Biodegradation of low-density polyethylene by mixed fungi composed of Alternaria sp. and Trametes sp. isolated from landfill sites.

With the development of industry and modern manufacturing, nondegradable low-density polyethylene (LDPE) has been widely used, posing a rising environmental hazard to natural ecosystems and public health. In this study, we isolated a series of LDPE-degrading fungi from landfill sites and carried out LDPE degradation experiments by combining highly efficient degrading fungi in pairs. The results showed that the mixed microorganisms composed of Alternaria sp. CPEF-1 and Trametes sp. PE2F-4 (H-3 group) had a greater degradation effect on heat-treated LDPE (T-LDPE). After 30 days of inoculation with combination strain H-3, the weight loss rate of the T-LDPE film was approximately 154% higher than that of the untreated LDPE (U-LDPE) film, and the weight loss rate reached 0.66 ± 0.06%. Environmental scanning electron microscopy (ESEM) and Fourier transform infrared spectroscopy (FTIR) were used to further investigate the biodegradation impacts of T-LDPE, including the changes on the surface and depolymerization of the LDPE films during the fungal degradation process. Our findings revealed that the combined fungal treatment is more effective at degrading T-LDPE than the single strain treatment, and it is expected that properly altering the composition of the microbial community can help lessen the detrimental impact of plastics on the environment.

Epigenetic therapy potentiates transposable element transcription to create tumor-enriched antigens in glioblastoma cells.

Inhibiting epigenetic modulators can transcriptionally reactivate transposable elements (TEs). These TE transcripts often generate unique peptides that can serve as immunogenic antigens for immunotherapy. Here, we ask whether TEs activated by epigenetic therapy could appreciably increase the antigen repertoire in glioblastoma, an aggressive brain cancer with low mutation and neoantigen burden. We treated patient-derived primary glioblastoma stem cell lines, an astrocyte cell line and primary fibroblast cell lines with epigenetic drugs, and identified treatment-induced, TE-derived transcripts that are preferentially expressed in cancer cells. We verified that these transcripts could produce human leukocyte antigen class I-presented antigens using liquid chromatography with tandem mass spectrometry pulldown experiments. Importantly, many TEs were also transcribed, even in proliferating nontumor cell lines, after epigenetic therapy, which suggests that targeted strategies like CRISPR-mediated activation could minimize potential side effects of activating unwanted genomic regions. The results highlight both the need for caution and the promise of future translational efforts in harnessing treatment-induced TE-derived antigens for targeted immunotherapy.

A machine learning model to predict liver-related outcomes after the functional cure of chronic hepatitis B.

BACKGROUND & AIMS: The risk of hepatocellular carcinoma (HCC) and hepatic decompensation persists after hepatitis B surface antigen (HBsAg) seroclearance. This study aimed to develop and validate a machine learning model to predict the risk of liver-related outcomes (LROs) following HBsAg seroclearance. METHODS: A total of 4,787 consecutive patients who achieved HBsAg seroclearance between 2000 and 2022 were enrolled from 6 centers in South Korea and a territory-wide database in Hong Kong, comprising the training (n=944), internal validation (n=1,102), and external validation (n=2,741) cohorts. Three machine learning-based models were developed and compared in each cohort. The primary outcome was the development of any LRO, including HCC, decompensation, and liver-related death. RESULTS: During a median follow-up of 55.2 (interquartile range=30.1-92.3) months, 123 LROs were confirmed (1.1%/person-year) in the Korean cohort. A model with the best predictive performance in the training cohort was selected as the final model (designated as PLAN-B-CURE), which was constructed using a gradient boosting algorithm and 7 variables (age, sex, diabetes, alcohol consumption, cirrhosis, albumin, and platelet count). Compared to previous HCC prediction models, PLAN-B-CURE showed significantly superior accuracy in the training cohort (c-index: 0.82 vs. 0.63-0.70, all P<0.001; area under the receiver operating characteristic curve: 0.86 vs. 0.62-0.72, all P<0.01; area under the precision-recall curve: 0.53 vs. 0.13-0.29, all P<0.01). PLAN-B-CURE showed a reliable calibration function (Hosmer-Lemeshow test P>0.05) and these results were reproduced in the internal and external validation cohorts. CONCLUSION: This novel machine learning model consisting of 7 variables provides reliable risk prediction of LRO after HBsAg seroclearance that can be used for personalized surveillance.

Relationship between short-term ozone exposure, cause-specific mortality, and high-risk populations: A nationwide, time-stratified, case-crossover study.

BACKGROUND: Previous studies reported that short-term exposure to ground-level ozone is associated with mortality risk. However, due to the limited monitored areas, existing studies were limited in assessing the nationwide risk and suggesting specific vulnerable populations to the ozone-mortality risk. METHODS: We performed a nationwide time-stratified case-crossover study to evaluate the association between short-term ozone and cause-specific mortality in South Korea (2015-2019). A machine learning-ensemble prediction model (a test R2 > 0.96) was used to assess the short-term ozone exposure. Stratification analysis was conducted to examine the high-risk populations, and the excess mortality due to non-compliance with the WHO guideline was also assessed. RESULTS: For all-cause mortality (1,343,077 cases), the risk associated with ozone (lag0- 1) was weakly identified (odd ratio: 1.005 with 95% CI: 0.997-1.014), and the risk was prominent in mortality with circulatory system diseases. In addition, based on the point estimates, the ozone-mortality risk was higher in people aged less than 65y, and this pattern was also observed in circulatory system disease deaths and urban areas. CONCLUSIONS: This study provides national estimates of mortality risks associated with short-term ozone. Results showed that the benefits of stricter air quality standards could be greater in vulnerable populations.

Impact of Fat Mass on Osteoporosis, Sarcopenia, and Osteosarcopenia in Peritoneal Dialysis Patients.

INTRODUCTION: The relationship between fat mass and osteoporosis, sarcopenia and osteosarcopenia is complex. While higher fat mass generally has a negative impact on bone and muscle health in the general population, the impact in peritoneal dialysis (PD) patients is less well understood. METHODS: In this study of 359 PD patients, sarcopenia was identified using appendicular skeletal muscle per square meter (ASM/m²), with cut-off values of <7.0 kg/m² for men and <5.5 kg/m² for women. Fat tissue index (FTI) and lean tissue index (LTI) were determined using body composition monitoring, with the lowest tertile classified as low FTI and low LTI. Bone mineral density (BMD) was measured, with a T-score below -2.5 indicating osteoporosis. RESULTS: The prevalence of osteoporosis, sarcopenia, and osteosarcopenia was 25%, 32%, and 15%, respectively. Notably, 60% of osteoporotic patients had sarcopenia, and about 45% of sarcopenic patients had osteoporosis. Patients with osteoporosis were older and had significantly lower LTI (15.3 vs. 12.7 kg/m², p<0.001) and ASM (7.3 vs. 5.8 kg/m2, p<0.001). Osteoporotic patients also had lower FTI, but this was more pronounced in men than in women. Patients with both sarcopenia and osteoporosis had the lowest LTI and FTI compared to those with only one or neither condition. Low FTI was a significant determinant for osteoporosis (OR, 2.34; 95% CI, 1.43-3.85; P = 0.001), sarcopenia (OR, 2.91; 95% CI, 1.82-4.64; P < 0.001), and osteosarcopenia (OR, 2.34; 95% CI, 1.30-4.24; P = 0.005) in univariate analysis, and these associations remained significant after adjustment for age and body mass index. CONCLUSION: Osteoporosis and sarcopenia are common and interrelated in PD patients. Low fat mass, but not normal/high fat mass, was significantly associated with these conditions, suggesting the importance of maintaining adequate fat mass in PD patients.

Prediction of intraoperative hypotension using deep learning models based on non-invasive monitoring devices.

PURPOSE: Intraoperative hypotension is associated with adverse outcomes. Predicting and proactively managing hypotension can reduce its incidence. Previously, hypotension prediction algorithms using artificial intelligence were developed for invasive arterial blood pressure monitors. This study tested whether routine non-invasive monitors could also predict intraoperative hypotension using deep learning algorithms. METHODS: An open-source database of non-cardiac surgery patients ( https://vitadb.net/dataset ) was used to develop the deep learning algorithm. The algorithm was validated using external data obtained from a tertiary Korean hospital. Intraoperative hypotension was defined as a systolic blood pressure less than 90 mmHg. The input data included five monitors: non-invasive blood pressure, electrocardiography, photoplethysmography, capnography, and bispectral index. The primary outcome was the performance of the deep learning model as assessed by the area under the receiver operating characteristic curve (AUROC). RESULTS: Data from 4754 and 421 patients were used for algorithm development and external validation, respectively. The fully connected model of Multi-head Attention architecture and the Globally Attentive Locally Recurrent model with Focal Loss function were able to predict intraoperative hypotension 5 min before its occurrence. The AUROC of the algorithm was 0.917 (95% confidence interval [CI], 0.915-0.918) for the original data and 0.833 (95% CI, 0.830-0.836) for the external validation data. Attention map, which quantified the contributions of each monitor, showed that our algorithm utilized data from each monitor with weights ranging from 8 to 22% for determining hypotension. CONCLUSIONS: A deep learning model utilizing multi-channel non-invasive monitors could predict intraoperative hypotension with high accuracy. Future prospective studies are needed to determine whether this model can assist clinicians in preventing hypotension in patients undergoing surgery with non-invasive monitoring.

The Necroptosis Pathway Is Upregulated in the Cornea in Mice With Ocular Graft-Versus-Host Disease.

Purpose: To identify molecular signatures specific for ocular graft-versus-host disease (GVHD) by proteomic analysis of corneas from mice with GVHD. Methods: We identified differentially expressed proteins (DEPs) in corneal samples from GVHD model mice and syngeneic control mice 4 weeks after bone marrow transplantation. Data-independent acquisition analysis was performed on individual samples, and the roles of DEPs in biological pathways related to GVHD were evaluated via bioinformatics and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses. Results: Three important signaling pathways were upregulated in the cornea in mice with GVHD: (1) the necroptosis pathway, (2) the mitogen-activated protein kinase (MAPK) pathway, and (3) as previously reported, the neutrophil extracellular trap (NET) pathway. In those signaling pathways, we identified new upregulated molecules, including (1) receptor-interacting protein kinase 1 (RIPK1), RIPK3, interferon regulatory factor 9, the interferon-induced double-stranded RNA-activated protein kinase lipoxygenase, and high mobility group box1 (HMGB1) which are damage-associated molecular patterns (DAMPs) in the necroptosis pathway; (2) the sequentially upregulated interleukin 1 (IL-1) receptor-associated kinase (IRAK), an evolutionarily conserved signaling intermediate in the Toll pathway (ECSIT), and p38, which is downstream of the IL-1 receptor and increased CDC42/Rac (Rac2), a Rho family GTPase in the MAPK pathway; and (3) the integrin components CR3 and macrophage-1 antigen (MAC-1), which are DAMPs, and the pyroptosis-related protein gasdermin D (GSDMD) in the NET pathway. Conclusions: These novel molecules may help researchers elucidate the pathogenesis of GVHD and identify new therapeutic targets for corneal changes in patients with ocular GVHD.

Territories of Nerve Endings of the Medial Plantar Nerve within the Abductor Hallucis Muscle: Clinical Implications for Potential Pain Management.

This study aimed to elucidate the intramuscular distribution pattern of the medial plantar nerve and determine its motor nerve ending territories within the abductor hallucis muscle using modified Sihler's staining and external anatomical landmarks. The study included 40 specimens of the abductor hallucis muscle (13 men and seven women) from formalin-fixed (ten cadavers) and fresh cadavers (ten cadavers), with a mean age of 77.6 years. The entry point of the medial plantar nerve into the muscle was examined, followed by Sihler's staining to analyze the intramuscular distribution pattern and motor nerve ending location within the abductor hallucis muscle. Ultrasound- and palpation-guided injections were performed to verify the applicability of motor nerve ending location-based injections. The areas with the highest concentrations of nerve entry points and nerve endings were identified in the central portion of the muscle. Ultrasound- and palpation-guided injections were safely positioned near the densest nerve ending region of the muscle. These detailed anatomical data and injection methods would be beneficial for proceeding with safe and effective injection treatments using various analgesic agents to alleviate abductor hallucis muscle-associated pain disorders.

Machine-learning model to predict the tacrolimus concentration and suggest optimal dose in liver transplantation recipients: a multicenter retrospective cohort study.

Titrating tacrolimus concentration in liver transplantation recipients remains a challenge in the early post-transplant period. This multicenter retrospective cohort study aimed to develop and validate a machine-learning algorithm to predict tacrolimus concentration. Data from 443 patients undergoing liver transplantation between 2017 and 2020 at an academic hospital in South Korea were collected to train machine-learning models. Long short-term memory (LSTM) and gradient-boosted regression tree (GBRT) models were developed using time-series doses and concentrations of tacrolimus with covariates of age, sex, weight, height, liver enzymes, total bilirubin, international normalized ratio, albumin, serum creatinine, and hematocrit. We conducted performance comparisons with linear regression and populational pharmacokinetic models, followed by external validation using the eICU Collaborative Research Database collected in the United States between 2014 and 2015. In the external validation, the LSTM outperformed the GBRT, linear regression, and populational pharmacokinetic models with median performance error (8.8%, 25.3%, 13.9%, and - 11.4%, respectively; P < 0.001) and median absolute performance error (22.3%, 33.1%, 26.8%, and 23.4%, respectively; P < 0.001). Dosing based on the LSTM model's suggestions achieved therapeutic concentrations more frequently on the chi-square test (P < 0.001). Patients who received doses outside the suggested range were associated with longer ICU stays by an average of 2.5 days (P = 0.042). In conclusion, machine learning models showed excellent performance in predicting tacrolimus concentration in liver transplantation recipients and can be useful for concentration titration in these patients.

Prediction for Perioperative Stroke Using Intraoperative Parameters.

BACKGROUND: Perioperative stroke is a severe complication following surgery. To identify patients at risk for perioperative stroke, several prediction models based on the preoperative factors were suggested. Prediction models often focus on preoperative patient characteristics to assess stroke risk. However, most existing models primarily base their predictions on the patient's baseline characteristics before surgery. We aimed to develop a machine-learning model incorporating both pre- and intraoperative variables to predict perioperative stroke. METHODS AND RESULTS: This study included patients who underwent noncardiac surgery at 2 hospitals with the data of 15 752 patients from Seoul National University Hospital used for development and temporal internal validation, and the data of 449 patients from Boramae Medical Center used for external validation. Perioperative stroke was defined as a newly developed ischemic lesion on diffusion-weighted imaging within 30 days of surgery. We developed a prediction model composed of pre- and intraoperative factors (integrated model) and compared it with a model consisting of preoperative features alone (preoperative model). Perioperative stroke developed in 109 (0.69%) patients in the Seoul National University Hospital group and 11 patients (2.45%) in the Boramae Medical Center group. The integrated model demonstrated superior predictive performance with area under the curve values of 0.824 (95% CI, 0.762-0.880) versus 0.584 (95% CI, 0.499-0.667; P<0.001) in the internal validation; and 0.716 (95% CI, 0.560-0.859) versus 0.505 (95% CI, 0.343-0.654; P=0.018) in the external validation, compared to the preoperative model. CONCLUSIONS: We suggest that incorporating intraoperative factors into perioperative stroke prediction models can improve their accuracy.

Can ultrasonography be used to differentiate parathyroid masses abutting the thyroid gland from thyroid masses extending into the parathyroid area?

AIM: To determine the ultrasonographic (US) features that could help to distinguish between parathyroid masses abutting the thyroid gland and thyroid masses extending into the parathyroid area. MATERIALS AND METHODS: Two blinded readers retrospectively evaluated the US images of 76 histopathologically confirmed parathyroid masses abutting the thyroid gland and 34 thyroid masses extending into the parathyroid area. Maximal diameter, transverse diameter/anterior-posterior diameter (T/AP) ratio, longitudinal diameter/AP diameter (L/AP) ratio, margin, shape, echogenicity, echotexture, and echogenic interface were evaluated and compared between the two groups. RESULTS: Echogenic interface (p<0.001) and L/AP ratio (p<0.001) were statistically significant US features that differentiated parathyroid and thyroid masses. Other US features did not show any significant differences between the two groups. Interobserver agreement was excellent for all US features. Sensitivity/specificity of the presence of echogenic interface and L/AP ratio >2.0 were 85.5%/100% and 43.2%/82.4% in distinguishing parathyroid from thyroid masses, respectively. CONCLUSION: The presence of an echogenic interface and L/AP ratio >2.0 were useful US features for differentiating parathyroid masses abutting the thyroid gland from thyroid masses extending into theparathyroid area.

Ultrasound-Guided Botulinum Neurotoxin Injection for Alleviating Cricopharyngeus Muscle Spasticity: A Cadaveric Feasibility Study with Nerve Ending Analysis.

Botulinum neurotoxin (BNT) injection into the cricopharyngeus muscle (CPM) under ultrasound (US) guidance is a minimally invasive technique performed to relieve cricopharyngeal dysphagia by reducing CPM spasticity. This technique is basically accessible only to both lateral sides of the CPM. This cadaveric study aimed to evaluate whether US-guided injection could effectively deliver BNT to abundant areas of gross nerve endings within the CPM. We utilized a newly modified Sihler's staining method to identify regions with abundant neural endings within the CPM while preserving the three-dimensional morphology of the muscle in 10 sides of 5 fresh cadavers. A mixture of 0.2 mL dye was injected into the 16 sides of CPM under US guidance in 8 cadavers. Nerve endings were abundant in posterolateral areas of the CPM; the injected dye was identified at the posterolateral area on 12 sides (12/16 side, 75%) without diffusion into the posterior cricoarytenoid muscle. The injection failed on four sides (two sides of the prevertebral fascia and two sides of the esophagus below the CPM). These results suggest that US-guided injection could be a feasible technique as it can deliver BNT to the most abundant nerve distribution areas within the CPM in most cases.

Antagonistic Efficacy of Symbiotic Bacterium Xenorhabdus sp. SCG against Meloidogyne spp.

The inhabitation and parasitism of root-knot nematodes (RKNs) can be difficult to control, as its symptoms can be easily confused with other plant diseases; hence, identifying and controlling the occurrence of RKNs in plants remains an ongoing challenge. Moreover, there are only a few biological agents for controlling these harmful nematodes. In this study, Xenorhabdus sp. SCG isolated from entomopathogenic nematodes of genus Steinernema was evaluated for nematicidal effects under in vitro and greenhouse conditions. The cell-free filtrates of strain SCG showed nematicidal activity against Meloidogyne species J2s, with mortalities of > 88% at a final concentration of 10%, as well as significant nematicidal activity against the three other genera of plant-parasitic nematodes in a dose-dependent manner. Thymine was isolated as active compounds by assay-guided fractionation and showed high nematicidal activity against M. incognita. Greenhouse experiments suggested that cell-free filtrates of strain SCG efficiently controlled the nematode population in M. incognita-infested tomatoes (Solanum lycopersicum L., cv. Rutgers). In addition, a significant increase in host plant growth was observed after 45 days of treatment. To our knowledge, this is the first to demonstrate the nematicidal activity spectrum of isolated Xenorhabdus species and their application to S. lycopersicum L., cv. Rutgers under greenhouse conditions. Xenorhabdus sp. SCG could be a promising biological nematicidal agent with plant growth-enhancing properties.

A Power-Efficient Envelope-Detector-Less Amplitude-Shift-Keying Forward Telemetry for Wirelessly Powered Biomedical Devices.

This paper proposes an envelope-detector-less (EDL) amplitude-shift-keying (ASK) forward telemetry (FT) demodulator for wireless power/data transfer (WPDT) systems. The EDL ASK FT demodulator can substitute bulky and power-hungry components, which are an envelope detector and an analog comparator in the conventional ASK FT demodulator, with a digital controller, reducing both power dissipation and chip area. The proposed demodulator shares the gate control signals of pass transistors, which are used in an ac-dc regulator for wireless power reception, to maintain a constant load voltage while efficiently demodulating the forward telemetry data. Also, a proposed digital cleaner in the EDL demodulator refines this control signal into a wide pulse without suffering from resonant frequency noise, while a synchronizer can align its frequency with the data rate and resonant frequency. The 0.25-µm CMOS prototype chip of the proposed power-path-less EDL ASK FT demodulator, equipped with the ac-dc regulator, demonstrates a significant 38.2% reduction in power dissipation compared to the conventional ASK FT demodulator. Moreover, the EDL ASK FT demodulator occupies only 0.023-mm2 silicon area and achieves a low bit error rate (BER) less than 10-4 while maintaining a regulated voltage of 4.5 V on the load.

Risk factor analysis and clinical experience of treating capsular contracture after prepectoral implant-based breast reconstruction.

Background: Capsular contracture is one of the most common and severe complications after implant-based breast reconstruction. Recently, prepectoral implant-based breast reconstruction using acellular dermal matrix (ADM) has become an alternative to subpectoral implant-based reconstruction. However, risk factors for capsular contracture associated with recent prepectoral reconstruction trends are not well refined yet. Thus, the aim of this study was to determine risk factors for capsular contracture, and share our experience of treating capsular contracture in prepectoral reconstruction. Methods: This retrospective comparative study focused on 110 patients who underwent prepectoral implant-based breast reconstruction with ADM. Risk factors of capsular contracture were analyzed by comparing a capsular contracture group (27 cases) and a non-capsular contracture group (83 cases). Secondary treatment after capsular contracture development was analyzed in capsular contracture group. Results: According to univariate and multivariate analyses of risk factors for capsular contracture, single staged implant-based reconstruction (direct-to-implant), infection, and postoperative radiotherapy were significantly related to the development of capsular contracture. Also, surgical intervention including capsulectomy and capsulotomy with implant change showed a significant higher remission rate than other groups. Conclusions: Our study provides insights into risk factors and treatment choices for capsular contracture after prepectoral implant-based breast reconstruction with ADM. These findings can aid selection of patients, postoperative care and preventative treatment before reconstruction.

Capabilities of satellite Geostationary Environment Monitoring Spectrometer (GEMS) NO2 data for hourly ambient NO2 exposure modeling.

The Geostationary Environment Monitoring Spectrometer (GEMS) is the world's first geostationary instrument that monitors hourly gaseous air pollutant levels, including nitrogen dioxide (NO2). Using the first-of-its-kind capabilities of GEMS NO2 data, we examined how well GEMS NO2 levels can explain the spatiotemporal variabilities in hourly NO2 concentrations in the Republic of Korea for the year 2022. A correlation analysis between hourly GEMS NO2 levels and ground NO2 concentrations showed a higher spatial correlation [Pearson r = 0.56 (SD = 0.20)] than a temporal one [Pearson r = 0.42 (SD = 0.14)], on average. To take advantage of the enhanced spatial predictability of GEMS NO2 data, we employed a mixed effects model to allow hour-specific relationships between GEMS NO2 and NO2 concentrations on a given day in each region and subsequently estimated hourly NO2 concentrations in all urban and rural areas. The 10-fold cross validation demonstrated R2 = 0.72, mean absolute error (MAE) = 3.7 ppb, and root mean squared error (RMSE) = 5.5 ppb. The hourly variations of the relationships were attributed particularly to those of wind speed among meteorological parameters considered in this study. The spatial distributions of hourly estimated NO2 concentrations were highly correlated between hours [average r = 0.91 (SD = 0.06)]. Nonetheless, they represented the diurnal patterns of urban versus rural NO2 contrasts during the day [urban/rural NO2 ratios from 1.22 (5 p.m.) to 1.37 (12 p.m.)]. The newly retrieved GEMS NO2 data enable temporally as well as spatially resolved NO2 exposure assessment. In combination with the time-activity patterns of individual subjects, the GEMS NO2 data can generate 'sub-population' exposure estimates and therefore enhance health effect studies.

Corrigendum: Localization of hyperpolarization-activated cyclic nucleotide-gated channels in the vertebrate retinas across species and their physiological roles.

[This corrects the article DOI: 10.3389/fnana.2024.1385932.].

Non-invasive prediction of massive transfusion during surgery using intraoperative hemodynamic monitoring data.

OBJECTIVE: Failure to receive prompt blood transfusion leads to severe complications if massive bleeding occurs during surgery. For the timely preparation of blood products, predicting the possibility of massive transfusion (MT) is essential to decrease morbidity and mortality. This study aimed to develop a model for predicting MT 10 min in advance using non-invasive bio-signal waveforms that change in real-time. METHODS: In this retrospective study, we developed a deep learning-based algorithm (DLA) to predict intraoperative MT within 10 min. MT was defined as the transfusion of 3 or more units of red blood cells within an hour. The datasets consisted of 18,135 patients who underwent surgery at Seoul National University Hospital (SNUH) for model development and internal validation and 621 patients who underwent surgery at the Boramae Medical Center (BMC) for external validation. We constructed the DLA by using features extracted from plethysmography (collected at 500 Hz) and hematocrit measured during surgery. RESULTS: Among 18,135 patients in SNUH and 621 patients in BMC, 265 patients (1.46%) and 14 patients (2.25%) received MT during surgery, respectively. The area under the receiver operating characteristic curve (AUROC) of DLA predicting intraoperative MT before 10 min was 0.962 (95% confidence interval [CI], 0.948-0.974) in internal validation and 0.922 (95% CI, 0.882-0.959) in external validation, respectively. CONCLUSION: The DLA can successfully predict intraoperative MT using non-invasive bio-signal waveforms.

Distinguishing discolored caries lesions using biofluorescence and dental bleaching: An in vitro simulation model study.

BACKGROUND: Distinguishing between discoloration caused by caries and organic stains is challenging for dentists in clinical settings. Biofluorescence (BF)-bleaching assesses caries lesions by evaluating BF changes after removing organic stains through dental bleaching, leaving cariogenic discoloration. This study aimed to apply BF-bleaching to a simulation model mimicking cariogenic discoloration and compare the BF color changes between organic staining and cariogenic discoloration. METHODS: Thirty artificial caries lesions in bovine incisors were equally divided into three groups: non-stained (NS), organic-stained (OS), and cariogenic-stained (CS) groups. The specimens were treated with bleaching agent, then BF color of each specimen was evaluated using red BF intensity (ΔR), BF hue angle (h°), and hyperspectral BF spectrum. RESULTS: The ΔR of CS was approximately 2.74 and 1.73 times higher than that of OS, at baseline and after bleaching for 20 min, respectively. After 20 min of bleaching, the h° of CS increased by approximately 8.1° compared to the baseline, while maintaining the red BF hue range (345‒15°). In contrast, the BF hue of OS shifted from orange (15‒45°) to yellow (45‒75°) simultaneously, and the h° change was approximately 21.9°. Both CS and OS exhibited first emission peaks near 515 nm, and CS showed second peaks in the red range (620‒780 nm). After bleaching, the first peaks were restored to the sound enamel direction (peak at 486 nm), whereas the second peaks of red BF in CS were maintained. CONCLUSION: Applying BF-bleaching to discolored caries lesions allowed differentiation between cariogenic discoloration and organic staining based on BF color changes.