Animal model research on spleen and stomach diseases in traditional Chinese medicine （TCM） is of great significance for elucidating the nature of diseases and syndromes and for revealing the mechanisms of action of Chinese herbal medicinals. At present， studies on classical TCM syndrome models of spleen and stomach diseases mainly focus on spleen deficiency syndrome， liver constraint syndrome， and damp-heat syndrome. Model construction is mostly based on the etiological and pathophysiological characteristics of syndrome， and model evaluation primarily involves macroscopic manifestations and physicochemical indicators. This paper summarizes the current research status of animal models integrating disease and syndrome for seven common spleen and stomach diseases， including chronic gastritis and gastric precancerous lesions， gastroesophageal reflux disease， functional dyspepsia， inflammatory bowel disease， irritable bowel syndrome， functional constipation， and functional diarrhea. The modeling methods and characteristics of disease-syndrome combined animal models for each disease are analyzed. It is proposed that future research on disease-syndrome integration in spleen and stomach diseases should move toward syste-matic， precise， and integrative development， and that interdisciplinary and cross-disciplinary research approaches should be adopted to enhance the predictive value and application efficiency of disease-syndrome combined animal models.

ObjectiveTo explore the 28-day mortality risk of Klebsiella pneumoniae (KP) bloodstream infections (BSI) and its related influencing factors, thereby providing a scientific basis for the effective control of KP-BSI and improvement of patient prognosis. MethodsFrom January 2018 to December 2024, a retrospective review was conducted on hospitalized patients aged >18 years old treated for KP-BSI at a tertiary hospital in Hangzhou. Logistic and Cox regression analyses were performed to identify the epidemiological characteristics and the risk factors for the 28-day mortality associated with KP-BSI. ResultsA total of 123 patients with KP-BSI were included in this study, comprising 64 cases infected with carbapenem-resistant Klebsiella pneumoniae (CRKP) and 59 cases infected with carbapenem-susceptible Klebsiella pneumoniae (CSKP). Compared with CSKP-BSI, patients with CRKP-BSI more frequently presented with chronic pulmonary disease (χ²=4.29, P=0.038), concomitant infections at other sites (χ²=10.90, P=0.001), and a higher frequency of invasive procedures prior to infection (central venous catheterization, mechanical ventilation, and indwelling urinary catheter), as well as glucocorticoid use, hemodialysis, and blood transfusion (all P<0.05). The 28-day mortality was significantly higher in BSI cases caused by CRKP compared to that caused by CSKP (37.50% vs 5.08%, P<0.001). Cox regression analyses revealed that carbapenem resistance (HR=6.67, 95%CI: 1.48‒30.08, P=0.014) and blood transfusion (HR=3.58, 95%CI: 1.15‒11.19, P=0.028) were risk factors for the 28-day mortality in KP-BSI, while removal of central venous catheters after infection (HR=0.24, 95%CI: 0.08‒0.67, P=0.006) was associated with a reduced risk for the 28-day mortality. ConclusionCarbapenem resistance is associated with mortality outcomes in patients with KP-BSI. Strengthening infection control measures targeting the identified risk factors for CRKP-BSI may improve patient prognosis.

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.

Background Arsenic exposure has been implicated as an important environmental contributor to pulmonary fibrosis, the pathogenesis of which is closely associated with abnormal activation of pulmonary fibroblasts. However, the specific mechanism remain incompletely understood. Objective To examine sirtuin 3 (SIRT3) expression during arsenite-induced fibrotic responses in lung fibroblasts, and to investigate its effects on aerobic glycolysis and profibrotic progression, as well as its underlying mechanisms. Methods Human embryonic lung fibroblasts (HELF) were treated with sodium arsenite (NaAsO₂) at different concentrations (0, 2.5, 5, 10, 20, 40, and 80 μmol·L⁻¹) for 48 h. Cell viability was assessed, and lactate and hydroxyproline (HYP) levels were measured as indicator of glycolytic activity and fibrotic response. Western blot and quantitative polymerase chain reaction (q-PCR) were used to determine the protein and mRNA expression levels of SIRT3, hypoxia-inducible factor 1-alpha (HIF-1α), fibrosis-related genes [Collagen type Ⅰ (Collagen-Ⅰ), and α-smooth muscle actin (α-SMA)], and glycolysis-related genes [pyruvate kinase M2 (PKM2), hexokinase 2 (HK2), and lactate dehydrogenase A (LDHA)]. Results Based on the cell viability results, the NaAsO₂ concentrations of 2.5, 5, and 10 μmol·L⁻¹ for 48 h were selected for subsequent experiments. Compared with the control group, HYP levels were significantly increased in the 2.5, 5, and 10 μmol·L⁻¹ NaAsO₂ exposure groups (P <0.05). The protein and mRNA expression levels of HIF-1α, glycolysis-related genes (PKM2, HK2, and LDHA) and fibrosis-related genes (Collagen-Ⅰ, and α-SMA) were significantly upregulated, whereas SIRT3 protein and mRNA expression levels were significantly down-regulated, in the NaAsO₂ treated groups compared with the control group (P<0.05). SIRT3 overexpression significantly reduced HYP levels and downregulated the protein and mRNA expression levels of HIF-1α, glycolysis-related genes (PKM2, HK2, and LDHA), fibrosis-related genes (Collagen-Ⅰ, and α-SMA) compared with the NaAsO₂ + negative control group (P<0.05). Similarly, HIF-1α knockdown significantly decreased HYP levels and downregulated the protein and mRNA expression levels of glycolysis-related genes (PKM2, HK2, and LDHA) and fibrosis-related genes (Collagen-Ⅰ, and α-SMA) compared with the NaAsO₂ + negative control group (P<0.05). In contrast, simultaneous overexpression of SIRT3 and HIF-1α abolished the inhibitory effects of SIRT3 overexporession, as HYP levels and the expression of glycolysis- and fibrosis-related markers showed no statistically significant differences compared with the NaAsO₂ + negative control group (P>0.05). Conclusion NaAsO₂ exposure could induce profibrotic and glycolysis-related responses in HELF cells, accompanied by SIRT3 downregulation and HIF-1α activation. These findings suggest that the SIRT3/HIF-1α regulatory axis may be a potential target for preventing or attenuating arsenic exposure-related pulmonary fibrotic responses.

AIM:To analyze the characteristics and correlation of phacoemulsification parameters and anterior segment parameters in cataract patients with different blood glucose levels.METHODS:A total of 45 type 2 diabetic cataract patients(45 eyes)treated in our hospital from March 2023 to April 2024 were stratified into two groups based on glycosylated hemoglobin(HbA1c)levels: group A: HbA1c <7%(n=18)and group B: 7%≤HbA1c<8.5%(n=27); a total of 94 age-matched age-related cataract patients(94 eyes)were enrolled as the control group(group C). All underwent phacoemulsification with intraocular lens implantation. Anterior segment parameters, including corneal, lens and anterior chamber measurements, were recorded. Correlations between phacoemulsification parameters and anterior segment parameters were analyzed, and differences among groups were compared.RESULTS: In groups A and B, effective phacoemulsification time(EPT)negatively correlated with corneal endothelial cell density(CECD)(r=-0.315, P=0.035). Average phacoemulsification time(APT)positively correlated with the anterior corneal surface radius of curvature(Rm; r=0.402, P=0.006)and negatively correlated with the flat axis meridian curvature(K1), steep axis meridian curvature(K2), mean curvature(Km)of the anterior corneal surface, and lens density at 6 mm zones(PDZ3; all P<0.05). Average phacoemulsification energy(AVE)positively correlated with mean lens density(LD-mean), lens density at 2 mm zones(PDZ1), lens density at 4 mm zones(PDZ2), and PDZ3(all P<0.05), and negatively with pupil diameter(r=-0.385, P=0.009). In the group C, EPT showed a positive correlation with Pentacam nucleus staging(PNS)density grade, PDZ1, PDZ2, and PDZ3(all P<0.05). A positive correlation was observed between AVE and PNS classification(r=0.246, P=0.018). Conversely, AVE exhibited a negative correlation with CECD(r=-0.245, P=0.018). EPT in groups A and B was higher than that in the group C(P<0.05). Both EPT and APT in the group B were higher than those in the group A(P<0.05). In diabetic cataract patients, CECD, corneal density(CD), and posterior corneal surface height positively correlated with diabetes duration(P<0.05). Posterior corneal surface K1 and Rm positively correlated with 7%≤HbA1c<8.5%(P<0.05). Total corneal astigmatism negatively correlated with HbA1c, 2-hour post-breakfast blood glucose(2hPBG), and fasting insulin(FINS; P<0.05). CD and lens thickness(LT)positively correlated with FINS(P<0.05).CONCLUSION: Phacoemulsification parameters and blood glucose-related indices exhibited varying degrees of correlation with anterior segment parameters in cataract patients with different blood glucose levels. EPT in diabetic cataract patients was higher than that in age-related cataract patients, while EPT and APT in diabetic cataract patients with poor glycemic control were higher than those with good glycemic control.

In recent years,significant breakthroughs have been achieved in the immunotherapy for Alzheimer's disease.In line with global advancements,two anti-amyloid-β monoclonal antibodies have been approved and successfully launched in China for clinical use.Lecanemab and Donanemab were officially used in June 2024 and April 2025 in China,respectively.In order to standardize the rational and safe application of anti-amyloid-β monoclonal antibodies for Alzheimer's disease in China,this article integrates recom-mendations from the clinical trials and real-world experience from the author's team and domestic peers to further update the recom-mendations for the clinical use of anti-amyloid-β monoclonal antibody based on the 2024 version.It includes indications for therapy,pre-treatment evaluation and preparation,administration protocols and safety measures during treatment,and post-treatment monitor-ing strategies.

Objective To investigate the impact of sleep modes on the risk for diseases of the body systems.Methods Based on a subset of UK Biobank dataset comprising 87 617 participants,3 sleep dimensions including 6 sleep indicators were obtained through a wrist-worn accelerometer,that is sleep duration and onset,sleep rhythm(relative amplitude and stability),and sleep quality(sleep efficiency and number of awakenings).Latent profile analysis(LPA)was applied to identify and classify distinct sleep modes.Then their longitudinal medical records were the association between different sleep modes and the risk for 467 diseases.Results LPA identified 5 subgroups of unique sleep modes in the participants.Among the 5 subgroups,the subgroup 4 had relatively optimal levels in above sleep indicators.Compared to the subgroup 4,the other 4 subgroups exhibited variations in different sleep dimensions,with at least one indicator demonstrating an unfavorable trend.These subgroups also revealed differences in racial composition,shift work and social deprivation index.Moreover,there were notable differences in the risk of various system diseases among the subgroups(P<0.05).When compared to the subgroup 4,the other 4 subgroups exhibited an elevated risk for certain diseases(comprising a total of 126 diseases),with the diseases of the circulatory system,digestive system and musculoskeletal system most common.Among the 5 subgroups,the subgroup 2(shorter sleep duration and later sleep onset)and the subgroup 5(rhythm disorder)had the highest counts of associated risks,amounting to 85 and 91 types,respectively,but there was certain difference in their systematic composition.Conclusion There are different sleep modes within the participants,and the modes are potentially associated with an increased risk for diseases of body systems.Comprehensive interventions targeting overall sleep modes rather than single sleep indicator may yield obvious health benefits.

The traditional detection methods for monitoring the biomass,protein,chlorophyll content and other key indicators in the growth of chlorella have some problems,including complicated operation,slow detection speed and difficult large-scale application.In this study,a fast and efficient monitoring method for the key indicators in the growth of chlorella was established using near infrared spectroscopy and chemometrics.Near-infrared spectroscopy was used to collect near-infrared spectra of chlorella algal fluid at different growth stages,and standard methods were used to detect the biomass,protein and chlorophyll contents of corresponding samples.A quantitative analysis model was established based on partial least squares regression(PLSR).To improve the prediction ability of the model,multiplicative scatter correction(MSC)was used to reduce the interference of scattering on the raw spectrum(RS),standard normal variate(SNV)was used to normalize the original spectral data to eliminate differences between samples,continuous wavelet transform(CWT)was used to obtain the key features of spectral data,the first derivative(1st)was used to enhance the differentiation of the original spectral features,and monte carlo-uninformative variable elimination(MC-UVE)and randomization test(RT)were used to screen the valid variables in the wavelength.By evaluating the prediction ability of different models,the quantitative analysis models of chlorella biomass,protein and chlorophyll content were finally determined.The results showed that the model based on 1st combined with RT spectra had better predictive ability for chlorella nutrient content detection,and the root mean square errors of prediction(RMSEP)and coefficients of determination(R2)were 0.041 and 0.933 for biomass,0.012 and 0.973 for protein,and 0.517 and 0.962 for chlorophyll,respectively.This model showed practical application value,and could realize the rapid and accurate detection of chlorella biomass,protein and chlorophyll content at the same time.

In recent years,micro photoionization detectors(μPID),with their rapid response speed and excellent sensitivity,have attracted widespread attention in both scientific research and industry.This study developed a portable gas chromatograph based on μPID technology(GC-μPID),and examined its key performance characteristics such as reproducibility,sensitivity,and online analytical capability.The results showed that the method's relative standard deviation(RSD)was controlled within 2.7%,demonstrating good reproducibility;for the standard curves of 27 kinds of volatile organic compounds(VOCs),the linearity was excellent(R2≥0.99),with detection limits of≤10 μg/m3 and benzene series compounds reaching detection limits as low as 0.5 μg/m3.In field applications at an industrial park,this method successfully identified and quantified 17 kinds of VOCs,accurately capturing their diurnal concentration variations.The results above validated that the method developed here had the capability of onsite real-time monitoring and provided an effective tool for in situ monitoring atmospheric pollutants.

Objective To explore the correlation between the actual age and the pulp chamber volume(PCV)and pulp dentinal index(PDI)of the right first molars based on cone beam computed tomog-raphy(CBCT)technology,and to construct an accurate and convenient model for age estimation.Methods CBCT image data of 1 857 Han adults(883 males and 974 females)from the Department of Stomatology,Affiliated Hospital of North Sichuan Medical College were collected.The data were di-vided into training and validation sets at a ratio of 8∶2.A total of 1 485 training samples were used to construct the age estimation model,and 372 samples were used to validate the accuracy of the model.The Mimics 21.0 software was used to measure the PCV and calculate the PDI of the right first molars.Their correlations with age and the differences between different sexes and tooth positions were analyzed.Results Both the PCV and the PDI of the first molars showed strong negative correla-tions with the actual age(r values ranged from 0.82 to 0.89).The differences in PCV and PDI be-tween different sexes and tooth positions were statistically significant(P<0.05).The age estimation model based on PDI was superior to that based on PCV.The model based on the PDI values of the two right first molars(y=73.72-44.15 x3-28.27 x4,where x3 and x4 are the PDI values of the right maxil-lary and mandibular first molars,respectively)was the best,with the R2 of 0.79 and the mean abso-lute error of 4.90 years.Conclusion Both PCV and PDI of the first molars are effective indicators for age estimation.The age estimation model based on the PDI is more convenient and accurate than that based on the PCV,providing a more effective method for age estimation in forensic practice.