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 investigate the efficacy and safety of Wuling capsules combined with fluoxetine in the treatment of adolescents with first-episode moderate-to-severe depressive disorder accompanied by insomnia. METHODS The clinical data of 476 adolescents with first-episode moderate-to-severe depression accompanied by insomnia admitted to our hospital from June 2022 to May 2025， were retrospectively collected. According to the initial treatment regimen， patients were divided into a control group （241 cases， treated with fluoxetine alone） and an observation group （235 cases， treated with Wuling capsules combined with fluoxetine）. The depression severity （Hamilton Depression Rating Scale-17 Item and the Self-Rating Depression Scale scores）， sleep quality （Pittsburgh Sleep Quality Index score， sleep latency， wake after sleep onset， total sleep time， sleep efficiency）， serum neuroendocrine indicator （cortisol） and inflammatory markers （C-reactive protein， interleukin-6） were compared between the two groups before treatment and at 4th and 8th weeks of treatment. The effective rate at 8th weeks and the occurrence of adverse drug reactions （ADRs） were also compared between the two groups. RESULTS Before treatment， there were no significant differences in depression severity， sleep quality， serum neuroendocrine indicator， and inflammatory markers between the two groups （ P ＞0.05）. At 4th and 8th weeks， both groups showed significant improvement in these indicators compared to those before treatment， with the observation group demonstrating significantly greater improvement than the control group at the corresponding time points （ P ＜0.05）. At 8th week， the eff ective rate of the observation group was 90.21%， significantly higher than 80.50% in the control group （ P ＜0.05）. The incidence of nausea， headache， fatigue， dry mouth， and palpitations， as well as the total incidence of ADRs， did not differ significantly between the two groups （ P ＞0.05）. CONCLUSIONS Wuling capsules combined with fluoxetine can significantly improve the effective rate in adolescents with first-episode moderate-to-severe depression accompanied by insomnia， accelerate the relief of depressive symptoms， improve sleep quality， and reduce serum neuroendocrine indicator and inflammatory markers， with a favorable safety profile.

AIM To evaluate the chemical constituent consistency in formula granules and traditional decoctions of Gouteng Jiangya Formula.METHODS HPLC characteristic chromatograms were established,the analysis was performed on a 30 ℃ thermostatic YMC-Triart C18 column(4.6 mm× 250 mm,5 μm),with the mobile phase comprising of acetonitrile-0.2％phosphoric acid flowing at 1.0 mL/min in a gradient elution manner,and the detection wavelength was set at 240 nm.Puerarin was used as an internal standard to calculate the relative correction factors of 3'-methoxy puerarin,puerarin apioside,magnolflorine,paeoniflora,daidzin,baicalin,palmatine,berberine,wogonoside and benzoylpaeoniflorin,after which the content detemination was made by quantitative analysis of multi-components by single-marker(QAMS).RESULTS The characteristic chromatograms of 9 batches of formula granules and 15 bacthes of traditional decoctions demonstrated the similarities of more than 0.90 at the detection wavelengths of 192,210,240,260,280,300,320,360 nm,along with similar total peak areas.Eleven constituents showed good linear relationships within their own ranges(r＞0.999 0),whose average recoveries were 97.27％-101.64％with the RSDs of 0.36％-1.11％,the result obtained by QAMS and external standard method demonstrated no significant differences(P＞0.05).The contents of various constituents in the formula granules approximated those in the traditional decoctions.CONCLUSION The consistent kinds and contents of various constituents are obversable in formula granules and traditional decoctions of Gouteng Jiangya Formula,which can provide a reference for the reasonable clinical application of this formula.

Objective Under the operation background of Diagnosis-Intervention Packet(DIP),whether there is interaction between reducing medical cost and average length of stay combined with pre-hospitalization mode,and whether there is difference between different departments and diseases in interaction.Methods Based on real-world data from 71 453 patients admitted to Guizhou Provincial People's Hospital from July to December 2021,a two-way analysis of variance was employed.When the interaction effect was statistically significant,parameter estimation was used to determine the magnitude and direction of the interaction effect,followed by subgroup analyses by department and disease.Results Without adjustment,both total medical costs and average length of stay exhibited a negative interaction effect(P＜0.05).Subgroup analyses revealed that in terms of total medical costs,the effect size for the surgical system was 0.18％,lower than that for the internal medicine system(0.70％);for core diseases,it was 6.62％,lower than that for comprehensive diseases(7.71％).Regarding average length of stay,the effect size for the surgical system was 0.55％,better than that for the internal medicine system(0.22％);for core diseases,it was 8.70％,higher than that for comprehensive diseases(2.90％).Conclusion The combination of DIP payment reform and pre-admission management model demonstrates a synergistic effect,effectively reducing patients' medical costs and length of stay.This effect is influenced by disease complexity and the standardization of diagnostic and treatment processes.

Objective:To explore the predictive value of serum interleukin-6(IL-6)combined with Montreal Cognitive Assessment(MoCA)score and CHANGE risk score for post-stroke cognitive impairment(PSCI),and to provide a basis for early identification and intervention of high-risk patients.Methods:The general data of 200 patients with acute stroke who were admitted to our hospital from October 2022 to September 2024 were retrospectively analyzed,they were divided into PSCI group(49 cases)and non PSCI group(151 cases)based on whether PSCI occurred 3 months after acute stroke.The general data of two groups were compared,multiple logistic regression was used to analyze the influencing factors of PSCI,and receiver operating characteristic(ROC)curves were used to evaluate predictive efficiency of serum IL-6,MoCA score and CHANGE risk score for of PSCI.Results:There was a statistically significant difference in age and education level between the two groups(P＜0.05).The serum IL-6 level and CHANGE risk score in the PSCI group were higher than those in the non PSCI group,while the MoCA score was lower than that in the non PSCI group(P＜0.05).Multivariate logistic regression showed that elevated IL-6 levels(OR=1.851,P=0.001)and elevated CHANGE risk scores(OR=1.076,P=0.016)were independent risk factors of the occurrence of PSCI,while elevated in MoCA score(OR=0.806,P=0.001)was a protective factor(P＜0.05).IL-6 levels,MoCA scores and CHANGE risk scores have high predictive efficiency for the occurrence of PSCI,the area under the curve(AUC)for predicting occurrence of PSCI by the three alone were 0.783,0.825 and 0.857 respectively,the AUC for the combined detection of the three indicators was 0.912,significantly higher than that of each indicator detected separately.Conclusion:Elevated serum IL-6,decreased MoCA score and increased CHANGE risk score are risk factors for PSCI,the combined detection model of the three has the highest predictive efficiency for occurrence of PSCI and can provide scientific basis for early clinical intervention.

Objective Under the operation background of Diagnosis-Intervention Packet(DIP),whether there is interaction between reducing medical cost and average length of stay combined with pre-hospitalization mode,and whether there is difference between different departments and diseases in interaction.Methods Based on real-world data from 71 453 patients admitted to Guizhou Provincial People's Hospital from July to December 2021,a two-way analysis of variance was employed.When the interaction effect was statistically significant,parameter estimation was used to determine the magnitude and direction of the interaction effect,followed by subgroup analyses by department and disease.Results Without adjustment,both total medical costs and average length of stay exhibited a negative interaction effect(P＜0.05).Subgroup analyses revealed that in terms of total medical costs,the effect size for the surgical system was 0.18％,lower than that for the internal medicine system(0.70％);for core diseases,it was 6.62％,lower than that for comprehensive diseases(7.71％).Regarding average length of stay,the effect size for the surgical system was 0.55％,better than that for the internal medicine system(0.22％);for core diseases,it was 8.70％,higher than that for comprehensive diseases(2.90％).Conclusion The combination of DIP payment reform and pre-admission management model demonstrates a synergistic effect,effectively reducing patients' medical costs and length of stay.This effect is influenced by disease complexity and the standardization of diagnostic and treatment processes.

Objective:To explore the predictive value of serum interleukin-6(IL-6)combined with Montreal Cognitive Assessment(MoCA)score and CHANGE risk score for post-stroke cognitive impairment(PSCI),and to provide a basis for early identification and intervention of high-risk patients.Methods:The general data of 200 patients with acute stroke who were admitted to our hospital from October 2022 to September 2024 were retrospectively analyzed,they were divided into PSCI group(49 cases)and non PSCI group(151 cases)based on whether PSCI occurred 3 months after acute stroke.The general data of two groups were compared,multiple logistic regression was used to analyze the influencing factors of PSCI,and receiver operating characteristic(ROC)curves were used to evaluate predictive efficiency of serum IL-6,MoCA score and CHANGE risk score for of PSCI.Results:There was a statistically significant difference in age and education level between the two groups(P＜0.05).The serum IL-6 level and CHANGE risk score in the PSCI group were higher than those in the non PSCI group,while the MoCA score was lower than that in the non PSCI group(P＜0.05).Multivariate logistic regression showed that elevated IL-6 levels(OR=1.851,P=0.001)and elevated CHANGE risk scores(OR=1.076,P=0.016)were independent risk factors of the occurrence of PSCI,while elevated in MoCA score(OR=0.806,P=0.001)was a protective factor(P＜0.05).IL-6 levels,MoCA scores and CHANGE risk scores have high predictive efficiency for the occurrence of PSCI,the area under the curve(AUC)for predicting occurrence of PSCI by the three alone were 0.783,0.825 and 0.857 respectively,the AUC for the combined detection of the three indicators was 0.912,significantly higher than that of each indicator detected separately.Conclusion:Elevated serum IL-6,decreased MoCA score and increased CHANGE risk score are risk factors for PSCI,the combined detection model of the three has the highest predictive efficiency for occurrence of PSCI and can provide scientific basis for early clinical intervention.

AIM To evaluate the chemical constituent consistency in formula granules and traditional decoctions of Gouteng Jiangya Formula.METHODS HPLC characteristic chromatograms were established,the analysis was performed on a 30 ℃ thermostatic YMC-Triart C18 column(4.6 mm× 250 mm,5 μm),with the mobile phase comprising of acetonitrile-0.2％phosphoric acid flowing at 1.0 mL/min in a gradient elution manner,and the detection wavelength was set at 240 nm.Puerarin was used as an internal standard to calculate the relative correction factors of 3'-methoxy puerarin,puerarin apioside,magnolflorine,paeoniflora,daidzin,baicalin,palmatine,berberine,wogonoside and benzoylpaeoniflorin,after which the content detemination was made by quantitative analysis of multi-components by single-marker(QAMS).RESULTS The characteristic chromatograms of 9 batches of formula granules and 15 bacthes of traditional decoctions demonstrated the similarities of more than 0.90 at the detection wavelengths of 192,210,240,260,280,300,320,360 nm,along with similar total peak areas.Eleven constituents showed good linear relationships within their own ranges(r＞0.999 0),whose average recoveries were 97.27％-101.64％with the RSDs of 0.36％-1.11％,the result obtained by QAMS and external standard method demonstrated no significant differences(P＞0.05).The contents of various constituents in the formula granules approximated those in the traditional decoctions.CONCLUSION The consistent kinds and contents of various constituents are obversable in formula granules and traditional decoctions of Gouteng Jiangya Formula,which can provide a reference for the reasonable clinical application of this formula.

ObjectiveTriple-negative breast cancer (TNBC) is the breast cancer subtype with the worst prognosis, and lacks effective therapeutic targets. Colony stimulating factors (CSFs) are cytokines that can regulate the production of blood cells and stimulate the growth and development of immune cells, playing an important role in the malignant progression of TNBC. This article aims to construct a novel prognostic model based on the expression of colony stimulating factors-related genes (CRGs), and analyze the sensitivity of TNBC patients to immunotherapy and drug therapy. MethodsWe downloaded CRGs from public databases and screened for differentially expressed CRGs between normal and TNBC tissues in the TCGA-BRCA database. Through LASSO Cox regression analysis, we constructed a prognostic model and stratified TNBC patients into high-risk and low-risk groups based on the colony stimulating factors-related genes risk score (CRRS). We further analyzed the correlation between CRRS and patient prognosis, clinical features, tumor microenvironment (TME) in both high-risk and low-risk groups, and evaluated the relationship between CRRS and sensitivity to immunotherapy and drug therapy. ResultsWe identified 842 differentially expressed CRGs in breast cancer tissues of TNBC patients and selected 13 CRGs for constructing the prognostic model. Kaplan-Meier survival curves, time-dependent receiver operating characteristic curves, and other analyses confirmed that TNBC patients with high CRRS had shorter overall survival, and the predictive ability of CRRS prognostic model was further validated using the GEO dataset. Nomogram combining clinical features confirmed that CRRS was an independent factor for the prognosis of TNBC patients. Moreover, patients in the high-risk group had lower levels of immune infiltration in the TME and were sensitive to chemotherapeutic drugs such as 5-fluorouracil, ipatasertib, and paclitaxel. ConclusionWe have developed a CRRS-based prognostic model composed of 13 differentially expressed CRGs, which may serve as a useful tool for predicting the prognosis of TNBC patients and guiding clinical treatment. Moreover, the key genes within this model may represent potential molecular targets for future therapies of TNBC.