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Worldwide, various types of pepper are used in food as an additive due to their unique pungency, aroma, taste, and color. This spice is valued for its pungency contributed by the alkaloid piperine and aroma attributed to volatile essential oils. The essential oils are composed of volatile organic compounds (VOCs) in different concentrations and ratios. In chromatography, the identification of compounds is done by comparing obtained peaks with a reference standard. However, there are cases where reference standards are either unavailable or the chemical information of VOCs is not documented in reference libraries. To overcome these limitations, theoretical methodologies are applied to estimate the retention indices (RIs) of new VOCs. The aim of the present work is to develop a reliable QSPR model for the RIs of 273 identified VOCs of different types of pepper. Experimental retention indices were measured using comprehensive two-dimensional gas chromatography coupled to quadrupole mass spectrometry (GC × GC/qMS) using a coupled BPX5 and BP20 column system. The inbuilt Monte Carlo algorithm of CORAL software is used to generate QSPR models using the hybrid optimal descriptor extracted from a combination of SMILES and HFG (hydrogen-filled graph). The whole dataset of 273 VOCs is used to make ten splits, each of which is further divided into four sets: active training, passive training, calibration, and validation. The balance of correlation method with four target functions i.e. TF0 (WIIC = WCII = 0), TF1 (WIIC = 0.5 & WCII = 0), TF2 (WIIC = 0 & WCII = 0.3) and TF3 (WIIC = 0.5 & WCII = 0.3) is used. The results of the statistical parameters of each target function are compared with each other. The simultaneous application of the index of ideality of correlation (IIC) and correlation intensity index (CII) improves the predictive potential of the model. The best model is judged on the basis of the numerical value of R2 of the validation set. The statistical result of the best model for the validation set of split 6 computed with TF3 (WIIC = 0.5 & WCII = 0.3) is R2 = 0.9308, CCC = 0.9588, IIC = 0.7704, CII = 0.9549, Q2 = 0.9281 and RMSE = 0.544. The promoters of increase/decrease for RI are also extracted using the best model (split 6). Moreover, the proposed model was used for an external validation set.
RESUMO
AIMS: This study aimed to compare the changes in the left ventricle (LV) and right ventricle (RV) geometry and performance after the implantation of HeartMate II (HMII) and HeartMate 3 (HM3). In addition, we investigated whether the echocardiographic parameters LV sphericity index (LVSI) and the novel pressure-dimension index (PDI) can predict post-operative right ventricular failure (RVF). METHODS AND RESULTS: Between 2012 and 2020, 46 patients [HMII (n = 22) and HM3 (n = 24)] met the study's criteria and had echocardiography tests pre-operatively, 6 and 12 months post-operatively. The LVSI and PDI were calculated together with the standard LV and RV echocardiographic parameters. The mean follow-up was 24 ± 7 months. In both groups, the LV end-diastolic diameter (LVEDD) significantly decreased 12 months post-operatively compared with the pre-operative values (HMII: 6.4 ± 1.4 cm vs. 5.7 ± 0.9 cm, P = 0.040; HM3: 6.7 ± 1.3 cm vs. 5.5 ± 0.9 cm, P < 0.01, respectively). RV function 12 months post-operatively was better in the HM3 group than in the HMII group, as indicated by a significantly higher RV fractional area change (RVFAC) in the HM3 group than in the HMII group 12 months post-operatively (35 ± 12% vs. 26 ± 16%, P = 0.039), significantly higher tricuspid annular plane systolic excursion (TAPSE) in the HM3 group 12 months post-operatively compared with the HMII group (13.9 ± 1.9 mm vs. 12.0 ± 2.1 mm, P = 0.002), and the tissue Doppler estimated tricuspid annular systolic velocity (TASV) was also significantly higher in the HM3 group 12 months post-operatively compared with the HMII group (11.5 ± 2.7 mm/s vs. 9.9 ± 1.5 mm/s, P = 0.020). The LVSI value was significantly higher 12 months post-operatively in the HMII group than in the HM3 group (1.2 ± 0.4 vs. 0.8 ± 0.2, P = 0.001, respectively), indicating worse geometric changes. The PDI decreased 12 months post-operatively in the HM3-group compared with the baseline (3.4 ± 1.4 mmHg/cm2 vs. 2.0 ± 0.8 mmHg/cm2, P < 0.001). In the univariate and multivariate analyses, only the pre-operative PDI was a predictor of post-operative RVF [odds ratio: 3.84 (95% CI: 1.53-18.16, P = 0.022)]. The area under the curve for pre-operative PDI was 0.912. The 2 year survival was significantly better in the HM3 group (log-rank, P = 0.042). CONCLUSIONS: The design of HM3 offered better geometrical preservation of the LV and enabled normal PDI values, leading to improved RV function, as indicated by better RVFAC, TAPSE, and TASV values. The use of pre-operative PDI as an additional tool for established risk scores might offer a better pre-operative predictor of RVF.
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OBJECTIVE: Considering the controversial benefits of video-assisted thoracoscopic surgery (VATS), we intended to evaluate the impact of surgical approach on cardiac function after lung resection using myocardial work analysis. METHODS: Echocardiographic data of 48 patients (25 thoracotomy vs. 23 VATS) were retrospectively analyzed. All patients underwent transthoracic echocardiography (TTE) within 2 weeks before and after surgery, including two-dimensional speckle tracking and tissue Doppler imaging. RESULTS: No notable changes in left ventricular (LV) function, assessed mainly using the LV global longitudinal strain (GLS), global myocardial work index (GMWI), and global work efficiency (GWE), were observed. Right ventricular (RV) TTE values, including tricuspid annular plane systolic excursion (TAPSE), tricuspid annular systolic velocity (TASV), right ventricular global longitudinal strain (RVGLS), and RV free-wall GLS (RVFWGLS), indicated greater RV function impairment in the thoracotomy group than in the VATS group [TAPSE(mm) 17.90 ± 3.80 vs. 21.00 ± 3.48, p = 0.006; d = 0.84; TASV(cm/s): 12.40 ± 2.90 vs. 14.70 ± 2.40, p = 0.004, d = 0.86; RVGLS(%): - 16.00 ± 4.50 vs. - 19.40 ± 2.30, p = 0.012, d = 0.20; RVFWGLS(%): - 11.50 ± 8.50 vs. - 18.31 ± 5.40, p = 0.009, d = 0.59; respectively]. CONCLUSIONS: Unlike RV function, LV function remained preserved after lung resection. The thoracotomy group exhibited greater RV function impairment than did the VATS group. Further studies should evaluate the long-term impact of surgical approach on cardiac function.