Quantitative analysis of four PAHs in oily sludge by surface-enhanced Raman spectroscopy (SERS) combined with partial least squares regression (PLS) based on a novel nano-silver-silicon coupling substrate.

Polycyclic aromatic hydrocarbons (PAHs) present in oily sludge generated by the petroleum and petrochemical industries have emerged as a prominent concern within the realm of environmental conservation. The precise determination of PAHs holds immense significance in both petroleum geochemistry and environmental protection. In this study, a combination of surface-enhanced Raman spectroscopy (SERS) and solid-liquid extraction was employed for the screening of PAHs in oily sludge. Methanol was utilized as the extraction solvent for PAHs, while nanosilver-silicon coupling substrates were employed for their detection. The SERS spectrum was acquired using a portable Raman spectrometer. The nano silver-silicon coupling substrate exhibits excellent uniformity, with relative standard deviations (RSDs) of Phenanthrene, Fluoranthrene, Fluorene and Naphthalene (Phe, Flt, Flu and Nap) being 2.8%, 1.08%, 1.41%, and 5.44% respectively. Moreover, the limits of detection (LODs) achieved remarkable values of 0.542 µg/g, 0.342 µg/g, 0.541 µg/g, and 5.132 µg/g. The quantitative analysis of PAHs in oily sludge was investigated using SERS technology combined with partial least squares (PLS). The optimal PLS calibration model was optimized by combining spectral preprocessing methods and using the SiPLS (Synergy interval partial least squares)-VIP (Variable Importance in Projection) hybrid variable selection strategy. The prediction performance of the D1st (First derivative)-WT (Wavelet transform)-SiPLS-VIP-PLS model was deemed satisfactory, as evidenced by high R2P values of 0.9851, 0.9917, and 0.9925 for Phe, Flt, and Flu respectively; additionally, the corresponding MREP values were found to be 0.0580, 0.0668, and 0.0669 respectively. However, for Nap analysis, the D1st-WT-PLS model proved to be a better calibration model with an R2P value of 0.9864 and an MREP (Mean relative error of prediction) value of 0.0713. In summary, SERS technology combined with PLS based on different spectral pretreatment methods and mixed variable selection strategies is a promising method for quantitative analysis of PAHs in oily sludge, which will provide new ideas and methods for the quantitative analysis of PAHs in oily sludge.

Raman spectroscopy combined with partial least squares (PLS) based on hybrid spectral preprocessing and backward interval PLS (biPLS) for quantitative analysis of four PAHs in oil sludge.

Polycyclic aromatic hydrocarbons (PAHs) contained in a large amount of oily sludge produced in petroleum and petrochemical production has become one of the main environmental protection concerns in the industry. The accurate determination of PAHs is of great significance in the field of petroleum geochemistry and environmental protection. In this study, Raman spectroscopy combined with partial least squares (PLS) based on different hybrid spectral preprocessing methods and variable selection strategies was proposed for quantitative analysis of phenanthrene, fluoranthrene, fluorene and naphthalene (Phe, Flt, Flu and Nap) in oil sludge. At first, PAHs in oily sludge was extracted by solid-liquid extraction with methanol as extractant, and Raman spectra of 21 oily sludge samples were collected by portable Raman spectrometer. And then, the influence of first derivative (D1st), wavelet transform (WT) and their hybrid spectral preprocessing on the predictive performance of the PLS calibration model was discussed. Thirdly, biPLS (backward interval partial least squares) was used to optimize the input variables before and after the hybrid spectral preprocessing methods, and the influence of biPLS and the hybrid spectral preprocessing sequence on the predictive performance of the PLS calibration model was discussed. Finally, the predictive performance of the PLS calibration model was optimized according to the results of leave-one-out cross-validation (LOOCV) method. The results show that the biPLS-D1st-WT-PLS calibration model established by using biPLS first to select the characteristic variables, followed by hybrid spectral preprocessing of the characteristic variables, has better prediction performance for Flt (determination coefficient of prediction (R2P) = 0.9987, and the mean relative error of prediction (MREP) = 0.0606). For Phe, Flu and Nap, the WT-biPLS-PLS calibration model has a better predictive effect (R2P are 0.9995, 0.9996 and 0.9983, and MREP are 0.0426, 0.0719 and 0.0497, respectively). In general, portable Raman spectroscopy combined with PLS calibration model based on different hybrid spectral preprocessing and variable selection strategies has achieved good prediction results for quantitative analysis of four PAHs in oily sludge. It is a new strategy to firstly select the characteristic variables of the original spectra, and secondly to preprocess the characteristic variables by the hybrid spectral preprocessing, which will provide a new idea for the establishment of quantitative analysis methods for PAHs in oily sludge.

Hydromorphone combined with ropivacaine for erector spinae plane block in patients undergoing modified radical mastectomy: A prospective randomized controlled trial.

BACKGROUND: Combining hydromorphone with ropivacaine in ultrasound-guided erector spinae plane blocks enhances postoperative analgesia and reduces interleukin-6 expression in breast surgery patients. METHODS: In this study, breast cancer patients undergoing modified radical mastectomy were randomized into 3 groups for anesthesia (30 patients in each group): standard general (group C), Erector Spinae Plane Block (ESPB) with ropivacaine (group R), and ESPB with ropivacaine plus hydromorphone (group HR). Diagnosis: Breast cancer patients. Postsurgery, pain levels, IL-6, anesthetic doses, additional analgesia needs, and recovery milestones were compared to evaluate the efficacy of the ESPB enhancements. RESULTS: The 3 groups were not significantly different in baseline characteristics, operation time, number of cases with postoperative nausea, and serum IL-6 concentrations at T1 (the time of being returned to the ward after surgery). At T2 (at 6:00 in the next morning after surgery), the serum IL-6 concentration in group HR was significantly lower than that in groups R and C (P < .05); the intraoperative doses of remifentanil, sufentanil, and propofol were significantly lower in groups HR and R than those in group C (P < .05); Groups HR and R had significantly lower visual analog scale scores at T3 (4 hours postoperatively), T4 (12 hours postoperatively), and T5 (24 hours postoperatively) than those in group C (P < .05); the proportions of patients receiving postoperative remedial analgesia were significantly lower in groups HR and R than in group C (P < .05); groups HR and R had significantly lower proportions of patients with postoperative nausea than group C (P < .05); the time to the first anal exhaust and the time to the first ambulation after surgery were significantly shorter in groups HR and R than those in group C (P < .05). CONCLUSION: Hydromorphone combined with ropivacaine for ESPB achieved a greater postoperative analgesic effect for patients receiving MRM under general anesthesia. The combined analgesia caused fewer adverse reactions and inhibited the expression level of the inflammatory factor IL-6 more effectively, thereby facilitating postoperative recovery. ESPB using hydromorphone with ropivacaine improved pain control post-MRM, reduced adverse effects, and more effectively suppressed IL-6, enhancing recovery.