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.

AIM To investigate the mechanism of Jiedu Yizhi Formula on cognitive function and neuroinflammation in a mouse model of Alzheimer's disease(AD).METHODS 50 APP/PS1 double transgenic mice were randomly divided into the model group,the donepezil group,and the low-dose,moderate-dose,and high-dose Jiedu Yizhi Formula group(1.78,3.56 and 7.12 g/kg),with 10 mice in each group,in contrast to the 10 WT mice of the blank group.Following anesthesia administration and 8-week oral gavage regimen with respective drugs,all mice underwent final tissue sample collection.The mice had their learning and memory ability assessed by Morris water maze and nesting behavior scores;their pathology of brain tissue and Aβ expression observed using HE,Nissl and IHC staining;their polarization of microglia and the expression of inflammatory factors in hippocampal tissue detected by IF and ELISA;their hippocampal expression of PI3K/Akt/mTOR signaling pathway detected by RT-qPCR and Western blot.RESULTS Compared with the blank group,the model group had lower scores in total swimming distance,frequency in crossing the platform,residence time in the target quadrant,and nesting behavior scores(P＜0.05,P＜0.01);prolonged evasion latency(P＜0.01);more disorganized arrangement of pyramidal cells,solidification and deep staining,unclear demarcation,irregular cell shapes,reduction of Nyctinidia,and increased Aβ deposition in the brain tissue(P＜0.01);elevated expression of hippocampal microglia M1-type markers CD16/32 and lba-1(P＜0.01);decreased levels of M2-type marker CD206(P＜0.05);elevated levels of TNF-α and IL-1β(P＜0.01);decreased expressions of IL-13 and IL-4(P＜0.01);and decreased levels of PI3K,Akt and mTOR mRNA,and reduced p-PI3K,p-Akt and p-mTOR protein expressions(P＜0.01).Compared to the model group,the donepezil group and the Jiedu Yizhi Formula groups showed statistically significant improvements in the aforementioned indexes(P＜0.05,P＜0.01),with the magnitude of improvement being higher in the high-dose Jiedu Yizhi Formula group.CONCLUSION Jiedu Yizhi Formula suppresses microglia Ml-type polarization while enhancing M2-type polarization via activation the PI3K/Akt/mTOR signaling pathway,which subsequently reduces inflammatory cytokine secretion.This mechanism attenuates Aβ deposition in brain tissues and ameliorates cognitive dysfunction in AD mouse models.

In recent decades,the incidence of human papillomavirus(HPV)-associated oropharyngeal squamous cell carcinoma(OPSCC)has shown a marked increase.Significant changes have also occurred in the OPSCC diagnosis and treatment paradigm.Deter-mining HPV status prior to treatment is now essential,and radiotherapy/chemotherapy,immunotherapy,and minimally invasive surgical techniques have progressively emerged as key modalities for managing OPSCC.However,alongside these paradigm shifts,a comprehen-sive technical consensus guiding the entire diagnostic and therapeutic process for OPSCC patients is currently lacking.Given China's large population base and the rising incidence of OPSCC,an expert panel convened to develop a clinical technical consensus on OPSCC diagno-sis and management tailored to China's specific context.This consensus aims to further enhance and standardize understanding of OPSCC management techniques among relevant healthcare professionals.

Heatstroke,especially in high-temperature and high-humidity environments,is a life-threatening acute heat-injury disease that seriously endangers human health.Timely and effective on-site treatment is crucial for patients'survival and prognosis.Early recognition,rapid assessment,and on-site cooling are the core of pre-hospital treatment of heatstroke.Currently,there is a lack of standardized application procedures for pre-hospital emergency care of heatstroke.Therefore,the"Expert Consensus on Pre-hospital Emergency Management of Heatstroke(2024 edition)"was initiated by the Expert Group on Heatstroke Prevention of the People's Liberation Army and developed in collaboration with experts from local pre-hospital emergency care,emergency departments,and intensive care units.This consensus focuses on heatstroke prevention,on-site and ambulance-based treatment,and early emergency room interventions,and puts forward 10 evidence-based recommendations,aiming to provide a reference for scientific and standardized pre-hospital emergency care of heatstroke.

AIM To investigate the mechanism of Jiedu Yizhi Formula on cognitive function and neuroinflammation in a mouse model of Alzheimer's disease(AD).METHODS 50 APP/PS1 double transgenic mice were randomly divided into the model group,the donepezil group,and the low-dose,moderate-dose,and high-dose Jiedu Yizhi Formula group(1.78,3.56 and 7.12 g/kg),with 10 mice in each group,in contrast to the 10 WT mice of the blank group.Following anesthesia administration and 8-week oral gavage regimen with respective drugs,all mice underwent final tissue sample collection.The mice had their learning and memory ability assessed by Morris water maze and nesting behavior scores;their pathology of brain tissue and Aβ expression observed using HE,Nissl and IHC staining;their polarization of microglia and the expression of inflammatory factors in hippocampal tissue detected by IF and ELISA;their hippocampal expression of PI3K/Akt/mTOR signaling pathway detected by RT-qPCR and Western blot.RESULTS Compared with the blank group,the model group had lower scores in total swimming distance,frequency in crossing the platform,residence time in the target quadrant,and nesting behavior scores(P＜0.05,P＜0.01);prolonged evasion latency(P＜0.01);more disorganized arrangement of pyramidal cells,solidification and deep staining,unclear demarcation,irregular cell shapes,reduction of Nyctinidia,and increased Aβ deposition in the brain tissue(P＜0.01);elevated expression of hippocampal microglia M1-type markers CD16/32 and lba-1(P＜0.01);decreased levels of M2-type marker CD206(P＜0.05);elevated levels of TNF-α and IL-1β(P＜0.01);decreased expressions of IL-13 and IL-4(P＜0.01);and decreased levels of PI3K,Akt and mTOR mRNA,and reduced p-PI3K,p-Akt and p-mTOR protein expressions(P＜0.01).Compared to the model group,the donepezil group and the Jiedu Yizhi Formula groups showed statistically significant improvements in the aforementioned indexes(P＜0.05,P＜0.01),with the magnitude of improvement being higher in the high-dose Jiedu Yizhi Formula group.CONCLUSION Jiedu Yizhi Formula suppresses microglia Ml-type polarization while enhancing M2-type polarization via activation the PI3K/Akt/mTOR signaling pathway,which subsequently reduces inflammatory cytokine secretion.This mechanism attenuates Aβ deposition in brain tissues and ameliorates cognitive dysfunction in AD mouse models.

In recent decades,the incidence of human papillomavirus(HPV)-associated oropharyngeal squamous cell carcinoma(OPSCC)has shown a marked increase.Significant changes have also occurred in the OPSCC diagnosis and treatment paradigm.Deter-mining HPV status prior to treatment is now essential,and radiotherapy/chemotherapy,immunotherapy,and minimally invasive surgical techniques have progressively emerged as key modalities for managing OPSCC.However,alongside these paradigm shifts,a comprehen-sive technical consensus guiding the entire diagnostic and therapeutic process for OPSCC patients is currently lacking.Given China's large population base and the rising incidence of OPSCC,an expert panel convened to develop a clinical technical consensus on OPSCC diagno-sis and management tailored to China's specific context.This consensus aims to further enhance and standardize understanding of OPSCC management techniques among relevant healthcare professionals.

Objective To investigate the value of constructing a risk prediction model of brain metastasis in lung cancer based on clinical-CT imaging.Methods The clinical and CT imaging data of 208 patients with lung cancer confirmed by surgical pathology or puncture biopsy were analyzed retrospectively,including 98 patients in the metastasis group and 110 patients in the non-metastasis group.Univariable and binary logistic regression analyses were performed between the two groups,and the clinical,CT imaging,and clinical-CT imaging models were constructed according to the selected independent risk factors.Prediction model performance was eval-uated with receiver operating characteristic(ROC)curve,calibration curve and decision curve analysis(DCA).Results Multivariate analysis showed that T stage,pathological type,radiotherapy and chemotherapy,surgery,long diameter(LD),short diameter(SD),minimum CT value(CTmin)were the independent risk factors for predicting brain metastasis in lung cancer(P<0.05).The area under the curve(AUC)of clinical,CT imaging and clinical-CT imaging models were 0.925,0.764,0.941,respectively.DeLong test analysis showed that the AUC of clinical-CT imaging model,clinical model and CT imaging model was statistical difference(Z=2.093,5.777,all P<0.05).The calibration curve suggested a good fit of the clinical-CT imaging model.The DCA suggested that the clinical-CT imaging model demonstrates good clinical benefits.Conclusion The clinical-CT imaging model can effectively predict the occurrence of brain metastasis in lung cancer,which is helpful to guide the development of accurate diagnosis and treatment plan.

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.