Objective To analyze the epidemiological characteristics and disease burden of liver cancer in Guangdong Province in 2020, and to provide a scientific foundation for the development of regionalized prevention and control strategies for liver cancer. Methods According to the cancer registry data of Guangdong Province, the incidence, mortality and age-standardized rate by Chinese standard population in 2020 were calculated to analyze the epidemiological characteristics of liver cancer. The disability adjusted life years (DALYs), year of life loss (YLL), year of lived with disability (YLD), and cause-eliminated life expectancy were used to assess the disease burden of liver cancer. Results In 2020, the crude incidence rate and the age-standardized incidence rate of liver cancer in Guangdong Province were 27.79/100 000 and 20.84/100 000，respectively, and the crude mortality rate and the age-standardized mortality rate of liver cancer were 25.49/100,000 and 17.64/100 000, respectively. The total DALY and DALY rate of liver cancer in Guangdong Province were 515 311 person-years and 513.83/100 000, respectively. After eliminating the causes of death from liver cancer, the life expectancy in Guangdong Province increased from 84.60 years to 84.99 years. All indicators consistently demonstrated that the burden of liver cancer was higher in males than that in females, and the burden of liver cancer was higher in rural areas than that in urban areas. Conclusion Liver cancer in Guangdong Province exhibits a high incidence, mortality and disease burden level in 2020. There are obvious differences of gender, age and region in cancer burden. It is necessary to strengthen liver cancer screening and diagnosis and treatment in men, the elderly and those in rural areas to reduce the burden of liver cancer gradually in Guangdong Province.

Esophageal cancer is a prevalent malignant tumor of the digestive tract in China, and radical surgery remains the cornerstone of its comprehensive treatment. However, multifactorial challenges such as postoperative gastrointestinal tract reconstruction, traumatic stress, and tumor-related metabolic disturbances render esophageal cancer patients highly susceptible to malnutrition. Perioperative nutritional support therapy plays a crucial role in enhancing surgical safety, improving clinical outcomes, and elevating patients' quality of life by regulating metabolic homeostasis, preserving organ function, and optimizing the immune microenvironment. This article reviews the mechanisms underlying malnutrition in esophageal cancer, methods for nutritional status assessment, and precision intervention pathways based on multi-omics evaluations. The aim is to strengthen clinicians' awareness of standardized perioperative nutritional management for esophageal cancer patients and promote its clinical implementation, thereby facilitating postoperative recovery and improving long-term quality of life.

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 causal relationship between immune cells and various molecular subtypes of breast cancer (BC) by using two-sample Mendelian randomization (MR). Methods This study employed a two-sample MR analysis, with 731 immune cell types from the GWAS catalog as the exposure factors and four BC molecular subtypes (HR+/HER2−, HR+/HER2+, HR−/HER2+, and HR−/HER2−) from the BCAC Consortium as the outcome variables. For causal inference, inverse variance weighting (IVW) was employed as the primary analytical method, alongside multiple consistency validation approaches, including MR-Egger, weighted median, weighted mode, simple mode, and Bayesian weighted Mendelian randomization. Reverse MR and sensitivity analyses were employed to effectively evaluate and exclude potential biases and interference from reverse causality. Results Significant causal associations were identified for specific immune cell phenotypes across subtypes. In HR+ BC, the HER2+ subtype was associated with seven immunophenotypes (five protective and two risk increasing), whereas the HER2− subtype was associated with eight immunophenotypes (four protective and four risk increasing). In HR− BC, the HER2+ subtype was associated with five immunophenotypes (one protective and four risk increasing), and the HER2− subtype (triple-negative BC) was associated with seven immunophenotypes (six protective and one risk-increasing). CD28+CD45RA−CD8+ T cells and naive CD8+ T cells have a bidirectional causal relationship with HR+/HER2+ breast cancer, Whereas the expression of CD8 on CD39+CD8+ cells also has a bidirectional relationship with HR+/HER2− breast cancer. Furthermore, CD4−CD8− NKT cells exhibited opposing effect directions in HER2+ versus HER2− subtypes. Conclusion From a genetic perspective, this study confirms the existence of subtype-specific causal associations between immune cell phenotypes and distinct molecular subtypes of BC, revealing heterogeneity in immune regulation.

Owing to its inherent advantages—such as being non-destructive, rapid, highly molecule-specific, and minimally interfered with by moisture—Raman spectroscopy has been widely adopted in the fields of skin barrier function assessment, monitoring the transdermal penetration of active cosmetic ingredients, and the identification and quality control of cosmetic products. Despite these strengths, the practical application of this technique faces a significant bottleneck: the strong fluorescence background generated by endogenous skin components and exogenous cosmetic additives. Endogenous skin substances, such as structural proteins (e.g., collagen and elastin), metabolic coenzymes (e.g., nicotinamide adenine dinucleotide), and pigments (e.g., melanin), together with exogenous cosmetic constituents like organic colorants, chemical sunscreens, and fragrances, often possess strong absorption and emission characteristics. When excited by lasers, these components produce a fluorescence background that can be 10⁶ to 10⁸ times stronger than the Raman scattering signals, effectively masking the inherently weak vibrational fingerprint information. In recent years, driven by the rapid development of optoelectronic hardware and artificial intelligence algorithms, fluorescence suppression strategies have evolved from isolated, single-method approaches into comprehensive, multi-level synergistic systems. These systems are categorized into three distinct tiers: sample preparation, signal acquisition, and data processing. At the sample preparation level, techniques such as photobleaching and surface-enhanced Raman spectroscopy (SERS) are employed to eliminate or bypass the generation of fluorescence at the source. At the signal acquisition level, instrumental improvements—including the use of long-wavelength near-infrared excitation (typically 785 nm or 1 064 nm), confocal spatial filtering, and shifted excitation Raman difference spectroscopy (SERDS)— are utilized to physically isolate Raman signals from the fluorescence background. Furthermore, at the data processing level, numerical baseline correction methods such as polynomial fitting, penalized least squares (e.g., airPLS, arPLS), wavelet transform, and derivative algorithms are increasingly integrated into the analytical pipeline to extract Raman spectral features from mixed signals without increasing hardware costs or acquisition time. This review provides a systematic categorization and critical evaluation of these fluorescence suppression methods, detailing their underlying principles, technical advantages, and inherent limitations in diverse experimental setups. By focusing on critical application scenarios—including skin barrier assessment, percutaneous absorption monitoring, the routine quality control of cosmetics, and the emerging field of portable on-site detection—this paper explores the current state of technique selection and optimization. Finally, the article discusses future development trends, emphasizing the necessity of constructing adaptive, tiered suppression strategies, developing intelligent and automated data processing algorithms, and promoting the integration of portable, multi-modal diagnostic devices. The objective of this review is to provide a comprehensive technical reference to facilitate the transition of Raman spectroscopy from a specialized laboratory tool into a routine, robust analytical platform for advancements in skin science and cosmetic research.

Objective To evaluate the application of rabbit liver cancer model in teaching interventional medicine for graduate students.Methods A total of 10 first-year master graduate students majoring in Radiological Imaging(Interventional Medicine).who were studying at Zhengzhou University of China,were enrolled in this study.The rabbit liver cancer model was used as the experimental teaching materials.The teaching contents included the establishment of rabbit liver cancer model,the interventional operation of rabbit liver cancer,the method of scientific research and teaching,the evaluation of the teaching effect,and the survey of student satisfaction.Results Under the guidance of teaching tutor,the success rate of VX2 rabbit liver cancer modeling performed by the 10 master graduate students majoring in interventional medicine was 100％,and the mean operational quality assessment score was(11.5±2.0)points.During the operation of interventional surgery,the success rate of femoral artery puncture was also 100％,and the mean score for each interventional operation was(11.8±2.3)points.The students'experimental designs were evaluated by the expert group,the results were as follows:2 cases were rated as excellent,7 cases were rated as good,and one case was rated as moderate.The degree of students'satisfaction with experimental teaching method was high,the specific scores of each item are as follows:the understanding of the rabbit liver cancer model was(4.80±0.40)points,the command of interventional technology was(4.60±0.49)points,and the quality and practicability of teaching materials was(4.90±0.30)points.Conclusion This teaching method of using rabbit liver cancer model experiment can improve the animal experiment ability,interventional operation ability and scientific research innovation ability of graduate students.Animal model teaching method is an innovation of teaching mode for graduate students majoring in interventional medicine.

Objective To investigate the correlation between the anterior ethmoidal artery(AEA)and anatomical variations of the anterior cranial base,and to analyze the predictive factors for AEA suspension.Methods Sinus CT imaging data of 159 patients undergoing endoscopic sinus sur-gery(ESS)were retrospectively analyzed.Mimics 21.0 software was utilized for three-dimensional reconstruction,measuring parameters of AEA and anterior cranial base anatomy and performing classi-fication.Pearson and Spearman correlation analyses were used to evaluate the correlations among vari-ous anatomical parameters and their classifications.Multivariate binary logistic regression analysis was performed to screen for independentpredictive factors of AEA suspension.Results The rates of AEA suspension differed significantly across different Keros classifications(P＜0.001),with an increase rate as the Keros classification level increased(P＜0.001).The transverse diameter,height and vol-ume of supraorbital ethmoid cells(SOEC),olfactory fossa depth,lateral lamella of the cribriform plate(LLCP)length and frontal sinus pneumatization classification grade were positively correlated with the distance from AEA to the cranial base(P＜0.05).Multivariate binary Logistic regression analysis showed that the presence of SOEC(OR=4.178,95％CI,2.517 to 6.935,P＜0.001),in-creased olfactory fossa depth(OR=1.433,95％CI,1.197 to 1.715,P＜0.001),and higher frontal sinus pneumatization classification grade(OR=1.621,95％CI,1.121 to 2.345,P=0.01)were independent predictive factors for AEA suspension.Conclusion Detailed preoperative CT imaging assessment,especially the analysis of SOEC,olfactory fossa depth and frontal sinus pneumatization classification,aids in accurately assessing the anatomical position of AEA,thereby effectively reduc-ing the risk of AEA injury,and improving the safety and success rate of surgery.

Objective To develop a deep learning algorithm(Bio-section to Gene,B2G)for predicting spatially resolved gene expression profiles directly from histopathological images.Methods Digital histopathological images were processed through an integrated framework comprising convolutional neural networks(CNNs)and the Transformer architecture.Local histological features were extracted by the CNN module while global feature correlations were captured by the Transformer module.Cellular characteristics in digital tissue sections were systematically identified,followed by regression-based prediction of spatially resolved gene expression profiles.Results The B2G algorithm demonstrated significantly higher prediction accuracy than existing methods(weighted median PCC 0.1776).This framework exhibited robust performance across multiple cancer types and histological preparation protocols.Conclusion This computational approach may provide a morphology-driven strategy for spatial transcriptomic analysis.The framework could facilitate cost-effective biomarker discovery in clinical specimens while reducing reliance on specialized molecular techniques.Additionally,it might enable further exploration of tumor microenvironment heterogeneity.

Accurate timing of myelination is crucial for the proper functioning of the central nervous system. Here, we identified a de novo heterozygous mutation in TMEM63A (c.1894G>A; p. Ala632Thr) in a 7-year-old boy exhibiting hypomyelination. A Ca²⁺ influx assay suggested that this is a loss-of-function mutation. To explore how TMEM63A deficiency causes hypomyelination, we generated Tmem63a knockout mice. Genetic deletion of TMEM63A resulted in hypomyelination at postnatal day 14 (P14) arising from impaired differentiation of oligodendrocyte precursor cells (OPCs). Notably, the myelin dysplasia was transient, returning to normal levels by P28. Primary cultures of Tmem63a^-/- OPCs presented delayed differentiation. Lentivirus-based expression of TMEM63A but not TMEM63A_A632T rescued the differentiation of Tmem63a^-/- OPCs in vitro and myelination in Tmem63a^-/- mice. These data thus support the conclusion that the mutation in TMEM63A is the pathogenesis of the hypomyelination in the patient. Our study further demonstrated that TMEM63A-mediated Ca²⁺ influx plays critical roles in the early development of myelin and oligodendrocyte differentiation.
Animals ; Cell Differentiation/physiology* ; Oligodendroglia/metabolism* ; Mice, Knockout ; Mice ; Male ; Myelin Sheath/metabolism* ; Humans ; Child ; Cells, Cultured ; Oligodendrocyte Precursor Cells/metabolism*