Objective: To explore the relationship of screen time and sleep duration with screening myopia among junior and senior high school students, so as to provide evidence for the prevention and control of myopia among students. Methods: From March to October 2024, 429 junior and senior high school students from a district of Guangzhou were selected using stratified cluster random sampling method. Standardized logarithmic visual acuity chart was used for vision assessment, while Questionnaire for the Physical Health Monitoring System of Students in Guangzhou was employed to collect students screen time and sleep duration. The Chi square test was used to compare differences across different groups, and binary Logistic regression analysis was employed to analyze the association of screen time and sleep duration with screening myopia. Results: The overall prevalence of screening myopia was 79.5%, with significant differences across educational stage, sex, screen time and sleep duration groups( χ 2=41.64, 9.75, 23.89 , 8.17, all P <0.05).Binary Logistic regression analysis revealed that, compared to the high screen time & insufficient sleep group, the low screen & sufficient sleep group ( OR=0.25, 95%CI =0.09-0.68), the low screen & insufficient sleep group ( OR= 0.27 , 95%CI =0.13-0.56), and the high screen & sufficient sleep group ( OR=0.26, 95%CI =0.10-0.70) exhibited significantly lower screening myopia risks (all P <0.05). After adjusting for sex and educational stage, low screen time & insufficient sleep was significantly associated with screening myopia ( OR=0.48, 95%CI =0.23-0.98); the multiplicative interaction term was statistically significant ( OR=0.99,95%CI =0.98-1.00)(both P <0.05). Conclusion The interaction effect between screen time and sleep duration in relation to screening myopia suggests a need to focus on daily routines and screen use habits among junior and senior high school students for ensuring sufficient sleep and limiting screen exposure.

Background Prolonged vibration exposure can lead to vascular endothelial cell dysfunction and cellular injury. However, research on the association between vibration and ferroptosis in vascular endothelial cells remains insufficient. Objective To explore whether occupational vibration exposure is associated with alterations in serum markers related to ferroptosis in patients with hand-arm vibration disease (HAVD), and to further investigate, through in vitro cell experiments, whether vibration exposure may induce ferroptosis in vascular endothelial cells. Methods ①A judgmental sampling method was employed to select 50 workers with HAVD (the HAVD group), 50 vibration-exposed workers without HAVD (the vibration exposure group), and 50 non–hand-transmitted vibration-exposed workers (the control group). Serum iron levels, malondialdehyde (MDA) content, and superoxide dismutase (SOD) levels were measured using serum iron assay kits, MDA detection kits, and SOD detection kits, respectively. One-way analysis of variance and binary logistic regression analysis were performed to examine the relationships between these indicators and HAVD. ②Human umbilical vein endothelial cells (HUVEC) were divided into a vibration group and a control group. The vibration group was subjected to vibration at 120 Hz with an acceleration of 6.5 m·s⁻² and further subdivided into four subgroups: 1 d 2 h, 1 d 4 h, 2 d 2 h, and 2 d 4 h. The control group was treated identically except for vibration exposure. Cellular iron (Fe²⁺) content and reduced glutathione (GSH) levels in HUVEC were measured using ferrous iron colorimetric assay kits and GSH colorimetric assay kits, respectively, to assess the effects of different vibration exposure schedules. Real-time quantitative polymerase chain reaction (RT-qPCR) was performed to detect the mRNA expression levels of ferroptosis-related genes, including acyl-CoA synthetase long-chain family member 4 (ACSL4), tumor suppressor protein P53 (P53), ferritin heavy chain 1 (FTH1), and glutathione peroxidase 4 (GPX4). Western blot analysis was conducted to determine the protein expression levels of ferroptosis-related markers in HUVEC. Results ①Compared with the control group, the patients in the HAVD group showed increased serum iron and MDA levels, along with decreased SOD levels (P<0.05). The logistic regression analysis indicated that elevated serum iron levels were significantly associated with an increased risk of HAVD (OR=4.034; 95%CI: 2.063, 7.887), and elevated MDA levels were also associated with an increased risk of HAVD (OR=1.523; 95%CI: 1.026, 1.936). ②Compared with the control group, increased intracellular Fe²⁺ content and decreased GSH content were observed in HUVECs in the 1 d 4 h and 2 d 4 h vibration subgroups (P<0.05). The RT-qPCR results showed that, compared with the control group, vibration exposures of 1 d 4 h and 2 d 4 h significantly upregulated the expression of ACSL4 and P53 (P<0.05), whereas the mRNA expression levels of GPX4 and FTH1 were downregulated in all vibration-exposed endothelial cells (P<0.05). The Western blot results revealed that, compared with the control group, the vibration exposure schedules of 1 d 2 h and 1 d 4 h significantly upregulated the protein expression levels of ACSL4 and P53 (P<0.05), while the vibration exposure schedules of 1 d 4 h, 2 d 2 h, and 2 d 4 h significantly downregulated the protein expression levels of FTH1 and GPX4 (P<0.05). Conclusion Occupational vibration exposure is associated with alterations in iron metabolism and oxidative stress status in workers with HAVD. The in vitro experiments further demonstrates that vibration stimulation induces intracellular iron accumulation and reduces antioxidant capacity in vascular endothelial cells, accompanied by dysregulated expression of ferroptosis-related molecules. These findings suggest that ferroptosis may play a role in vibration-induced vascular injury and the pathogenesis of HAVD.

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 construct an aptamer-functionalized carboxylated graphene oxide(CGO)fluo-rescent sensor to achieve highly sensitive and specific detection of ketamine(KET)and its metabolite norketamine(NK)using an aptamer capable of simultaneously recognizing KET and NK.Methods A specific aptamer for simultaneous recognition of KET and NK was screened using graphene oxide-sys-tematic evolution of ligand by exponential enrichment(GO-SELEX)and molecular docking tech-niques.The aptamer,labeled with Cy5 fluorescence,was chemically conjugated to CGO to construct an aptamer-functionalized CGO fluorescent sensor.By optimizing detection conditions,including the mass concentration of CGO,aptamer concentration,reaction temperature,and incubation time,quantita-tive analysis of the target analytes was achieved using the ratio of fluorescence intensity changes be-fore and after target addition.The stability of the sensor in biological matrices was evaluated by moni-toring fluorescence intensity changes over incubation time in blank blood and urine,in comparison with the traditional physical adsorption-based CGO fluorescent sensor.Spiked recovery experiments in blank blood and urine were conducted to compare performance with that of HPLC-MS/MS.Results A specific aptamer A5 was selected and chemically conjugated with CGO to construct the aptamer-functionalized CGO fluorescent sensor.Under optimized conditions,the proposed fluorescent sensor ex-hibited a linear detection range of 1.0-5.0 ng/mL for KET,with a limit of detection(LOD)of 0.86 ng/mL;while for NK,the linear detection range was 1.0-5.0 ng/mL,with an LOD of 0.70 ng/mL.Com-pared with the CGO fluorescent sensor constructed via physical adsorption,this sensor demonstrated greater stability in blood and urine.The spiked recovery rates of KET and NK in blank blood and urine ranged from 81.50%to 110.03%,exhibiting detection performance comparable to that of HPLC-MS/MS.Conclusion The aptamer screening method offers a novel approach for selecting aptamers tar-geting drugs and their metabolites.The constructed aptamer-functionalized CGO fluorescent sensor pro-vides an efficient and reliable strategy for the high-performance detection of KET and NK.

OBJECTIVE: This study aimed to investigate possible serum 25-hydroxyvitamin D [25(OH)D] cutoffs for the associations between 25(OH)D and Bone turnover markers (BTMs), and how GC gene variation influences such cutoffs in Chinese women of childbearing age. METHODS: In total, 1,505 non-pregnant or non-lactating women (18-45 years) were recruited from the 2015 Chinese Adult Chronic Disease and Nutrition Surveillance. Serum 25(OH)D, osteocalcin (OC), procollagen type 1 N-terminal propeptide (P1NP), β-CrossLaps of type 1 collagen containing cross-linked C-telopeptide (β-CTX), and single nucleotide polymorphisms were determined. Locally weighted regression and smoothing scatterplot and segmented regression were performed to estimate the 25(OH)D thresholds. RESULTS: The median serum 25(OH)D was 16.63 (11.96-22.55) ng/mL and the prevalence of low serum 25(OH)D (< 12 ng/mL) was 25.2%. Women with the lowest 25(OH)D had the highest β-CTX. After adjustment for the confounders, 25(OH)D cutoffs for OC [14.04 (12.84-15.23) ng/mL], β-CTX [13.94 (12.49-15.39) ng/mL], and P1NP [13.87 (12.37-15.37) ng/mL] in the whole population, cutoffs for OC [12.30 (10.68-13.91) ng/mL], β-CTX [12.23 (10.22-14.23) ng/mL], and P1NP [11.85 (10.40-13.31) ng/mL] in women with the GC rs2282679 G allele, and cutoffs for OC [12.75 (11.81-13.68) ng/mL], β-CTX [13.05 (11.78-14.32) ng/mL], and P1NP [12.81 (11.57-14.06) ng/mL] in women with the GC rs2282679 T allele, were observed. Below these cutoffs, BTMs were negatively associated with 25(OH)D, while above these cutoffs, BTMs plateaued. CONCLUSION In Chinese women of childbearing age, there were thresholds effect of serum 25(OH)D concentrations on BTMs. The results indicated that serum 25(OH)D concentrations < 13.87 ng/mL in this population had adverse influences on maintaining bone remodeling. BTMs were suppressed at a relatively lower serum 25(OH)D in women with the GC rs2282679 G allele compared with those with the T allele.
Humans ; Female ; Vitamin D/blood* ; Adult ; Middle Aged ; Polymorphism, Single Nucleotide ; Adolescent ; Young Adult ; China ; Biomarkers/blood* ; Bone Remodeling/genetics* ; Vitamin D-Binding Protein/genetics* ; Procollagen/blood* ; Osteocalcin/blood* ; Peptide Fragments/blood* ; East Asian People

OBJECTIVE: To investigate the association between long-term exposure to ambient fine particulate matter (PM _2.5) and its constituents and the risk of incident type 2 diabetes mellitus (T2DM), and to examine the modification roles of overweight status. METHODS: This prospective study included 27,507 adults living in rural China. The annual mean residential exposure to PM _2.5 and its constituents was estimated using a satellite-based statistical model. Cox models were used to estimate the risk of T2DM associated with PM _2.5 and its constituents. Stratified analysis quantified the role of overweight status in the association between PM _2.5 constituents and T2DM. RESULTS: Over a median follow-up of 9.4 years, 3,001 new T2DM cases were identified. The hazard ratio ( HR) for a 10 μg/m ³ increase in ambient PM _2.5 was 1.30 (95% confidence interval [ CI]: 1.17, 1.45). Among the constituents, the strongest association was observed with black carbon. Being overweight significantly modified the association between certain constituents and the risk of T2DM. Participants who were overweight and exposed to the highest quartile of PM _2.5 constituents had the highest risk of T2DM ( HR: 2.46, 95% CI: 2.04, 2.97). CONCLUSIONS Our findings indicate that PM _2.5 was associated with an increased risk of T2DM, with black carbon potentially being the primary contributor. Being overweight appeared to enhance the association between PM _2.5 and T2DM. This suggests that controlling both PM _2.5 exposure and overweight status may reduce the burden of T2DM.
Humans ; Diabetes Mellitus, Type 2/chemically induced* ; China/epidemiology* ; Particulate Matter/analysis* ; Overweight/epidemiology* ; Female ; Male ; Middle Aged ; Rural Population ; Air Pollutants/analysis* ; Adult ; Prospective Studies ; Environmental Exposure/adverse effects* ; Aged ; Risk Factors

Objective To explore the value of deep learning image reconstruction(DLIR)by comparing subjective and objec-tive evaluation of DLIR and adaptive statistical iterative reconstruction(ASIR-V)images in gastric cancer CT.Methods Abdominal CT images in the venous phase of 80 untreated patients with primary gastric cancer were included,and five CT reconstruction meth-ods of 50％ASIR-V,80％ASIR-V,DLIR-low(DLIR-L),DLIR-medium(DLIR-M)and DLIR-high(DLIR-H)were adopted,respec-tively.The objective evaluation included background standard deviation(SD),signal-to-noise ratio(SNR),contrast-to-noise ratio(CNR)values and pericancerous fat density resolution.The subjective evaluation included SD,overall image quality,the display of gastric cancer lesions,and diagnostic confidence in whether the serosal surface of the gastric wall was infiltrated.Results The subjective and objective evalua-tion indicators showed statistically significant differences among the five reconstruction models(P＜0.001).In terms of objective evalua-tion,the SD value of gastric cancer lesions in the DLIR-H was the lowest,while the SNR and CNR values were the highest among the five groups.In terms of subjective evaluation,the DLIR-M had the highest scores in gastric cancer lesions display,overall image quality and diagnostic confidence among the five groups.Conclusion Compared with ASIR-V,DLIR can significantly reduce image noise and improve image quality,and DLIR-M and DLIR-H are respectively the optimal subjective and objective reconstruction models for showing gastric cancer lesions.

Objective:To develop a preoperative CT-based radiomics model integrating multidimensional features for the accurate prediction of TFE3-rearranged renal cell carcinoma（TFE3-rRCC）.Methods:This study retrospectively enrolled 865 pathologically confirmed renal cell carcinoma（RCC）patients in The First Affiliated Hospital of Naval Medical University from June 2013 to June 2023，including 60 cases of TFE3-rRCC and 805 cases of non-TFE3 RCC（comprising clear cell RCC，papillary RCC，and chromophobe RCC）. Among them，627 were male and 238 were female，with a mean age of（54.1 ± 12.7）years（range：14?82 years）. The median maximum tumor diameter was 4.0（2.6，6.0）cm. Based on the chronological order of CT examinations，the patients were divided into training（ n=478），validation（ n=206），and test（ n=181）sets in an approximate 6∶2∶2 ratio. Using precontrast and corticomedullary phase CT images，we extracted peritumoral imaging features，habitat features，3D radiomic features，and 2.5D deep learning radiomic features. A deep learning radiomics score（DLR-SCORE）prediction model was constructed using least absolute shrinkage and selection operator（LASSO）regression. The diagnostic performance of the model was evaluated by receiver operating characteristic（ROC）curve analysis，with the area under the curve（AUC）as the primary metric. Additionally，sensitivity，specificity，and accuracy were calculated based on the confusion matrix. Results:A total of 12 442 features were extracted from non-contrast and corticomedullary phase CT images，from which eight key features were selected to construct the DLR-SCORE model. The model demonstrated diagnostic accuracies for TFE3-rRCC of 98.5%（471/478）in the training set，81.6%（168/206）in the validation set，and 86.2%（156/181）in the test set. The AUC of ROC curve was 0.98（95% CI 0.96?1.00）in the training set，0.83（95% CI 0.71?0.94）in the validation set，and 0.88（95% CI 0.76?1.00）in the test set. In the test set，the DLR-SCORE model achieved a sensitivity of 88.9%（16/18）and a specificity of 85.9%（140/163）for detecting TFE3-rRCC. Conclusions:The DLR-SCORE model integrating multidimensional CT radiomics features demonstrated favorable predictive performance for TFE3-rRCC，offering a promising noninvasive tool to assist preoperative diagnosis.

Objective:To investigate the correlation between interleukin-10, albumin levels and short-term prognosis in patients with acute lung injury.Methods:A retrospective study was conducted to collect data on 150 patients with acute lung injury admitted to the Fourth People′s Hospital of Longgang District, Shenzhen from January 2021 to December 2023. The short-term prognosis was evaluated based on the mortality rate within 28 d of admission, and the patients were divided into a mortality group 53 cases and a survival group 97 cases. General information, levels of interleukin-10 and albumin within 24 h of admission, and other laboratory indicators were compared between the two groups, with a focus on analyzing the correlation between interleukin-10, albumin levels and the short-term prognosis of patients.Results:Murray lung injury score, acute physiology and chronic health evaluation Ⅱ (APACHE Ⅱ) score and levels of C-reactive protein, interleukin-10 in the mortality group were higher than those in the survival group: (2.27 ± 0.36) scores vs. (1.98 ± 0.28) scores, (22.72 ± 3.27) scores vs. (19.85 ± 3.12) scores, (106.27 ± 14.22) mg/L vs. (93.22 ± 15.27) mg/L, (51.75 ± 8.12) ng/L vs. (46.27 ± 9.47) ng/L, the levels of platelet and albumin were lower than those in the survival group: (186.67 ± 23.11) ×10 9/L vs. (203.25 ± 25.36) ×10 9/L, (27.86 ± 4.75) g/L vs. (32.21 ± 5.61) g/L, with statistical significant differences ( P<0.05). Cox regression analysis showed that the mortality risk of patients with acute lung injury was related to Murray lung injury score, APACHEⅡ score, platelet, C-reactive protein, interleukin-10 and albumin levels at admission ( P<0.05). Restricted cubic spline (RCS) analysis and interaction testing found that the mortality risk of patients with acute lung injury showed a non-linear dose-response relationship with serum interleukin-10 and albumin levels ( P<0.05), and the two had a negative interaction with the mortality risk of patients. The interleukin-10, albumin-assisted Murray lung injury score, APACHE Ⅱ score, platelet and C-reactive protein were used to construct a nomogram prediction model, and the decision curve and nomogram measurement model were drawn. The model has certain predictive value for the short-term risk of death in patients with acute lung injury. Conclusions:The short-term mortality risk in patients with acute lung injury may be related to abnormal levels of interleukin-10 and albumin, which can assist in the early screening of high-risk mortality patients and serve as clinical intervention targets.

BACKGROUND:Implant restoration has become an important means to treat anterior tooth loss,and it is particularly important to select appropriate implant restoration materials.However,at present,there are some deficiencies in clinical implant materials,and researchers have been exploring suitable implant materials.OBJECTIVE:To compare the biomechanical characteristics of implants made of different materials in restoring single missing maxillary anterior teeth.METHODS:The cone beam CT data of a patient with single maxillary central incisor loss were imported into 3-matic software to establish a three-dimensional finite element analysis model of single maxillary anterior tooth loss.The model was then imported into Marc Mentat.Eight sets of implant restoration models were designed according to different implant materials(polyetheretherketone,titanium-zirconium alloy,titanium alloy,and zirconia,with the elastic modulus of the four materials increasing in sequence)and cancellous bone density(high density,low density)to simulate the stress conditions of the maxillary anterior teeth in centric occlusion.The total displacements and von Mises stresses of implants,cortical bone stresses and cancellous bone strains were compared and analyzed.RESULTS AND CONCLUSION:(1)The maximum displacement of the implant gradually decreased with the increase of the modulus of elasticity of the material,and the value of the maximum displacement of the implant in the polyetheretherketone group exceeded 10 μm;the implant stress was concentrated in the labial neck in the models.The maximum stress gradually increased with the increase of the modulus of elasticity of the implant material,among which,the zirconia-low density bone model had the highest stress,which was 21.31 MPa;the cortical bone stress was concentrated in the cortical bone at the junction of the implant with the labial side,and the polyetheretherketone-low density bone group had the highest value,which was 29.90 MPa.(2)From the biomechanical point of view,titanium-zirconium alloy,titanium alloy,and zirconia can be used as implant materials for restoration of a single missing anterior tooth,and implant displacement is one of the common problems during implant restorations,but pure polyetheretherketone material may cause excessive implant displacement in implant restorations of anterior areas,causing implant failure.