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.

The Type III Secretion System (T3SS) serves as a pivotal virulence apparatus for numerous Gram-negative bacterial pathogens, enabling them to infect both animal and plant hosts. Functioning as a molecular syringe, the T3SS directly translocates bacterial effector proteins from the bacterial cytoplasm into the interior of eukaryotic host cells. These effectors are central weapons that precisely manipulate a wide spectrum of host cellular physiological processes, ranging from cytoskeletal dynamics to immune signaling, to establish a favorable niche for bacterial survival and proliferation. Among the diverse arsenal of T3SS effectors, the YopJ family constitutes a critical group of virulence factors. Members of this family are characterized by a conserved catalytic triad structure—a hallmark of the CE clan of cysteine proteases that has been evolutionarily repurposed to confer acetyltransferase activity. A defining and intriguing feature of these enzymes is their stringent dependence on a host-derived eukaryotic cofactor, inositol hexakisphosphate (IP₆), for allosteric activation. This requirement acts as a sophisticated molecular safeguard, ensuring enzymatic activity only within the appropriate host environment, thereby preventing detrimental effects on the bacterium itself. While seminal studies on individual members such as Yersinia’s YopJ and Salmonella’s AvrA have provided deep mechanistic insights, a systematic and integrative understanding of the structure-function relationships across the entire family remains fragmented. Key questions persist regarding how a conserved catalytic core has diverged to recognize distinct host substrates in different kingdoms of life. To address this gap, this article provides a systematic review of the YopJ family, focusing on three interconnected aspects: their structural features, their catalytic mechanism, and their divergent immunosuppressive strategies in animal versus plant hosts. By conducting a comparative analysis of the sequences and resolved three-dimensional structures of three representative members (e.g., HopZ1a, PopP2, AvrA), we elucidate regions of significant variation embedded within the conserved core catalytic architecture. These variable regions, often involving surface loops and substrate-binding interfaces, are crucial determinants of target specificity and functional specialization. The functional divergence of this effector family is most apparent when comparing their modes of action in different hosts. In animal hosts, YopJ-family effectors primarily sabotage innate immune signaling pathways. They achieve this by acetylating key serine and threonine residues within the activation loops of critical kinases in the MAPK and NF‑κB pathways. This post-translational modification blocks the phosphorylation and subsequent activation of these kinases, leading to potent suppression of inflammatory cytokine production. Conversely, in plant hosts, the strategy broadens to dismantle the two-tiered plant immune system. YopJ homologs target a more diverse set of substrates, including immune-associated receptor-like cytoplasmic kinases (RLCKs), microtubule networks via tubulin acetylation (which disrupts cellular trafficking and signaling), and transcription factors central to defense gene regulation. This multi-target approach effectively suppresses both Pattern-Triggered Immunity (PTI) and Effector-Triggered Immunity (ETI). In conclusion, this synthesis aims to deepen the mechanistic understanding of YopJ family-mediated pathogenesis by integrating structural biology with cellular function across host kingdoms. Elucidating the precise molecular basis for substrate selection—how conserved platforms achieve target diversity—is a major frontier. Furthermore, this knowledge provides a vital theoretical foundation for developing novel anti-virulence strategies. Targeting the conserved IP₆-binding pocket or the catalytic acetyltransferase activity itself represents a promising avenue for designing broad-spectrum inhibitors that could disarm this critical family of bacterial effectors, potentially offering new therapeutic approaches against a range of pathogenic bacteria.

Aim To investigate the protective effect of Gualou Guizhi granules(GLGZG)on neuronal injury induced by LPS-activated microglia based on Notch signaling pathway.Methods LPS-activated microglia were co-cultured with neurons to construct neuron inju-ry models,and the cells were divided into the control group,model group,Notch inhibitor(DAPT)group,GLGZG(50,100,200 mg·L-1)group,DAPT+100 mg·L-1GLGZG group.After intervention,the activity of HT22 cells was detected by CCK-8 method,and rel-ative mRNA expression was detected by real-time PCR.The relative protein expression was detected by Western blot.Results Compared with the model group,after GLGZG intervention,the cell activity was significantly improved,GLGZG decreased IL-6,IL-12,Bax,Notch 1,caspase-3,Delta-1,NICD,RBPSUH,HES1 expression,and increased Bcl-2 expression(P＜0.05).Compared with the model group,the NICD,RBPSUH and HES1 mRNA and protein expressions significantly decreased after DAPT treatment(P＜0.05),and there was no superposition effect with GLG-ZG.Conclusion GLGZG may play a neuroprotective role by inhibiting inflammatory factors and apoptosis,and inhibiting Notch signaling pathway.

Objective:To analyze the effects of the Focused Solution Model Nursing intervention on quality of life,negative emotions of the patients with prostate cancer.Methods:A total of 82 prostate cancer patients who were diagnosed and treated at the General Hospital of Eastern Theater Command between September 2022 and September 2024 were included and randomly divided into study group and control group by the method of random number table,with 41 patients in each group.The patients in the study group were treated with Focused Solution Model Nursing intervention.And the routine care was used in the control group The quality of life and negative emotions were compared between the two groups by using the scales of World Health Organization Quality of Life-Brief(WHOQOL-BREF),HAMA and HAMD.Results:Compared to the control group,the patients in the study group exhibited signifi-cantly higher scores in the physiological,psychological,environmental,and social relationship domains of the WHOQOL-BREF scale(P＜0.05).The scores of HAMA and HAMD in study group were lower than those of the control group(P＜0.05).Additionally,all subscales of the Social Impact Scale including social exclusion,internalized shame,social isolation and economic discrimination were significantly lower than those of the study group(P＜0.05).Conclusion:Focused Solution Model Nursing intervention can effec-tively improve the quality of life and negative emotions of the prostate cancer patients in the clinical treatment.

Objective To investigate the therapeutic efficacy of inspiratory muscle training(IMT)combined with external diaphragm pacing(EDP)in elderly patients with chronic heart failure(CHF).Methods 147 patients with CHF admitted to the Department of Cardiology of the Second Affiliated Hospital of Xi'an Jiaotong University from March 2024 to October 2024 were selected,of which 38 patients were in the conventional drug therapy group(standard care group),52 patients were in the conventional drug therapy+EDP therapy(dual therapy group),and 57 patients were in the conventional drug therapy+EDP therapy+IMT therapy(triple therapy group).Com-parative analyses were performed for maximum inspiratory pressure(MIP),maximum expiratory pressure(MEP),handgrip strength,6-minute walk distance(6MWD),modified Medical Research Council(mMRC)scores,resting heart rate,and blood pressure before treatment and 4 weeks post-intervention.Results After treatment,The dual therapy group demonstrated higher MIP,6MWD,and lower mMRC scores than the standard care group(P<0.05).The triple therapy group exhibited superior improvements in MIP,MEP,handgrip strength,6MWD,and lower mMRC scores compared to both standard care and dual therapy groups(P<0.05),with additional benefits including lower resting systolic blood pressure versus dual therapy group(P<0.05)and reduced resting heart rate compared to standard care group(P<0.05).Conclusion The combined IMT and EDP significantly enhances respiratory and upper limb muscle strength in CHF patients,effectively improves cardiopulmonary function,alleviates dys-pnea,and reduces resting heart rate and blood pressure,thus improving the quality of life.It is worthy of clinical promotion and application.

Objective To investigate the factors influencing the persistence of residual low back pain following percutaneous vertebroplasty(PVP)in patients with osteoporotic vertebral fractures(OVF),in order to provide a scientific basis for clinical intervention strategies.Methods A retrospective analysis was conducted on data from 1 120 patients diagnosed with OVF who received PVP treatment between July 2020 and June 2025.Among them,61 patients who experienced residual low back pain in the early postoperative period(defined as 2 days to 1 month after surgery)with a postoperative visual analog scale(VAS)score greater than 3 points were selected as the observation group.An additional 61 control subjects were matched to the observation group at a 1∶1 ratio based on age(±5 years),gender,and preoperative bone mineral density(±0.5 standard deviation).Univariate and logistic regression analyses were subsequently performed to evaluate potential influencing factors.Results Univariate analysis revealed statistically significant differences between the two groups with respect to preoperative thoracolumbar fascia injury(TFI),MRI-detected liquefaction signals in the affected vertebrae,the number of involved vertebrae(≥2),and suboptimal bone cement distribution(P<0.05).Multivariate regression analysis confirmed that these factors were independent risk factors,with corresponding odds ratios(ORs)of 5.378,6.111,3.245,and 2.890(all P<0.05).The area under the curve(AUC)of the predictive model was 0.929,indicating a high level of predictive accuracy.Conclusion Preoperative TFI,MRI-demonstrated liquefaction signals in the affected vertebrae,the presence of multiple responsible vertebrae,and suboptimal bone cement distribution may contribute to an increased risk of early residual low back pain following PVP.

Objective To propose a multiple regression-variational auto-encoders(MR-VAE)model to realize precise and non-invasive prediction of intra-abdominal pressure(IAP)in critically ill patients.Methods At first,a dataset was constructed by retrospectively analysing baseline characteristics and clinical indicators of 100 critically ill patients admitted to the Intensive Care Unit of Daping Hospital of Army Medical University between 30 August 2019 and 30 March 2021.Then,a MR-VAE prediction model was developed by integrating a feedforward neural network for supervised regression onto a variational autoencoder(VAE)framework and incorporating multiple regression strategies to mitigate feature interference.Finally,the MR-VAE model had its performance evaluated by its comparison with five classical models including support vector machines(SVM),convolutional neural networks(CNN),Scikit-learn integrated model(SIM),multi-layer perceptron(MLP)and K-nearest neighbors(KNN),and its prediction accuracy verified by testing the data of 10 randomly selected patients.Results The MR-VAE model behaved the best when compared with the five classical models,with a mean squared error(MSE)of 0.207,a root mean square error(RMSE)of 0.454,a mean absolute error(MAE)of 0.361,a median absolute deviation(MAD)of 0.243,an explained variance score(EVS)of 0.814 and a R2of 0.823,which also outperformed the five models in fitting performance,convergence and final loss.In random sample testing,the MR-VAE model exhibited high consistency between predicted and actual values.Conclusion The MR-VAE model proposed can accurately predict IAP,which has great potential in reducing the repeated measurements of IAP in critically ill patients and providing new ideas for the early diagnosis and treatment of IAH.

Objective:To analyze the epidemiological characteristics of wasting, spinal curvature abnormalities and multimorbidity among children and adolescents aged 6-18 in Inner Mongolia and explore the related factors of these two health problems.Methods:In September 2022, a stratified random cluster sampling method was employed to select 188 635 children and adolescents aged 6-18 in Inner Mongolia for physical examinations and questionnaire surveys. Data on height, weight, as well as dietary behavior, physical activity, classroom environment, academic tasks, writing posture, and screen behavior were collected. The epidemiological characteristics of wasting, spinal curvature abnormalities and multimorbidity were analyzed. Additionally, a multivariate logistic regression model was used to analyze the factors associated with wasting, spinal curvature abnormalities and multimorbidity.Results:A total of 188 635 children and adolescents aged 6-18 years participated in this study, including 95 393 boys (50.6%) with an average age of (11.53±3.32) years. The detection rate of wasting was 3.79%, with a higher detection rate in boys (4.18%) than in girls (3.38%) ( P<0.001). The detection rate of spinal curvature abnormalities was 3.64%, with a higher detection rate in girls (4.04%) than in boys (3.25%) ( P<0.001). The detection rate of multimorbidity between wasting and spinal curvature abnormalities was 0.17%, and there was no statistically significant difference between genders ( P>0.05). The detection rates of wasting, spinal curvature abnormalities, and multimorbidity all increased with age ( P t<0.001). The multivariate logistic regression analysis showed that, after adjusting for gender, age, urban/rural status, and school grade, compared to children and adolescents who exercised ≥1 hour of moderate-to-vigorous physical activity (MVPA) for at least 5 days per week and had daily screen time <2 hours, those who exercised <5 days per week ( OR=1.28, 95% CI: 1.19-1.37) and had daily screen time ≥2 hours ( OR=1.11, 95% CI: 1.03-1.19) had a higher risk of wasting. Compared to children and adolescents who had ≥5 physical education (PE) classes per week, adjusted desk and chair height,<1 hour of after-school study/writing time, and whose parents or teachers rarely or never reminded them about posture, those with <5 PE classes per week ( OR=1.11, 95% CI: 1.02-1.21), unadjusted desk and chair height ( OR=1.08, 95% CI: 1.01-1.15),≥1 hour of after-school study/writing time ( OR=1.15, 95% CI: 1.07-1.24), frequent reminders from parents ( OR=1.16, 95% CI: 1.09-1.23), and frequent reminders from teachers ( OR=1.10, 95% CI: 1.04-1.16) had a higher risk of spinal curvature abnormalities. Compared to children and adolescents who did not consume sugary drinks daily, exercised ≥1 hour of MVPA for at least 5 days per week, and whose teachers rarely or never reminded them about posture, those who consumed sugary drinks daily ( OR=1.61, 95% CI: 1.00-2.46), exercised <5 days per week ( OR=1.33, 95% CI: 1.01-1.79), and had teachers who frequently reminded them about posture ( OR=1.35, 95% CI: 1.05-1.75) had a higher risk of multimorbidity between wasting and spinal curvature abnormalities. Conclusion:The detection rates of wasting, spinal curvature abnormalities and multimorbidity among children and adolescents aged 6-18 in Inner Mongolia are generally low, with an increasing trend observed with age. Both lifestyle and school environmental factors are associated with wasting, spinal curvature abnormalities and multimorbidity.

Objective To propose a multiple regression-variational auto-encoders(MR-VAE)model to realize precise and non-invasive prediction of intra-abdominal pressure(IAP)in critically ill patients.Methods At first,a dataset was constructed by retrospectively analysing baseline characteristics and clinical indicators of 100 critically ill patients admitted to the Intensive Care Unit of Daping Hospital of Army Medical University between 30 August 2019 and 30 March 2021.Then,a MR-VAE prediction model was developed by integrating a feedforward neural network for supervised regression onto a variational autoencoder(VAE)framework and incorporating multiple regression strategies to mitigate feature interference.Finally,the MR-VAE model had its performance evaluated by its comparison with five classical models including support vector machines(SVM),convolutional neural networks(CNN),Scikit-learn integrated model(SIM),multi-layer perceptron(MLP)and K-nearest neighbors(KNN),and its prediction accuracy verified by testing the data of 10 randomly selected patients.Results The MR-VAE model behaved the best when compared with the five classical models,with a mean squared error(MSE)of 0.207,a root mean square error(RMSE)of 0.454,a mean absolute error(MAE)of 0.361,a median absolute deviation(MAD)of 0.243,an explained variance score(EVS)of 0.814 and a R2of 0.823,which also outperformed the five models in fitting performance,convergence and final loss.In random sample testing,the MR-VAE model exhibited high consistency between predicted and actual values.Conclusion The MR-VAE model proposed can accurately predict IAP,which has great potential in reducing the repeated measurements of IAP in critically ill patients and providing new ideas for the early diagnosis and treatment of IAH.