BackgroundThe administration of levosimendan prophylactically to patients undergoing cardiac surgery remains a controversial practice, and few studies have specifically assessed the value of this approach in pediatric patients. This study therefore sought to explore the safety and efficacy of prophylactic levosimendan administration to pediatric patients as a means of preventing low cardiac output syndrome (LCOS) based upon hemodynamic, biomarker, and pharmacokinetic readouts.MethodsThis was a single-center, double-blind, randomized, placebo-controlled trial. Patients ≤ 48 months old were enrolled between July 2018 and April 2019 and were randomly assigned to groups that received either placebo or levosimendan infusions for 48 h post-surgery, along with all other standard methods of care. LCOS incidence was the primary outcome of this study.ResultsA total of 187 patients were enrolled, of whom 94 and 93 received levosimendan and placebo, respectively. LCOS incidence did not differ significantly between the levosimendan and placebo groups (10 [10.6%] versus 18 [19.4%] patients, respectively; 95% confidence interval [CI] 0.19–1.13; p = 0.090) nor did 90-day mortality (3 [3.2%] versus 4 [4.3%] patients, CI 0.14–3.69, p = 0.693), duration of mechanical ventilation (median, 47.5 h and 39.5 h, respectively; p = 0.532), ICU stay (median, 114.5 h and 118 h, respectively; p = 0.442), and hospital stay (median, 20 days and 20 days, respectively; p = 0.806). The incidence of hypotension and cardiac arrhythmia did not differ significantly between the groups. Levels of levosimendan fell rapidly without any plateau in plasma concentrations during infusion. A multiple logistic regression indicated that randomization to the levosimendan group was a predictor of LCOS.ConclusionsProphylactic levosimendan administration was safe in pediatric patients and had some benefit to postoperative hemodynamic parameters, but failed to provide significant benefit with respect to LCOS or 90-day mortality relative to placebo.Trial registrationName of the registry: Safety evaluation and therapeutic effect of levosimendan on the low cardiac output syndrome in patients after cardiopulmonary bypass. Trial registration number: ChiCTR1800016594. Date of registration: 11 June 2018. URL of trial registry record: http://www.chictr.org.cn/index.aspx

BACKGROUND: Non-destructive determination of the internal quality of fruit with a thick rind and of a large size is always difficult and challenging. To investigate the feasibility of the dielectric spectroscopy technique with respect to determining the sugar content of melons during the postharvest stage, three cultivars of melon samples (160 melons for each cultivar) were used to acquire dielectric spectra over the frequency range 20-4500 MHz. The three cultivars of melons were divided separately into a calibration set and a prediction set in a ratio of 3:1 by a joint x-y distance algorithm. Partial least squares (PLS) and extreme learning machine (ELM) methods were applied to develop individual-cultivar and multi-cultivar models based on full frequencies (FFs) and effective dielectric frequencies (EDFs) selected by the successive projection algorithm (SPA). RESULTS:The results showed that ELM models demonstrated a better performance than PLS models for the same input dielectric variables. Most of the models built based on the EDFs selected by SPA had a slightly worse performance compared to those based on FFs. For both PLS and ELM methods, the models for multi-cultivars demonstrated a worse calibration and prediction performance compared to those for individual cultivars. When individual-cultivar and multi-cultivar samples were used to build sugar content determination models, the best model was FFs-ELM (R p = 0.887, RMSEP = 0.986), FFs-ELM (R p = 0.870, RMSEP = 1.028), FFs-PLS (R p = 0.882, RMSEP = 1.010) and FFs-ELM (R p = 0.849, RMSEP = 1.085) for 'Hongyanliang', 'Xinzaomi', 'Manao' and multi-cultivar melons, respectively. CONCLUSION: The present study indicates that it is possible to develop both individual-cultivar and multi-cultivar models for determining the sugar content of melons based on the dielectric spectroscopy technique.

Nondestructive evaluation of the internal quality of pears during maturation is helpful to instruct production and give advice on harvesting. This study explores the feasibility of predicting the soluble solids content (SSC), firmness, and moisture content (MC) of pears during maturation stage using near-infrared (NIR) spectroscopy. The NIR spectra of 185 "Longxiang" pears were obtained in the wavelength range of 833-2500 nm. Partial least square (PLS) and least squares support vector machine (LSSVM) were used to develop determination models. The LSSVM obtained better performance than PLS, among which the FS-LSSVM model had the best prediction

Early detection of bruising is one of the major challenges in postharvest quality sorting processes for pears. In this study, visible/near infrared (VIS/NIR) hyperspectral imaging technology (400–1000 nm) was used to rapidly detect the type of damage and the time period (1, 12, and 24 h) for damage to pears. Spectral images of nonbruised pears and pears subject to mechanical collision and compression bruises were acquired for three different time periods (1, 12, and 24 h), and the average spectrum was calculated for modeling. After analyzing and processing the spectral data obtained for the samples, principal component analysis (PCA) and uninformative variable elimination (UVE) were used to select optimum wavelengths, and an extreme learning machine (ELM) and support vector machine (SVM) were used to build the classification model. Then, the classification results were compared with the genetic algorithm-sooty tern optimization algorithm-support vector machine (STOA-GA-SVM). The accuracy of the PCA-ELM, UVE-ELM, PCA-SVM and UVE-SVM calibration and validation sets is determined to be 98.99%, 89.29%, 98.98%, 87.97%, 96.94%, and 88.78% and 99.23% and 88.78%, respectively, with varying degrees of overfitting. The STOA-GA-SVM model shows the best performance, and the accuracy of the calibration set and validation set is determined to be 95.92% and 91.84%, respectively. This study shows that the use of the VIS/NIR hyperspectral imaging technique combined with the STOA-GA-SVM algorithm is feasible for the rapid and nondestructive identification of the damage type and time for pears.