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 compare the effects of different detector combinations of 320-row CT on the image quality and radiation dose of head CT to explore the feasibility of using a wide detector for head CT scanning.Methods Totally 100 patients underwent head CT scanning due to trauma or cerebrovascular disease at some hospital from June to August 2023 were collected prospectively and divided into group A and group B by using block randomization grouping method,with the length of the block group being 2 and 50 patients in each group.In group A,all the detectors had the widths at z-axis direction being 40×0.5 mm and head scanning was completed after multiple exposures;in group B,detector combinations with widths of 280×0.5 mm or 320×0.5 mm were chosen based on the patient's head size in the head-foot direction(z-axis direction),and head scanning was performed with a single-turn exposure.The remaining scanning and image reconstruction parameters in the two groups were kept completely consistent.The head image quality of the 2 groups was evaluated objectively and scored subjectively by 2 radiologists.The volume CT dose index(CTDIvol),dose length product(DLP)and exposure time of the 2 groups were recorded,and the effective dose(ED)was calculated.SPSS 22.0 software was used for statistical analysis.Results In terms of objective evaluation of image quality,at the level of the parietal skull group B had the CT value of gray matter,image noise and contrast to noise ratio(CNR)of the images higher than those of group A,and the differences were statistically significant(all P<0.05);at the level of the posterior skull group B had the CT values of gray and white matter,image noise and air noise lower while CNR higher than those of group A,and the differences were statistically significant(all P<0.05).In terms of subjective scoring of image quality,at the levels of parietal and posterior skull group A behaved better than group B,and the differences were statistically significant(all P<0.05).In group A 5 patients had obvious motion artifacts affecting the diagnosis and the image quality scores not higher than 2,and secondary scanning had to be carried out;In group B all the patients had no obvious motion artifacts and met the diagnosis requirements.When compared with group A Group B had the CTDIvol,DLP,ED and exposure time decreased by 17.44%,17.24%,17.48%and 85.53%,respectively,and the differences were statistically significant(all P<0.05).Conclusion A wide detector gains advantages over a 20 mm detector in image quality when 320-row CT is used for head CT scanning,with the diagnosis requirements satisfied.[Chinese Medical Equipment Journal,2025,46(4):57-62]

AIM To compare the chemical constituents in traditional decoction and formula granule decoction of classical famous prescription Wendan Decoction.METHODS The HPLC fingerprints were established,after which the contents of adenosine,synephrine,liquiritin,naringin,hesperidin,6-gingerol and adenosine cyclophosphate were determined,cluster analysis,principal component analysis and multidimensional scaling analysis were adopted in the investigation of component differences,and the equivalent of formula granules was adjusted.RESULTS The similarities of HPLC fingerprints for 10 batches of traditional decoctions were higher than those of HPLC fingerprints for 9 batches of formula granule decoctions(P＜0.01).Adenosine,synephrine,liquiritin,hesperidin and cyclic adenosine monophosphate demonstrated higher contents in traditional decoctions than those in formula granule decoctions(P＜0.05),6-gingerol displayed lower content than that in the latter produced by manufacturers A,C(P＜0.05),which was higher than that in the latter produced by manufacturer B(P＜0.01).Various batches of traditional decoctions and formula granule decoctions could be obviously distinguished,adenosine,synephrine and hesperidin exhibited great influences on the classification of principal component analysis,and the quality of formula granule decoctions produced by manufacturer C was closer to that of traditional decoctions.After equivalent correction,the contents of various constituents in formula granule decoctions produced by manufacturers A,C showed no significant differences as compared with those in traditional decoction(P＞0.05).CONCLUSION The formula granules of Wendan Decoction from different manufacturers exist quality differences,so the preparation process and extraction process of this preparation should be optimized to improve quality,and equivalent ratio should be adjusted according to actual requirements to ensure its scientific and rational clinical application.

The field(emergency)rapid inspection systems involving in the backpack,chest,vehicle and shelter had their research advances introduced and characteristics and deficiencies analyzed,and some improvement suggestions were put forward accordingly.It's pointed out the backpack,chest,vehicle and shelter be combined effectively to enhance the mobility and flexibility of field(emergency)rapid inspection systems.References were provided for the future enhancement and effecient operation of field(emergency)rapid inspection systems.[Chinese Medical Equipment Journal,2025,46(2):80-86]

Objective To analyze the risk factors for increased drainage volume after open transforaminal lumbar interbody fusion(TLIF),and to establish a predictive model and then validate it.Methods The clinical data of 680 patients who underwent open TLIF at the General Hospital of Northern Theater Command from January 2016 to December 2019 were collected and the patients were randomly divided into the training group(n=476)and the validation group(n=204).Taking the predictive factors screened out by LASSO regression analysis as independent variables,a multivariate Logistic regression predictive model was constructed.The model was internally validated through the receiver operating characteristic(ROC)curve,Hosmer-Lemeshow goodness-of-fit test,and calibration curve,and its clinical utility was assessed via decision curve analysis(DCA).Results LASSO regression analysis screened out four predictive variables:age,number of surgical segments,operative duration,and intraoperative blood loss.The multivariate Logistic regression predictive model demonstrated that age≥60 years,number of surgical segments≥4,operative duration≥2 hours,and intraoperative blood loss≥200 mL were independent influencing factors for the increased postoperative drainage volume in patients undergoing TLIF(P<0.05).ROC curve analysis revealed an area under the curve(AUC)of 0.816(95%CI:0.798 to 0.867)in the training group and 0.783(95%CI:0.685 to 0.823)in the validation group,indicating that the predictive model had good discriminatory ability.Additionally,the Hosmer-Lemeshow goodness-of-fit test and calibration curve indicated that the predictive model had a good degree of fit,and the predicted probability was basically consistent with the actual probability,demonstrating a good calibration.The DCA results confirmed that this predictive model could be applied in clinical practice.Conclusion The risk factors for increased drainage volume after open TLIF include age,number of surgical segments,operative duration,and intraoperative blood loss.The predictive model established based on these factors demonstrates good performance,and it can be applied in clinical guidance for the selection of drainage tube removal time after TLIF.

Objective To explore the risk factors for noncontiguous spinal fractures(NSFs)in the elderly.Methods The clinical data of 614 elderly patients with spinal fracture from January 2013 to December 2019 were analyzed retrospectively.Patients were divided into the NSFs group and the Non-NSFs group according to whether NSFs occurred or not.Univariate analysis and multivariate Logistic regression analysis were used to screen the risk factors of NSFs.Results Univariate analysis showed that female(P=0.003),high-energy violent injury(P=0.032),osteoporosis(P=0.004),fracture in spring(P=0.020),and previous spinal fracture history(P<0.001)were associated with the occurrence of NSFs.Multivariate Logistic regression analysis showed that fracture in spring(P=0.024),previous spinal fracture history(P<0.001)and high-energy violent injury(P=0.038)were the independent risk factors for the occurrence of NSFs in the elderly.Conclusion High-energy violent injury,fracture in spring and previous spinal fracture history are the independent risk factors for the occurrence of NSFs in the elderly.Therefore,elderly patients with the above risk factors should be examined more carefully and comprehensively to avoid missed diagnosis and delayed diagnosis.In order to reduce the incidence of this disease,corresponding measures should be taken according to the preventable risk factors.

Objective To analyze the risk factors for increased drainage volume after open transforaminal lumbar interbody fusion(TLIF),and to establish a predictive model and then validate it.Methods The clinical data of 680 patients who underwent open TLIF at the General Hospital of Northern Theater Command from January 2016 to December 2019 were collected and the patients were randomly divided into the training group(n=476)and the validation group(n=204).Taking the predictive factors screened out by LASSO regression analysis as independent variables,a multivariate Logistic regression predictive model was constructed.The model was internally validated through the receiver operating characteristic(ROC)curve,Hosmer-Lemeshow goodness-of-fit test,and calibration curve,and its clinical utility was assessed via decision curve analysis(DCA).Results LASSO regression analysis screened out four predictive variables:age,number of surgical segments,operative duration,and intraoperative blood loss.The multivariate Logistic regression predictive model demonstrated that age≥60 years,number of surgical segments≥4,operative duration≥2 hours,and intraoperative blood loss≥200 mL were independent influencing factors for the increased postoperative drainage volume in patients undergoing TLIF(P<0.05).ROC curve analysis revealed an area under the curve(AUC)of 0.816(95%CI:0.798 to 0.867)in the training group and 0.783(95%CI:0.685 to 0.823)in the validation group,indicating that the predictive model had good discriminatory ability.Additionally,the Hosmer-Lemeshow goodness-of-fit test and calibration curve indicated that the predictive model had a good degree of fit,and the predicted probability was basically consistent with the actual probability,demonstrating a good calibration.The DCA results confirmed that this predictive model could be applied in clinical practice.Conclusion The risk factors for increased drainage volume after open TLIF include age,number of surgical segments,operative duration,and intraoperative blood loss.The predictive model established based on these factors demonstrates good performance,and it can be applied in clinical guidance for the selection of drainage tube removal time after TLIF.

Lens injury is an important etiological factor in the reduction of visual function following ocular trauma.Currently, there are no clear standards for the classification of lens injury, and comprehensive diagnostic tools are lacking.This deficiency leads to numerous controversies and challenges in critical areas, such as diagnosis and preoperative evalution, timing of surgery, surgical strategy, and assessment of postoperative prognosis.Tomographic imaging technology, such as computed tomography, magnetic resonance imaging, optical coherence tomography, has introduced a new dimension to the evaluation of lens injury, which is crucial for assessing the transparency, texture, location, morphology, and integrity of the lens, as well as the zonules and nearby intraocular structures.However, the use of tomographic imaging technology is somewhat limited due to the limitations of relying on a single method.With the ongoing advancement of imaging technologies and the rapid development of big data and artificial intelligence, tomographic imaging will become an increasingly essential tool in the future management of lens injury.Our expert group reviewed the epidemiological characteristics and classification of lens injury and the major challenges currently faced in the diagnosis and treatment of lens injury, and provided expert recommendations mainly focusing on the application, shortcomings and limitations of current tomographic imaging technology in the diagnosis and treatment of lens injury, and future development directions.

Pancreatic cancer has emerged as one of the most challenging malignancies worldwide,with its high resistance to chemotherapy being the primary cause of treatment failure.Therefore,enhancing the chemosensitivity of pancreatic cancer has become a major focus of current research.In this study,we in-vestigated how Bufotaline,a bufadienolide extracted from the traditional Chinese medicine toad venom,exhibits its antitumor activity.Specifically,we explored the potential of Bufotaline to enhance the chemo-sensitivity of pancreatic cancer cells to Adriamycin and elucidated its underlying molecular mechanisms.Using CCK-8 and colony formation assays,we demonstrated that Bufotaline enhances the inhibitory effect of Adriamycin on the survival of pancreatic cancer cell lines Patu-8988T,Aspc-1,and Patu-8988S.No-tably,Bufotaline treatment reduced the IC50 of Adriamycin in drug-resistant pancreatic cancer cells to lev-els comparable to those in non-resistant cells.Results from Western blot,immunofluorescence,comet as-say,and TUNEL assays revealed that Bufotaline promotes Adriamycin-induced DNA damage in pancreatic cancer cells.RNA-seq analysis of Patu-8988T cells treated with Adriamycin alone or in combination with Bufotaline showed significant changes in gene expression,and qRT-PCR analysis further confirmed that Bu-fotaline downregulates the expression of DNA damage repair proteins NBS1 and RAD50.Moreover,Western blot analysis revealed that Bufotaline reduces the levels of DNA damage response repair proteins,and Im-munofluorescence experiments indicated that Bufotaline inhibits the activation of the ATM/CHK2 signaling pathway.Finally,in a subcutaneous xenograft mouse model,the combination of Adriamycin and Bufotaline treatment significantly suppressed pancreatic cancer cell growth.In conclusion,Bufotaline enhances Adria-mycin-induced chemosensitivity in pancreatic cancer cells;the combination of Adriamycin and Bufotaline downregulates the expression of DNA damage response repair proteins NBS1 and RAD50,and inhibits the ATM/CHK2-mediated DDR signaling pathway,thereby delaying DNA damage repair.

Aim To investigate the protective effect of Shengmai Yin on myocardial ischemia/reperfusion in-jury(MI/RI)in vitro and in vivo and to unravel the underlying mechanism.Methods SD rats were divid-ed into the sham group,model group,and Shengmai Yin group(SM).Rat MI/RI model was established.Cardiac function,infarct area,pathological changes,cardiomyocyte apoptosis,macrophage infiltration,and serum cTnT and CK-MB levels were measured.The mRNA and protein expressions of Calpain-1 and Cal-pain-2 were assessed.The hypoxia/reoxygenation(H/R)model was constructed in H9c2 cells.The active ingredients of Shengmai Yin were screened using net-work pharmacology and verified by CCK-8.In the car-diomyocytes H/R model,Fluo-4 AM staining was used to detect the changes of Ca2+levels.Results Com-pared with model group,LVEF and LVFS of Shengmai Yin-treated rats increased,myocardial infarction area was reduced,while myocardial tissue injury was allevi-ated.Myocardial apoptosis rate and the number of macrophages were reduced.Similarly,cTnT and CK-MB levels decreased.In addition,the expression lev-els of Calpain-1 and Calpain-2 mRNA and protein de-creased in the SM treatment group.Under the H/R model,all the active ingredients of Shengmai decoction had protective effects on cardiomyocytes,and the treat-ment could reduce the level of Ca2+in cardiomyocytes.Conclusions Shengmai Yin has protective effects on MI/RI in rats.This effect may be related to the de-crease in Ca2+levels,as well as Calpain-1 and Calap-in-2 mRNA and protein expression.