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 develop a melanoma diagnosis framework based on large-scale vision-language models,and to explore the feasibility and accuracy of the framework for melanoma diagnosis.Methods The publicly available Derm7pt dataset,which was divided into a training set(346 cases),a validation set(161 cases),and a test set(320 cases)was utilized.A melanoma diagnosis framework based on large-scale vision-language models was proposed,comprising two text branches and one visual branch.In the text branches,one branch processed fixed clinical prompts,while the other handled learnable prompts.This design aimed to optimize the effectiveness of learnable prompts through guidance from fixed clinical prompts.The visual branch processed dermoscopic images and enhanced melanoma feature recognition through fine-tuning the image encoder.Results On the Derm7pt dataset,our method outperformd other existing method.It achieved an area under the receiver operating characteristic curve(AUC)of 87.35％,an accuracy of 84.17％,and an F1-score of 84.01％.Conclusion The study demonstrates that with appropriate fine-tuning strategies,methods based on large-scale vision-language pre-trained models can effectively adapt to melanoma diagnosis tasks.This approach can serve as a powerful auxiliary tool for doctors,helping them make more accurate diagnostic decisions.

Aim To elucidate the molecular mecha-nism underlying the inhibitory effect of liquidambaric acid(LDA)targeting TNF receptor associated factor 6(TRAF6)in colorectal cancer.Methods This study employed microscale thermophoresis(MST),drug af-finity responsive target stability assay(DARTS)and cellular thermal shift assay(CETSA)to confirm the direct binding of LDA to TRAF6.Additionally,we generated TRAF6 knockout colorectal cancer HCT116 cells using CRISPR/Cas9 technology,and assessed the impact of LDA on TRAF6-regulated Hippo/YAP and Wnt signaling pathways through immunofluorescence a-nalysis and TOPFlash/Renilla luciferase reporter sys-tem.Co-IP and proximity ligation assays(PLA)were conducted to investigate LDA-regulated TRAF6 pro-tein-protein interactions and elucidate molecular mech-anisms.Results The direct binding of LDA to TRAF6 was confirmed in cell lysates and living cells.LDA promoted TRAF6-dependent nuclear translocation of YAP in colorectal cancer cells,and inhibited Wnt signaling by overexpressing TRAF6.Co-IP and PLA revealed that TRAF6 formed a tripartite complex with YAP and β-catenin in colon cancer cells,where TRAF6 was a key scaffolding protein of the tripartite complex.LDA disrupted the interactions between the TRAF domain of TRAF6 and YAP,as well as YAP and β-catenin.Conclusion LDA regulates Hippo/YAP signaling pathway by targeting TRAF6 and inhib-its colorectal cancer.

Objective To explore and identify the nutritional/inflammatory indicator with the highest predictive potential for overall survival(OS)in postoperative tumor patients so as to provide guidance for postoperative rehabilitation of tumor patients.Methods Data from 3 191 surgical patients were collected,including 15 nutritional/inflammatory indicators.The maximum selection rank statistic method was used to calculate the optimal cut-off values for continuous indicators.The Kaplan-Meier method was used to assess OS,and Cox proportional hazards models were used to analyze the association between the aforementioned 15 indicators and survival.The predictive value of these 15 indicators was evaluated with receiver operating characteristic(ROC)curves and C-index.Results Multivariate analysis showed that all 15 indicators were significantly associated with poorer OS in surgical patients(P＜0.05 for all).Time-dependent area under the curve(AUC)and C-index analysis indicated that 3 indicators with the highest predictive potential in OS in postoperative tumor patients were the nutritional risk index(NRI)(C-index:0.597),C-reactive protein-to-albumin ratio(CAR)(C-index:0.587),and C-reactive protein-to-lymphocyte ratio(CLR)(C-index:0.587).The optimal cut-off value for NRI was determined to be 104.31(i.e.,NRI＜104.31 suggests malnutrition)with the maximum selection rank statistic method,the optimal cut-off value for CAR to be 0.05(i.e.,CAR≥0.05 suggests a strong inflammatory response,often accompanied by malnutrition),and the optimal cut-off value for CLR to be 1.18(i.e.,CLR≥1.18 suggests a strong inflammatory response).Subgroup analysis indicated that NRI,CAR,and CLR had good correlation with tumor staging,and there were significant differences between tumor node metastasis(TNM)Ⅲ/Ⅳ stage patients and TNM Ⅰ/Ⅱ stage patients when there was a strong inflammatory response or malnutrition.Conclusion In postoperative tumor patients,NRI,CLR,and CAR have high prognostic value.Combining these with the patient's clinical stage,it enables more precise guidance for clinical diagnosis and treatment strategies.

Aim To elucidate the molecular mecha-nism underlying the inhibitory effect of liquidambaric acid(LDA)targeting TNF receptor associated factor 6(TRAF6)in colorectal cancer.Methods This study employed microscale thermophoresis(MST),drug af-finity responsive target stability assay(DARTS)and cellular thermal shift assay(CETSA)to confirm the direct binding of LDA to TRAF6.Additionally,we generated TRAF6 knockout colorectal cancer HCT116 cells using CRISPR/Cas9 technology,and assessed the impact of LDA on TRAF6-regulated Hippo/YAP and Wnt signaling pathways through immunofluorescence a-nalysis and TOPFlash/Renilla luciferase reporter sys-tem.Co-IP and proximity ligation assays(PLA)were conducted to investigate LDA-regulated TRAF6 pro-tein-protein interactions and elucidate molecular mech-anisms.Results The direct binding of LDA to TRAF6 was confirmed in cell lysates and living cells.LDA promoted TRAF6-dependent nuclear translocation of YAP in colorectal cancer cells,and inhibited Wnt signaling by overexpressing TRAF6.Co-IP and PLA revealed that TRAF6 formed a tripartite complex with YAP and β-catenin in colon cancer cells,where TRAF6 was a key scaffolding protein of the tripartite complex.LDA disrupted the interactions between the TRAF domain of TRAF6 and YAP,as well as YAP and β-catenin.Conclusion LDA regulates Hippo/YAP signaling pathway by targeting TRAF6 and inhib-its colorectal cancer.

Cilia,as cellular sensory organelles,actively partici-pate in and regulate cellular processes such as autophagy and metabolic breakdown during their generation and transportation.Autophagy,on the other hand,is a cell self-protection mecha-nism that maintains cellular homeostasis by clearing aggregates and damaged organelles.Combining recent research findings,this review comprehensively elucidates the bidirectional crosstalk between primary cilia and autophagy.Specifically,it highlights the crucial role of cilia-dependent signaling pathways in activa-ting cellular autophagy and how autophagy regulates cilia genera-tion and length by degrading specific ciliary proteins.Moreover,the dysregulation of primary cilia and autophagy is closely asso-ciated with the clinical manifestations and pathogenesis of vari-ous ciliopathy-related diseases such as polycystic kidney disease and tuberous sclerosis.In terms of pharmacotherapy,this review provides a comprehensive and in-depth overview of small mole-cule inhibitors targeting ciliogenesis,including cytoskeletal drugs and Hedgehog signaling pathway inhibitors.Despite the current limitations in clinical use,these drugs lay the groundw-ork for developing highly specific targeted small molecule inhibi-tors of ciliogenesis and for the treatment of ciliopathies and canc-ers.By systematically discussing ciliogenesis,autophagy,disea-ses and drugs,this review offers new insights for further elucida-ting the crosstalk between ciliogenesis and autophagy,exploring their pathological mechanisms in disease development,and de-veloping therapeutic strategies in the future.

Cilia,as cellular sensory organelles,actively partici-pate in and regulate cellular processes such as autophagy and metabolic breakdown during their generation and transportation.Autophagy,on the other hand,is a cell self-protection mecha-nism that maintains cellular homeostasis by clearing aggregates and damaged organelles.Combining recent research findings,this review comprehensively elucidates the bidirectional crosstalk between primary cilia and autophagy.Specifically,it highlights the crucial role of cilia-dependent signaling pathways in activa-ting cellular autophagy and how autophagy regulates cilia genera-tion and length by degrading specific ciliary proteins.Moreover,the dysregulation of primary cilia and autophagy is closely asso-ciated with the clinical manifestations and pathogenesis of vari-ous ciliopathy-related diseases such as polycystic kidney disease and tuberous sclerosis.In terms of pharmacotherapy,this review provides a comprehensive and in-depth overview of small mole-cule inhibitors targeting ciliogenesis,including cytoskeletal drugs and Hedgehog signaling pathway inhibitors.Despite the current limitations in clinical use,these drugs lay the groundw-ork for developing highly specific targeted small molecule inhibi-tors of ciliogenesis and for the treatment of ciliopathies and canc-ers.By systematically discussing ciliogenesis,autophagy,disea-ses and drugs,this review offers new insights for further elucida-ting the crosstalk between ciliogenesis and autophagy,exploring their pathological mechanisms in disease development,and de-veloping therapeutic strategies in the future.

Objective To explore and identify the nutritional/inflammatory indicator with the highest predictive potential for overall survival(OS)in postoperative tumor patients so as to provide guidance for postoperative rehabilitation of tumor patients.Methods Data from 3 191 surgical patients were collected,including 15 nutritional/inflammatory indicators.The maximum selection rank statistic method was used to calculate the optimal cut-off values for continuous indicators.The Kaplan-Meier method was used to assess OS,and Cox proportional hazards models were used to analyze the association between the aforementioned 15 indicators and survival.The predictive value of these 15 indicators was evaluated with receiver operating characteristic(ROC)curves and C-index.Results Multivariate analysis showed that all 15 indicators were significantly associated with poorer OS in surgical patients(P＜0.05 for all).Time-dependent area under the curve(AUC)and C-index analysis indicated that 3 indicators with the highest predictive potential in OS in postoperative tumor patients were the nutritional risk index(NRI)(C-index:0.597),C-reactive protein-to-albumin ratio(CAR)(C-index:0.587),and C-reactive protein-to-lymphocyte ratio(CLR)(C-index:0.587).The optimal cut-off value for NRI was determined to be 104.31(i.e.,NRI＜104.31 suggests malnutrition)with the maximum selection rank statistic method,the optimal cut-off value for CAR to be 0.05(i.e.,CAR≥0.05 suggests a strong inflammatory response,often accompanied by malnutrition),and the optimal cut-off value for CLR to be 1.18(i.e.,CLR≥1.18 suggests a strong inflammatory response).Subgroup analysis indicated that NRI,CAR,and CLR had good correlation with tumor staging,and there were significant differences between tumor node metastasis(TNM)Ⅲ/Ⅳ stage patients and TNM Ⅰ/Ⅱ stage patients when there was a strong inflammatory response or malnutrition.Conclusion In postoperative tumor patients,NRI,CLR,and CAR have high prognostic value.Combining these with the patient's clinical stage,it enables more precise guidance for clinical diagnosis and treatment strategies.

Objective:To identify the gene mutation types of 4 suspected β-thalassemia patients in Yunnan Province,and to analyze the genotypes and hematological phenotypes.Methods:Whole genome sequencing was performed on the samples of 4 suspected β-thalassemia patients from the Dai ethnic group in a thalassemia endemic area of Yunnan Province,whose hematological phenotypes were not consistent with the results of common thalassemia gene mutations.The mutations of β-globin gene clusters were confirmed by polymerase chain reaction(PCR)and Sanger DNA sequencing technology.Results:The 3.5 kb deletion in β-globin gene cluster(NC_000011.10:g.5224302-5227791 del3490bp)was detected in 4 patients'samples,of which 1 case was also detected with HbE mutation and 1 case with CD17 mutation.These 2 patients displayed moderate anemia phenotype,while the two patients with only the 3.5 kb deletion presented with other mild anemia phenotype.Conclusion:Heterozygous carriers with rare 3.5 kb deletion of the β-globin gene cluster may develop mild anemia,compound mutations of the 3.5 kb deletion with other mutations may led to intermediate thalasemia with moderate to sever anemia.In areas with a high incidence of thalassemia,suspected patients should undergo genetic testing to avoid missing or misdiagnosing rare mutations.

Objective The leptin receptor,encoded by the LEPR gene,is involved in tumorigenesis.A potential functional variant of LEPR,rs1137101(Gln223Arg),has been extensively investigated for its contribution to the risk of digestive system(DS)cancers,but results remain conflicting rather than conclusive.Here,we performed a case-control study and subsequent meta-analysis to examine the association between rs1137101 and DS cancer risk. Methods A total of 1,727 patients with cancer(gastric/liver/colorectal:460/480/787)and 800 healthy controls were recruited.Genotyping of rs1137101 was conducted using a polymerase chain reaction-restriction fragment length polymorphism(PCR-RFLP)assay and confirmed using Sanger sequencing.Twenty-four eligible studies were included in the meta-analysis. Results After Bonferroni correction,the case-control study revealed that rs1137101 was significantly associated with the risk of liver cancer in the Hubei Chinese population.The meta-analysis suggested that rs1137101 is significantly associated with the risk of overall DS,gastric,and liver cancer in the Chinese population. Conclusion The LEPR rs1137101 variant may be a genetic biomarker for susceptibility to DS cancers(especially liver and gastric cancer)in the Chinese population.