Background Amid global climate change, extreme environmental events are occurring more frequently, and it is imperative to investigate the impacts of combined exposure to fine particluate matter (PM_2.5) and cold spells (CS) on population mortality. Objective To analyze the association between sequential extreme PM_2.5-cold spell (EP-CS) events and non-accidental mortality among residents in Zigong City from 2016 to 2021. Methods Using time-series study design, meteorological data in Zigong were collected from the Zigong Meteorological Bureau for the period from January 1, 2016 to December 31, 2021, while daily non-accidental mortality data were obtained from the mortality surveillance system of the Zigong Center for Disease Control and Prevention. We adopted the percentile method to define extreme PM_2.5 events and cold spells. We analyzed the risk effect of EP-CS events on non-accidental mortality among residents in this city and explored the potential amplification of damage resulting from different patterns of consecutive extreme events by using distributed lag nonlinear model (DLNM). We also conducted stratified analyses based on age, gender, education level, and marital status. Results The EP-CS events demonstrated a significant impact on non-accidental mortality among the local residents, exhibiting a certain lagged effect. The effects on the overall residents lasted from lag0 (RR=1.030, 95%CI: 1.013, 1.048) to lag14 (RR=1.035, 95%CI: 1.019, 1.052). Notably, the effects were more pronounced among females, individuals aged 65 years and above, and those who were never married, divorced, or widowed. Different patterns of EP-CS events all associated with adverse effects, the health impact of EP-CS events was significantly greater than that of individual PM_2.5 pollution or CS events. The analysis of lag effects across different event patterns revealed that the overall effect of EP-CS events with shorter intervals (0–7 d) had a stronger effect compared to EP-CS with longer intervals (8–14 d), and the RR values of lag14 were 1.034 (95%CI: 1.015, 1.054) and 1.017 (95%CI: 1.007, 1.027), suggesting that the damaging effect of compound events occurring in the short term was more significant. Conclusion All sequential extreme EP-CS events have an impact on non-accidental mortality among residents in this city, with compound events demonstrating a stronger effect. Females, individuals aged ≥65 years, and those who were never married, divorced, or widowed are more sensitive to EP-CS events.

Objective To explore the epidemiological characteristics of gouty arthritis in Northwest China from 2023 to 2025, and to formulate preventive intervention measures. Methods By retrospectively analyzing the case data of medical institutions in Northwest China from January 2023 to June 2025 (a total of 8 139 cases), the incidence trend and population distribution characteristics of gouty arthritis in this area were analyzed. Multivariate logistic regression analysis was performed to identify risk factors. Results From 2023 to 2025, the prevalence rate of gouty arthritis in adult residents in Northwest China was 3.74% (304/8 139). Among the sites affected by gouty arthritis, the metatarsophalangeal joint accounted for the highest proportion (P<0.05). From the perspective of age distribution, the prevalence rate was the highest in 40-59 years old group (5.90%), followed by 66-80 years old group (4.21%) and >80 years old group (2.75%). The incidence rate in 40-65 years old group was higher than that in the other age groups (P<0.05). High blood uric acid and creatinine, alcohol drinking, obesity, high purine diet, concurrent chronic kidney disease and metabolic syndrome were risk factors affecting gouty arthritis in Northwest China (P<0.05). Conclusion High blood uric acid level, high creatinine level, alcohol drinking, obesity, high purine diet, concurrent chronic kidney disease and metabolic syndrome are risk factors influencing gouty arthritis in Northwest China. Based on the above factors, this study proposes comprehensive prevention strategies from the individual, community and public health levels to provide a scientific basis for reducing the incidence rate of gouty arthritis.

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 evaluate the radiation impact of a self-developed digital miniature CT on the human body and the environment under simulated scanning conditions, and verify its safety and regulatory compliance. Methods Under typical head scanning conditions with the digital miniature CT (70 kV/10 mA), the equivalent doses received at the body surface sites corresponding to the thyroid, breast, stomach, liver, kidney, and gonads of the phantom were measured without protection and with 0.5 mmPb equivalent protection using LiF (Mg, Cu, P) thermoluminescent dosimeters. The ambient dose equivalent rates at the bed level inside the CT room at different directions and distances from the scanning center were measured using a model AT1121 X/γ dosimeter. The equivalent doses of organs on both sides of the phantom and the ambient equivalent dose rates on the left and right sides of the longitudinal axis of the bed in the CT room were compared. The Mann-Whitney test was used at a significance level of P < 0.05. Results During a single scan of the head with the digital miniature CT, the equivalent doses at the body surface sites corresponding to the thyroid, breast, stomach, liver, kidney, and gonads without protection were 1.04, 0.95, 0.55, 0.57, 0.40, and 0.12 mSv, respectively, which were only 0.84% to 8.24% of the doses inside the irradiation field. With 0.5 mm Pb equivalent protection, the equivalent dose of the thyroid decreased from 8.24 mSv to 3.27 mSv with a reduction of 60.3%, and the doses of the other organs were reduced to 1.5-11.5 μSv with the maximum reduction of 14 times. In the longitudinal axis direction of the CT bed, the ambient dose equivalent rate at a distance of 2 m from the scanning center was reduced to 0.066 mSv/h, which was only 9.6% of the ambient equivalent dose rate at a distance of 50 cm from the scanning center. Conclusion The digital miniature CT has advantages in ensuring patient safety, optimizing imaging quality, and promoting technological development, demonstrating promising application potential. However, the radiation protection of personal and CT room should not be ignored.

Objective: To investigate the association between overweight, obesity, central obesity and hypertension, so as to provide the basis for formulating targeted hypertension prevention and control strategies. Methods: Permanent residents aged ≥18 years were selected in Wenzhou City, Zhejiang Province from June 2023 to August 2024 by a multistage cluster random sampling method. Data on demographic information, lifestyle, height, weight, waist circumference (WC), blood pressure, and blood biochemical indicators were collected through questionnaire surveys, physical examinations, and laboratory tests. The prevalence of hypertension was calculated and standardized using the data of the Sixth National Population Census in 2010. Body mass index (BMI) was calculated to determine overweight and obesity, while WC was used to identify central obesity. The association between overweight, obesity, central obesity and hypertension were analyzed using multivariable logistic regression models. Results: A total of 38 593 residents were surveyed, including 19 481 (50.48%) males and 19 112 (49.52%) females. The median age was 46.00 (interquartile range, 26.00) years. The rates of overweight, obesity, and central obesity were 32.74% (12 634 individuals), 10.27% (3 963 individuals), and 27.87% (10 755 individuals), respectively. There were 11 813 cases of hypertension, with a prevalence and standardized prevalence of 30.61% and 24.41%, respectively. Multivariable logistic regression analysis showed that after adjusting for demographic information, lifestyle, diabetes and dyslipidemia, the likelihood of hypertension in the overweight and obesity groups was 1.927 (95%CI: 1.815-2.045) times and 3.724 (95%CI: 3.404-4.073) times that of the normal BMI group, respectively. The likelihood of hypertension in the central obesity group was 2.346 (95%CI: 2.214-2.486) times that of the normal WC group. The likelihood of hypertension in the central obesity only, overweight only, overweight with central obesity, obesity only and obesity with central obesity groups was 1.586 (95%CI: 1.391-1.809), 1.704 (95%CI: 1.582-1.835), 2.433 (95%CI: 2.254-2.626), 1.768 (95%CI: 1.424-2.194), and 4.466 (95%CI: 4.053-4.921) times that of the normal BMI and WC group, respectively. Conclusions Overweight, obesity and central obesity were all associated with hypertension among adult residents. The highest likelihood of hypertension was observed among adult residents with both general obesity and central obesity.

Objective To explore the effects of different glucose concentrations on the synthesis and secretion of bone collagen in osteoblasts and the impact of diabetes on bone quality in mice.Methods(1)Primary osteoblasts were extracted from the skulls of neonatal mice via collagenase digestion and cultured in four groups under different glucose concentrations:normal glucose(5.5 mmol/L),moderate glucose(11.5 mmol/L),moderate-high glucose(16.5 mmol/L),and high glucose(25 mmol/L).EdU staining was performed to evaluate cell proliferation,while the Transwell assay was used to assess cell migration.Immunofluorescence and Western blotting were performed to detect and quantitatively analyze the content of type Ⅰ collagen(Col-1).Alizarin red S(ARS)staining and alkaline phosphatase(ALP)staining were applied to assess the effects of different glucose concentrations on osteogenic differentiation.(2)Six-week-old male C57BL/6 mice were randomly divided into control group and model group(5 in each group).The model group was fed a high-fat diet for 4 weeks followed by streptozotocin(STZ)injection to establish a diabetic mouse model.The osteogenic differentiation capacity of primary osteoblasts from both groups was assessed.(3)Micro-computed tomography(Micro-CT)was employed to analyze femoral bone mineral density(BMD),bone volume/tissue volume(BV/TV),trabecular number(Tb.N),and trabecular separation(Tb.Sp).Three-point bending test was conducted to evaluate mechanical parameters including maximum load,Young's modulus,fracture energy,and stiffness.RT-qPCR was employed to assess the expression of osteogenic differentiation genes(Alp,Opn,Col1a1,and Lox).Masson staining and Mallory staining were used to evaluate Col-1 content in trabecular bone.Results(1)EdU and Transwell assay results demonstrated that with the gradual increase in glucose concentration,the proliferation and migration abilities of osteoblasts were significantly decreased(P<0.001),and the protein expression levels of Col-1 and lysyl oxidase(LOX)were significantly reduced(P<0.01 or P<0.001).ARS and ALP staining revealed that calcium salt deposition and ALP activity in osteoblasts were significantly decreased with increasing glucose concentration(P<0.05 or P<0.001).(2)Compared with control group,mice in model group exhibited typical"three polies and one weight loss"symptoms(polyuria,polydipsia,polyphagia,and weight loss)of diabetes,and ARS and ALP staining showed a significant reduction in osteoblasts(P<0.001).(3)Micro-CT and three-point bending test results indicated that,compared with control group,mice in model group showed microarchitectural deterioration of bone,decreased Tb.N,increased Tb.Sp,and significantly reduced maximum load,Young's modulus,fracture energy,and stiffness(P<0.05).RT-qPCR results showed that the relative mRNA expression levels of osteogenic differentiation genes(Alp,Opn,Col1a1,and Lox)were significantly decreased in model group compared with control group(P<0.01 or P<0.001).Masson and Mallory staining indicated a significant reduction in collagen content in model group compared with control group(P<0.01).Conclusions High-glucose environment inhibits osteoblast proliferation,differentiation,and migration.Diabetic mice exhibit reduced bone quality and increased bone fragility,potentially mediated by decreased lysyl oxidase and collagen levels.

Objective To investigate the genetic differences among different populations based on 13 autosomal STR loci in CODIS core.Methods Data of 13 autosomal STR loci(CSF1PO,FGA,THO1,TPOX,vWA,D3S1358,D5S818,D7S820,D8S1179,D13S317,D16S539,D18S51,D21S11)were collected from 95 populations in scientific journals between 1999 and 2021,soursed from the PubMed database,which had been published.Allele frequencies of loci were sorted out and forensic genetic parameters including gene differentiation coefficient(Gst),total heterozygosity(Ht),subpopula-tion heterozygosity(Hs)values,and Nei's DA genetic distance were calculated.Principal component analysis,phylogenetic tree,and multidimensional scale analysis were conducted to assess population ge-netic structure.Results A total of 265 alleles were detected at the 13 STR loci in these 95 popula-tions.The mean values of Gst,Ht,and Hs were 0.023 247,0.797 915 and 0.779 365.Population genetic analyses reflected significant differences among populations from Asia,Africa and Europe.In Asian populations,there was a certain degree of distinction between mainland and island populations;the Han population showed a certain degree of distinction with surrounding populations in mainland;while within the Han population,there were two distinct clusters formed by the northern Han and the south-ern Han.Conclusion The 13 autosomal STR loci in CODIS core demonstrate potential value for popu-lation identification across different groups,and may be used for the differentiation of ethnic groups,among different continental populations.

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.

Hepatocellular carcinoma (HCC) is a leading cause of cancer-associated death globally. Liver transplantation (LT) has emerged as a key treatment for patients with HCC, and the Milan criteria have been adopted as the cornerstone of the selection policy. To allow more patients to benefit from LT, a number of expanded criteria have been proposed, many of which use radiologic morphological characteristics with larger and more tumors as surrogates to predict outcomes. Other groups developed indices incorporating biological variables and dynamic markers of response to locoregional treatment. These expanded selection criteria achieved satisfactory results with limited liver supplies. In addition, a number of prognostic models have been developed using clinicopathological characteristics, imaging radiomics features, genetic data, and advanced techniques such as artificial intelligence. These models could improve prognostic estimation, establish surveillance strategies, and bolster long-term outcomes in patients with HCC. In this study, we reviewed the latest findings and achievements regarding the selection criteria and post-transplant prognostic models for LT in patients with HCC.

Hepatocellular carcinoma (HCC) is a leading cause of cancer-associated death globally. Liver transplantation (LT) has emerged as a key treatment for patients with HCC, and the Milan criteria have been adopted as the cornerstone of the selection policy. To allow more patients to benefit from LT, a number of expanded criteria have been proposed, many of which use radiologic morphological characteristics with larger and more tumors as surrogates to predict outcomes. Other groups developed indices incorporating biological variables and dynamic markers of response to locoregional treatment. These expanded selection criteria achieved satisfactory results with limited liver supplies. In addition, a number of prognostic models have been developed using clinicopathological characteristics, imaging radiomics features, genetic data, and advanced techniques such as artificial intelligence. These models could improve prognostic estimation, establish surveillance strategies, and bolster long-term outcomes in patients with HCC. In this study, we reviewed the latest findings and achievements regarding the selection criteria and post-transplant prognostic models for LT in patients with HCC.