential support for the digitization, objective standardization, and intelligent advancement of modern TCM eye diagnosis systems.

ObjectiveIn traditional Chinese medicine (TCM), the foundational doctrine that the eyes reflect the essence of the internal viscera establishes ocular observation as a cornerstone of diagnostic practice. Specifically, the morphological characteristics and coloration variations of the scleral microvasculature serve as critical clinical indicators for assessing the dynamic balance of Qi and Blood, as well as the pathological status of internal organs. Historically, however, TCM eye diagnosis has relied predominantly on the subjective clinical experience and visual acuity of individual practitioners, leading to inherent challenges in standardization and reproducibility. While automated computer-aided diagnostic systems offer a promising solution, existing vessel segmentation algorithms encounter significant domain-specific bottlenecks when applied to scleral imagery. These challenges primarily stem from the highly reflective and moist nature of the ocular surface, which generates severe reflective interference. Furthermore, the inherent low contrast of fine capillary networks against complex background textures, compounded by non-uniform illumination, frequently results in high false-positive rates, misdetections, and severe vessel fragmentation. To address these critical limitations and advance the objective quantification of TCM diagnostics, this paper proposes a novel, highly robust sclera vessel segmentation framework that innovatively integrates Frangi-Sato dual-filter adaptive enhancement with pixel-level reflection detection. MethodsThe proposed methodology systematically addresses the segmentation pipeline through three synergistic stages. First, to overcome the structural limitations of single-filter approaches, a multi-scale weighted fusion strategy is meticulously designed to harness the complementary extraction capabilities of both Frangi and Sato filters. This adaptive enhancement optimally balances the preservation of main vessel trunk continuity with the heightened sensitivity required for delineating delicate, low-contrast peripheral capillaries. Second, to tackle the persistent issue of reflective highlights, a sophisticated multi-feature synergistic reflection detection module is introduced. By jointly analyzing local information entropy, gradient field variations, and intensity statistical distributions, this module achieves precise, pixel-level identification and elimination of reflective artifacts without compromising the underlying vascular structures. Finally, a dual-level adaptive thresholding strategy, featuring an innovative “core protection” mechanism, is implemented. This critical step effectively suppresses complex background noise while rigorously preserving the structural and topological integrity of the intricate vessel network, preventing the structural breaks often seen in conventional binarization methods. ResultsThe efficacy of the proposed framework was rigorously evaluated using both self-constructed clinical datasets specifically acquired for TCM research and standardized public datasets. Extensive experimental results demonstrate that the proposed method consistently outperforms state-of-the-art traditional approaches and contemporary deep learning models. Specifically, the proposed method achieves a Dice similarity coefficient of approximately 0.71 on the private clinical dataset, and secures the best performance across the majority of quantitative metrics on both datasets. Notably, the framework exhibits exceptional robustness and generalization capabilities in highly challenging scenarios characterized by intense reflective interference, low signal-to-noise ratios, and cross-domain image variations. ConclusionThis study successfully realizes the high-integrity, automated segmentation of scleral vessel networks under complex clinical imaging conditions. By overcoming the fundamental algorithmic challenges of reflection interference and micro-vessel loss, the proposed methodology provides potential support for the digitization, objective standardization, and intelligent advancement of modern TCM eye diagnosis systems.

Currently, the drug delivery system (DDS) based on nanomaterials has become a hot interdisciplinary research topic. One of the core issues is drug loading and controlled release, in which the key lever is carriers. Vaterite, as an inorganic porous nano-material, is one metastable structure of calcium carbonate, full of micro or nano porous. Recently, vaterite has attracted more and more attention, due to its significant advantages, such as rich resources, easy preparations, low cost, simple loading procedures, good biocompatibility and many other good points. Vaterite, gained from suitable preparation strategies, can not only possess the good drug carrying performance, like high loading capacity and stable loading efficiency, but also improve the drug release ability, showing the better drug delivery effects, such as targeting release, pH sensitive release, photothermal controlled release, magnetic assistant release, optothermal controlled release. At the same time, the vaterite carriers, with good safety itself, can protect proteins, enzymes, or other drugs from degradation or inactivation, help imaging or visualization with loading fluorescent drugs in vitro and in vivo, and play synergistic effects with other therapy approaches, like photodynamic therapy, sonodynamic therapy, and thermochemotherapy. Latterly, some renewed reports in drug loading and controlled release have led to their widespread applications in diverse fields, from cell level to clinical studies. This review introduces the basic characteristics of vaterite and briefly summarizes its research history, followed by synthesis strategies. We subsequently highlight recent developments in drug loading and controlled release, with an emphasis on the advantages, quantity capacity, and comparations. Furthermore, new opportunities for using vaterite in cell level and animal level are detailed. Finally, the possible problems and development trends are discussed.

Objective:To construct the inflammation score(IS)and nutrition-immunity score(NIS)for patients with multiple myeloma(MM),and to verify their prognostic stratification effects and significance.Methods:The clinical data of 129 newly diagnosed MM patients admitted to our hospital from August 2011 to September 2022 were retrospectively analyzed.Univariate and multivariate Cox regression analysis of overall survival(OS)were comducted on clinical parameters,including inflammatory indicators such as red blood cell volume distribution width(RDW)and platelet count(PLT),nutritional-immune indicators such as albumin(ALB),absolute lymphocyte count(ALC),and suppressed immunoglobulin count(S-Ig count).To construct IS and NIS for prognosis,X-tile software and multivariate Cox regression analysis were used to verify the prognostic stratification role and significance of IS and NIS.The time-dependent receiver operating characteristic(ROC)curve,C-index curve,calibration curve,and decision curve analysis(DCA)were used to evaluate the discrimination,accuracy,and clinical net benefit of IS and NIS in predicting overall survival(OS),and compared to the international staging system(ISS).Results:IS was constructed based on the scores of RDW and PLT,and NIS was constructed based on the scores of ALB,ALC,and S-Ig count.According to X-tile analysis and multivariate Cox regression analysis,IS and NIS can divide the patients into three risk strata respectively:low,medium and high IS and NIS groups.The differences in OS and hazard ratio(HR)between the low,medium,and high strata were statistically significant(P＜0.05).IS and NIS are both independent prognostic predictors for MM.The area under the ROC curve(AUC)and C index of IS and NIS for predicting 1-to 7-year OS were greater than those of ISS,and both were greater than 0.7.The prediction results of IS and NIS for 1-,3-,and 5-year OS rates were well consistent with the actual observed results.The DC A curves of IS and NIS for predicting 1-,3-,and 5-year OS were higher than that of ISS in a wide range of threshold probability intervals.Conclusion:IS and NIS have independent predictive significance for OS in MM patients.Their predictive discrimination,accuracy,and clinical net benefit are higher and better than ISS,and they may have potential application value in MM prognosis.

Objective:To construct a competency-oriented assessment index system based on entrustable professional activities (EPAs) for 5-year undergraduate clinical medical students in oncology internship.Methods:From June to December 2023, the scoping review approach and Bicomb 2.0 were used to construct and manage an item pool. The draft of EPAs and competencies was designed based on truncated word frequency. SPSS 25.0 was used for cluster analysis and UCINET 6.0 was used for visualization. Combining the characteristics and consensus of oncology, a multi-center expert group used the KJ method to draft the framework of EPAs and competencies. Subsequently, the expert group defined milestones and mapped the milestones to the framework to establish the assessment system.Results:Based on 26 included studies, a draft was created containing 19 EPA indicators and 72 competency characteristic indicators. After cluster analysis, 13 experts from 6 medical institutions established a framework including 13 EPAs and 10 competencies as well as 50 milestones, leading to the construction of the "EPAs-competencies-milestones" assessment system.Conclusions:The "EPAs-competencies-milestones" assessment system aligns with the trend of reform, demonstrating universality, specificity, and scientificity. It provides a reference for the development and assessment of oncology internship courses in medical universities.

Objective To explore the effect of hypoxia-inducible factor-1α(HIF-1α)inhibitor LW6 on ferroptosis in septic cardiomyopathy rats.Methods Rat septic cardiomyopathy model was prepared using cecal ligation and puncture(CLP)method.Thirty-six specific pathogen-free(SPF)6-8 weeks male SD rats were randomly divided into the sham-operated group,CLP group,CLP+solvent group,LW6 group,ferrostatin-1(Fer-1)group,and LW6+Fer-1 group.The degree of myocardial damage in each group was evaluated through hematoxylin-eosin stai-ning and detection of lactate dehydrogenase and creatine kinase content in cardiac tissue.Myocardial mitochondrial damage was observed by transmission electron microscopy.Ferroptosis level was determined by detecting iron ion concentration,reduced glutathione,malondialdehyde,and reactive oxygen species.Protein expression levels of HIF-1α,solute carrier family 7 member 11(SLC7A11),and glutathione peroxidase 4(GPX4)in cardiac tissue were detected by Western blotting.Results Compared with the CLP group and the CLP+solvent group,the LW6 group could ameliorate myocardial damage,alleviate mitochondrial damage,inhibit ferroptosis-related indicators(all P＜0.05),reduce HIF-1α protein expression levels(P＜0.05),and enhance SLC7A11 and GPX4 protein expression levels(both P＜0.05).Conclusion LW6 decreases HIF-1α expression and ferroptosis levels through the SLC7A11/GPX4 pathway,and ameliorates sepsis-induced cardiomyopathy.

Objective:To construct and validate a competency-oriented entrustable professional activities (EPAs)-Competency-Milestones system for assessment of laparoscopic skills (ESALS).Methods:A research team composed of 15 members from five medical institutions was established. Taking the Staged Training and Assessment of Laparoscopic Skills program as the basis for EPAs, ESALS was constructed through scoping review and behavioral event interviews and the use of the Kawakita Jiro method. ESALS was applied to evaluate 49 trainees and 10 specialists (including 5 novices and 5 experts) on basic and advanced laparoscopic skills, respectively, in comparison with two other assessment tools—the Training and Assessment of Basic Laparoscopic Techniques (TABLT) and the Global Operative Assessment of Laparoscopic Skills (GOALS). Perform Mann Whitney U test using SPSS 23.0 software, and use Spearman coefficient for correlation analysis.Results:Through reviewing 13 literuature articles and interviewing 10 senior surgeons, the ESALS was developed, comprising 10 EPAs, 8 dimensions of competency characteristics, and 5 entrustable levels. In the basic skills evaluation, the ESALS score was significantly positively correlated with the TABLT score ( R=0.881, P<0.001). In the advanced skills evaluation, significant differences were observed between the novice and expert groups in all the ESALS competency scores (all P<0.05), while no difference was detected in the GOALS score of tissue handling ability. Conclusions:ESALS provides comprehensive evaluation, detailed standards, and precise feedback, with comparable efficacy to conventional tools. Future work should focus on expanding sample size to verify its generalizability and developing an electronic tool to enhance application efficiency.

Objective:To explore the predictive value of platelet aggregation function for acute kidney injury (AKI) in sepsis patients based on decision curve.Methods:A retrospective study was conducted to collect and analyze the clinical data of 120 sepsis patients admitted to the Affiliated Hospital of Jiangnan University from January 2021 to December 2023. According to the incidence of AKI during hospitalization, they were divided into AKI group (37 cases) and non-AKI group (83 cases). The general data, platelet aggregation function index (platelet aggregation rate) and other laboratory indexes of the two groups were collected and compared. Logistic regression model was used to analyze the relationship between AKI and main indexes of platelet aggregation function in patients with sepsis. The area under the curve (AUC) was obtained by drawing the receiver operating characteristic (ROC) curve, and the predictive value of platelet aggregation function on AKI in patients with sepsis was analyzed. R language software was used to construct a nomogram model of platelet aggregation function combined with other main indicators to predict AKI in patients with sepsis. Based on the decision curve, the predictive efficacy of the model on AKI in patients with sepsis was analyzed.Results:The platelet aggregation rate in the AKI group was lower than that in the non-AKI group: (56.23 ± 7.86)% vs. (68.79 ± 8.54)%, and the thrombin time was longer than that in the non-AKI group: 17.00 (16.50, 18.00) s vs. 16.00 (15.00, 17.00) s. The levels of D-dimer, C-reactive protein and procalcitonin were higher than those in the non-AKI group: (1.55 ± 0.45) mg/L vs. (1.32 ± 0.41) mg/L, (107.53 ± 18.41) mg/L vs. (99.86 ± 17.25) mg/L, (3.10 ± 0.46) μg/L vs. (2.88 ± 0.42) μg/L, and the differences were statistically significant ( P<0.05). The results of constructing a Logistic regression model showed that AKI in sepsis patients may be related to abnormal levels of platelet aggregation rate, thrombin time, C-reactive protein and procalcitonin ( P<0.05). The ROC curve was drawn to obtain the corresponding AUC: the AUC of platelet aggregation rate predicting sepsis complicated with AKI was 0.860 (95% CI 0.789 to 0.931), which had certain predictive value. When the platelet aggregation rate was set to 62.84%, the best predictive value can be obtained, with sensitivity, specificity, and Jorden index of 83.80%, 80.70%, and 0.645, respectively. The nomogram model of platelet aggregation function assisting other major indicators in predicting AKI in sepsis patients had a C-index of 0.904 (95% CI 0.851 to 0.957), indicating good discrimination of the model. Through decision curve analysis of the clinical net benefit of the model, the results showed that the clinical net benefit of the model was higher than that of platelet aggregation rate and other major indicators when applied alone. When the risk threshold was within the range of 0 to 0.81 and 0.97 to 1.00, the model could provide a significant increase in clinical net benefit rate. Conclusions:Platelet aggregation function (platelet aggregation rate) can serve as an early auxiliary predictive indicator for the risk of AKI in sepsis patients, and can assist other major indicators to improve the predictive value of AKI in sepsis patients.

Rheumatoid arthritis(RA)is characterized by bidi-rectional bone remodeling imbalance,clinically termed the "high resorption-low formation" paradox,stemming not only from osteoclast hyperactivation but also critically involving pro-found suppression of osteoblast differentiation and function.No-tably,this suppression cannot be fully attributed to osteoclast hyperactivity;synovium-resident immune cells exert a pivotal regulatory influence through distinct mechanisms.This review systematically examines how synovial immune cells orchestrate bone remodeling in RA through both paracrine cytokine networks and direct cell-cell communication with bone lineage cells,thereby perturbing physiological homeostasis and driving patho-logical progression.These mechanistic revelations yield innova-tive perspectives on RA pathogenesis,positioning immune-medi-ated osteoimmune dysregulation as a promising therapeutic fron-tier for targeted intervention.