The Effect of Hydration on Urine Color Objectively Evaluated in CIE L*a*b* Color Space

Lignocellulose based biofiller reinforced biopolymer composites from fruit peel wastes as natural pigment

In this study, the utilization of mangosteen and durian peel wastes as bio-filler and natural pigment in biopolymer of polybutyrate adipate terephthalate (PBAT) were examined. The related research work of hybridization of both mangosteen and durian peels reinforced in biopolymer as cellulose-based bio fillers and natural pigment is rarely studied. The content variation of mangosteen powder and durian powder ranged from 0 to 30 wt% with an increment of 10. The influence of mangosteen and durian powders reinforced in PBAT on color change, morphological, chemical composition, mechanical, thermal, and rheological properties were determined. Mangosteen peel and durian peel provided dark appearance for the green composites without pre-burn of these fruit peels. It can be concluded that mangosteen peel and durian peel can be used as bio pigment and natural reinforcement material in biopolymer matrix which can reduce massive waste of mangosteen and durian peel and add value to these wastes. These black biopolymer composites can be used in applications of eco-friendly food packaging and medicine zipper packaging. The overall mechanical properties, thermal stability, and dark color of mangosteen/PBAT composites were greater than those of durian/PBAT composites. However, durian/PBAT composites presented greater thermal and rheological properties than mangosteen/PBAT composites.

Effect of Natural Variation and Rootstock on Fruit Quality and Volatile Organic Compounds of 'Kiyomi tangor' (Citrus reticulata Blanco) Citrus

In this study, we compared the fruit quality and color of 'Kiyomi' (WT) and its mutant (MT) grafted on Ziyang xiangcheng (Cj) (WT/Cj, MT/Cj), and the MT grafted on Trifoliate orange (Pt) (MT/Pt). The differences in sugar, organic acid, flavonoids, phenols, and volatile substances of the three materials were also analyzed by high performance liquid chromatography (HPLC) and headspace solid-phase microextraction-gas chromatography-mass spectrometry (HS-SPME-GC-MS). The results showed significant differences in the appearance of WT/Cj, MT/Cj, and MT/Pt. MT/Pt, compared to WT/Cj, MT/Cj, had lower sugar, acid, phenol and flavonoid contents in the pulp. However, MT/Pt pulp was higher in vitamin C (VC), and the peel had significantly higher total phenol and flavonoid contents. In terms of pulp, WT/Cj had the greatest diversity of volatile organic compounds (VOCs). 4-methyl-1-pentanol was significantly higher in MT/Cj pulp, while MT/Pt pulp had a unique octanoic acid, methyl ester. VOCs were more diverse in the peels of the three materials. β-Myrcene and valencen were significantly higher in MT/Cj peels. In contrast, 16 unique VOCs were detected in MT/Pt, and D-limonene content was significantly higher than in WT/Cj and MT/Cj. The results suggest Trifoliate orange is a suitable rootstock for MT.

Extraction and characterisation of pigment from Yanzhiguo [Prunus napaulensis (Ser.) Steud.]

Yanzhiguo [Prunus napaulensis (Ser.) Steud] belongs to Rosaceae family and is consumed as wild fruit, pulp and juice. However, its potential for extracting natural pigment has not yet been explored. Herein, the components in the fresh Yanzhiguo pulp were preliminarily analyzed by liquid chromatography coupled to mass spectrometry. And, the optimal pre-treatment conditions were established for further extraction of Yanzhiguo pigment based on the a* value. Then, by combining the data from single-factor experiments and response surface methodology, the optimal extraction process was established as: 35% EtOH, a liquid-solid ratio of 200:1 mL g-1, an extraction time of 65 min, and an extraction temperature of 100 °C. Moreover, it was found that the a* value and yield had high fitness except when extracted into ethanol (EtOH) with different concentrations. Meanwhile, our result demonstrated Yanzhiguo pigment had high stability in general environments with carmine (a synthetic pigment) as control, except for extreme environments such as direct (hot) sunlight, high temperature (75 °C) and strong alkaline (pH ≥ 11). Also, Yanzhiguo pigment exhibited good antioxidant activity. Our results contribute to more information on Yanzhiguo pigment and promote its application by providing efficient extraction technology.

A lung cancer risk warning model based on tongue images

Objective: To investigate the tongue image features of patients with lung cancer and benign pulmonary nodules and to construct a lung cancer risk warning model using machine learning methods. Methods: From July 2020 to March 2022, we collected 862 participants including 263 patients with lung cancer, 292 patients with benign pulmonary nodules, and 307 healthy subjects. The TFDA-1 digital tongue diagnosis instrument was used to capture tongue images, using feature extraction technology to obtain the index of the tongue images. The statistical characteristics and correlations of the tongue index were analyzed, and six machine learning algorithms were used to build prediction models of lung cancer based on different data sets. Results: Patients with benign pulmonary nodules had different statistical characteristics and correlations of tongue image data than patients with lung cancer. Among the models based on tongue image data, the random forest prediction model performed the best, with a model accuracy of 0.679 ± 0.048 and an AUC of 0.752 ± 0.051. The accuracy for the logistic regression, decision tree, SVM, random forest, neural network, and naïve bayes models based on both the baseline and tongue image data were 0.760 ± 0.021, 0.764 ± 0.043, 0.774 ± 0.029, 0.770 ± 0.050, 0.762 ± 0.059, and 0.709 ± 0.052, respectively, while the corresponding AUCs were 0.808 ± 0.031, 0.764 ± 0.033, 0.755 ± 0.027, 0.804 ± 0.029, 0.777 ± 0.044, and 0.795 ± 0.039, respectively. Conclusion: The tongue diagnosis data under the guidance of traditional Chinese medicine diagnostic theory was useful. The performance of models built on tongue image and baseline data was superior to that of the models built using only the tongue image data or the baseline data. Adding objective tongue image data to baseline data can significantly improve the efficacy of lung cancer prediction models.

Natural Variation Confers 'Aiyuan 38' Citrus Mutant a New Color and Unique Flavor

Citrus exhibits unique nutritional values. Most citrus cultivars are derived from mutations. However, the effect of these mutations on fruit quality is unclear. We have previously found a yellowish bud mutant in the citrus cultivar 'Aiyuan 38'. Therefore, this study aimed to determine the effect of the mutation on fruit quality. 'Aiyuan 38' (WT) and a bud mutant variant (MT) were used to analyze variations in fruit color variation and flavor substances using colorimetric instruments, high-performance liquid chromatography (HPLC), headspace solid-phase microextraction-gas chromatography-mass spectrometry (HS-SPME-GC-MS), and odor activity values (OAVs). The mutation in MT conferred yellowish characteristics to its peel. Although the differences in total sugar and acid content of the pulp were not statistically significant between WT and MT, the MT glucose content was significantly lower and the malic acid level was significantly higher. HS-SPME-GC-MS analysis revealed that the MT pulp released more types and contents of volatile organic compounds (VOCs) than the WT, whereas the opposite trend was observed for the peel. Analysis of the OAV revealed that the MT pulp contains 6 unique VOCs, whereas the peel contains only 1. This study provides a useful reference for the study of flavor substances associated with citrus bud mutations.

Storing urine samples with moisture preserves urine hydration marker stability up to 21 days

INTRODUCTION

To assess hydration status, hydration markers [urine color, osmolality, and urine-specific gravity (USG)] are used. Urine color, osmolality, and USG have shown to be stable for 7, 7, and 3 days, respectively, at 4 °C. However, refrigeration could produce a dry environment which enhances evaporation and potentially affects urine hydration markers.

PURPOSE

To examine the effect of duration and moisture on urine markers with refrigeration.

METHODS

24 participants provided urine samples between 9 and 10 AM. Urine color, osmolality, and USG were analyzed within 2 h (baseline). Then, each urine sample was divided into two urine cups and placed in a storage container with (moisture condition) and without (no moisture condition) water bath at 3 °C. Hydration markers were analyzed at day 1(D1), D2, D7, D10, D14, and D21. A two-way ANOVA (time x condition) and repeated-measures ANOVA on time were performed to examine differences.

RESULTS

No significant (p > 0.05) condition x time effect was observed for urine color (p = 0.363), urine osmolality (p = 0.358), and USG (p = 0.248). When urine samples were stored in moisture condition, urine color (p = 0.126) and osmolality (p = 0.053) were stable until D21, while USG was stable until D2 (p = 0.394).

CONCLUSION

When assessing hydration status, it appears that the urine color and osmolality were stable for 21 days, while USG was stable for 2 days when stored with moisture at 3 °C. Our results provide guidelines for practitioners regarding urine storage duration and conditions when urine cannot be analyzed immediately.

Hydration monitoring and rehydration guidance system for athletes based on urine color’s L*a*b* parameters

Maintaining proper hydration is essential for athletes to sustain optimal performance and preserve their physical health. Existing studies have confirmed that urine color is one of the effective indicators for the subjective evaluation of athletes’ hydration through the urine color chart. However, the use of urine color charts to evaluate hydration is easily affected by the test environment, urine container and subjective feeling. At present, there are few hydration monitoring instruments based on quantitative analysis of urine color. In recent years, the L*a*b* color model has been widely used in the objective quantitative analysis of color. The L* value represents the luminance change from black to white, the a* value represents the chromaticity change from green to red, and the b* value represents the chromaticity change from blue to yellow. Our previous research has confirmed that the urine color b ∗ value is an effective new indicator to evaluate the hydration of athletes. The research team developed a urine hydration monitoring and rehydration guidance system based on the urine color’s L*a*b* parameters via wireless network technology and digital image technology. The hardware structure of the system is composed of a cuvette, a standard light source, a camera, an image collector, a host system, and a touch screen system. The system software is composed of functional modules, such as user information, image acquisition, image processing, and image recognition. The system operation process includes starting the system, filling in basic information, putting the sample, testing the sample, local data review, local data upload, and cloud data review. The system exhibits stable performance, a friendly operation interface, and simple and fast testing. It can objectively and accurately evaluate the hydration of athletes and provide personalized rehydration guidance. The system offers a new method for solving practical problems in sports training, and it has broad application prospects.

Validation of urine colour L*a*b* for assessing hydration amongst athletes

Objectives

Existing studies have confirmed that urine colour through a urine colour chart is one of the effective indicators for assessing hydration. In recent years, the L*a*b* colour space has been widely used in the objective quantitative analysis of colour. The L*, a* and b* values represent the luminance change from black to white, the chromaticity change from green to red and the chromaticity change from blue to yellow, respectively. This study aimed to examine the validity of the urine colour L*a*b* parameters for assessing the level of hydration amongst athletes.

Methods

The study included a total of 474 young elite athletes (251 males and 223 females, age: 24.59 ± 4.86 years). A total of 803 urine samples were collected from the subjects in various stages of hydration, including morning urine and spot urine sample during rehydration. L*a*b* parameters were measured by spectrophotometer. Hydration status was assessed via urine osmolality and urine specific gravity.

Results

Urine colour b* value has a high correlation with urine specific gravity and urine osmolality (r = 0.811, 0.741, both p < 0.01); L* value has a moderate correlation with urine specific gravity and urine osmolality (r = –0.508, –0.471, both p < 0.01); there was no significant correlation between a* value and urine specific gravity, urine osmolality (p > 0.05). Whether the diagnosis of hypohydration is based on Usg ≥ 1.020 or Uosm ≥ 700 mmol/kg: The AUC of b* values were all above 0.9 and the specificity and sensitivity of b* values were high (both greater than 80%). The AUC of both L* and a* values were less than 0.5. Whether the diagnosis of hyperhydration is based on Usg ≤ 1.010 or Uosm ≤ 500 mmol/kg: The AUC of b* values were all above 0.9 and the specificity and sensitivity of b* value were high (both greater than 90%). The AUC of both L* and a* values were less than 0.5.

Conclusion

These results suggested that the validity of urine colour b* value for assessing hydration amongst athletes was high, however, the validity of urine colour L* and a* values were low.

Validity of Urine Color Scoring Using Different Light Conditions and Scoring Techniques to Assess Urine Concentration

CONTEXT

Urine color (Uc) is used to asses urine concentration when laboratory techniques are not feasible.

OBJECTIVE

To compare the accuracy of Uc scoring using 4 light conditions and 2 scoring techniques with a 7-color Uc chart. Additionally, to assess the results' generalizability, a subsample was compared with scores obtained from fresh samples.

DESIGN

Descriptive laboratory study.

SAMPLES

A total of 178 previously frozen urine samples were scored, and 78 samples were compared with their own fresh outcomes.

MAIN OUTCOME MEASURE(S)

Urine color and accuracy for classifying urine samples were calculated using receiver operating characteristics analysis, allowing us to compare the diagnostic capacity against a 1.020 urine specific gravity cutoff and defining optimal Uc cutoff value.

RESULTS

Urine color was different among light conditions (P < .01), with the highest accuracy (80.3%) of correct classifications of low or high urine concentrations occurring at the brightest light condition. Lower light intensity scored 1.5 to 2 shades darker on the 7-color Uc scale than bright conditions (P < .001), but no further practical differences in accuracy occurred between scoring techniques. Frozen was 0.5 to 1 shade darker than freshly measured Uc (P < .004), but the values were moderately correlated (r = 0.64). A Bland-Altman plot showed that reporting bias mainly affected darker Uc without affecting the diagnostic ability of the method.

CONCLUSIONS

Urine color scoring, accuracy, and Uc cutoff values were affected by lighting condition but not by scoring technique, with greater accuracy and a 1-shade-lower Uc cutoff value at the brightest light (ie, light-emitting diode flashlight).

Urine color expressed in CIE L*a*b* colorspace during rapid changes in hydration status

Background

To investigate how rapid changes in hydration affect urine color expressed in CIE L*a*b* colorspace.

Methods

This study was a two-day crossover design where subjects (N = 30) came in one visit dehydrated, after a 15 h overnight fluid deprivation, and rapidly rehydrated by drinking at least 1000 mL of water in 2 h. On the other visit subjects reported euhydrated and then rapidly dehydrated 2% by walking (3 mph) in a heat chamber (100°F, 50% humidity) for 2 h. Urine samples on both days were collected pre- and post-dehydration/rehydration. Urine osmolality, urine specific gravity, subjective urine color and objective urine color expressed in CIE L*a*b* colorspace were measured.

Results

In the dehydration trial participants experienced a significant weight loss of approximately 2% of their starting, euhydrated body weight. The CIE urine color L*-value significantly decreased (−2.3 units) while the b*-value significantly increased (16 units). Subjective urine color significantly increased (1 unit). Urine osmolality increased (25 mmol/kg) and urine specific gravity increased (0.002 g/mL) between the pre- and post-dehydration conditions, however, neither of these changes were statistically significant. In the rehydration trial participants had a significant 1.5% increase in body weight after the ingestion of water. Significant increases were observed in the CIE urine color L*-value (7 units) and a*-value (1.1 units), while the b*-value significantly decreased (−24 units). Subjective urine color significantly decreased (−3 units). Urine osmolality (−600 mmol/kg) and urine specific gravity (−0.018 g/mL) significantly decreased between the pre- and post-rehydration conditions.

Conclusions

Traditional markers of hydration, including urine osmolality and urine specific gravity, did not significantly change in the acute dehydration trial, suggesting that these values may not be responsive to rapid changes in hydration status. However, the CIE L*- and b*-values of urine color significantly decreased in the rapid dehydration trial and significantly increased in the rapid rehydration trial. Thus, the results of the current study suggest that urine color L*- and b*-values expressed in the CIE L*a*b* colorspace were more responsive to changes in hydration status during rapid dehydration than traditional indices of urine concentration and thus may be better markers under such conditions.

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Rapid dehydration significantly increases both subjective and objective urine color.

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Rapid rehydration significantly decreases both subjective and objective urine color.

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CIE L*a*b* colorspace quantifies urine color to better assess hydration status during rapid dehydration.

Colorimetric detection of acidic pesticides in water

A water-stable, porphyrin-based metal-organic framework (MOF) produces a distinct colour change in response to acids' pK_a and concentrations. This colour change is associated with the protonation of the N-atoms within the porphyrin ligand present in the MOF structure. As a proof-of-concept, we demonstrate the use of this MOF for detecting traces of different acidic pesticides present in water samples spontaneously.

Analysis of the Distribution of Urine Color and Its Relationship With Urine Dry Chemical Parameters Among College Students in Beijing, China - A Cross-Sectional Study

Objectives: The objective of this study was to provide a new classification method by analyzing the relationship between urine color (Ucol) distribution and urine dry chemical parameters based on image digital processing. Furthermore, this study aimed to assess the reliability of Ucol to evaluate the states of body hydration and health.

Methods: A cross-sectional study among 525 college students, aged 17–23 years old, of which 59 were men and 466 were women, was conducted. Urine samples were obtained during physical examinations and 524 of them were considered valid, including 87 normal samples and 437 abnormal dry chemistry parameters samples. The urinalysis included both micro- and macro-levels, in which the CIE L^*a^*b^* values and routine urine chemical examination were performed through digital imaging colorimetry and a urine chemical analyzer, respectively.

Results: The results showed that L^* (53.49 vs. 56.69) in the abnormal urine dry chemistry group was lower than the normal group, while b^* (37.39 vs. 33.80) was greater. Urine color can be initially classified based on shade by grouping b^*. Abnormal urine dry chemical parameter samples were distributed more in the dark-colored group. Urine dry chemical parameters were closely related to Ucol. Urine specific gravity (USG), protein, urobilinogen, bilirubin, occult blood, ketone body, pH, and the number of abnormal dry chemical parameters were all correlated with Ucol CIE L^*a^*b^*; according to a stepwise regression analysis, it was determined that more than 50% of the variation in the three-color space values came from the urine dry chemical parameters, and the b^* value was most affected by USG (standardized coefficient β = 0.734, p < 0.05). Based on a receiver operating characteristic curve (ROC) analysis, Ucol ≥ 4 provided moderate sensitivity and good specificity (AUC = 0.892) for the detection of USG ≥ 1.020.

Conclusions: Our findings on the Ucol analysis showed that grouping Ucol based on b^* value is an objective, simple, and practical method. At the same time, the results suggested that digital imaging colorimetry for Ucol quantification is a potential method for evaluating body hydration and, potentially, health.

Estimates of fluid intake, urine output and hydration-levels in women from Somaliland: a cross-sectional study

The study objective was to measure fluid intake and associations with background characteristics and hydration biomarkers in healthy, free-living, non-pregnant women aged 15–69 years from Hargeisa city. We also wanted to estimate the proportion of euhydrated participants and corresponding biomarker cut-off values. Data from 136 women, collected through diaries and questionnaires, 24h urine samples and anthropometric measurements, were obtained with a cross-sectional, purposeful sampling from fifty-two school and health clusters, representing approximately 2250 women. The mean (95 % CI) 24 h total fluid intake (TFI) for all women was 2⋅04 (1⋅88, 2⋅20) litres. In multivariate regression with weight, age, parity and a chronic health problem, only weight remained a predictor (P 0.034, B 0.0156 (l/kg)). Pure water, Somali tea and juice from powder and syrup represented 49⋅3, 24⋅6 and 11⋅7 % of TFI throughout the year, respectively. Mean (95 % CI) 24 h urine volume (Uvol) was 1⋅28 (1⋅17, 1⋅39) litres. TFI correlated strongly with 24 h urine units (r 0.67) and Uvol (r 0.59). Approximately 40 % of the women showed inadequate hydration, using a threshold of urine specific gravity (Usg) of 1⋅013 and urine colour (Ucol) of 4. Five percent had Usg > 1⋅020 and concomitant Ucol > 6, indicating dehydration. TFI lower cut-offs for euhydrated, non-breast-feeding women were 1⋅77 litres and for breast-feeding, 2⋅13 litres. Euhydration cut-off for Uvol was 0⋅95 litre, equalling 9⋅2 urine units. With the knowledge of adverse health effects of habitual hypohydration, Somaliland women should be encouraged to a higher fluid intake.