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 understand the distribution, species composition, seasonal fluctuations, and presence of Dabie bandavirus in ticks in Tai'an City, providing a basis for assessing tick-borne disease risks and formulating prevention strategies. Methods Free-living ticks were monitored using the flagging method, whereas parasitic ticks were monitored through host surface examination. Reverse transcription-polymerase chain reaction (RT-qPCR) was used to detect the presence of Bandavirus dabieense in tick specimens. Results The density of free-living ticks in Tai'an City showed a continuous decreasing trend over the 3 years from 2021 to 2023, with an average tick density of 0.43 ticks/(flag·100 m). The dominant habitats were scenic areas and forests, and the seasonal fluctuations exhibited a bimodal pattern, peaking in March and August. The only free-living tick species captured was Haemaphysalis longicornis. Over the 3 years, the average tick index for parasitic ticks was 1.85, with sheep as the primary host. Seasonal fluctuations also followed a bimodal pattern, peaking in March and August. The primary parasitic tick species captured were H. longicornis and Rhipicephalus sanguineus. No Dabie bandavirus was detected in the tick specimens. Conclusions Tick density in Tai'an City remains relatively high, necessitating continued efforts to enhance tick surveillance and implement targeted prevention measures in rural environments to further reduce the health risks posed by tick-borne diseases.

Background:Bushen Zhuanggu Formula(BZF),derived from the classic Yougui Pills,has shown favorable clinical efficacy in treating advanced nontraumatic osteonecrosis of the femoral head(NONFH),particularly by promoting bone repair.However,its underlying mechanisms remain unclear.Objective:This study aimed to explore the mechanisms by which BZF promotes bone repair in advanced NONFH.Materials and methods:A total of 518 potential BZF targets were identified from the ETCM v2.0 database.Transcriptomic profiling of clinical cohorts revealed 485 differentially expressed genes in advanced NONFH patients compared to healthy controls.A drug target-disease gene interaction network was constructed to identify candidate BZF targets involved in NONFH pathogenesis.In vivo experiments were conducted to validate the effects of BZF in a rat model of advanced NONFH.Results:Network analysis identified key pathways associated with blood circulation obstruction,immune-inflammatory imbalance,and abnormal bone metabolism.Protein kinase C alpha(PKCA),Ras proto-oncogene(RAS),mitogen-activated protein kinase 3(ERK),ETS proto-oncogene 1(ETS1),and receptor activator of nuclear factor-κB ligand(RANKL)formed a signaling axis implicated in NONFH pathogenesis.BZF treatment alleviated joint inflammation,preserved trabecular bone morphology,reduced bone loss,and promoted bone repair.Mechanistically,BZF significantly downregulated the expression of PKCA,RAS,ERK,ETS1,and RANKL,improved blood circulation,and inhibited osteoclast activation while promoting osteoblast activation.Conclusion:BZF may promote bone repair in advanced NONFH by enhancing blood circulation and modulating the PKC-RAS-ERK-ETS1-RANKL signaling axis,thereby reversing dysregulated bone metabolism.

AIM To investigate the effects of Modified Baitouweng Decoction and Lizhong Decoction on mouse ulcerative colitis(UC).METHODS The mouse model of UC was established by 3％dextran sulfate sodium(DSS)induction.The C57BL/6 mice were randomly divided into the blank group,the model group,the low,medium and high dose Modified Baitouweng Decoction and Lizhong Decoction groups(3,6,12 g/kg),and sulfasalazine group(300 mg/kg),for 7 days gavage of the appropriate drugs,with 10 mice in each group.The mice had their disease activity index(DAI)and colonic mucosal damage index(CMDI)calculated;their colonic length and unit colonic weight measured;their histopathologic changes of colon observed by HE;their colonic ROS,MDA levels and GSH-Px,SOD activities detected by superoxide anion fluorescent probes and kits;their colonic levels of TNF-α,IL-6 and IL-1β detected by ELISA;their colonic LC3 expression detected by immunofluorescence method;and their colonic AMPK,mTOR and p70S6K protein expressions detected by Western blot method.RESULTS Compared with the blank group,the model group displayed significantly higher DAI score,CMDI score,unit colon weight,pathology score,ROS and MDA content,TNF-α,IL-6,and IL-1β levels,and mTOR and p70S6K protein expression(P＜0.01);and significantly lower colon length,GSH-Px and SOD activity,LC3 level,and phosphorylated AMPK protein expression(P＜0.01).Compared with the model group,the groups intervened with Modified Baitouweng Decoction and Lizhong Decoction or sulfasalazine shared decreased DAI score,CMDI score,unit colon mass,pathology score,ROS,MDA,TNF-α,IL-6,IL-1β levels,mTOR,p70S6K protein expressions(P＜0.01);and significantly improved symptomsin terms of the elevated colonic length,GSH-Px,SOD activities,LC3 level,AMPK protein expression(P＜0.01).CONCLUSION Modified Baitouweng Decoction and Lizhong Decoction may attenuate inflammatory response and oxidative damage in UC mouse models via AMPK/mTOR/p70S6K signaling pathway.

Objective:The predictive value of oxidized low density lipoprotein(ox-LDL)and electrocardiogram(ECG)ischaemia grade for major adverse cardiovascular events(MACE)in patients with ST elevation myocardial infarction(STEMI)after percutaneous coronary intervention(PCI)was assessed by a retrospective cohort study de-sign.Methods:A total of 336 STEMI patients admitted to Cangzhou People's Hospital between October 2019 and May 2022 were selected,and the medical record information was obtained through the hospital medical record sys-tem,and all patients received PCI and physician-recommended basic treatment.With occurrence of MACE with in 12-month follow-up as the evaluation index,they were divided into MACE group(n=65)and no MACE group(n=271).Multifactorial Logistic regression model was used to study the influencing factors of MACE after PCI in STEMI patients,and Spearman test for association of ox-LDL level,ECG ischaemia grade with MACE after PCI.ROC curve was used to evaluate the predictive efficacy of ox-LDL,ECG ischaemia grade and their combination for MACE after PCI.Results:The overall MACE incidence was 19.35％.Compared with patients in no MACE group,those in MACE group had significant higher ox-LDL level[46.34(29.46,66.29)U/L vs.33.00(23.02,50.03)U/L]and proportion of ECG grade Ⅲ ischaemia(64.62％vs.42.80％)(P＜0.01 all).Multifactorial Logistic re-gression analysis showed that ox-LDL(OR=1.022,95％CI 1.011～1.033,P=0.001)and ECG grade Ⅲ ischae-mia(OR=1.878,95％CI 1.007～3.504,P=0.048)were the independent risk factors of post-PCI MACE in STEMI patients.Spearman test showed that ox-LDL and ECG grade Ⅲ ischaemia were positively correlated with post-PCI MACE(r=0.209,0.173,P＜0.001 all).ROC curve analysis showed that the AUCs of ox-LDL,ECG grade Ⅲ ischaemia and their combination in predicting post-PCI MACE were respectively 0.653(95％CI 0.599～0.704),0.609(95％CI 0.555～0.662)and 0.758(95％CI 0.709～0.803),in which the predictive value of the combination of the two was significantly higher than any single detection(Z=2.030,3.097,P=0.042,0.002).Conclusion:ox-LDL combined with ECG ischaemia grading has a high predictive value for the occurrence of MACE with in 12 months after PCI in STEMI patients.

OBJECTIVE: Humans are exposed to complex mixtures of environmental chemicals and other factors that can affect their health. Analysis of these mixture exposures presents several key challenges for environmental epidemiology and risk assessment, including high dimensionality, correlated exposure, and subtle individual effects. METHODS: We proposed a novel statistical approach, the generalized functional linear model (GFLM), to analyze the health effects of exposure mixtures. GFLM treats the effect of mixture exposures as a smooth function by reordering exposures based on specific mechanisms and capturing internal correlations to provide a meaningful estimation and interpretation. The robustness and efficiency was evaluated under various scenarios through extensive simulation studies. RESULTS: We applied the GFLM to two datasets from the National Health and Nutrition Examination Survey (NHANES). In the first application, we examined the effects of 37 nutrients on BMI (2011-2016 cycles). The GFLM identified a significant mixture effect, with fiber and fat emerging as the nutrients with the greatest negative and positive effects on BMI, respectively. For the second application, we investigated the association between four pre- and perfluoroalkyl substances (PFAS) and gout risk (2007-2018 cycles). Unlike traditional methods, the GFLM indicated no significant association, demonstrating its robustness to multicollinearity. CONCLUSION GFLM framework is a powerful tool for mixture exposure analysis, offering improved handling of correlated exposures and interpretable results. It demonstrates robust performance across various scenarios and real-world applications, advancing our understanding of complex environmental exposures and their health impacts on environmental epidemiology and toxicology.
Humans ; Environmental Exposure/analysis* ; Linear Models ; Nutrition Surveys ; Environmental Pollutants ; Body Mass Index

Objective:Using ecological niche width and situation model,the operation and management of public Traditional Chinese Medicine(TCM)hospitals in 16 cities in Shandong Province were evaluated to put forward countermeasures.Methods:The relevant index data of public TCM hospitals in 16 cities in Shandong Province from 2019 to 2022 were collected to analyze the development status.The ecological niche width model and niche situation model were applied to evaluate the operation and management of public TCM hospitals in 16 cities in Shandong.Results:The top three public TCM hospitals in terms of average ecological niche width were City G,City P and City F.The ecological niche situation value of public TCM hospitals in City K,City A and City J ranked the top three.Conclusion:The dimensions of operation management structure of public TCM hospitals in Shandong need to be enhanced and the development of operation management space needs to be balanced.It is feasible to evaluate operation management by using ecological niche width and situation model.It is suggested to improve the allocation efficiency of health personnel,facilities,funds and other resources;promote the spatial balanced development of operation management;promote the application of ecological niche width and situation model in the field of medicine and health management.

Background:Bushen Zhuanggu Formula(BZF),derived from the classic Yougui Pills,has shown favorable clinical efficacy in treating advanced nontraumatic osteonecrosis of the femoral head(NONFH),particularly by promoting bone repair.However,its underlying mechanisms remain unclear.Objective:This study aimed to explore the mechanisms by which BZF promotes bone repair in advanced NONFH.Materials and methods:A total of 518 potential BZF targets were identified from the ETCM v2.0 database.Transcriptomic profiling of clinical cohorts revealed 485 differentially expressed genes in advanced NONFH patients compared to healthy controls.A drug target-disease gene interaction network was constructed to identify candidate BZF targets involved in NONFH pathogenesis.In vivo experiments were conducted to validate the effects of BZF in a rat model of advanced NONFH.Results:Network analysis identified key pathways associated with blood circulation obstruction,immune-inflammatory imbalance,and abnormal bone metabolism.Protein kinase C alpha(PKCA),Ras proto-oncogene(RAS),mitogen-activated protein kinase 3(ERK),ETS proto-oncogene 1(ETS1),and receptor activator of nuclear factor-κB ligand(RANKL)formed a signaling axis implicated in NONFH pathogenesis.BZF treatment alleviated joint inflammation,preserved trabecular bone morphology,reduced bone loss,and promoted bone repair.Mechanistically,BZF significantly downregulated the expression of PKCA,RAS,ERK,ETS1,and RANKL,improved blood circulation,and inhibited osteoclast activation while promoting osteoblast activation.Conclusion:BZF may promote bone repair in advanced NONFH by enhancing blood circulation and modulating the PKC-RAS-ERK-ETS1-RANKL signaling axis,thereby reversing dysregulated bone metabolism.

Objective:To analyze the incidence of abnormal hemoglobin(Hb)in neonates in Guangzhou area,as well as the results of quantitative analysis of Hb in neonatal umbilical cord blood and genetic diagnosis of thalassemia in neonates with abnormal Hb;And to explore the hematological phenotypes and clinical characteristics of neonates with abnormal Hb and their parents,providing a reference for eugenics and childcare.Methods:650 neonates born at Guangdong Provincial People's Hospital who underwent Hb electrophoresis were included in this study.The results of routine blood test of umbilical cord blood,Hb electrophoresis and α-,β-thalassemia gene detection of the neonates were collected.The genotype distribution of thalassemia in the neonates was analyzed.Additionally,the abnormal Hb content of α and β variants was studied.Furthermore,the differences in hematological parameters between abnormal Hb neonates and normal neonates and α-thalassemia neonates,as well as between the parents of abnormal Hb neonates and normal adults were compared.Results:Among the 650 neonates,332(51.08％)were diagnosed with thalassemia,including 235 cases of α-thalassemia(36.15％),79 cases of β-thalassemia(12.15％),and 18 cases of compound α β-thalassemia(2.77％).Among all the α-thalassemia genotypes,the most prevalent one was--SEA/α α(48.94％),followed by-α3.7/α α(20.00％),-α42/α α(11.06％),and α α CS/α α(8.94％).The four most common genotypes of β-thalassemia were β CD41-42(32.91％),βIVS-Ⅱ-654(26.58％),β-28(21.52％),and β E(10.13％),respectively.275 cases of abnormal bands were found in Hb electrophoresis of umbilical cord blood,with a detection rate of 42.31％.The abnormal Hb content ofα-variant in the neonates was significantly higher than that of β-variant(P＜0.001).The levels of Hb,MCV,MCH,Hb A,and Hb F in neonates with abnormal Hb were lower than those in normal neonates,while the RDW-CV was higher than that in normal neonates,with statistical significantce(P＜0.05).The levels of RBC and Hb A in neonates with abnormal Hb were lower than those in neonates with α-thalassemia,while the level of MCH was higher than that in neonats withα-thalassemia,with statistical significance(P＜0.05).The levels of Hb,MCV,MCH,and Hb A in parents of neonates with abnormal Hb were lower than those in normal adults,while the RDW-CV was higher than that in normal adults,and the differences were statistically significant(P＜0.05).Conclusion:The abnormal Hb content of α-variant in the neonates is significantly higher than that of β-variant in the neonates in Guangzhou,which can help to presume whether it isα chain or β chain based on the abnormal Hb content,providing a reference for globin gene sequencing.Meanwhile,analysis of various hematological screening-related indicators in neonates in the early stage is beneficial for early warning of the occurrence of abnormal Hb combined with thalassemia,reducing missed diagnoses to a certain extent.

Objective:To develop an artificial intelligence (AI)-based platelet review strategy to identify abnormal platelet histograms with no significant difference between initial impedance platelet count (PLT-I) and PLT-F results.Methods:This study included 5 119 routine blood analysis in Nanfang Hospital of Southern Medical University and its Ganzhou branch from July 2023 and March 2024. Specimens exhibiting abnormal platelet histograms and an initial platelet count >40×10?/L underwent review using the fluorescent platelet count (PLT-F) channel. Consistency of the results was defined as a difference between impedance platelet count (PLT-I) and PLT-F less than ±20% of the PLT-F results. A deep learning model was developed using platelet and red blood cell histogram data from a training set of 3 807 specimens. The model′s diagnostic performance was evaluated on an independent external validation set ( n=805) using receiver operating characteristic (ROC) curve analysis. Changes in the number of reviewed samples and sample turnaround time were analyzed to assess its clinical utility. Results:The deep learning model based on platelet and red blood cell histograms achieved an area under the ROC curve (AUC) of 0.854 in the training set. At a cutoff value of 0.1, the sensitivity was 0.954 and specificity was 0.358. The model could reduce review by 16.80% (190/1 131). In the validation set, the AUC was 0.805, with a sensitivity of 0.955 and specificity of 0.307, corresponding to a reduction of 17.41% (47/270) in reviewed specimens.Conclusion:The platelet review prediction model developed based on deep learning technology can efficiently identify samples with consistent results before and after review, reducing unnecessary reviews and shortening specimen testing time, thereby improving the efficiency of platelet test.