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In this study, a phase-generated carrier (PGC) demodulation algorithm combined with the extended Kalman filter (EKF) algorithm based on an electro-optic modulator (EOM) is proposed, which can achieve nonlinear distortion (such as modulation depth drift and carrier phase delay) suppression for high-frequency phase carrier modulation. The improved algorithm is implemented on a field-programmable gate array (FPGA) hardware platform. The experimental results by the PGC-EKF method show that total harmonic distortion (THD) decreases from −32.61 to −54.51 dB, and SINAD increases from 32.59 to 47.86 dB, compared to the traditional PGC-Arctan method. This indicates that the PGC-EKF demodulation algorithm proposed in this paper can be widely used in many important fields such as hydrophone, transformer, and ultrasound signal detection. [ABSTRACT FROM AUTHOR]

Objective Individual differences challenge the treatment of vancomycin, linezolid and voriconazole in severe infections. This study aimed to build a simple and economical method for simultaneous determination of the three antibiotics in human plasma by ultra-high performance liquid chromatography-tandem mass spectrometry (UHPLC–MS/MS) and provided a reference for therapeutic drug monitoring (TDM) of infected patients. Methods The plasma samples were precipitated by acetonitrile and detected and separated on a shim-pack GIST C18 column following the gradient elution within 5 min. Mass quantification was performed on multiple reaction monitoring mode under positive electrospray ionization. Results The linear ranges of vancomycin, linezolid and voriconazole were 1.00–100.00, 0.10–15.00 and 0.10–20.00 μg·mL−1, respectively, with good linearity (R 2 > 0.99). The accuracy and precision, matrix effect, extraction recovery and stability were validated, and the results all meet the acceptance criteria of China Food and Drug Administration (CFDA) guidelines. Conclusion The UHPLC–MS/MS method was established and validated for the simultaneous determination of vancomycin, linezolid and voriconazole in human plasma and successfully applied to routine TDM for individualized treatment. [ABSTRACT FROM AUTHOR]

Anlotinib and osimertinib are a class of tyrosine kinase inhibitors for the treatment of malignant tumor. The combination of anlotinib and osimertinib is currently used for treating non-small cell lung cancer (NSCLC) patients. This study aimed to develop a simple and rapid isotope-labeled UHPLC–MS/MS method for the simultaneous determination of anlotinib and osimertinib in human plasma. The analytes were extracted by protein precipitation with acetonitrile and were then separated on a Shim-pack GIST C18 column. The detection was performed on Shimadzu 8050 triple quadruple mass spectrometer in the positive electrospray ionization mode with multiple reaction monitoring. The precursor-to-product ion transitions were m/z 408.10→ 339.75, 500.25→ 72.20 and 413.50 → 344.50 for anlotinib, osimertinib and D5-anlotinib, respectively. Validation is based on US Food and Drug Administration guidelines. The linearity ranges were 0.5–100 ng/mL for anlotinib and were 1–500 ng/mL for osimertinib with the correlation coefficients (r  2) ≥ 0.99. Accuracy and precision, matrix effect, extraction recovery and stability of anlotinib and osimertinib were acceptable after validation. The UHPLC–MS/MS method was successfully validated and was applied to monitor the concentration of anlotinib and osimertinib in NSCLC patients. [ABSTRACT FROM AUTHOR]

Dissolved gas analysis is an important method for diagnosing the operating condition of power transformers. Traditional methods such as IEC Ratios and Duval Triangles and Pentagon methods are not applicable in the case of abnormal or missing values of DGA data. A novel transformer fault diagnosis method based on an extreme gradient boosting algorithm is proposed in this paper. First, the traditional statistical method is replaced by the random forest regression algorithm for filling in missing values of dissolved gas data. Normalization and feature derivation of the outlier data is adopted based on the gas content. Then, hyperparameter optimization of the transformer fault diagnosis model based on an extreme gradient boosting algorithm is carried out using the tree-structured probability density estimator algorithm. Finally, the influence of missing data and optimization algorithms on transformer fault diagnosis models is analyzed. The effects of different algorithms based on incomplete datasets are also discussed. The results show that the performance of the random forest regression algorithm on missing data filling is better than classification and regression trees and traditional statistical methods. The average accuracy of the fault diagnosis method proposed in the paper is 89.5%, even when the missing data rate reaches 20%. The accuracy and robustness of the TPE-XGBoost model are superior to other machine learning algorithms described in this paper, such as k-nearest neighbor, deep neural networks, random forest, etc. [ABSTRACT FROM AUTHOR]

Background: bacterial meningitis (BM) is more common in infants than at any other time in life and remains a devastating disease with considerable risk of death and morbidity. This article aims to gather the currently available evidence to perform a systematic review of clinical factors that may predict or be associated with BM death and/or sequelae in infants < 90 days of age., Methods: The Medline/PubMed, Cochrane Library and Embase databases were systematically searched for prognostic studies that described risk factors for mortality and sequelae in infants aged <90d with BM. The databases were searched from the beginning of the database to December 31st, 2022.The quality of cohort studies was assessed by the Newcastle-Ottawa Scale (NOS). The quality of cross-section studies was assessed by the Agency for Healthcare Research and Quality (AHRQ). A systematic review was undertaken to ascertain the prognostic factors proven to be noteworthy., Results: Of the 1,431 studies retrieved, 20 were eligible for the final analysis including 11 cohort and 9 cross-sectional studies were identified. Four risk factors predicting poor outcome were mentioned mostly in those studies, including prematurity or low birth weight (LBW), seizures, coma, and elevated CSF protein. But only preterm, coma and elevated CSF protein were identified by multivariate analyses in more than one study., Conclusions: This study demonstrates several potential predictive factors to the poor outcomes of BM in infant. But with large heterogeneity, these predictors should be evaluated by further well-designed prospective studies., Systematic Review Registration: https://www.crd.york.ac.uk/, identifier CRD42017074949., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (© 2024 Liu, Feng, Guo, Chen, Liu and Liang.)

Objective: To fabricate in situ crosslinking hyaluronic acid hydrogel and evaluate its biocompatibility in vitro., Methods: The acrylic acid chloride and polyethylene glycol were added to prepare crosslinking agent polyethylene glycol acrylate (PEGDA), and the molecular structure of PEGDA was analyzed by Flourier transformation infrared spectroscopy and 1H nuclear magnetic resonance spectroscopy. Hyaluronic acid hydrogel was chemically modified to prepare hyaluronic acid thiolation (HA-SH). And the degree of HA-SH was analyzed qualitatively and quantitatively by Ellman method. HA-SH solution in concentrations ( W/V ) of 0.5%, 1.0%, and 1.5% and PEGDA solution in concentrations ( W/V ) of 2%, 4%, and 6% were prepared with PBS. The two solutions were mixed in different ratios, and in situ crosslinking hyaluronic acid hydrogel was obtained; the crosslinking time was recorded. The cellular toxicity of in situ crosslinking hyaluronic acid hydrogel (1.5% HA-SH and 4% PEGDA mixed) was tested by L929 cells. Meanwhile, the biocompatibility of hydrogel was tested by co-cultured with human bone mesenchymal stem cells (hBMSCs)., Results: Flourier transformation infrared spectroscopy showed that most hydroxyl groups were replaced by acrylate groups; 1H nuclear magnetic resonance spectroscopy showed 3 characteristic peaks of hydrogen representing acrylate and olefinic bond at 5-7 ppm. The thiolation yield of HA-SH was 65.4%. In situ crosslinking time of hyaluronic acid hydrogel was 2 to 70 minutes in the PEGDA concentrations of 2%-6% and HA-SH concentrations of 0.5%-1.5%. The hyaluronic acid hydrogel appeared to be transparent. The toxicity grade of leaching solution of hydrogel was grade 1. hBMSCs grew well and distributed evenly in hydrogel with a very high viability., Conclusions: In situ crosslinking hyaluronic acid hydrogel has low cytotoxicity, good biocompatibility, and controllable crosslinking time, so it could be used as a potential tissue engineered scaffold or repairing material for tissue regeneration.