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.

Hyperlipidemia is a common metabolic disorder driven by dysregulated lipid metabolism， whose pathological progression involves multifaceted interactions across various signaling pathways， including disrupted cholesterol homeostasis， insulin resistance， chronic inflammation， and oxidative stress. Although existing clinical medications such as statins can effectively reduce low-density lipoprotein cholesterol through single-target inhibition， significant limitations remain in comprehensively improving reverse cholesterol transport， metabolic inflammation， and coordinated regulation of glucose and lipid metabolism. Curcumin， the primary polyphenolic active compound derived from the traditional medicinal herb turmeric， exhibits multi-dimensional pharmacological effects including modulation of lipid metabolism， improvement of insulin sensitivity， suppression of inflammatory responses， and enhancement of antioxidant defense. This review systematically integrates the multi-target regulatory network of curcumin， elucidating its key mechanisms： Balancing the low density lipoprotein receptor/proprotein convertase subtilisin/kexin type 9 （LDLR/PCSK9） signaling pathway to promote reverse cholesterol transport， activating peroxisome proliferator-activated receptor α/γ （PPARα/γ） signaling pathways to coordinate glucolipid metabolic homeostasis， remodeling the gut microbiota-bile acid axis， inhibiting nuclear factor kappa-B （NF-κB）-mediated inflammatory responses， and activating the nuclear factor erythroid 2-related factor 2/antioxidant response element （Nrf2/ARE） antioxidant signaling pathway. Furthermore， supported by clinical research data， the review validates curcumin's therapeutic potential in reducing total cholesterol （TC） and triglyceride （TG） levels， increasing high-density lipoprotein cholesterol （HDL-C）， as well as improving vascular endothelial function and insulin sensitivity. The study highlights the multi-target regulatory properties of curcumin and discusses future clinical applications based on nano-delivery systems and personalized treatment strategies， providing a theoretical basis and novel insights for the prevention and treatment of hyperlipidemia and related metabolic disorders.

Objective:To evaluate the safety and clinical efficacy of enteral nutrition (EN) initiated within 24 h after heart transplantation in pediatric patients.Methods:A retrospective cohort study was conducted. Clinical data from 16 pediatric heart transplant recipients at the Seventh Medical Center of the Chinese People′s Liberation Army General Hospital between October 2022 and October 2024 were collected, including demographics, anthropometric measurements, biochemical markers, cytokine levels, and clinical outcomes. Based on the timing of EN initiation, the patients were divided into EN-initiated within 24 h and EN-initiated after 24 h 2 groups. Demographic data, preoperative extracorporeal membrane oxygenation (ECMO) support, physical examination indicators, laboratory parameters, and cytokine levels were compared between groups using independent samples t-test, Mann-Whitney U test, Fisher′s exact probability test. Results:The cohort comprised 16 patients (10 males and 6 females) with an age of (12.5±1.9) years. The EN-initiated within 24 h group comprised 6 cases, and the EN-initiated after 24 h group comprised 10 cases. No significant difference was observed between the two groups in age, preoperative body mass index Z-score, preoperative ECMO support, physical examination indicators, laboratory parameters (total protein, albumin, hemoglobin), or cytokine levels (all P>0.05). Compared to the EN-initiated after 24 h group, the EN-initiated within 24 h group exhibited a shorter intensive care unit stay ( t=2.65, P<0.05) and shorter mechanical ventilation duration ( t=2.23, P<0.05) than EN-initiated after 24 h group. Total hospitalization length had no significant difference ( P>0.05). At 72 h post-transplant, the EN-initiated within 24 h group had a lower interleukin-12 P70 ( t=2.46, P<0.05) and interferon-γ levels ( t=2.55, P<0.05) than EN-initiated after 24 h group. Prior to discharge, the EN-initiated within 24 h group has a lower mean skinfold thickness ( t=2.49, P<0.05) and lower mid-upper arm circumference ( t=2.36, P<0.05) compared with the EN-initiated after 24 h group. Conclusions:Initiating EN within 24 h postoperatively is safe and feasible in pediatric heart transplant recipients. Early EN may shorten the length of intensive care unit stay and mechanical ventilation while attenuating postoperative release of inflammatory cytokine.

Objective To investigate application value of three-dimensional light sheet microscopy imaging for evaluating intraplaque neovascularization in arterial plaques and the efficacy of intervention,and to assess the effect of melatonin(MLT)on neovascularization by these means.Methods Thirty-six ApoE-/-model mice were randomly divided into three groups(n=12):vehicle group,MLT group,and MLT+GW9662 intervention group(MLT+GW).The mice were treated with vehicle,MLT alone,or MLT combined with peroxisome proliferator activated receptor-γ(PPARγ)inhibitor GW9662,respectively.The carotid arteries of the models were three-dimensionally imaged using a light sheet microscopy,and the length,volume and other indicators of neovascularization were quantitatively analyzed using Imaris software.Subsequently,CD31 immunohistochemical staining was performed for verification.Results The light sheet microscopy preliminarily achieved the three-dimensional visualization of intraplaque neovascularization,and its structure was observed to be three-dimensionally reticular and scattered.The results of Imaris quantitative analysis showed that,compared with vehicle group,the total intraplaque neovas cularization length in the MLT group was shortened[(15.79±12.90)mm vs.(33.42±11.16)mm,P<0.05],the total volume was reduced[(1.34±1.47)×10-3 mm3 vs.(13.44±7.35)×10-3 mm3,P<0.05],and the volume ratio was decreased(0.44%±0.47%vs.3.76%±1.74%,P<0.05).The above indicators in MLT+GW group were significantly increased compared with those in MLT group[total length:(35.31±4.69)mm,total volume:(8.87±3.46)×10-3 mm3,volume ratio:2.89%±0.38%;P<0.05].The CD31 immunohistochemical staining also supported the above findings(P<0.05).Conclusions Based on the light sheet microscopy imaging technology,the three-dimensional visualization and quantitative analysis of intraplaque neovascularization were preliminarily realized.It was found that MLT could reduce the overall burden of intraplaque neovascularization,and PPARγ might be involved in its regulatory process.

Objective:To Investigate the impact of blood glucose fluctuations within 24 hours of admission on the short-term (3-month) prognosis of patients with acute pancreatitis.Methods:A total of 416 patients with acute pancreatitis admitted to the Department of Gastroenterology of the First Affiliated Hospital of Nanchang University from November 2022 to October 2023 were enrolled as the research subjects. According to whether re-admission occurred within 3 months after discharge, they were divided into good prognosis group ( n=352) and poor prognosis group ( n=64). General data, laboratory indicators, and blood glucose values within 24 hours of admission [including initial blood glucose, 24-hour average blood glucose, maximum blood glucose, minimum blood glucose, standard deviation of blood glucose (SDBG), and largest amplitude of glycemic excursion (LAGE)] were compared between the two groups. Logistic regression analysis was used to identify risk factors affecting the prognosis of patients with acute pancreatitis. Receiver operating characteristic curves (ROC) were plotted and the area under the curve (AUC), sensitivity, and specificity were calculated, so as to evaluate the predictive efficacy of each indicator for the prognosis of patients with acute pancreatitis. Results:Compared with the good prognosis group, the poor prognosis group showed significantly higher levels of initial blood glucose [12.80(7.13, 17.75) mmol/L vs 8.90(6.80, 11.60) mmol/L], maximum blood glucose [16.15(13.45, 21.10) mmol/L vs 11.2(9.10, 14.40) mmol/L], SDBG [4.19(2.47, 5.03) mmol/L vs 1.79(1.15, 2.81) mmol/L], and LAGE [5.15(3.58,7.65) mmol/L vs 4.05(2.40, 5.70) mmol/L], as well as a significantly longer length of hospital stay [10.5(6, 26.75) days vs 9(6, 15) days], with all differences being statistically significant (all P value <0.05). Multivariate logistic regression analysis showed that initial blood glucose ( OR=1.201, 95% CI 1.099-1.313), SDBG ( OR=1.681, 95% CI 1.306-2.164), LAGE ( OR=1.848, 95% CI 1.524-2.240), and length of hospital stay ( OR=1.136, 95% CI 1.082-1.193) were influencing factors for the prognosis of patients with acute pancreatitis. ROC analysis showed that the AUC values for initial blood glucose, SDBG, LAGE, and length of hospital stay were 0.741(0.676-0.806), 0.794 (0.728-0.860), 0.836(95% CI 0.793-0.879), and 0.847(95% CI 0.807-0.887), respectively, with sensitivities of 80.1%, 91.8%, 60.8%, and 64.8%, and specificities of 56.3%, 56.3%, 93.8%, and 93.8%. Conclusions:Blood glucose fluctuations within 24 hours of admission are risk factors for poor prognosis in patients with acute pancreatitis.

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

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.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.