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.

ObjectiveTo investigate the risk factors for post-acute pancreatitis diabetes mellitus （PPDM-A） in patients with acute pancreatitis （AP）， to construct a nomogram prediction model， and to provide a reference for the development of individualized treatment regimens. MethodsA total of 351 patients with AP who were admitted to Xuzhou Municipal Hospital Affiliated to Xuzhou Medical University from June 2021 to January 2025 were prospectively enrolled， and they were randomly divided into modeling group with 246 patients and validation group with 105 patients at a ratio of 7∶3. According to the presence or absence of PPDM-A in the patients with AP， the modeling group was further divided into PPDM-A group with 86 patients and non-PPDM-A group with 160 patients. Clinical data were collected from all patients. The least absolute shrinkage and selection operator （LASSO） regression analysis was used to determine independent variables， and a Logistic regression analysis was used to investigate the influencing factors for PPDM-A. R software was used to construct a nomogram model. The receiver operating characteristic curve was used to assess the discriminatory ability of the model， and the Hosmer-Lemeshow test was used to test the model fitting degree， and the calibration curve was used to evaluate the model consistency； and decision curve analysis （DCA） was used to assess its clinical application value. The independent-samples t test was used for comparison of continuous data between two groups， and the chi-square test was used for comparison of categorical data between two groups. ResultsAmong the 246 patients， 86 developed PPDM-A， resulting in an incidence rate of 34.96%. There were significant differences between the PPDM-A group and the non-PPDM-A group in the proportion of patients with an age of ≥60 years （65.12% vs 40.62%， P<0.05）， male sex （75.58% vs 55.63%， P<0.05）， a body mass index （BMI） of ≥24 kg/m² （63.95% vs 37.50%， P<0.05）， alcoholic AP （56.98% vs 36.87%， P<0.05）， moderate-to-severe AP （54.65% vs 35.00%， P<0.05）， or a computed tomography severity index （CTSI） score of ≥4 points （48.84% vs 28.75%， P<0.05）， as well as significant differences in the levels of blood calcium （1.46±0.35 mmol/L vs 1.89±0.37 mmol/L， P<0.05） and random blood glucose （Glu） （17.68±4.12 mmol/L vs 11.68±4.27 mmol/L， P<0.05）. The LASSO regression analysis obtained 8 independent variables. The Logistic regression analysis showed that age， sex， BMI， alcoholic AP， moderate-to-severe AP， CTSI score， and Glu were risk factors for PPDM-A （all P<0.05）， while blood calcium was a protective factor （P<0.05）. The model had an area under the ROC curve （AUC） of 0.932 （95% confidence interval ［CI］： 0.903 — 0.962） in the modeling group， and the Hosmer-Lemeshow goodness-of-fit test yielded χ²=7.346 （P=0.728）， the accuracy of model fitting was good； the calibration curve showed that the predicted probability was consistent with the actual probability， indicating that the consistency was good. The model had an AUC of 0.835 （95%CI： 0.753 — 0.917） in the validation group， and the Hosmer-Lemeshow goodness-of-fit test yielded χ²=7.014 （P=0.711）， the accuracy of model fitting was good； the calibration curve showed that the predicted probability was consistent with the actual probability， indicating that the consistency was good. The DCA results of the modeling group showed that the model exhibited a high clinical value in evaluating PPDM-A when the threshold probability was 0.13 — 0.94. ConclusionAge， sex， BMI， alcoholic AP， moderate-to-severe AP， blood calcium， CTSI score， and Glu are influencing factors for PPDM-A. The nomogram model constructed based on the above influencing factors shows good performance in predicting the risk of PPDM-A and can thus provide a reference for developing prevention strategies for PPDM-A in clinical practice.

OBJECTIVE: To investigate platelet count trajectories after induction therapy with venetoclax combined with azacitidine (VA regimen) in newly diagnosed AML patients and further analyze its clinical significance. METHODS: Clinical date of 50 newly diagnosed AML patients who received VA treatment from March 2020 to July 2023 in Department of Hematology of the First Hospital of Lanzhou University were retrospectively collected. The platelet trajectories after induction chemotherapy were constructed by using group-based trajectory modeling. To study the association between diverse trajectories of platelet counts and compound complete remission (cCR) rate, overall response rate (ORR), minimal residual disease (MRD) negative rate and overall survival (OS) rate. The Cox proportional hazard model was used to evaluate the relationship between platelet trajectory and OS. The logistic regression was used to analyze the influence of individual characteristics on platelet trajectory. RESULTS: Two platelet trajectories were identified based on the model, including platelet slowly increased group (n=31, 62.0%) and platelet rapidly increased group (n=19, 38.0%). There were statistically significant differences in cCR rate, ORR and OS rate between platelet slowly increased group and platelet rapidly increased group (all P < 0.05). The Cox regression analysis showed that platelet rapidly increased group was associated with a decreased risk of mortality compared with platelet slowly increased group (HR=0.153, 95%CI : 0.045-0.527, P =0.003). Logistic regression analysis showed that IDH1/2 mutation (OR =3.908, 95%CI : 1.023-14.923, P =0.046) and platelet transfusion (OR =0.771, 95%CI : 0.620-0.959, P =0.020) were independent influencing factors of platelet trajectory. CONCLUSION The dynamic trajectory of platelet counts in newly diagnosed AML patients who received VA treatment can serve as a significant indicator to observe the efficacy and prognosis. The platelet rapidly increased is an independent protective factor for good prognosis. TheIDH1 /2 mutation and platelet transfusion are independent influencing factors of platelet trajectory.
Humans ; Leukemia, Myeloid, Acute/blood* ; Sulfonamides/administration & dosage* ; Azacitidine/therapeutic use* ; Platelet Count ; Retrospective Studies ; Bridged Bicyclo Compounds, Heterocyclic/administration & dosage* ; Male ; Female ; Antineoplastic Combined Chemotherapy Protocols/therapeutic use* ; Induction Chemotherapy ; Survival Rate

BACKGROUND: Biomarkers-based prediction of long-term risk of acute coronary syndrome (ACS) is scarce. We aim to develop a risk score integrating clinical routine information (C) and plasma biomarkers (B) for predicting long-term risk of ACS patients. METHODS: We included 2729 ACS patients from the OCEA (Observation of cardiovascular events in ACS patients). The earlier admitted 1910 patients were enrolled as development cohort; and the subsequently admitted 819 subjects were treated as validation cohort. We investigated 10-year risk of cardiovascular (CV) death, myocardial infarction (MI) and all cause death in these patients. Potential variables contributing to risk of clinical events were assessed using Cox regression models and a score was derived using main part of these variables. RESULTS: During 16,110 person-years of follow-up, there were 238 CV death/MI in the development cohort. The 7 most important predictors including in the final model were NT-proBNP, D-dimer, GDF-15, peripheral artery disease (PAD), Fibrinogen, ST-segment elevated MI (STEMI), left ventricular ejection fraction (LVEF), termed as CB-ACS score. C-index of the score for predication of cardiovascular events was 0.79 (95% CI: 0.76-0.82) in development cohort and 0.77 (95% CI: 0.76-0.78) in the validation cohort (5832 person-years of follow-up), which outperformed GRACE 2.0 and ABC-ACS risk score. The CB-ACS score was also well calibrated in development and validation cohort (Greenwood-Nam-D'Agostino: P = 0.70 and P = 0.07, respectively). CONCLUSIONS CB-ACS risk score provides a useful tool for long-term prediction of CV events in patients with ACS. This model outperforms GRACE 2.0 and ABC-ACS ischemic risk score.

Objective:To develop a treatment-related quality of life scale for Chinese patients with multiple myeloma (MM) and to test its reliability and validity.Methods:The initial scale was constructed through a literature search, Delphi expert correspondence, and cognitive testing. This study conducted a preliminary survey of 379 patients with MM and a formal survey of 865 patients from the hematology departments of 155 hospitals nationwide from February 2024 to March 2024. The final scale was obtained after conducting item analysis and reliability and validity tests on the initial scale.Results:The constructed scale contains 36 items covering six domains: physiological, psychological, social, treatment side effects, general health, and others. In the preliminary survey, the Cronbach’s alpha coefficient of each item ranged from 0.597 to 0.939, and the test-retest reliability was 0.747 ( P<0.001). Exploratory factor analysis extracted eight common factors with a cumulative variance contribution of 60.058%. In the formal survey, the Cronbach’s alpha coefficient of each item ranged from 0.484 to 0.930, and the test-retest reliability was 0.835 ( P<0.001). Confirmatory factor analysis revealed a comparative fit index of 0.750, a root-mean-square error of approximation of 0.090, and a root-mean-square residual of 0.067. Conclusion:The treatment-related quality of life scale for Chinese patients with MM designed in this study exhibited good reliability and validity, reflecting the impact of treatment on the quality of life of patients. This scale can provide a reference to clinicians for assessing the disease status of patients.

Real-world study (RWS), based on multi-source data from real medical environments, is gradually becoming an important supplement to traditional randomized controlled trials, and its application in the field of transfusion medicine is becoming increasingly widespread. This article systematically reviews the definition and methodological system of RWS, examines its application cases in clinical blood transfusion research, and discusses the advantages, limitations, and future research directions of RWS, aiming to provide a reference for evidence-based research in blood transfusion medicine.

Real-world study (RWS), based on multi-source data from real medical environments, is gradually becoming an important supplement to traditional randomized controlled trials, and its application in the field of transfusion medicine is becoming increasingly widespread. This article systematically reviews the definition and methodological system of RWS, examines its application cases in clinical blood transfusion research, and discusses the advantages, limitations, and future research directions of RWS, aiming to provide a reference for evidence-based research in blood transfusion medicine.

Objective:To explore the application value of three-dimensional high-resolution anorectal manometry(3D-HRAM)model in the diagnosis and localization of anal sphincter injury after surgery for complex anal fistula.Methods:A prospective study was con-ducted on 92 patients who had undergone surgery for complex anal fistula in the Department of Coloproctology of The People's Hospi-tal Affiliated to Fujian University of Traditional Chinese Medicine from January 2023 to January 2024.The study was conducted in two stages.In the first stage,92 patients underwent 3D-HRAM and endoanal ultrasonography(EAUS)to examine the sphincter,and the data were compared with intraoperative records to evaluate the diagnostic efficiency and localization accuracy of 3D-HRAM and EAUS.In the second stage,92 patients who had been examined were grouped according to the presence or absence of symptoms of anal dysfunction to further verify the diagnostic and localization values of 3D-HRAM and EAUS for postoperative compensated/decompen-sated sphincter injury.Results:Among 92 patients,41 and 57 patients were diagnosed with sphincter injury through 3D-HRAM and EAUS,with a sensitivity of 61.19%and 85.07%,a specificity of 88%and 76%,an area under the curve of 0.739 and 0.813 calcu-lated by plotting the receiver operating characteristic curve,and a localization accuracy of 44.77%and 71.64%,respectively,showing significant differences between 3D-HRAM and EAUS(P=0.002),indicating that 3D-HRAM had lower diagnostic efficiency and local-ization accuracy than EAUS for anal sphincter injury after surgery for complex anal fistula.After grouping by symptoms,the diagnostic efficiency and localization accuracy of 3D-HRAM for symptomatic sphincter injury(decompensated)were significantly better than those for asymptomatic sphincter injury,and were similar to those of EAUS(P=0.763).Conclusion:The application advantage of 3D-HRAM lies in the diagnosis and localization of decompensated anal sphincter injury after surgery for complex anal fistula,which provides effective technical support for the study of anal defecation control mechanisms and injury compensation mechanisms.

Depression is a prevalent mental and emotional disor-der that often results in significant emotional disturbances,cog-nitive dysfunction,and memory impairments.It is characterized by a high incidence rate,a substantial disability burden,and limited therapeutic efficacy.Currently,the long-term use of medications for the treatment of depression can result in a range of adverse reactions,highlighting the urgent need to explore no-vel approaches that can effectively alleviate depressive symptoms while minimizing side effects.Curcumin,a natural polyphenolic compound derived from the rhizome of turmeric,demonstrates considerable potential in the prevention and treatment of depres-sion,owing to its diverse array of biological activities.In recent years,numerous studies have investigated the use of curcumin for the treatment of depression.This article aims to provide a comprehensive review of the mechanisms of action underlying curcumin's efficacy in treating depression.Specifically,it focu-ses on its ability to improve neurotransmitter imbalances,restore neural plasticity,alleviate neural damage,mitigate dysfunction of the hypothalamic-pituitary-adrenal(HPA)axis,regulate in-flammatory factors and neuroinflammatory signaling pathways,and inhibit oxidative stress.This review is intended to offer in-sights and methodological references for basic research on curcu-min,as well as for the development of novel therapeutic agents for the treatment of depression.

Objectives:The study assessed the relationship between atherogenic index of plasma(AIP)and the rapid progression of coronary non-target lesions.Methods:A total of 1 247 patients with coronary artery disease who underwent two coronary angiography examinations at Fuwai Hospital,Chinese Academy of Medical Sciences between January 2010 and September 2014 were enrolled in this retrospective study.The AIP is defined as the base 10 logarithm of the ratio of the concentrations of triglyceride to high-density lipoprotein cholesterol.Patients were divided into the high AIP group(n=623)and the low AIP group(n=624)based on the median value of AIP.Lesion rapid progression is defined as an increase of more than 10%in the lumen stenosis of the lesion with a stenosis rate of more than 50%,or an increase of more than 30%in the lumen stenosis rate of the lesion with a stenosis rate of less than 50%,or a progression to total occlusion within 2 years.Results:Median AIP was 0.39(0.23-0.56)in this patient cohort.Rapid progression of non-target lesions occurred in 65(5.21%),including 42(6.74%)in the high AIP group.The Kaplan-Meier curve showed that the cumulative incidence of rapid progression of non-target lesions was higher in the high AIP group than in the low AIP group(HR=1.751,95%CI:1.053-2.912,log-rank P=0.028).In univariate cox analysis,the AIP and high AIP correlated with rapid progression of non-target lesions.After multivariate adjustment,AIP was an independent risk factor for rapid progression of non-target lesions(adjusted HR=2.731,95%CI:1.090-6.844,P=0.032).Conclusions:AIP is an independent risk factor for rapid progression of non-target lesions.AIP should be considered as a biomarker for estimating the risk of cardiovascular disease,along with other traditional risk factors.