Performance Improvement of Partial Least Squares Regression Soluble Solid Content Prediction Model Based on Adjusting Distance between Light Source and Spectral Sensor according to Apple Size.

Apples are widely cultivated in the Republic of Korea and are preferred by consumers for their sweetness. Soluble solid content (SSC) is measured non-destructively using near-infrared (NIR) spectroscopy; however, the SSC measurement error increases with the change in apple size since the distance between the light source and the near-infrared sensor is fixed. In this study, spectral characteristics caused by the differences in apple size were investigated. An optimal SSC prediction model applying partial least squares regression (PLSR) to three measurement conditions based on apple size was developed. The three optimal measurement conditions under which the Vis/NIR spectrum is less affected by six apple size levels (Levels I-VI) were selected. The distance from the apple center to the light source and that to the sensor were 125 and 75 mm (Distance 1), 123 and 75 mm (Distance 2), and 135 and 80 mm (Distance 3). The PLSR model applying multiplicative scatter correction pretreatment under Distance 3 measurement conditions showed the best performance for Level IV-sized apples (Rpre2 = 0.91, RMSEP = 0.508 °Brix). This study shows the possibility of improving the SSC prediction performance of apples by adjusting the distance between the light source and the NIR sensor according to fruit size.

When should indocyanine green be assessed in colorectal surgery, and at what distance from the tissue? Quantitative measurement using the SERGREEN program.

BACKGROUND: Suture dehiscence is one of the most feared postoperative complications. Correct intestinal vascularization is essential for its prevention. Indocyanine green (ICG) is one of the methods used to assess vascularization, but this assessment is usually subjective. Our group designed the SERGREEN program to obtain an objective measurement of the degree of vascularization. We do not know how long after ICG administration the fluorescence of the tissues should be evaluated, or how far away the measurement should be performed. The aim of this study is to establish the optimal moment and distance for analyzing the fluorescence saturation of ICG. METHODS: Prospective observational study in patients undergoing elective laparoscopic colorectal surgery. The optimal time for ICG analysis was tested in a sample of 20 patients (10 right colon and 10 left colon), and the optimal distance in a sample of ten patients. ICG was administered intravenously, and colon vascularization was quantified using SERGREEN; RGB (Red, Green, Blue) encoding was used. The intensity curve of the ICG was analyzed for ten minutes after its administration. Distances of 1, 3, and 5 cm were tested. RESULTS: The intensity of fluorescence increased until 1.5 min after ICG administration (reaching figures of 112.49 in the right colon and 93.95 in the left). It then remained fairly stable until 3.5 min (98.49 in the right and 83.35 in the left), at which point it began to decrease gradually. ICG saturation was inversely proportional to the distance between the camera and the tissue. The best distance was 5 cm, where the confidence interval was narrower [CI 86.66-87.53]. CONCLUSION: The optimal time for determining ICG in the colon is between 1.5 and 3.5 min, in both right and left colon. The optimal distance is 5 cm. This information will help to establish parameters of comparison in normal and pathological situations.

Distance disintegration delineates the brain connectivity failure of Alzheimer's disease.

Alzheimer's disease (AD) is associated with brain network dysfunction. Network-based investigations of brain connectivity have mainly focused on alterations in the strength of connectivity; however, the network breakdown in AD spectrum is a complex scenario in which multiple pathways of connectivity are affected. To integrate connectivity changes that occur under AD-related conditions, here we developed a novel metric that computes the connectivity distance between cortical regions at the voxel level (or nodes). We studied 114 individuals with mild cognitive impairment, 24 with AD, and 27 healthy controls. Results showed that areas of the default mode network, salience network, and frontoparietal network display a remarkable network separation, or greater connectivity distances, from the rest of the brain. Furthermore, this greater connectivity distance was associated with lower global cognition. Overall, the investigation of AD-related changes in paths and distances of connectivity provides a novel framework for characterizing subjects with cognitive impairment; a framework that integrates the overall network topology changes of the brain and avoids biases toward unreferenced connectivity effects.