Huinan Yang

With the rise in global temperatures, it is of great significance to achieve rapid and accurate detection of greenhouse gases, such as carbon dioxide and methane. Raman spectroscopy not only overcomes the weakness of absorption spectroscopy in simultaneously measuring homonuclear diatomic molecules but also enables the simultaneous detection of multiple gases using a single-wavelength laser. However, due to the small Raman scattering cross-section and weak intensity of molecules, its application in gas detection is limited. To enhance the intensity of Raman scattering, this paper designs and constructs a multi-pass enhanced Raman spectroscopy setup. This study focuses on the effects of Raman scattering collection geometry, laser multi-pass patterns, and laser polarization relative to the Raman collection direction on signal intensity. Investigations into Raman scattering collection angles of 30°, 60°, and 90° reveal that the Raman scattering signal intensity increases as the collection angle decreases. Different laser multi-pass patterns also impact the signal, with the near-concentric linear multi-pass pattern found to collect more signals. To minimize the influence of excitation light on the signal, a side collection system is employed. Experiments show that the Raman scattering signal is stronger when the laser polarization is perpendicular to the collection direction. This study achieves overall system performance enhancement through coordinated optimization of multiple physical mechanisms, including Raman scattering collection geometry, laser multi-pass patterns, and laser polarization characteristics. The optimized setup was employed to characterize the laser power dependence for nitrogen, oxygen, and carbon dioxide detection. The results showed that the Raman scattering intensity varied linearly with the laser power of the gases, with linear fitting goodness R² values of 0.9902, 0.9848, and 0.9969, respectively. Finally, by configuring different concentrations of carbon dioxide gas using nitrogen, it was found that the Raman scattering intensity varied linearly with the concentration of carbon dioxide, with a linear fitting goodness R² of 0.9812. The system achieves a CO₂ detection limit of 500 ppm at 200 s integration time, meeting the requirements for greenhouse gas emission monitoring applications.

Introduction: The progression evaluation of autosomal dominant polycystic kidney disease (ADPKD) is critical to the treatment strategy and prognosis prediction of the disease, but the current evaluation methods are time-consuming and costly. Methods: ADPKD patients were recruited in Shanghai Changzheng Hospital from February 2023 to October 2023. Based on the Mayo imaging classification (MIC) model, patients with different disease progression rates were classified into slowly progressive (SP) group (MIC 1A, 1B) or rapidly progressive (RP) group (MIC 1C, 1D, and 1E). The Raman spectra of urine samples from ADPKD patients were obtained by Surface-enhanced Raman spectroscopy (SERS) protocol and the characteristics of urine Raman spectra from SP and RP groups were analyzed. The ADPKD progression prediction model was constructed based on principal component analysis (PCA) and support vector machine (SVM). Results: After adjusting for age, gender, and renal function, there were differences in Raman intensity of the six major Raman peaks (758/794/1,184/1,288/1,346/1,385 cm−1) between patients with SP and RP ADPKD (p < 0.05). The substances of the above Raman peaks include tryptophan, uracil, adenine, phosphodiester bond, glucose, lipids, etc. The accuracy, sensitivity, and specificity of the ADPKD progression prediction model were 82.93%, 77.55%, and 86.11%, and after leaving-one-out cross validation (LOOCV), the accuracy, sensitivity, and specificity of were 70.25%, 65.31%, and 73.61%, respectively. Conclusions: Urinary SERS detection can distinguish RP ADPKD patients from SP ones noninvasively, conveniently and quickly, with reasonable accuracy, sensitivity, and specificity. SERS combined with machine learning omics techniques might be a novel method to evaluate the progression of ADPKD.

Water-soluble components significantly contribute to the oxidative potential (OP) of atmospheric fine particles (PM_2.5), but our understanding of the water-soluble PM_2.5 OP and its sources, as well as its relationship with water-soluble components, is still limited. In this study, the water-soluble OP levels in wintertime PM_2.5 in the south and north of Beijing, representing the difference in sources, were measured with the dithiothreitol (DTT) assay. The volume-normalized DTT (DTT_v) in the north (3.5±1.2 nmol min⁻¹ m⁻³) was comparable to that in the south (3.9±0.9 nmol min⁻¹ m⁻³), while the mass-normalized DTT (DTT_m) in the north (65±28 pmol min⁻¹ µg⁻³) was almost twice that in the south (36±14 pmol min⁻¹ µg⁻³). In both the south and north of Beijing, DTT_v was better correlated with soluble elements instead of total elements. In the north, soluble elements (mainly Mn, Co, Ni, Zn, As, Cd and Pb) and water-soluble organic compounds, especially light-absorbing compounds (also known as brown carbon), had positive correlations with DTT_v. However, in the south, DTT_v was mainly related to soluble As, Fe and Pb. The sources of DTT_v were further resolved using the positive matrix factorization (PMF) model. Traffic-related emissions (39 %) and biomass burning (25 %) were the main sources of DTT_v in the south, and traffic-related emissions (>50 %) contributed the most to DTT_v in the north. Our results indicate that vehicle emission was an important contributor to the OP in Beijing ambient PM_2.5 and suggest that more study is needed to understand the intrinsic relationship between the OP and light-absorbing organic compounds.

Water-soluble components have significant contribution to the oxidative potential (OP) of atmospheric fine particles, while our understanding of their relationship is still limited. In this study, the water-soluble OP levels in wintertime PM_2.5 in the south and north of Beijing, representing the difference in sources, were measured with dithiothreitol (DTT) assay. The volume normalized DTT (DTT_v) in the north (3.5 ± 1.2 nmol min^-1 m^-3) was comparable to that in the south (3.9 ± 0.9 nmol min^-1 m^-3), while the mass normalized DTT (DTT_m) in the north (65.3 ± 27.6 pmol min^-1 μg^-3) was almost twice that in the south (36.1 ± 14.5 pmol min^-1 μg^-3). In both the south and north of Beijing, DTT_v was better correlated with soluble elements instead of total elements. In the north, soluble elements (mainly Mn, Co, Ni, Zn, As, Cd and Pb) and water-soluble organic compounds, especially light-absorbing compounds (also known as brown carbon), had positive correlations with DTT_v. However, in the south, the DTT_v was mainly related to soluble As, Fe and Pb. The sources of DTT_v were further resolved using the positive matrix factorization (PMF) model. Traffic-related emissions (39.1 %) and biomass burning (25.2 %) were the main sources of DTT_v in the south, and traffic-related emissions (> 50 %) contributed the most of DTT_v in the north. Our results indicate that vehicle emission was the important contributor to OP in Beijing ambient PM_2.5 and suggest that more study is needed to understand the intrinsic relationship between OP and light absorbing organic compounds.

Water-soluble components have significant contribution to the oxidative potential (OP) of atmospheric fine particles, while our understanding of their relationship is still limited. In this study, the water-soluble OP levels in wintertime PM_2.5 in the south and north of Beijing, representing the difference in sources, were measured with dithiothreitol (DTT) assay. The volume normalized DTT (DTT_v) in the north (3.5 ± 1.2 nmol min^-1 m^-3) was comparable to that in the south (3.9 ± 0.9 nmol min^-1 m^-3), while the mass normalized DTT (DTT_m) in the north (65.3 ± 27.6 pmol min^-1 μg^-3) was almost twice that in the south (36.1 ± 14.5 pmol min^-1 μg^-3). In both the south and north of Beijing, DTT_v was better correlated with soluble elements instead of total elements. In the north, soluble elements (mainly Mn, Co, Ni, Zn, As, Cd and Pb) and water-soluble organic compounds, especially light-absorbing compounds (also known as brown carbon), had positive correlations with DTT_v. However, in the south, the DTT_v was mainly related to soluble As, Fe and Pb. The sources of DTT_v were further resolved using the positive matrix factorization (PMF) model. Traffic-related emissions (39.1 %) and biomass burning (25.2 %) were the main sources of DTT_v in the south, and traffic-related emissions (> 50 %) contributed the most of DTT_v in the north. Our results indicate that vehicle emission was the important contributor to OP in Beijing ambient PM_2.5 and suggest that more study is needed to understand the intrinsic relationship between OP and light absorbing organic compounds.

Water-soluble components have significant contribution to the oxidative potential (OP) of atmospheric fine particles, while our understanding of their relationship is still limited. In this study, the water-soluble OP levels in wintertime PM_2.5 in the south and north of Beijing, representing the difference in sources, were measured with dithiothreitol (DTT) assay. The volume normalized DTT (DTT_v) in the north (3.5 ± 1.2 nmol min^-1 m^-3) was comparable to that in the south (3.9 ± 0.9 nmol min^-1 m^-3), while the mass normalized DTT (DTT_m) in the north (65.3 ± 27.6 pmol min^-1 μg^-3) was almost twice that in the south (36.1 ± 14.5 pmol min^-1 μg^-3). In both the south and north of Beijing, DTT_v was better correlated with soluble elements instead of total elements. In the north, soluble elements (mainly Mn, Co, Ni, Zn, As, Cd and Pb) and water-soluble organic compounds, especially light-absorbing compounds (also known as brown carbon), had positive correlations with DTT_v. However, in the south, the DTT_v was mainly related to soluble As, Fe and Pb. The sources of DTT_v were further resolved using the positive matrix factorization (PMF) model. Traffic-related emissions (39.1 %) and biomass burning (25.2 %) were the main sources of DTT_v in the south, and traffic-related emissions (> 50 %) contributed the most of DTT_v in the north. Our results indicate that vehicle emission was the important contributor to OP in Beijing ambient PM_2.5 and suggest that more study is needed to understand the intrinsic relationship between OP and light absorbing organic compounds.