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.

Objective To explore the prevalence of depressive symptoms in postoperative patients with ovarian cancer and to analyze its influencing factors from multiple dimensions, including clinical characteristics, psychological factors, and laboratory indicators. Methods A cross-sectional study was conducted, which enrolled 235 postoperative patients with ovarian cancer. Depressive status was assessed using the patient health questionnaire, and the demographic, pathological, and medical record data of the patients were collected using the generalized anxiety disorder scale, Pittsburgh sleep quality index, European organization for research and treatment of cancer quality of life questionnaire core 30, and ECOG performance status score. Peripheral blood tumor marker (CA125), routine blood test, lymphocyte subsets, and serum cytokine levels were measured. Univariate and multivariate binary logistic regression analysis were used for statistical analysis. Results The prevalence of depression in postoperative patients with ovarian cancer was 39.15% (92/235). Univariate analysis showed that ECOG score ≥ 2 points, pain, anxiety, poor sleep quality, low quality of life, low life satisfaction, tumor recurrence, six or more cycles of chemotherapy, as well as higher levels of CA125, NLR, and NAR, and lower hemoglobin levels were significantly associated with depression (all P<0.05). Multivariate binary Logistic regression analysis showed that anxiety (OR=1.975, 95%CI: 1.231-3.170), sleep efficiency (OR=4.181, 95%CI: 1.211-14.43), sleep latency (OR=34.806, 95%CI: 4.258-284.542), ECOG performance status score, cognitive function (OR=0.918, 95%CI: 0.868-0.97), and life satisfaction were independent risk factors for depression (all P<0.05). Laboratory indicators were not independent influencing factors in the multivariate Logistic regression model. Conclusion Depression in postoperative patients with ovarian cancer is influenced by physiological, psychological, and social factors. Clinical management should focus on patients with anxiety, sleep disorders, poor physical condition, and low life satisfaction, and a comprehensive prevention and treatment strategy centered on psychological intervention and taking into account symptom management and social support should be implemented.

Objective On the basis of the theory of the tumor metastatic state, this work aims to explore the metastasis trajectories and peripheral immune response patterns in patients with non-small cell lung cancer (NSCLC) receiving vital qi-strengthening and toxin-eliminating therapy (Fuzheng Juandu) and reveal the value of peripheral immunity in assessing vital qi deficiency during metastasis. Methods A retrospective study design was adopted. Patients with NSCLC admitted from January 1, 2018, to October 31, 2025 were enrolled. Data on metastasis status and peripheral immune indices were collected at the follow-up time points of one, two, three, and five years. Group-based trajectory modeling was used to fit metastasis trajectories, and the independent predictors of trajectory grouping were analyzed through multifactor and multiclassification logistic regression. Results A total of 184 patients with NSCLC were included, and three different groups of metastasis trajectories were identified, namely, the low-risk stable (46.74%, n=86), low-risk rising (13.59%, n=25), and high-risk stable (39.67%, n=73) groups. Univariate analysis revealed substantial differences in peripheral immune indices among the three trajectory groups. Multivariate analysis showed that TNM stage, absolute neutrophil count, lymphocyte count, absolute monocyte count, platelet volume, SAA:CRP ratio, and NLR were independent predictors of the low-risk rising group, whereas TNM stage, absolute monocyte count, basophil count, SII, and NLR were independent predictors of the high-risk stable group. Conclusion Under Fuzheng Juandu therapy, patients with NSCLC exhibit three distinct metastasis trajectories, each corresponding to a specific peripheral immune response pattern. Elucidating these peripheral immune response patterns may facilitate the objective quantification of the degree of vital qi deficiency, prediction of future metastasis risk, and providing an important reference for the individualized clinical implementation of Fuzheng Juandu therapy.

Ischemic stroke accounts for approximately 80% of all stroke cases worldwide and remains a leading cause of long‑term neurological disability and mortality. Intravenous thrombolysis and endovascular thrombectomy constitute the mainstay of acute reperfusion therapies, yet their clinical utility is severely constrained by narrow therapeutic time windows. Even when large‑vessel recanalization is successfully achieved, a considerable proportion of patients still suffer poor functional outcomes due to futile reperfusion and ischemia‑reperfusion injury. Historically, preclinical studies have largely focused on direct neuronal protection against calcium overload, oxidative stress and ferroptosis. Unfortunately, most promising neuroprotective agents that exhibited robust benefits in rodent models have failed to demonstrate satisfactory efficacy in phase‑Ⅱ and phase‑Ⅲ clinical trials. One critical contributor to such translational failure is the disregard for the pathological disturbance within the cerebral vascular microenvironment. Instead of merely regarding neuronal death as an autonomous cellular event, accumulating evidence indicates that sequential biochemical disruption of perivascular microenvironment acts as an initiating amplifier that propagates damage toward brain parenchyma after ischemic insult. The cerebral vascular microenvironment centers on brain microvessels and comprises endothelial cells, endothelial glycocalyx, basement membrane, pericytes, astrocytic end‑feet, perivascular microglia, as well as interstitial ions, inflammatory mediators, reactive oxygen species and extracellular matrix components. Distinct from the concept of neurovascular unit which emphasizes functional coupling between neurons, glia and vessels, the vascular microenvironment highlights dynamic biochemical homeostasis in perivascular interstitial space. Following cerebral ischemia, injured brain tissue can be spatially divided into the irreversibly damaged infarct core, metabolically‑stressed ischemic penumbra and mildly‑affected peripheral regions. These three zones lack rigid anatomical boundaries and evolve dynamically depending on reperfusion timing, presenting divergent features in blood perfusion, blood‑brain barrier integrity, cellular viability and immune‑inflammatory profiles. Four interrelated pathological cascades jointly disrupt microenvironmental homeostasis: calcium‑overload‑triggered cytotoxic cascades; blood‑brain barrier breakdown resulting from glycocalyx shedding, tight‑junction dissociation and matrix metalloproteinase‑driven basement‑membrane degradation; inflammatory‑immune dysregulation dominated by microglial phenotypic reprogramming; and mutual crosstalk between coagulation disturbance and neuroinflammation that exacerbates secondary brain injury. Multiple molecular layers orchestrate these pathological alterations. Excessive activation of HIF‑1α, NF‑κB and MAPK/ERK signaling pathways promotes barrier leakage, pro‑inflammatory factor secretion and extracellular‑matrix remodeling. Epigenetic modulation mediated by non‑coding RNAs including miRNAs and lncRNAs reshapes vascular microenvironment via three major patterns: modulating endothelial‑pericyte barrier integrity, switching microglia‑astrocyte inflammatory phenotypes, and driving metabolic reprogramming among multiple cell populations within microdomains. In addition, metabolic shift toward glycolysis among endothelial cells, microglia, astrocytes and compromised neurons establishes self‑amplifying vicious cycles of energy depletion and oxidative stress in perivascular niches. Targeted theranostic approaches oriented toward vascular microenvironment bring new opportunities for precision medicine of ischemic stroke. Magnetic nanoprobes and near‑infrared fluorescent probes respond to elevated reactive oxygen species, pH shift and inflammatory signals, enabling in situ visualization of pathological signatures of microenvironment and risk evaluation of hemorrhagic transformation. Function‑tailored nanodelivery systems exert multi‑modal protective effects: reactive oxygen species‑responsive polymeric micelles deliver calcium chelators to block calcium‑overload‑initiated injury cascades; nanozymes scavenge reactive oxygen/nitrogen species and revert microglial pro‑inflammatory polarization; biomimetic membrane‑coated nanoparticles accumulate at micro‑thrombosis sites to break thrombo‑inflammatory loops and mitigate no‑reflow phenomenon; ferroptosis‑inhibitor‑loaded nanocarriers eliminate excessive labile iron within perivascular toxic microdomains. During subacute and recovery phases, spatiotemporally controlled release of angiogenic factors by nanocarriers facilitates maturation of newly‑formed microvessels rather than blind vascular sprouting, which helps reconstruct intact blood‑brain barrier and restore microenvironmental homeostasis. Nevertheless, substantial translational bottlenecks still impede clinical transformation of these nanomedicines, including potential biosafety risks caused by in vivo material accumulation, protein‑corona‑induced impairment of targeting capacity, intrinsic blood brain barrier transport obstacles, lack of unified quality‑control criteria for large‑scale manufacture, reliance on high‑end clinical imaging instruments, and prominent interspecies discrepancies between experimental animals and human patients. On the basis of summarizing spatiotemporal pathological characteristics, multi‑level regulatory mechanisms and cutting‑edge microenvironment‑oriented diagnostic and interventional strategies, the present review advocates a conceptual shift from isolated neuronal protection to comprehensive reconstruction of perivascular vascular microenvironment homeostasis. Such perspective provides theoretical foundations for expanding therapeutic time windows and inspires future development of novel therapeutic modalities for ischemic stroke.

Gastric polyps, as a common digestive system disease, have shown an increasing detection rate and are regarded as one of the precancerous states of gastric cancer. In TCM, gastric polyps can be classified as diseases such as "stomachache" and "fullness and distension in the stomach". TCM holds that the disease is often related to the accumulation of pathogenic factors such as phlegm and blood stasis in the body to form "kenang", which has the characteristics of insidiousness, stubbornness, and recurrence. Deficiency of healthy qi and disorder of qi movement can lead to the adhesion of phlegm and blood stasis, which highly aligns with the etiology and pathogenesis of gastric polyps. The treatment principles are promoting blood circulation to remove blood stasis, regulating qi movement, and strengthening the body resistance to consolidate the essence. Understanding the etiology, pathogenesis, and treatment principles of gastric polyps from the theory of "kenang" has important guiding significance for clinical diagnosis and treatment, providing new ideas and methods for the treatment of gastric polyps.

Objective To establish and evaluate a nomogram prediction model for spontaneous peritonitis in HBV-related primary liver cancer.Methods A retrospective study was conducted on 1298 patients with HBV-related primary liver cancer hospitalized in the Kunming Third People's Hospital from January 2012 to December 2022.General data and serological indicators were collected,and patients were divided into infection group(n=262)and control group(n=1036)based on the occurrence of spontaneous peritonitis.Univariate and LASSO regression analyses were used to screen variables,followed by binary logistic regression to analyze the influencing factors of spontaneous peritonitis in HBV-related primary liver cancer patients,leading to the establishment of a nomogram prediction model.Finally,the Hosmer-lemeshow(H-L)goodness of fit test,receiver operating characteristic(ROC)curve,calibration curve,decision curve analysis(DCA)and clinical impact curve(CIC)were utilized to evaluate the fit degree,accuracy,calibration,and clinical practicability of the nomogram prediction model.Results Single factor analysis revealed significant differences between infection group and control group in portal vein cancer thrombus(PVTT),Child-Pugh grade,China Liver Cancer Staging(CNLC)stage,alcohol consumption history,smoking history,white blood cell count(WBC),neutrophil count(NE),hemoglobin(Hb),fibrinogen(FIB),abnormal prothrombin(PIVKA-Ⅱ),aspartate aminotransferase(AST),alanine aminotransferase(ALT),total protein(TP),prealbumin(PA),γ-glutamyltransferase(GGT),alkaline phosphatase(ALP),cholinesterase(CHE),total bile acid(TBA),total cholesterol(TC),low density lipoprotein(LDL),creatinine(Cr),HBV DNA,CD3+T cells count,CD4+T cells count,CD8+T cells count,CD4+T cells/CD8+T cells ratio,procalcitonin(PCT),serum amyloid A(SAA),interleukin-6(IL-6),high-sensitivity C-reactive protein(hs-CRP),alpha-fetoprotein(AFP),and IL-4(P＜0.05).LASSO regression analysis identified 5 variables:Child-Pugh grade,PVTT,WBC,CHE and hs-CRP.Binary logistic regression analysis indicated that Child-Pugh grade(Grade B:OR=5.780,95％CI 3.271-10.213,P＜0.001;Grade C:OR=14.818,95％CI 7.697-28.526,P＜0.001),PVTT(OR=2.893,95％CI 2.037-4.108,P＜0.001),WBC(OR=1.088,95％CI 1.031-1.148,P=0.002),and hs-CRP(OR=1.005,95％CI 1.001-1.010,P=0.026)were the independent risk factors of spontaneous peritonitis in HBV-related primary liver cancer patients.Using these 4 variables,a nomogram prediction model was constructed and evaluated.The P-value of the H-L goodness of fit test was 0.760.Moreover,the area under ROC curve(AUC)was 0.866,with a sensitivity of 0.870 and a specificity of 0.716.The average absolute error of the calibration curve is 0.022.DCA and CIC analyses demonstrated that the nomogram prediction model possessed some clinical utility.Conclusion The nomogram prediction model for spontaneous peritonitis in HBV-related primary liver cancer patients,constructed using Child-Pugh grade,PVTT,WBC and hs-CRP,exhibits a high fitting degree and accuracy,with the prediction probability highly consistent with the actual occurrence probability,and possesses certain clinical practicability.

Objective To assess the clinical value of a novel surgical technique—Tubeless subxiphoid uniportal video-assisted thoracoscopic surgery with percutaneous suspension technique via balance-shaped sternal elevation device in the resection of anterior mediastinal masses. Methods Patients who underwent tubeless subxiphoid uniportal video-assisted thoracoscopic surgery via balance-shaped sternal elevation device in anterior mediastinal masses process at the Department of Thoracic Surgery, West China Hospital, Sichuan University from March to April 2025 were included, and their clinical data were analyzed. Results A total of 4 patients were included, with 2 males and 2 females, aged 58-75 years. The diameter of the tumor was 2.5-3.0 cm. The operation time was 60.0-150.0 min, intraoperative blood loss was 5-10 mL, pain score on the 3rd day after surgery was 0 points, and postoperative hospital stay was 2-3 days. All patients achieved complete resection of the masses and thymus without perioperative complications. Conclusion The tubeless subxiphoid uniportal video-assisted thoracoscopic surgery with percutaneous suspension technique via balance-shaped sternal elevation device technique optimizes surgical visualization and instrument maneuverability while avoiding complications related to conventional anesthesia and tubing, thereby markedly enhancing the minimally invasive profile of anterior mediastinal masses resections. In addition to maintaining procedural safety, this approach effectively reduces postoperative pain and accelerates patient recovery, highlighting its potential for widespread clinical adoption.

Objective To explore the efficacy of DSA-guided intrathecal drug delivery system combined with Zi Wu Liu Zhu Acupoint Therapy for management of cancer pain and provide reference for its standardized clinical application.Methods and Results Recommendations were formulated based on literature review and expert group discussion,and consensus was reached following expert consultation.The consensus recommendations are comprehensive,covering the entire treatment procedures from preoperative assessment and preparation,surgical operation process,postoperative management and traditional Chinese medicine treatment to individualized treatment planning.The study results showed that the treatment plans combining traditional Chinese with Western medicine effectively alleviated cancer pain,reduced the use of opioid drugs,and significantly improved the quality of life and enhanced immune function of the patients.Postoperative follow-up suggested good treatment tolerance among the patients without serious complications.Conclusion The formulated consensus is comprehensive and can provide reference for clinicians to use DSA-guided intrathecal drug delivery system combined with Zi Wu Liu Zhu Acupoint Therapy.The combined treatment has a high clinical value with a good safety profile for management of cancer pain.

Objective:To evaluate whether the reconstructed image on the basis of deep learning(DL)can improve the success rate and display quality of automatic segmentation of computed tomography(CT)with ultralow dose for chest of children on airway.Methods:The clinical data of 41 consecutive cases who adopted ultralow dose CT to underwent reexamination on chest at Beijing Children's Hospital,Capital Medical University from February 2020 to September 2020 were selected,whose average age was(4.43±1.61 years).The scan protocol of ultralow dose CT was(0.05 mGy).The reconstructed images included 6 groups,which were respectively filtered reflection projection(FBP)image with 0.625 mm thickness,50%adaptive iterative recombination(ASIR-V)images,100%ASIR-V images,low energy DL(DL-L),medium energy DL(DL-M),and high energy DL(DL-H).The automatically segmentation software was used to conduct automatically segmentation for airway,and the success rate of automatic segmentation was recorded.For images that were successful segmented,a 5-point scale was adopted to subjectively evaluate the displayed quality for airway(5 point is the best).In addition,the CT values and noise values of the images of 6 groups for airway were objectively measured.Results:The success rate of automatic segmentation of DL-H image was the highest(60.98%),and that of the 100%ASIR-V was the lowest(39.02%).The subjective score of DL-H image of the automatic segmentation was the highest(4.06±0.55)point,and that of 100%ASIR-V was the lowest(2.44±0.76)point.DL-H can display more fine and small airways.The noise values of objective measurement showed that both of DL-H and 100%ASIR-V had the lowest noise value,and there was no statistical difference in that between them.Conclusion:The use of high energy deep learning iterative reconstruction(DLIR)algorithm can improve the success rate and display effect of automatic segmentation of ultralow dose CT for chest of children on airway,and DLIR is contribute to improve the accuracy of automatic segmentation algorithm of artificial intelligence.