Mast cell infiltration and subtype promote malignant transformation of oral precancer and progression of oral cancer.

The role of mast cell (MC), a common myeloid-derived immune cell, in the development of oral squamous cell carcinoma (OSCC) is unclear and the aim of this study was to investigate MC infiltration in oral precancer and oral cancer. Evaluation of immune cell infiltration and association with prognosis in OSCC using RNA sequencing and multiple public datasets. Multiplex immunofluorescence was used to explore the infiltration of MC in the microenvironment of OSCC and oral precancer and the interaction with CD8+ cells. The role of MC in OSCC progression was verified by in vivo experiments. The resting MC infiltration was mainly present in oral precancer, while activated MC infiltration was significantly higher in OSCC. Activated MC was associated with malignant transformation of oral precancer and poor prognosis of OSCC. In vivo studies showed that MC promoted the growth of OSCC. The infiltration of activated MC was negatively correlated with the infiltration of CD8+ T cells. The subtype of MC containing tryptase without chymase (MCT) was significantly higher in OSCC compared to oral precancer and was associated with poor survival. Furthermore, spatial distance analysis revealed a greater distance between MCT and CD8+ cells that was also linked to poor prognosis in OSCC. Cox regression analysis showed that MCT could be a potential diagnostic and prognostic biomarker. This study provides new insights into the role of MC in the immune microenvironment of OSCC. It might enhance the immunotherapeutic efficacy of OSCC through developing targeted therapies against MC.

The differences of fibrinogen levels in various types of hemorrhagic transformations.

Introduction: Hemorrhagic transformation (HT) is a serious complication that can occur spontaneously after an acute ischemic stroke (AIS) or after a thrombolytic/mechanical thrombectomy. Our study aims to explore the potential correlations between fibrinogen levels and the occurrence of spontaneous HT (sHT) and HT after mechanical thrombectomy (tHT). Methods: A total of 423 consecutive AIS patients diagnosed HT who did not undergone thrombolysis and 423 age- and sex-matched patients without HT (non-HT) were enrolled. Fibrinogen levels were measured within 24 h of admission after stroke. The cohorts were trisected according to fibrinogen levels. The HT were further categorized into hemorrhagic infarction (HI) or parenchymal hematoma (PH) based on their imaging characteristics. Results: In sHT cohort, fibrinogen levels were higher in HT patients than non-HT patients (p < 0.001 versus p = 0.002). High fibrinogen levels were associated with the severity of HT. HT patients without atrial fibrillation (AF) had higher levels of fibrinogen compared to non-HT (median 3.805 vs. 3.160, p < 0.001). This relationship did not differ among AF patients. In tHT cohort, fibrinogen levels were lower in HT patients than non-HT patients (p = 0.002). Lower fibrinogen levels were associated with the severity of HT (p = 0.004). The highest trisection of fibrinogen both in two cohorts were associated with HT [sHT cohort: OR = 2.515 (1.339-4.725), p = 0.016; that cohort: OR = 0.238 (0.108-0.523), p = 0.003]. Conclusion: Our study suggests that lower fibrinogen level in sHT without AF and higher fibrinogen level in tHT are associated with more severe HT.

ProcGCN: detecting malicious process in memory based on DGCNN.

The combination of memory forensics and deep learning for malware detection has achieved certain progress, but most existing methods convert process dump to images for classification, which is still based on process byte feature classification. After the malware is loaded into memory, the original byte features will change. Compared with byte features, function call features can represent the behaviors of malware more robustly. Therefore, this article proposes the ProcGCN model, a deep learning model based on DGCNN (Deep Graph Convolutional Neural Network), to detect malicious processes in memory images. First, the process dump is extracted from the whole system memory image; then, the Function Call Graph (FCG) of the process is extracted, and feature vectors for the function node in the FCG are generated based on the word bag model; finally, the FCG is input to the ProcGCN model for classification and detection. Using a public dataset for experiments, the ProcGCN model achieved an accuracy of 98.44% and an F1 score of 0.9828. It shows a better result than the existing deep learning methods based on static features, and its detection speed is faster, which demonstrates the effectiveness of the method based on function call features and graph representation learning in memory forensics.

Prediction of Halogenated MXenes as Electrode Materials for Halide-Ion Batteries.

Exploring and developing new rechargeable halide-ion batteries plays an important role in the advancement and growth of the ion battery family. Here, we systematically explored the feasibility of single-layer MXenes and their hydrogenated derivatives as electrode materials for halide-ion batteries via first-principles theory. The calculated results indicate that halide ions (T ions) can be stably and efficiently adsorbed on the surfaces of M2X and M2XH2, with theoretical specific capacities ranging from 227 to 497 mAh g-1. The diffusion barriers of the T ion on MXenes are from 0.55 to 0.10 eV, comparable to those of the Li ion in graphite and LiCoO2. The electronegativity of halide anions displays significant impacts on their discharge voltage plateaus on M2X, with the highest voltage up to 5.60 V for the F ion. As a comparison, the hydrogenation of M2XH2 with less surface activity raises a 2-3 V voltage reduction. All MXene-based full cells of TxTi2C|TyTi2CH2 (where x = 0-2 and y = 2-0) and TxTi2N|TyTi2NH2 (where x = 0-2 and y = 2-0) demonstrated high full battery specific energies for F-, Cl-, and Br-ion batteries, up to 462 Wh kg-1. These results demonstrate the potential of new halide-ion battery designs, paving the way for future research and innovation in battery technology.

Familial mesial temporal lobe epilepsy phenotype is associated with novel LGI1 variants: A report of two families.

OBJECTIVE: To expand the clinical phenotype and mutation spectrum of familial mesial temporal lobe epilepsy (FMTLE) and provide a new perspective for exploring the pathological mechanisms of epilepsy caused by leucine-rich glioma inactivated 1 (LGI1) variants. METHODS: We reported clinical data from two families with FMTLE and screened patients for variants in the LGI1 gene using Whole-exome sequencing and Sanger sequencing. The clinical features of FMTLE were analysed. The pathogenicity of the causative loci was assessed according to the American College of Medical Genetics and Genomics guidelines, and potential pathogenic mechanisms were predicted through multiple bioinformatics and molecular dynamics software. RESULTS: We identified two novel LGI1 truncating variants within two large families with FMTLE: LGI1 (c.1174C>T, p.Q392X) and LGI1 (c.703C>T, p.Q235X). Compared to previous reports, we found that focal to bilateral tonic-clonic seizures are a common type of seizure in FMTLE. The clinical phenotypes of patients with FMTLE caused by LGI1 variants were relatively mild, and all patients responded well to valproic acid. Bioinformatics analyses and molecular dynamics simulations showed that protein structure and interactions were considerably weakened or damaged as a result of both variants. CONCLUSION: This study presents the first report identifying LGI1 as a potential novel pathogenic gene within FMTLE families, thereby broadening the mutation spectrum associated with FMTLE. The findings of this study offer novel insights and avenues for understanding the intricate molecular mechanisms underlying LGI1 variants and their correlations with patient phenotypes. This study proposes the possibility of familial focal epilepsy syndromes overlapping.

Prognostic factors underlying the development of drug-resistant epilepsy in patients with autoimmune encephalitis: a retrospective cohort study.

OBJECTIVE: The aim of our study was to analyze the characteristics of patients with autoimmune encephalitis (AE) to identify prognostic factors associated with the development of drug-resistant epilepsy (DRE). METHODS: In this retrospective observational cohort study, we enrolled adult patients with AE between January 2016 and December 2022. The patients were categorized into two groups based on the presence or absence of DRE at the last follow-up. The predictors of the development of DRE were investigated using logistic regression analysis. RESULTS: Among 121 AE patients, 75.2% (n = 91) experienced acute symptomatic seizures, and 29.8% (n = 36) developed DRE at the last follow-up. On multivariate regression analysis, the factors associated with DRE were antibody negativity (OR 3.628, 95% CI 1.092-12.050, p = 0.035), focal seizure (OR 6.431, 95% CI 1.838-22.508, p = 0.004), refractory status epilepticus (OR 8.802, 95% CI 2.445-31.689, p = 0.001), interictal epileptiform discharges on EEG (OR 6.773, 95% CI 2.206-20.790, p = 0.001), and T2/FLAIR hyperintensity in the limbic system (OR 3.286, 95% CI 1.060-10.183, p = 0.039). CONCLUSIONS: In this study, the risk of developing DRE was mainly observed among AE patients who were negative for antibodies or had focal seizures, refractory status epilepticus, interictal epileptiform discharges on EEG, and T2/FLAIR hyperintensity in the limbic system.

A prognostic model built on amino acid metabolism patterns in HPV-associated head and neck squamous cell carcinoma.

OBJECTIVES: To compare amino acid metabolism patterns between HPV-positive and HPV-negative head and neck squamous cell carcinoma (HNSCC) patients and identify key genes for a prognostic model. DESIGN: Utilizing the Cancer Genome Atlas dataset, we analyzed amino acid metabolism genes, differentiated genes between HPV statuses, and selected key genes via LASSO regression for the prognostic model. The model's gene expression was verified through immunohistochemistry in clinical samples. Functional enrichment and CIBERSORTx analyses explored biological functions, molecular mechanisms, and immune cell correlations. The model's prognostic capability was assessed using nomograms, calibration, and decision curve analysis. RESULTS: We identified 1157 key genes associated with amino acid metabolism in HNSCC and HPV status. The prognostic model, featuring genes like IQCN, SLC22A1, SYT12, and TLX3, highlighted functions in development, metabolism, and pathways related to receptors and enzymes. It significantly correlated with immune cell infiltration and outperformed traditional staging in prognosis prediction, despite immunohistochemistry results showing limited clinical identification of HPV-related HNSCC. CONCLUSIONS: Distinct amino acid metabolism patterns differentiate HPV-positive from negative HNSCC patients, underscoring the prognostic model's utility in predicting outcomes and guiding therapeutic strategies.

A critical review of characteristics of domestic wastewater and key treatment techniques in Chinese villages.

As of 2022, China's rural sewage treatment rate is only approximately 31 %. Rapid rural development has led to higher demand. However, China's rural areas are complex and face many problems, such as uneven economic development, population distribution, and water availability. Long-lasting and low-cost wastewater treatment measures are needed for application in rural areas. The quantity and quality of rural domestic wastewater in China were characterized first. Next, the hot topic of domestic wastewater in Chinese villages was confirmed via bibliometric analysis using CiteSpace, and the treatment technologies for rural domestic wastewater were compared. Specifically, the technical status and challenges of the most common technology in rural domestic wastewater treatment, constructed wetlands, were summarized.

Digital pathology-based artificial intelligence models for differential diagnosis and prognosis of sporadic odontogenic keratocysts.

Odontogenic keratocyst (OKC) is a common jaw cyst with a high recurrence rate. OKC combined with basal cell carcinoma as well as skeletal and other developmental abnormalities is thought to be associated with Gorlin syndrome. Moreover, OKC needs to be differentiated from orthokeratinized odontogenic cyst and other jaw cysts. Because of the different prognosis, differential diagnosis of several cysts can contribute to clinical management. We collected 519 cases, comprising a total of 2 157 hematoxylin and eosin-stained images, to develop digital pathology-based artificial intelligence (AI) models for the diagnosis and prognosis of OKC. The Inception_v3 neural network was utilized to train and test models developed from patch-level images. Finally, whole slide image-level AI models were developed by integrating deep learning-generated pathology features with several machine learning algorithms. The AI models showed great performance in the diagnosis (AUC = 0.935, 95% CI: 0.898-0.973) and prognosis (AUC = 0.840, 95%CI: 0.751-0.930) of OKC. The advantages of multiple slides model for integrating of histopathological information are demonstrated through a comparison with the single slide model. Furthermore, the study investigates the correlation between AI features generated by deep learning and pathological findings, highlighting the interpretative potential of AI models in the pathology. Here, we have developed the robust diagnostic and prognostic models for OKC. The AI model that is based on digital pathology shows promise potential for applications in odontogenic diseases of the jaw.

A novel bearing current signal diagnosis method combining variational modal decomposition and improved random forests.

A new fault diagnosis approach based on bearing current signals is proposed in this paper. First, in view of strong background noise of the current signal, the variational modal decomposition method is applied to decompose the bearing current signal to obtain multiple intrinsic mode functions, and then the intrinsic mode functions are constructed as the input feature vector according to the kurtosis. Second, to avoid the influence of random forest parameters on the random forest classifier, a random forest faulty bearing diagnostic model optimized by the whale algorithm is established. Finally, the accuracy rate and confusion matrix are adopted to evaluate the prediction effects of both established and traditional models. The classification accuracy of the real damaged bearing fault type can reach 95.11%. The fault diagnosis accuracy of manually damaged bearings can reach 93.83%. The results show that the method proposed in this paper has high accuracy and good generalization ability for bearing fault diagnosis.

Genomic alterations in oral multiple primary cancers.

Oral squamous cell carcinoma (OSCC) is the predominant type of oral cancer, while some patients may develop oral multiple primary cancers (MPCs) with unclear etiology. This study aimed to investigate the clinicopathological characteristics and genomic alterations of oral MPCs. Clinicopathological data from patients with oral single primary carcinoma (SPC, n = 202) and oral MPCs (n = 34) were collected and compared. Copy number alteration (CNA) analysis was conducted to identify chromosomal-instability differences among oral MPCs, recurrent OSCC cases, and OSCC patients with lymph node metastasis. Whole-exome sequencing was employed to identify potential unique gene mutations in oral MPCs patients. Additionally, CNA and phylogenetic tree analyses were used to gain preliminary insights into the molecular characteristics of different primary tumors within individual patients. Our findings revealed that, in contrast to oral SPC, females predominated the oral MPCs (70.59%), while smoking and alcohol use were not frequent in MPCs. Moreover, long-term survival outcomes were poorer in oral MPCs. From a CNA perspective, no significant differences were observed between oral MPCs patients and those with recurrence and lymph node metastasis. In addition to commonly mutated genes such as CASP8, TP53 and MUC16, in oral MPCs we also detected relatively rare mutations, such as HS3ST6 and RFPL4A. Furthermore, this study also demonstrated that most MPCs patients exhibited similarities in certain genomic regions within individuals, and distinct differences of the similarity degree were observed between synchronous and metachronous oral MPCs.

Dynamic changes in the water and volatile compounds of chicken breast during the frying process.

The influence of frying times (0, 2, 4, 6, 8, and 10 min) on the continuous changes in the water distribution and the concentrations of key volatile compounds in chicken breast during the frying process were studied. The fried chicken samples could be distinguished by PCA of E-nose and PLS-DA of GC-MS. A total of 40 volatile compounds were identified by GC-MS, and 28 compounds were verified to be the key compounds after further screening by OAVs. The T22 was increased first and then decreased, while the M22 and M23 in fried chicken were considerably decreased and increased with increasing frying time, respectively. The content of the water and the total peak area of LF-NMR in fried chicken samples during the frying process significantly decreased, and the water was transferred from high to low degrees of freedom. In addition, water content, T21, T22, M22 and L* value were positively correlated with most alcohols and aldehydes, and were negatively correlated with pyrazines, while a*, b*, M23 and all amino acids were positively correlated with pyrazines and were negatively correlated with most alcohols and aldehydes. The results may guide the production processes of fried chicken and help produce high-quality chicken products.

Case Report: Extraocular muscles paralysis associated with GAD65 antibody: a case series study.

Objective: To explore the clinical manifestations of glutamic acid decarboxylase 65 (GAD65) antibody-positive patients with extraocular symptoms and the possible mechanism. Method: Assays for the presence of GAD65 antibodies were performed on patients' serum and cerebral spinal fluid (CSF). The brain and ocular structures involved in eye movement were assessed via magnetic resonance imaging (MRI). Tests such as electromyography (EMG), particularly repetitive nerve stimulation (RNS), and neostigmine tests were utilized for differential diagnosis. Additionally, the interaction of GAD65 antibodies with muscle tissue was confirmed using immunofluorescence techniques. Result: Each patient exhibited symptoms akin to extraocular myasthenia gravis (MG), with two individuals reporting diplopia and two experiencing ptosis. GAD65 antibodies were detected in either the serum or CSF, which were shown to bind with monkey cerebellum slides and mouse muscle slides. Neuroimaging of the brain and extraocular muscles via MRI showed no abnormalities, and all patients tested negative for the neostigmine test, RNS via EMG, and the presence of MG antibodies. However, thyroid-related antibodies were found to be abnormal in four of the patients. Conclusion: Our results showed that GAD65 antibodies are not only associated with encephalitis, cerebellum ataxia or stiff-person syndrome caused by the decrease of GABAergic transmission but also diplopia and ptosis. Therefore, we should pay more attention to extraocular muscle paralysis patients without pathogenic antibodies directed against the components of neuromuscular junctions.

Architectural and cytological features of epithelial dysplasia associated with transformation risk.

OBJECTIVES: This study explored associations between histological features of dysplasia and malignant transformation, as well as genomic copy number alterations. MATERIALS AND METHODS: Overall, 201 samples were collected from patients of oral leukoplakia. The associations of dysplastic features with malignant transformation and copy number alterations were investigated by Cox proportional hazards regression analysis and the Mann-Whitney U-test. RESULTS: Eight individual histological features, such as irregular epithelial stratification (p = 0.001), mitoses high in epithelium (p = 0.033), extension of changes along minor gland ducts (p < 0.001), etc., were associated with greater risk of malignant transformation. A model including histological features and age showed good performance for predicting malignant transformation (area under receiver operating characteristic curve: 0.806). Irregular epithelial stratification (p = 0.007), abnormal nuclear shape (p = 0.005), abnormal cell size (p = 0.004), etc. were associated with greater genomic instability. CONCLUSIONS: A Cox proportional hazards model using eight histological features and patient age reliably predicted the malignant potential of oral epithelial dysplasia. Identification of these histological features closely related to malignant transformation may aid the management of oral potentially malignant disorders and early detection of oral squamous cell carcinoma.

Head and neck carcinoma in children: A clinicopathological study of 42 cases.

Background/purpose: Cancer is an important part of the global burden of childhood diseases. Head and neck carcinoma in children is rare and related research is limited. This study aimed to investigate the clinicopathological features of childhood head and neck carcinoma. Materials and methods: Forty-two cases of childhood head and neck carcinoma treated in our institution were reviewed and analyzed. Results: Median age overall was 11 years. Twenty-three patients (54.8%) were male and 19 (45.2%) were female. Parotid gland location was most common (54.8%). Mucoepidermoid carcinoma and squamous cell carcinoma were the most common histological types (57.1% and 11.9%, respectively). Two patients had a history of bone marrow transplantation and two had a history of odontogenic keratocyst. The recurrence rate after treatment was 8.6%. Conclusion: Early diagnosis and treatment and close follow-up of childhood head and neck carcinoma are warranted to prevent recurrence and improve clinical outcome.

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Oral leukoplakia is a common precursor lesion of oral squamous cell carcinoma, which indicates a high potential of malignancy. The malignant transformation of oral leukoplakia seriously affects patient survival and quality of life; however, it is difficult to identify oral leukoplakia patients who will develop carcinoma because no biomarker exists to predict malignant transformation for effective clinical management. As a major problem in the field of head and neck pathologies, it is imperative to identify biomarkers of malignant transformation in oral leukoplakia. In this review, we discuss the potential biomarkers of malignant transformation reported in the literature and explore the translational probabilities from bench to bedside. Although no single biomarker has yet been applied in the clinical setting, profiling for genomic instability might be a promising adjunct.

Dynamic changes in the water distribution and key aroma compounds of roasted chicken during roasting.

The effects of roasting times (0, 2, 4, 6, 8, 10, 12, and 14 min) on the dynamic changes of the water distribution and key aroma compounds in roasted chicken during the electric roasting process were studied. In total, 36 volatile compounds were further determined by GC-MS and 11 compounds, including 1-octen-3-ol, 1-heptanol, hexanal, decanal, (E)-2-octenal, acetic acid hexyl ester, nonanal, 2-pentylfuran, heptanal, (E, E)-2,4-decadienal and octanal, were confirmed as key aroma compounds. The relaxation time of T22 and T23 was increased first and then decreased, while the M22 and M23 in roasted chicken were decreased and increased with increasing roasting time, respectively. The fluidity of the water in the chicken during the roasting process was decreased, and the water with a high degree of freedom migrated to the water with a low degree of freedom. In addition, the L*, a*, b*, M23 and all amino acids were positively correlated with all the key aroma compounds, while T22, M22 and moisture content were negatively correlated with all the key aroma compounds.

Isolation of Cells with Morphological and Spatial Information from Oral Submucous Fibrosis Samples by Laser Capture Microdissection.

Oral submucous fibrosis (OSF) is a common type of potentially malignant disorder in the oral cavity. The atrophy of epithelium and fibrosis of the lamina propria and the submucosa are often found on histopathological slides. Epithelial dysplasia, epithelial atrophy, and senescent fibroblasts have been proposed to be associated with the malignant transformation of OSF. However, because of the heterogeneity of potentially malignant oral disorders and oral squamous cell carcinoma, it is difficult to identify the specific molecular mechanisms of malignant transformation in OSF. Here, we present a method to obtain a small number of epithelial or mesenchymal cells carrying morphological data and spatial information by laser capture microdissection on formalin-fixed paraffin-embedded tissue slides. Using a microscope, we can precisely capture microscale (~500 cells) dysplastic or atrophic epithelial tissue and fibrotic subepithelial tissue. The extracted cells can be evaluated by genome or transcriptome sequencing to acquire genomic and transcriptomic data with morphological and spatial information. This approach removes the heterogeneity of bulk OSF tissue sequencing and the interference caused by cells in non-lesioned areas, allowing for precise spatial-omics analysis of OSF tissue.

Molecular mechanisms underlying the epigallocatechin-3-gallate-mediated inhibition of oral squamous cell carcinogenesis.

OBJECTIVES: To reveal the mechanisms underlying the epigallocatechin-3-gallate (EGCG)-mediated inhibition of carcinogenesis and the related regulatory signaling pathways. DESIGN: The effect of EGCG on the proliferation of OSCC cells was examined. SuperPred, ChEMBL, Swiss TargetPrediction, DisGeNET, GeneCards, and National Center for Biotechnology Information databases were used to predict the EGCG target genes and oral leukoplakia (OL)-related, oral submucosal fibrosis (OSF)-related, and OSCC-related genes. The binding of EGCG to the target proteins was simulated using AutoDock and PyMOL. The Cancer Genome Atlas (TCGA) dataset was subjected to consensus clustering analysis to predict the downstream molecules associated with these targets, as well as their potential functions and pathways. RESULTS: EGCG significantly inhibited OSCC cell proliferation (p < 0.001). By comparing EGCG target genes with genes linked to oral potentially malignant disorder (OPMD) and OSCC, a total of eleven potential EGCG target genes were identified. Furthermore, EGCG has the capacity to bind to eleven proteins. Based on consensus clustering and enrichment analysis, it is suggested that EGCG may hinder the progression of cancer by altering the cell cycle and invasive properties in precancerous lesions of the oral cavity. Some possible strategies for modifying the cell cycle and invasive properties may include EGCG-mediated suppression of specific genes and proteins, which are associated with cancer development. CONCLUSIONS: This study investigated the molecular mechanisms and signaling pathways associated with the EGCG-induced suppression of OSCC. The identification of specific pharmacological targets of EGCG during carcinogenesis is crucial for the development of innovative combination therapies involving EGCG.

Development of a Pathomics-Based Model for the Prediction of Malignant Transformation in Oral Leukoplakia.

Accurate prognostic stratification of oral leukoplakia (OLK) with risk of malignant transformation into oral squamous cell carcinoma is crucial. We developed an objective and powerful pathomics-based model for the prediction of malignant transformation in OLK using hematoxylin and eosin (H&E)-stained images. In total, 759 H&E-stained images from multicenter cohorts were included. A training set (n = 489), validation set (n = 196), and testing set (n = 74) were used for model development. Four deep learning methods were used to train and validate the model constructed using H&E-stained images. Pathomics features generated through deep learning combined with machine learning algorithms were used to develop a pathomics-based model. Immunohistochemical staining of Ki67, p53, and PD-L1 was used to interpret the black box of the model. Pathomics-based models predicted the malignant transformation of OLK (validation set area under curve [AUC], 0.899; testing set AUC, 0.813) and significantly identified high-risk and low-risk populations. The prediction performance of malignant transformation from dysplasia grading (validation set AUC, 0.743) was lower than that of the pathomics-based model. The expressions of Ki67, p53, and PD-L1 were correlated with various pathomics features. The pathomics-based model accurately predicted the malignant transformation of OLK and may be useful for the objective and rapid assessment of the prognosis of patients with OLK.