Cancer remains a leading cause of global mortality, necessitating the development of advanced therapeutic strategies with enhanced efficacy and reduced systemic toxicity. Among promising bioactive agents, lactoferrin (LF)—a multifunctional iron-binding glycoprotein abundantly found in mammalian milk and exocrine secretions—has garnered significant interest for its potent and multifaceted anti-cancer properties. This review provides a comprehensive analysis of the current understanding of LF’s role in oncology, encompassing its structural biology, diverse mechanisms of action, and groundbreaking advancements in its application through nano-engineering. LF exerts anti-tumor effects through multiple pathways, including extracellular action, intracellular action, and immune regulation. It demonstrates a remarkable affinity for cancer cell membranes, binding to overexpressed anionic components such as glycosaminoglycans and sialic acids, as well as to specific receptors including the low-density lipoprotein receptor-related protein-1 (LRP-1). This selective binding facilitates targeted uptake. Upon internalization, LF orchestrates a direct assault by inducing cell-cycle arrest in phases such as G0/G1 or S phase through the modulation of key regulators including cyclins, CDKs, and p53. Furthermore, it promotes programmed cell death via apoptotic pathways, involving caspase activation and downregulation of anti-apoptotic proteins such as survivin. A more recently elucidated mechanism is the induction of ferroptosis, an iron-dependent form of cell death characterized by overwhelming lipid peroxidation. Beyond direct cytotoxicity, LF acts as a potent immunomodulator. It enhances natural killer (NK) cell activity, modulates T-lymphocyte populations, and crucially reprograms tumor-associated macrophages (TAMs) from a pro-tumor M2 state to an anti-tumor M1 state, thereby reversing the immunosuppressive tumor microenvironment (TME). The translation of LF’s potential has been significantly accelerated by nanotechnology. The inherent biocompatibility and natural tumor-targeting capabilities of LF make it an ideal platform for sophisticated drug-delivery systems. This review details various fabrication strategies for LF-based nanoparticles (NPs), including self-assembly, sol-in-oil emulsion, and electrostatic nanocomplexes, among others. Research demonstrates that nano-formulations not only protect LF from degradation but also enhance its bioactivity and anti-cancer potency. More importantly, LF NPs serve as versatile carriers for a wide array of therapeutic agents, including conventional chemotherapeutics, natural compounds, and imaging agents. These engineered systems enable synergistic therapy and facilitate site-specific delivery. Notably, the ability of LF to bind to receptors on the blood-brain barrier (BBB) has been leveraged to develop nano-systems for glioblastoma treatment. Other innovative designs utilize LF to modulate the TME—for instance, by alleviating tumor hypoxia to sensitize cells to radiotherapy and chemotherapy. Despite compelling pre-clinical evidence, the clinical translation of LF and its nano-formulations remains nascent. While early-phase trials have established a favorable safety profile for recombinant human LF, larger Phase III studies have yielded mixed results, underscoring the complexity of its action in humans. Key challenges include enhancing drug targeting, optimizing loading efficiency, ensuring batch-to-batch reproducibility, and achieving deep tumor penetration. Future research must focus on the rational design of next-generation LF-NPs. This entails developing standardized manufacturing protocols, engineering “smart” stimuli-responsive systems for targeted drug release in the TME, and constructing multi-targeting platforms. A concerted interdisciplinary effort is paramount to bridge the gap between bench and bedside. In conclusion, LF, particularly in its nano-engineered forms, represents a highly promising and versatile agent in the oncological arsenal, holding immense potential for precise and effective cancer therapy.

Cancer remains a leading cause of global mortality, necessitating the development of advanced therapeutic strategies with enhanced efficacy and reduced systemic toxicity. Among promising bioactive agents, lactoferrin (LF)—a multifunctional iron-binding glycoprotein abundantly found in mammalian milk and exocrine secretions—has garnered significant interest for its potent and multifaceted anti-cancer properties. This review provides a comprehensive analysis of the current understanding of LF’s role in oncology, encompassing its structural biology, diverse mechanisms of action, and groundbreaking advancements in its application through nano-engineering. LF exerts anti-tumor effects through multiple pathways, including extracellular action, intracellular action, and immune regulation. It demonstrates a remarkable affinity for cancer cell membranes, binding to overexpressed anionic components such as glycosaminoglycans and sialic acids, as well as to specific receptors including the low-density lipoprotein receptor-related protein-1 (LRP-1). This selective binding facilitates targeted uptake. Upon internalization, LF orchestrates a direct assault by inducing cell-cycle arrest in phases such as G0/G1 or S phase through the modulation of key regulators including cyclins, CDKs, and p53. Furthermore, it promotes programmed cell death via apoptotic pathways, involving caspase activation and downregulation of anti-apoptotic proteins such as survivin. A more recently elucidated mechanism is the induction of ferroptosis, an iron-dependent form of cell death characterized by overwhelming lipid peroxidation. Beyond direct cytotoxicity, LF acts as a potent immunomodulator. It enhances natural killer (NK) cell activity, modulates T-lymphocyte populations, and crucially reprograms tumor-associated macrophages (TAMs) from a pro-tumor M2 state to an anti-tumor M1 state, thereby reversing the immunosuppressive tumor microenvironment (TME). The translation of LF’s potential has been significantly accelerated by nanotechnology. The inherent biocompatibility and natural tumor-targeting capabilities of LF make it an ideal platform for sophisticated drug-delivery systems. This review details various fabrication strategies for LF-based nanoparticles (NPs), including self-assembly, sol-in-oil emulsion, and electrostatic nanocomplexes, among others. Research demonstrates that nano-formulations not only protect LF from degradation but also enhance its bioactivity and anti-cancer potency. More importantly, LF NPs serve as versatile carriers for a wide array of therapeutic agents, including conventional chemotherapeutics, natural compounds, and imaging agents. These engineered systems enable synergistic therapy and facilitate site-specific delivery. Notably, the ability of LF to bind to receptors on the blood-brain barrier (BBB) has been leveraged to develop nano-systems for glioblastoma treatment. Other innovative designs utilize LF to modulate the TME—for instance, by alleviating tumor hypoxia to sensitize cells to radiotherapy and chemotherapy. Despite compelling pre-clinical evidence, the clinical translation of LF and its nano-formulations remains nascent. While early-phase trials have established a favorable safety profile for recombinant human LF, larger Phase III studies have yielded mixed results, underscoring the complexity of its action in humans. Key challenges include enhancing drug targeting, optimizing loading efficiency, ensuring batch-to-batch reproducibility, and achieving deep tumor penetration. Future research must focus on the rational design of next-generation LF-NPs. This entails developing standardized manufacturing protocols, engineering “smart” stimuli-responsive systems for targeted drug release in the TME, and constructing multi-targeting platforms. A concerted interdisciplinary effort is paramount to bridge the gap between bench and bedside. In conclusion, LF, particularly in its nano-engineered forms, represents a highly promising and versatile agent in the oncological arsenal, holding immense potential for precise and effective cancer therapy.

It is considered that lean metabolic associated fatty liver disease （MAFLD） is characte-rized by a state of "lean body but fatty liver". From the perspective of the pathomechanism evolution of "spleen failing to disperse essence， while kidney failing to transform qi"， the disease is systematically treated under the principle that spleen and kidney deficiency as the root and liver constraint with phlegm stasis as the branch. Spleen deficiency with impaired transformation and transportation leads to failure in the distribution of refined substances， initiating lipid turbidity accumulation and obstruction. Kidney dysfunction in qi transformation results in insufficient essence and blood， forming the root of bodily malnourishment. Over time， this further gives rise to liver constraint and loss of dispersing function， disorder in the movement of essential substances， and congealing of phlegm and stasis within hepatic collaterals. The dysfunction of three organs including spleen， kidney and liver constitutes the pathological basis of metabolic disturbances involving qi， blood， body fluids and essence. Treatment should follow the principle of "nourishing the healthy qi leads to spontaneous resolution of pathogenic accumulation"， with three approaches. First， fortifying the spleen and eliminating dampness， using Sini Powder （四逆散） and Erchen Pingwei Powder （二陈平胃散） to restore the transport and transformation function of the middle jiao （焦）， thereby guiding essential substances back to their proper physiological pathways. Second， tonifying the kidney and resolving turbidity， using Jinkui Shenqi Pill （金匮肾气丸） and Effective Integration Decoction （一贯煎） to replenish the lower jiao， promoting the restoration of essence and the transformation of turbid pathogen. Third， soothing the liver and resolving stasis， using Liujunzi Decoction （六君子汤） and Xiaozhi Qinggan Decoction （消脂清肝汤） to vent qi and blood stagnation， thereby interrupting disease progression. Together， these three methods reinforce healthy qi while eliminating pathogen， facilitating the restoration of proper essence transformation and the resolution of lipid turbidity.

Objective:To investigate the predictive value of pre-infarction angina(PIA)combined with serum lipo-protein-associated phospholipase A2(Lp-PLA2)for no-reflow during primary percutaneous coronary interven-tion(PCI)in elderly patients with new-onset acute ST-segment elevation myocardial infarction(STEMI).Meth-ods:A total of 189 patients who hospitalized because of acute STEMI and underwent primary PCI within 12h in De-partment of Cardiology,Cangzhou People's Hospital between January 2018 and December 2022 were enrolled.Ac-cording to their TIMI blood flow during PCI,the patients were divided into no reflow group(n=42)and normal re-flow group(n=147).The baseline data were compared between two groups.Multivariate Logistic regression analy-sis was used to analyze the risk factors of no-reflow during PCI.The receiver operating characteristic(ROC)curve was plotted to evaluate the predictive value of PIA and Lp-PLA2 for no-reflow.Results:PI A occurred in 73 cases(38.6％),and no reflow occurred in 42 cases(22.2％)during primary PCI.Compared with patients in normal re-flow group,those in no reflow group had significant higher Lp-PLA2[(341.33±98.32)ng/ml vs.(261.95±75.21)ng/ml]and onset to reperfusion time[(7.02±1.28)h vs.(5.14±1.48)h],and significant lower incidence of PIA(23.8％ vs.42.9％)(P＜0.05 or＜0.01).Multivariate Logistic regression analysis showed that Lp-PLA2(OR=1.528,95％CI 1.028～2.030,P＜0.001),onset to reperfusion time(OR=2.602,95％CI 1.848～3.665,P＜0.001)were independent risk factors for no reflow during PCI in elderly STEMI patients,while PIA was an inde-pendent protective factor(OR=0.261,95％CI 0.101～0.671,P=0.005).The area under ROC curve of Lp-PLA2 combined PIA was 0.863(95％CI 0.806～0.909),which was significantly higher than those of Lp-PLA2[0.733(95％CI 0.664～0.794),Z=2.690,P=0.007]and PIA alone[0.609(95％CI 0.535～0.679),Z=5.657,P＜0.001].Conclusion:Pre-infarction angina has an important protective effect on no-reflow in STEMI patients.High Lp-PLA2 and absence of pre-infarction angina at admission may be good predictors of no-reflow during primary PCI in elderly patients with newly-onset acute STEMI,and it contributes to risk stratification of high risk patients.

Aim To study the role and mechanism of ML210 in glioma.Methods The cell viability was detected by CCK8 assay.The percentage of dead cells was detected by SYTOXstaining.The role of ferroptosis-signaling pathway in gliomas was detected bygenomics.Cell proliferation was observed by EdU staining and clone formation assay.Cell migration ability was detec-ted by scratch healing assay.The apoptosis was detec-ted by flow cytometry.Cell mitochondrial function was assesses by JC-1 staining.The mechanism of action of ML210 was detected by molecular docking coupled with immunoblotting assay(Western blot).The levels of ROS,MDA were observed by ELISA.Results Compared with the control group,ML210 treatment dose-dependently decreased glioma cell viability,in-hibited cell proliferation,migration,and increased cell apoptosis and mitochondrial dysfunction,which were reversed by ferroptosis antagonists.Gene microarray screening showed that 688 genes of the ferroptosissig-naling pathway were aberrant and 10 signaling path-ways were altered in gliomas.Molecular docking re-sults showed that ML210 binding to GPX4 significantly inhibited the protein expression level of GPX4 and pro-moted the elevation of ROS and MDA levels.Conclu-sions ML210 produces anti-glioma cells via GPX4-mediated ferroptosis pathway.

Objective： The aim of this study is to explore the predictive value of biparametric magnetic resonance imaging(bpMRI)for pelvic lymph node metastasis in prostate cancer patients with PSA≤20 μg/L and establish a nomogram. Methods： The imaging data and clinical data of 363 patients undergoing radical prostatectomy and pelvic lymph node dissection in the First Affiliated Hospital of Nanjing Medical University from July 2018 to December 2023 were retrospectively analyzed. Univariate analysis and multivariate logistic regression were used to screen independent risk factors for pelvic lymph node metastasis in prostate cancer, and a nomogram of the clinical prediction model was established. Calibration curves were drawn to evaluate the accuracy of the model. Results： Multivariate logistic regression analysis showed extrocapusular extension (OR=8.08,95%CI=2.62－24.97, P<0.01), enlargement of pelvic lymph nodes (OR=4.45,95%CI=1.16－17.11,P=0.030), and biopsy ISUP grade(OR=1.97,95%CI=1.12－3.46, P=0.018)were independent risk factors for pelvic lymph node metastasis. The C-index of the prediction model was 0.834, which indicated that the model had a good prediction ability. The actual value of the model calibration curve and the prediction probability of the model fitted well, indicating that the model had a good accuracy. Further analysis of DCA curve showed that the model had good clinical application value when the risk threshold ranged from 0.05 to 0.70.Conclusion： For prostate cancer patients with PSA≤20 μg/L, bpMRI has a good predictive value for the pelvic lymph node metastasis of prostate cancer with extrocapusular extension, enlargement of pelvic lymph nodes and ISUP grade≥4.
Humans ; Male ; Prostatic Neoplasms/diagnostic imaging* ; Lymphatic Metastasis ; Retrospective Studies ; Nomograms ; Prostate-Specific Antigen/blood* ; Lymph Nodes/pathology* ; Pelvis ; Predictive Value of Tests ; Prostatectomy ; Lymph Node Excision ; Risk Factors ; Magnetic Resonance Imaging ; Logistic Models ; Middle Aged ; Aged

BACKGROUND: Medical informatics accumulated vast amounts of data for clinical diagnosis and treatment. However, limited access to follow-up data and the difficulty in integrating data across diverse platforms continue to pose significant barriers to clinical research progress. In response, our research team has embarked on the development of a specialized clinical research database for cardiology, thereby establishing a comprehensive digital platform that facilitates both clinical decision-making and research endeavors. METHODS: The database incorporated actual clinical data from patients who received treatment at the Cardiovascular Medicine Department of Chinese PLA General Hospital from 2012 to 2021. It included comprehensive data on patients' basic information, medical history, non-invasive imaging studies, laboratory test results, as well as peri-procedural information related to interventional surgeries, extracted from the Hospital Information System. Additionally, an innovative artificial intelligence (AI)-powered interactive follow-up system had been developed, ensuring that nearly all myocardial infarction patients received at least one post-discharge follow-up, thereby achieving comprehensive data management throughout the entire care continuum for high-risk patients. RESULTS: This database integrates extensive cross-sectional and longitudinal patient data, with a focus on higher-risk acute coronary syndrome patients. It achieves the integration of structured and unstructured clinical data, while innovatively incorporating AI and automatic speech recognition technologies to enhance data integration and workflow efficiency. It creates a comprehensive patient view, thereby improving diagnostic and follow-up quality, and provides high-quality data to support clinical research. Despite limitations in unstructured data standardization and biological sample integrity, the database's development is accompanied by ongoing optimization efforts. CONCLUSION The cardiovascular specialty clinical database is a comprehensive digital archive integrating clinical treatment and research, which facilitates the digital and intelligent transformation of clinical diagnosis and treatment processes. It supports clinical decision-making and offers data support and potential research directions for the specialized management of cardiovascular diseases.

Early-life stress (ES) leads to cognitive dysfunction in female adolescents, but the underlying neural mechanisms remain elusive. Recent evidence suggests that the cell adhesion molecules NECTIN1 and NECTIN3 play a role in cognition and ES-related cognitive deficits in male rodents. In this study, we aimed to investigate whether and how nectins contribute to ES-induced cognitive dysfunction in female adolescents. Applying the well-established limited bedding and nesting material paradigm, we found that ES impairs recognition memory, suppresses prefrontal NECTIN1 and hippocampal NECTIN3 expression, and upregulates corticotropin-releasing hormone (Crh) and its receptor 1 (Crhr1) mRNA levels in the hippocampus of adolescent female mice. Genetic experiments revealed that the reduction of dorsal CA1 (dCA1) NECTIN3 mediates ES-induced object recognition memory deficits, as knocking down dCA1 NECTIN3 impaired animals' performance in the novel object recognition task, while overexpression of dCA1 NECTIN3 successfully reversed the ES-induced deficits. Notably, prefrontal NECTIN1 knockdown did not result in significant cognitive impairments. Furthermore, acute systemic administration of antalarmin, a CRHR1 antagonist, upregulated hippocampal NECTIN3 levels and rescued object and spatial memory deficits in stressed mice. Our findings underscore the critical role of dCA1 NECTIN3 in mediating ES-induced object recognition memory deficits in adolescent female mice, highlighting it as a potential therapeutic target for stress-related psychiatric disorders in women.
Animals ; Female ; Mice ; CA1 Region, Hippocampal/metabolism* ; Cell Adhesion Molecules/metabolism* ; CRF Receptor, Type 1/metabolism* ; Memory Disorders/etiology* ; Mice, Inbred C57BL ; Nectins/genetics* ; Receptors, Corticotropin-Releasing Hormone/antagonists & inhibitors* ; Recognition, Psychology/physiology* ; Stress, Psychological/complications*

OBJECTIVE: This study examines utilizes the advantages of machine learning algorithms to discern key determinants in prognosticate postoperative circulatory complications (PCCs) for older patients. METHODS: This secondary analysis of data from a randomized controlled trial involved 1,720 elderly participants in five tertiary hospitals in Beijing, China. Participants aged 60-90 years undergoing major non-cardiac surgery under general anesthesia. The primary outcome metric of the study was the occurrence of PCCs, according to the European Society of Cardiology and the European Society of Anaesthesiology diagnostic criteria. The analysis metrics contained 67 candidate variables, including baseline characteristics, laboratory tests, and scale assessments. RESULTS: Our feature selection process identified key variables that significantly impact patient outcomes, including the duration of ICU stay, surgery, and anesthesia; APACHE-II score; intraoperative average heart rate and blood loss; cumulative opioid use during surgery; patient age; VAS-Move-Median score on the 1st to 3rd day; Charlson comorbidity score; volumes of intraoperative plasma, crystalloid, and colloid fluids; cumulative red blood cell transfusion during surgery; and endotracheal intubation duration. Notably, our Random Forest model demonstrated exceptional performance with an accuracy of 0.9872. CONCLUSION We have developed and validated an algorithm for predicting PCCs in elderly patients by identifying key risk factors.
Aged ; Aged, 80 and over ; Female ; Humans ; Male ; Middle Aged ; Cardiovascular Diseases/etiology* ; Machine Learning ; Postoperative Complications/etiology* ; Risk Factors ; Randomized Controlled Trials as Topic ; Secondary Data Analysis