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.

Based on plasma lipidomics combined with machine learning approaches, this study aimed to screen molecular biomarkers for the diagnosis of early-stage lung cancer in elderly patients and to evaluate their diagnostic performance.

ObjectiveTo observe the effect of rehabilitation robot training on abdominal muscles thickness and balance ability in children with hemiplegia. MethodsFrom October, 2024 to December, 2025, 58 children with hemiplegia were admitted to Beijing Bo'ai Hospital and randomly divided into control group (n = 29) and experimental group (n = 29). Both groups received conventional rehabilitation treatment, and the experimental group received rehabilitation robot training in addition, for four weeks. The thickness of bilateral external oblique, internal oblique and transversus abdominis, Berg Balance Scale (BBS) score, the time of Timed Up and Go Test (TUGT), the center of pressure (COP) ellipse area, and self-selected walking speed (SWS) and maximum walking speed (MWS) of 10-meter walk test were compared before and after training. ResultsThree cases dropped out in each group. After training, the thickness of the external oblique, internal oblique and transverse abdominis on the hemiplegic side increased significantly in the experimental group (|t| > 7.280, P < 0.001, Cohen's d = 1.43~2.01), and was better in the experimental group than in the control group (|t| > 2.895, P < 0.01, Cohen's d = 0.80~1.60); the BBS score increased in both groups (|t| > 6.667, P < 0.001, Cohen's d = 1.30~4.06), and was better in the experimental group than in the control group (t = -2.721, P < 0.01, Cohen's d = 0.75). The time of TUGT decreased in both groups (t > 5.790, P < 0.001, Cohen's d = 1.14~2.68), and was better in the experimental group than in the control group (t = 2.290, P < 0.05, Cohen's d = 0.63). The SWS and MWS increased in both groups (|Z| > 2.910, P < 0.01, r = 0.40~0.68), and were better in the experimental group than in the control group (|Z| > 2.912, P < 0.05, r = 0.40~0.45), and the differences remained significant after correction. ConclusionRehabilitation robot training can improve the thickness of external oblique, the internal oblique and transversus abdominis muscles on the hemiplegic side in children with hemiplegia, and improve their balance and walking functions.

The innate immune system can be boosted in response to subsequent triggers by pre-exposure to microbes or microbial products, known as “trained immunity”. Compared to classical immune memory, innate trained immunity has several different features. Firstly, the molecules involved in trained immunity differ from those involved in classical immune memory. Innate trained immunity mainly involves innate immune cells (e.g., myeloid immune cells, natural killer cells, innate lymphoid cells) and their effector molecules (e.g., pattern recognition receptor (PRR), various cytokines), as well as some kinds of non-immune cells (e.g., microglial cells). Secondly, the increased responsiveness to secondary stimuli during innate trained immunity is not specific to a particular pathogen, but influences epigenetic reprogramming in the cell through signaling pathways, leading to the sustained changes in genes transcriptional process, which ultimately affects cellular physiology without permanent genetic changes (e.g., mutations or recombination). Finally, innate trained immunity relies on an altered functional state of innate immune cells that could persist for weeks to months after initial stimulus removal. An appropriate inducer could induce trained immunity in innate lymphocytes, such as exogenous stimulants (including vaccines) and endogenous stimulants, which was firstly discovered in bone marrow derived immune cells. However, mature bone marrow derived immune cells are short-lived cells, that may not be able to transmit memory phenotypes to their offspring and provide long-term protection. Therefore, trained immunity is more likely to be relied on long-lived cells, such as epithelial stem cells, mesenchymal stromal cells and non-immune cells such as fibroblasts. Epigenetic reprogramming is one of the key molecular mechanisms that induces trained immunity, including DNA modifications, non-coding RNAs, histone modifications and chromatin remodeling. In addition to epigenetic reprogramming, different cellular metabolic pathways are involved in the regulation of innate trained immunity, including aerobic glycolysis, glutamine catabolism, cholesterol metabolism and fatty acid synthesis, through a series of intracellular cascade responses triggered by the recognition of PRR specific ligands. In the view of evolutionary, trained immunity is beneficial in enhancing protection against secondary infections with an induction in the evolutionary protective process against infections. Therefore, innate trained immunity plays an important role in therapy against diseases such as tumors and infections, which has signature therapeutic effects in these diseases. In organ transplantation, trained immunity has been associated with acute rejection, which prolongs the survival of allografts. However, trained immunity is not always protective but pathological in some cases, and dysregulated trained immunity contributes to the development of inflammatory and autoimmune diseases. Trained immunity provides a novel form of immune memory, but when inappropriately activated, may lead to an attack on tissues, causing autoinflammation. In autoimmune diseases such as rheumatoid arthritis and atherosclerosis, trained immunity may lead to enhance inflammation and tissue lesion in diseased regions. In Alzheimer’s disease and Parkinson’s disease, trained immunity may lead to over-activation of microglial cells, triggering neuroinflammation even nerve injury. This paper summarizes the basis and mechanisms of innate trained immunity, including the different cell types involved, the impacts on diseases and the effects as a therapeutic strategy to provide novel ideas for different diseases.

ObjectiveTo explore the correlation between the blood stasis score of coronary heart disease（CAD） and mild cognitive impairment（MCI）， as well as the changes in plasma metabolic profile of blood stasis in patients with CAD combined with MCI（CADMCI） through a cross-sectional study， and further explore the impact of different degrees of blood stasis on the plasma metabolite profile of CADMCI patients. MethodsAccording to the diagnostic criteria of CAD and CAD blood stasis， patients hospitalized in Xiyuan Hospital of China Academy of Chinese Medical Sciences from October 2022 to October 2023 were continuously included. According to the Montreal Cognitive Assessment（MoCA） scale score， the enrolled patients were divided into CADMCI blood stasis group and CAD blood stasis group. The association between blood stasis score and MCI was analyzed by multivariate Logistic regression model. The receiver operating characteristic（ROC） curve was drawn， and the area under the curve（AUC） was calculated to evaluate the sensitivity and specificity of the model. According to the blood stasis score， the first 30 patients in the CADMCI blood stasis group and CAD blood stasis group were divided into mild blood stasis and severe blood stasis. Ultra performance liquid chromatography-quadrupole-time-of-flight mass spectrometry（UPLC-Q-TOF-MS/MS） was used to detect plasma metabolites in each group of patients. The differential metabolites were screened according to variable importance in the projection（VIP） value≥1， fold change（FC）<0.67 or >1.5， and P<0.05. ROC curve analysis was further used to evaluate the discriminatory efficiency of the screened differential metabolites for each group of samples. ResultsA total of 266 CAD patients were included in this study. Multivariate Logistic regression analysis showed that the CAD blood stasis score was significantly correlated with MCI［odds ratio（OR）=1.619， 95% confidence interval（CI） 1.223-2.142， P<0.001， ROC curve AUC was 0.615（95% CI 0.547-0.683， P=0.001）］， indicating that the CAD blood stasis score has a certain predictive value for MCI. Plasma non-targeted metabolomics analysis showed that the main differential metabolites between CAD blood stasis and CADMCI blood stasis were lipid metabolites， among which phosphatidylcholine［20∶4（5Z， 8Z， 11Z， 14Z）/P-18∶1（11Z）］ had the best discriminatory efficiency（ROC curve AUC=0.867， 95% CI 0.754-0.942）. Further analysis of the differential metabolites between mild and severe blood stasis showed that lipid metabolites were also the main differential metabolites between mild and severe blood stasis. Among them， 1α，25-dihydroxy-2β-（2-hydroxyethoxy） vitamin D₃ had the best efficacy in distinguishing mild and severe CAD blood stasis（AUC=0.813， 95% CI 0.649-0.951）， and phosphatidylcholine 34∶2 had the best efficacy in distinguishing mild and severe CADMCI blood stasis（AUC=0.819， 95% CI 0.640-0.941）. ConclusionThere is a significant correlation between CAD blood stasis score and MCI. Phosphatidylcholine metabolites play an important role in the pathogenesis of CADMCI blood stasis and severe blood stasis. The CAD blood stasis score combined with the detection of phosphatidylcholine metabolites can provide a reference for the development of early and efficient identification strategies for CADMCI.

Immobilized enzyme-based enzyme electrode biosensors, characterized by high sensitivity and efficiency, strong specificity, and compact size, demonstrate broad application prospects in life science research, disease diagnosis and monitoring, etc. Immobilization of enzyme is a critical step in determining the performance (stability, sensitivity, and reproducibility) of the biosensors. Random immobilization (physical adsorption, covalent cross-linking, etc.) can easily bring about problems, such as decreased enzyme activity and relatively unstable immobilization. Whereas, directional immobilization utilizing amino acid residue mutation, affinity peptide fusion, or nucleotide-specific binding to restrict the orientation of the enzymes provides new possibilities to solve the problems caused by random immobilization. In this paper, the principles, advantages and disadvantages and the application progress of enzyme electrode biosensors of different directional immobilization strategies for enzyme molecular sensing elements by specific amino acids (lysine, histidine, cysteine, unnatural amino acid) with functional groups introduced based on site-specific mutation, affinity peptides (gold binding peptides, carbon binding peptides, carbohydrate binding domains) fused through genetic engineering, and specific binding between nucleotides and target enzymes (proteins) were reviewed, and the application fields, advantages and limitations of various immobilized enzyme interface characterization techniques were discussed, hoping to provide theoretical and technical guidance for the creation of high-performance enzyme sensing elements and the manufacture of enzyme electrode sensors.

ObjectiveTo observe the clinical efficacy and safety of hot ironing with Haitongpi Formula （海桐皮方， HF） in the treatment of lumbar disc herniation （LDH） of cold-dampness obstruction type. MethodsA total of 70 patients with cold-dampness obstruction type LDH were randomly divided into a treatment group and a control group， with 35 cases in each group. Both groups received three movements technique of Qinggong Spinal Manipulation （QSM） as the basis for treatment. In addition， the treatment group received hot ironing with HF， while the control group applied Diclofenac Sodium Gel externally. The treatment duration for both groups was 14 days. The clinical efficacy was compared between groups. Japanese Orthopedic Association （JOA） score， visual analog scale （VAS） for pain， pain pressure threshold （PPT） for lumbar positive response points， and traditional Chinese medicine （TCM） symptom scores were compared， on day 7， and day 14 of treatment， as well as on day 7 and day 14 of follow-up. The lumbar curvature index （LCI） was also compared before treatment and on day 14 of treatment. Adverse reactions during the study were recorded for both groups. ResultsA total of 35 patients in the treatment group and 34 patients in the control group were included for final analysis. The clinical total effective rate of the treatment group （91.43%， 32/35） was significantly higher than that of the control group （82.35%， 28/34， P＜0.05）. Both the JOA score and PPT of the two groups increased on day 7 and day 14 of treatment， and on day 7 and day 14 of follow-up. VAS scores and TCM symptom scores both decreased. The LCI of both groups increased on day 14 of treatment （P＜0.01）. Compared with the control group at the same time points， on day 14 of treatment and day 7 and day 14 of follow-up， the treatment group had higher JOA scores and PPT， and lower VAS scores and TCM symptom scores. The LCI of the treatment group increased on day 14 of treatment （P＜0.05 or P＜0.01）. One case in the control group showed mild skin allergy， with no other adverse reactions observed in either group. ConclusionBased on three movements technique of QSM， hot ironing with HF shows better clinical efficacy than external Diclofenac Sodium Gel in the treatment of cold-dampness obstruction type LDH. It can significantly reduce lumbar pain， increase pain pressure threshold， improve clinical symptoms， lumbar function， and lumbar curvature， with good safety.

With the increasing demand for dynamic,real-time and rapid qualitative analysis of chemical composition in areas such as emergency response and space exploration,chip-scale mass spectrometers have attracted significant attention.These devices are expected to drive the integration of mass spectrometry with micro/nano-fabrication and intelligent sensing technologies,fostering profound innovation and breakthroughs in analytical chemistry.As an excellent mass analyzer,the ion trap exhibits numerous advantages,and its miniaturization creates favorable conditions for the high-density integration of miniature mass spectrometers.However,the reduction in ion storage capacity may compromise its sensitivity and dynamic range,rendering the study of ion unidirectional ejection in highly miniaturized ion traps of significant practical importance.In this work,a research was conducted on achieving efficient ion unidirectional ejection while maintaining high mass resolution in the extremely miniature hyperbolic linear ion trap(M-HLIT)with a field radius of 1 mm,and an electric field compensation method was proposed,which combined asymmetric electrode stretching and unbalanced RF voltage to achieve high-precision optimization of the electric field composition.Simulations showed that in an ideal structure,this method achieved 100％unidirectional ejection efficiency with the mass resolution of 518,significantly outperforming traditional asymmetric structure method(365)and unbalanced voltage method(321).Following the introduction of ion ejection slots,further optimization through bidirectional stretching and electrical parameters improved the resolution to 790 while maintaining a unidirectional ejection efficiency of 93％.This method eliminated the requirement for additional excitation voltage,offering an ideal solution for the miniature mass analyzer with high detection performance of chip-level mass spectrometers.

A rapid and accurate method for textile fiber identification was developed for quality control and consumer protection.This method utilized electric soldering iron burning-mesh collision enhanced microtube plasma ionization mass spectrometry(ESIB-MC-μTP-MS)to acquire textile fiber MS data and used a random forest(RF)prediction model to identify fiber composition based on these MS data.The MC-μTP device involved in the method was a homemade low-temperature plasma ionization device constructed using cost-effective and readily available components.The system was applicable for direct analysis of small amount of textile samples without any complex sample pretreatment processes.Characteristic thermal decomposition products of different fibers were generated via soldering iron burning(350℃)in ambient atmosphere,and were subsequently analyzed by a mass spectrometer,with each analysis completed within 5 s.Raw MS data underwent noise reduction,normalization,and global binning steps to form a dataset,and its intrinsic class separability was evaluated using principal component analysis(PCA)combined with k-means clustering.Then,the RF model was trained based on the dimensionality-reduced textile fiber dataset.After grid search optimization,this model demonstrated robust performance with a 0.9762 out-of-bag score,a 0.9683 cross-validation accuracy(5-fold),and a 0.9636 test accuracy,supported by precision,recall,and F1-scores exceeding 0.889 for all fiber classes.The method was applied to analysis of 30 luxury apparel samples from eight brands,among which 20 samples achieved 100%prediction confidence,aligning with labeled compositions.The identification result of two low-confidence samples was further confirmed using attenuated total reflection Fourier transform infrared spectroscopy(ATR-FT-IR).The method has been proven to be simple,portable and with minimal sample requirements for on-site customs inspections,providing a viable tool in the fight against counterfeit products,therefore supporting regulatory enforcement and consumer trust in the textile goods market.