The pH, calcium, and phosphorus levels in the three solutions.

(A) pH values of the three solutions; (B) Calcium concentrations in the solutions; (C) Concentration of phosphorus in the three solutions. *P P P< 0.001.</p

SEM images of the surfaces of specimens from the deionized water, cola, and pomegranate juice groups.

SEM images of the surfaces of specimens from the deionized water, cola, and pomegranate juice groups.</p

The experimental flowchart.

AimDental erosion is a chemical-mechanical process that leads to the loss of dental hard tissues. This study aimed to investigate the effect of pomegranate juice on the enamel.MethodsEnamel blocks were randomly divided into three groups: deionized water, cola, and pomegranate juice. The blocks were immersed in the solutions four times a day for 14 days, and stored in artificial saliva for the remaining period. The surface hardness was measured on days 7 and 14. The surface structures of the demineralized blocks were observed via scanning electron microscopy (SEM), and the depth of demineralization was observed via confocal laser scanning microscopy (CLSM). The pH, calcium, and phosphorus levels of the three solutions were analyzed.ResultsThe microhardness values of the blocks in the pomegranate juice and cola groups decreased with the increase in the demineralization time. The blocks in the pomegranate juice group exhibited large fractures in the enamel column, whereas those in the cola group had pitted enamels with destruction of the interstitial enamel column. Compared with cola group, fluorescent penetration increased in pomegranate juice (P P P ConclusionThese findings indicate that pomegranate juice can cause enamel demineralization with an erosive potential comparable to that of cola.</div

S1 Data -

AimDental erosion is a chemical-mechanical process that leads to the loss of dental hard tissues. This study aimed to investigate the effect of pomegranate juice on the enamel.MethodsEnamel blocks were randomly divided into three groups: deionized water, cola, and pomegranate juice. The blocks were immersed in the solutions four times a day for 14 days, and stored in artificial saliva for the remaining period. The surface hardness was measured on days 7 and 14. The surface structures of the demineralized blocks were observed via scanning electron microscopy (SEM), and the depth of demineralization was observed via confocal laser scanning microscopy (CLSM). The pH, calcium, and phosphorus levels of the three solutions were analyzed.ResultsThe microhardness values of the blocks in the pomegranate juice and cola groups decreased with the increase in the demineralization time. The blocks in the pomegranate juice group exhibited large fractures in the enamel column, whereas those in the cola group had pitted enamels with destruction of the interstitial enamel column. Compared with cola group, fluorescent penetration increased in pomegranate juice (P P P ConclusionThese findings indicate that pomegranate juice can cause enamel demineralization with an erosive potential comparable to that of cola.</div

CLSM was used to detect the depth of demineralization in the enamel mass.

(A) CLSM images of the specimens after rhodamine B staining, wherein the width of the red area reflects the demineralization depth in the enamel. (B) Comparison of the demineralization depths in the specimens from the deionized water, cola, and pomegranate juice groups. *P P P < 0.001.</p

Comparison of the surface microhardness values of the specimens between the control and experimental groups at each time point (n = 10, mean ± SD).

(A) Initial microhardness value. (B) Microhardness values at day 7. (C) Microhardness values at day 14. *P P P < 0.001.</p

Image_3_Dynamic increase in myoglobin level is associated with poor prognosis in critically ill patients: a retrospective cohort study.TIFF

BackgroundMyoglobin is an important biomarker for monitoring critically ill patients. However, the relationship between its dynamic changes and prognosis remains unclear.MethodsWe retrospectively enrolled 11,218 critically ill patients from a general and surgical intensive care unit (ICU) of a tertiary hospital between June 2016 and May 2020. Patients with acute cardiovascular events, cardiac and major vascular surgeries, and rhabdomyolysis were excluded. To investigate the early myoglobin distribution, the critically ill patients were stratified according to the highest myoglobin level within 48 h after ICU admission. Based on this, the critically ill patients with more than three measurements within 1 week after ICU admission were included, and latent class trajectory modeling was used to classify the patients. The characteristics and outcomes were compared among groups. Sensitivity analysis was performed to exclude patients who had died within 72 h after ICU admission. Restricted mean survival time regression model based on pseudo values was used to determine the 28-day relative changes in survival time among latent classes. The primary outcome was evaluated with comparison of in-hospital mortality among each Trajectory group, and the secondary outcome was 28-day mortality.ResultsOf 6,872 critically ill patients, 3,886 (56.5%) had an elevated myoglobin level (≥150 ng/mL) at admission to ICU, and the in-hospital mortality significantly increased when myoglobin level exceeded 1,000 μg/mL. In LCTM, 2,448 patients were unsupervisedly divided into four groups, including the steady group (n = 1,606, 65.6%), the gradually decreasing group (n = 523, 21.4%), the slowly rising group (n = 272, 11.1%), and the rapidly rising group (n = 47, 1.9%). The rapidly rising group had the largest proportion of sepsis (59.6%), the highest median Sequential Organ Failure Assessment (SOFA) score (10), and the highest in-hospital mortality (74.5%). Sensitivity analysis confirmed that 98.2% of the patients were classified into the same group as in the original model. Compared with the steady group, the rapidly rising group and the slowly rising group were significantly related to the reduction in 28-day survival time (β = −12.08; 95% CI −15.30 to −8.86; β = −4.25, 95% CI −5.54 to −2.97, respectively).ConclusionElevated myoglobin level is common in critically ill patients admitted to the ICU. Dynamic monitoring of myoglobin levels offers benefit for the prognosis assessment of critically ill patients.</p

Table_5_Dynamic increase in myoglobin level is associated with poor prognosis in critically ill patients: a retrospective cohort study.docx

BackgroundMyoglobin is an important biomarker for monitoring critically ill patients. However, the relationship between its dynamic changes and prognosis remains unclear.MethodsWe retrospectively enrolled 11,218 critically ill patients from a general and surgical intensive care unit (ICU) of a tertiary hospital between June 2016 and May 2020. Patients with acute cardiovascular events, cardiac and major vascular surgeries, and rhabdomyolysis were excluded. To investigate the early myoglobin distribution, the critically ill patients were stratified according to the highest myoglobin level within 48 h after ICU admission. Based on this, the critically ill patients with more than three measurements within 1 week after ICU admission were included, and latent class trajectory modeling was used to classify the patients. The characteristics and outcomes were compared among groups. Sensitivity analysis was performed to exclude patients who had died within 72 h after ICU admission. Restricted mean survival time regression model based on pseudo values was used to determine the 28-day relative changes in survival time among latent classes. The primary outcome was evaluated with comparison of in-hospital mortality among each Trajectory group, and the secondary outcome was 28-day mortality.ResultsOf 6,872 critically ill patients, 3,886 (56.5%) had an elevated myoglobin level (≥150 ng/mL) at admission to ICU, and the in-hospital mortality significantly increased when myoglobin level exceeded 1,000 μg/mL. In LCTM, 2,448 patients were unsupervisedly divided into four groups, including the steady group (n = 1,606, 65.6%), the gradually decreasing group (n = 523, 21.4%), the slowly rising group (n = 272, 11.1%), and the rapidly rising group (n = 47, 1.9%). The rapidly rising group had the largest proportion of sepsis (59.6%), the highest median Sequential Organ Failure Assessment (SOFA) score (10), and the highest in-hospital mortality (74.5%). Sensitivity analysis confirmed that 98.2% of the patients were classified into the same group as in the original model. Compared with the steady group, the rapidly rising group and the slowly rising group were significantly related to the reduction in 28-day survival time (β = −12.08; 95% CI −15.30 to −8.86; β = −4.25, 95% CI −5.54 to −2.97, respectively).ConclusionElevated myoglobin level is common in critically ill patients admitted to the ICU. Dynamic monitoring of myoglobin levels offers benefit for the prognosis assessment of critically ill patients.</p

Image_4_Dynamic increase in myoglobin level is associated with poor prognosis in critically ill patients: a retrospective cohort study.TIF

BackgroundMyoglobin is an important biomarker for monitoring critically ill patients. However, the relationship between its dynamic changes and prognosis remains unclear.MethodsWe retrospectively enrolled 11,218 critically ill patients from a general and surgical intensive care unit (ICU) of a tertiary hospital between June 2016 and May 2020. Patients with acute cardiovascular events, cardiac and major vascular surgeries, and rhabdomyolysis were excluded. To investigate the early myoglobin distribution, the critically ill patients were stratified according to the highest myoglobin level within 48 h after ICU admission. Based on this, the critically ill patients with more than three measurements within 1 week after ICU admission were included, and latent class trajectory modeling was used to classify the patients. The characteristics and outcomes were compared among groups. Sensitivity analysis was performed to exclude patients who had died within 72 h after ICU admission. Restricted mean survival time regression model based on pseudo values was used to determine the 28-day relative changes in survival time among latent classes. The primary outcome was evaluated with comparison of in-hospital mortality among each Trajectory group, and the secondary outcome was 28-day mortality.ResultsOf 6,872 critically ill patients, 3,886 (56.5%) had an elevated myoglobin level (≥150 ng/mL) at admission to ICU, and the in-hospital mortality significantly increased when myoglobin level exceeded 1,000 μg/mL. In LCTM, 2,448 patients were unsupervisedly divided into four groups, including the steady group (n = 1,606, 65.6%), the gradually decreasing group (n = 523, 21.4%), the slowly rising group (n = 272, 11.1%), and the rapidly rising group (n = 47, 1.9%). The rapidly rising group had the largest proportion of sepsis (59.6%), the highest median Sequential Organ Failure Assessment (SOFA) score (10), and the highest in-hospital mortality (74.5%). Sensitivity analysis confirmed that 98.2% of the patients were classified into the same group as in the original model. Compared with the steady group, the rapidly rising group and the slowly rising group were significantly related to the reduction in 28-day survival time (β = −12.08; 95% CI −15.30 to −8.86; β = −4.25, 95% CI −5.54 to −2.97, respectively).ConclusionElevated myoglobin level is common in critically ill patients admitted to the ICU. Dynamic monitoring of myoglobin levels offers benefit for the prognosis assessment of critically ill patients.</p

Table_3_Dynamic increase in myoglobin level is associated with poor prognosis in critically ill patients: a retrospective cohort study.docx

BackgroundMyoglobin is an important biomarker for monitoring critically ill patients. However, the relationship between its dynamic changes and prognosis remains unclear.MethodsWe retrospectively enrolled 11,218 critically ill patients from a general and surgical intensive care unit (ICU) of a tertiary hospital between June 2016 and May 2020. Patients with acute cardiovascular events, cardiac and major vascular surgeries, and rhabdomyolysis were excluded. To investigate the early myoglobin distribution, the critically ill patients were stratified according to the highest myoglobin level within 48 h after ICU admission. Based on this, the critically ill patients with more than three measurements within 1 week after ICU admission were included, and latent class trajectory modeling was used to classify the patients. The characteristics and outcomes were compared among groups. Sensitivity analysis was performed to exclude patients who had died within 72 h after ICU admission. Restricted mean survival time regression model based on pseudo values was used to determine the 28-day relative changes in survival time among latent classes. The primary outcome was evaluated with comparison of in-hospital mortality among each Trajectory group, and the secondary outcome was 28-day mortality.ResultsOf 6,872 critically ill patients, 3,886 (56.5%) had an elevated myoglobin level (≥150 ng/mL) at admission to ICU, and the in-hospital mortality significantly increased when myoglobin level exceeded 1,000 μg/mL. In LCTM, 2,448 patients were unsupervisedly divided into four groups, including the steady group (n = 1,606, 65.6%), the gradually decreasing group (n = 523, 21.4%), the slowly rising group (n = 272, 11.1%), and the rapidly rising group (n = 47, 1.9%). The rapidly rising group had the largest proportion of sepsis (59.6%), the highest median Sequential Organ Failure Assessment (SOFA) score (10), and the highest in-hospital mortality (74.5%). Sensitivity analysis confirmed that 98.2% of the patients were classified into the same group as in the original model. Compared with the steady group, the rapidly rising group and the slowly rising group were significantly related to the reduction in 28-day survival time (β = −12.08; 95% CI −15.30 to −8.86; β = −4.25, 95% CI −5.54 to −2.97, respectively).ConclusionElevated myoglobin level is common in critically ill patients admitted to the ICU. Dynamic monitoring of myoglobin levels offers benefit for the prognosis assessment of critically ill patients.</p