DNMT1-targeting remodeling global DNA hypomethylation for enhanced tumor suppression and circumvented toxicity in oral squamous cell carcinoma.

BACKGROUND: The faithful maintenance of DNA methylation homeostasis indispensably requires DNA methyltransferase 1 (DNMT1) in cancer progression. We previously identified DNMT1 as a potential candidate target for oral squamous cell carcinoma (OSCC). However, how the DNMT1- associated global DNA methylation is exploited to regulate OSCC remains unclear. METHODS: The shRNA-specific DNMT1 knockdown was employed to target DNMT1 on oral cancer cells in vitro, as was the use of DNMT1 inhibitors. A xenografted OSCC mouse model was established to determine the effect on tumor suppression. High-throughput microarrays of DNA methylation, bulk and single-cell RNA sequencing analysis, multiplex immunohistochemistry, functional sphere formation and protein immunoblotting were utilized to explore the molecular mechanism involved. Analysis of human samples revealed associations between DNMT1 expression, global DNA methylation and collaborative molecular signaling with oral malignant transformation. RESULTS: We investigated DNMT1 expression boosted steadily during oral malignant transformation in human samples, and its inhibition considerably minimized the tumorigenicity in vitro and in a xenografted OSCC model. DNMT1 overexpression was accompanied by the accumulation of cancer-specific DNA hypomethylation during oral carcinogenesis; conversely, DNMT1 knockdown caused atypically extensive genome-wide DNA hypomethylation in cancer cells and xenografted tumors. This novel DNMT1-remodeled DNA hypomethylation pattern hampered the dual activation of PI3K-AKT and CDK2-Rb and inactivated GSK3ß collaboratively. When treating OSCC mice, targeting DNMT1 achieved greater anticancer efficacy than the PI3K inhibitor, and reduced the toxicity of blood glucose changes caused by the PI3K inhibitor or combination of PI3K and CDK inhibitors as well as adverse insulin feedback. CONCLUSIONS: Targeting DNMT1 remodels a novel global DNA hypomethylation pattern to facilitate anticancer efficacy and minimize potential toxic effects via balanced signaling synergia. Our study suggests DNMT1 is a crucial gatekeeper regarding OSCC destiny and treatment outcome.

Fractionated irradiation induces radioresistant oral carcinoma cells with enhanced malignant phenotypes.

OBJECTIVE: The fact that certain oral carcinoma patients experience radiotherapy failure implies that a more radioresistant and aggressive phenotype of surviving cancer cells potentially occurs during treatment. Our study aimed to establish radioresistant oral cancer cells through a fractionated irradiation protocol that mimics clinically relevant radiotherapy dosing strategies and to investigate all-round alterations in the malignant phenotype. METHODS: Radioresistant oral carcinoma cells were generated by exposing Cal27 and Detroit 562 cells to 60 Gy radiation in 10 dose-escalating fractions and verified by cell immunofluorescence. Specific markers related to the epithelial-mesenchymal transition (EMT) process and the cancer stem cell (CSC) phenotype were assessed by Western blotting. Cell invasion and migration were evaluated using Matrigel-coated transwell and wound healing assays, respectively. Nontargeted metabolomics was used to mechanistically delineate the potential metabolic patterns linked to EMT and CSCs; the CSC phenotype was also examined by sphere formation assays and cell immunofluorescence. RESULTS: Radioresistant oral carcinoma cell lines were successfully established and validated. These cells exhibited enhanced EMT and increase in both cell invasion and migration. These radioresistant cells further demonstrated a high metabolic profile, notably marked by lipid metabolism reprogramming and functional enrichment of ATP-binding cassette (ABC) transporters. Consistently, enhanced CSC phenotype in radioresistant cells was confirmed by elevated expression of stemness markers and increased sphere-forming capacity. CONCLUSION: Radioresistant oral carcinoma cells subjected to fractionated radiation exhibit an augmented malignant phenotype. The metabolic characteristics linked to enhanced EMT and CSC phenotypes provide potential targets for improving radiotherapy in oral carcinoma.

The multi-dimensional challenges of controlling respiratory virus transmission in indoor spaces: Insights from the linkage of a microscopic pedestrian simulation and SARS-CoV-2 transmission model.

SARS-CoV-2 transmission in indoor spaces, where most infection events occur, depends on the types and duration of human interactions, among others. Understanding how these human behaviours interface with virus characteristics to drive pathogen transmission and dictate the outcomes of non-pharmaceutical interventions is important for the informed and safe use of indoor spaces. To better understand these complex interactions, we developed the Pedestrian Dynamics-Virus Spread model (PeDViS), an individual-based model that combines pedestrian behaviour models with virus spread models incorporating direct and indirect transmission routes. We explored the relationships between virus exposure and the duration, distance, respiratory behaviour, and environment in which interactions between infected and uninfected individuals took place and compared this to benchmark 'at risk' interactions (1.5 metres for 15 minutes). When considering aerosol transmission, individuals adhering to distancing measures may be at risk due to the buildup of airborne virus in the environment when infected individuals spend prolonged time indoors. In our restaurant case, guests seated at tables near infected individuals were at limited risk of infection but could, particularly in poorly ventilated places, experience risks that surpass that of benchmark interactions. Combining interventions that target different transmission routes can aid in accumulating impact, for instance by combining ventilation with face masks. The impact of such combined interventions depends on the relative importance of transmission routes, which is hard to disentangle and highly context dependent. This uncertainty should be considered when assessing transmission risks upon different types of human interactions in indoor spaces. We illustrated the multi-dimensionality of indoor SARS-CoV-2 transmission that emerges from the interplay of human behaviour and the spread of respiratory viruses. A modelling strategy that incorporates this in risk assessments can help inform policy makers and citizens on the safe use of indoor spaces with varying inter-human interactions.

Risk factors for avian influenza in Danish poultry and wild birds during the epidemic from June 2020 to May 2021.

Exploring the risk factors of avian influenza (AI) occurrence helps us to monitor and control the disease. Since late 2020, the number of avian influenza outbreaks in domestic and wild birds has increased in most European countries, including Denmark. This study was conducted to identify potential risk factors for wild birds and poultry during the epidemic in 2020/2021 in Denmark. Using Danish AI surveillance data of actively surveyed poultry and passively surveyed wild birds from June 2020 to May 2021, we calculated geographical attributes for bird locations and assessed the potential risk factors of AI detections using logistic regression analyses. 4% of actively surveyed poultry and 39% of passively surveyed wild birds were detected with AI circulating or ongoing at the time. Of these, 10 and 99% tested positive for the H5/H7 AI subtypes, respectively. Our analyses did not find any statistically significant risk factors for actively surveyed poultry within the dataset. For passively surveyed wild birds, bird species belonging to the Anseriformes order had a higher risk of being AI virus positive than five other taxonomic bird orders, and Galliformes were of higher risk than two other taxonomic bird orders. Besides, every 1 km increase in the distance to wetlands was associated with a 5.18% decrease in the risk of being AI positive (OR (odds ratio) 0.95, 95% CI 0.91, 0.99), when all other variables were kept constant. Overall, bird orders and distance to wetlands were associated with the occurrence of AI. The findings may provide targets for surveillance strategies using limited resources and assist in risk-based surveillance during epidemics.

Impact of obesity on outcomes after surgical stabilization of multiple rib fractures: Evidence from the US nationwide inpatient sample.

BACKGROUND: Obesity is a global health issue with increasing prevalence. Surgical procedures, such as surgical stabilization of rib fractures (SSRF), may be affected by obesity-related complications. The objective of the study is to investigate the effects of obesity on SSRF outcomes in multiple rib fractures. METHODS: This retrospective study analyzed data from adults aged ≥ 20 years in the Nationwide Inpatient Sample (NIS) database diagnosed with multiple rib fractures who underwent SSRF between 2005 and 2018. It investigated the relationship between obesity and in-patient outcomes, such as discharge status, length of stay (LOS), in-hospital mortality, hospital costs, and adverse events using logistic and linear regression analyses. RESULTS: Analysis of data from 1,754 patients (morbidly obese: 87; obese: 106; normal weight: 1,561) revealed that morbid obesity was associated with longer LOS (aBeta = 0.07, 95% CI: 0.06, 0.07), higher hospital costs (aBeta = 47.35, 95% CI: 38.55, 56.14), increased risks of adverse events (aOR = 1.63, 95% CI: 1.02, 2.61), hemorrhage/need for transfusion (aOR = 1.77, 95% CI: 1.12, 2.79) and mechanical ventilation ≥ 96 hours (aOR = 2.14, 95% CI: 1.28, 3.58) compared to normal weight patients. Among patients with flail chest, morbid obesity was significantly associated with tracheostomy (aOR = 2.13, 95% CI: 1.05, 4.32), ARDS/respiratory failure (aOR = 2.01, 95% CI: 1.09, 3.70), and mechanical ventilation ≥ 96 hours (aOR = 2.80, 95% CI: 1.47, 5.32). In contrast, morbid obesity had no significant associations with these adverse respiratory outcomes among patients without a flail chest (p > 0.05). CONCLUSIONS: Morbid obesity is associated with adverse outcomes following SSRF for multiple rib fractures, especially for flail chest patients.

DctViT: Discrete Cosine Transform meet vision transformers.

Vision transformers (ViTs) have become one of the dominant frameworks for vision tasks in recent years because of their ability to efficiently capture long-range dependencies in image recognition tasks using self-attention. In fact, both CNNs and ViTs have advantages and disadvantages in vision tasks, and some studies suggest that the use of both may be an effective way to balance performance and computational cost. In this paper, we propose a new hybrid network based on CNN and transformer, using CNN to extract local features and transformer to capture long-distance dependencies. We also proposed a new feature map resolution reduction based on Discrete Cosine Transform and self-attention, named DCT-Attention Down-sample (DAD). Our DctViT-L achieves 84.8% top-1 accuracy on ImageNet 1K, far outperforming CMT, Next-ViT, SpectFormer and other state-of-the-art models, with lower computational costs. Using DctViT-B as the backbone, RetinaNet can achieve 46.8% mAP on COCO val2017, which improves mAP by 2.5% and 1.1% with less calculation cost compared with CMT-S and SpectFormer as the backbone.

Efficient and cold-tolerant moisture-enabled power generator combining ionic diode and ionic hydrogel.

The ionic diode structure has become one of the attractive structures in the field of moisture-based power generation. However, existing devices still suffer from poor moisture trapping, low surface charge, and inefficient ion separation, resulting in low output power. Moreover, water freezes at low temperatures (<0 °C), limiting the ionic diode structure to generate electricity in cold environments. In this paper, a moisture-enabled power generator has been designed and fabricated, which assembles a negatively charged ionic hydrogel film and a positively charged anodized aluminum oxide (AAO) film to construct a heterojunction. The hydrogel polymer network is modified with a large number of sulfonate groups that dissociate to provide nanoscale pores with high surface charge to improve the rectification ratio. And the lithium chloride (LiCl) salt with high hydration ability is added to the hydrogel as a moisture-trapping and anti-freezing component. Usually salt ions reduce the Debye length, so that the ion transport is finally not controlled by the electric double layer (EDL) and the rectification fails. Interestingly, due to the natural affinity of the hydrogel polymer network for LiCl, LiCl is locked on the hydrogel side and does not easily enter the AAO pores to change the distribution of EDL within the nanochannel. As a result, the device rectification ratio is almost independent of the amount of LiCl addition, demonstrating an excellent balance of high output power and high freeze resistance. Ultimately, the device exhibits excellent power generation performance in the -20 °C to 60 °C temperature range and 15% to 93% RH humidity range. Typically, under high humidity (93% RH) at room temperature (25 °C), it provides an open-circuit voltage of 1.25 V and a short-circuit current of 300 µA cm-2, with an on-load output power of up to 71.35 µW cm-2. Under medium humidity (50% RH) at low temperature (-20 °C), it provides an open-circuit voltage of 1.11 V and a short-circuit current of 15 µA cm-2.

Electronic Structure Modulation of Fe-N4-C for Oxygen Evolution Reaction via Transition Metal Dopants and Axial Ligands.

The popular single-atom catalyst (SAC) Fe-N4 is generally believed to be an excellent oxygen reduction reaction (ORR) electrocatalyst, which is less active in the oxygen evolution reaction (OER). Herein, FeM-N6 configuration catalysts (M = Fe, Co, Ni, Cu, Ag, and Au) were constructed for the oxygen evolution reaction by embedding M dopants on Fe-N4 systems based on the density functional theory. The electronic structure analysis reveals that the Fe-M metal interactions play dominant roles in regulating the d orbital distributions of Fe sites, which in turn alter the catalytic OER performance. Subsequent thermodynamic results indicate that the potential-determining step (PDS) for all catalysts is the formation of OOH*, which exhibits a tendency of decreased overpotentials with enhanced metal interactions. Apart from these, the effects of axial ligands on the OER activity of the catalysts in practical conditions were considered. Generally, most of the axial ligands are found to be thermodynamically favorable for the OER process. Interestingly, a competitive relationship of the electrons from the d orbital of Fe sites was found between the axial ligand and the adsorbed intermediate species during the reaction, which raises the energy barrier for OH* to O* conversion and can even alter the PDS in certain cases. The present work sheds new light on the design of future high-performance OER catalysts.

Significant efficacy of short-course, low-concentration betamethasone mouthwash therapy for severe erosive oral lichen planus: a randomized controlled trial.

OBJECTIVES: To evaluate the short-term efficacy of low-concentration betamethasone mouthwash for severe erosive oral lichen planus (EOLP). MATERIALS AND METHOD: In this randomized, investigator-blind, positive-controlled trial, OLP patients with erosive lesions received betamethasone mouthwash (0.137 mg/mL) or dexamethasone mouthwash (0.181 mg/mL) three times daily for 2 or 4 weeks and were followed up for 3 months to observe recurrence. The primary outcome was the week-2 reduction in erosive area. RESULTS: Fifty-seven participants were randomized to betamethasone (n = 29) and dexamethasone (n = 28). At week 2, participants using betamethasone (n = 28) experienced a greater reduction in erosive area than gargling with dexamethasone (n = 26). Similarly, secondary outcomes, including the healing proportion of erosions, reduced pain level, reduction in atrophic area, Thongprasom score, and recurrence interval, showed the superiority of betamethasone. At week 4, betamethasone (n = 7) was not superior to dexamethasone (n = 15) in further reducing lesional area and pain level. No serious adverse events were documented. CONCLUSIONS: The 0.137 mg/mL compound betamethasone mouthwash exhibited significant efficacy in rapidly enhancing erosion healing within 2 weeks and extending the recurrence interval with a good safety profile. CLINICAL RELEVANCE: This study proved the significant efficacy of short-course 0.137 mg/mL betamethasone mouthwash therapy for treating erosion and pain, providing a novel topical agent for patients with severe EOLP. TRIAL REGISTRATION: This study was prospectively registered at the International Clinical Trials Registry Platform ( ChiCTR1800016507 ) on 5 June 2018.

Bicarbonate enhanced heterogeneous activation of peroxymonosulfate by copper ferrite nanoparticles for the efficient degradation of refractory organic contaminants in water.

Nowadays, the treatment of residual refractory organic contaminants (ROCs) is a huge challenge for environmental remediation. In this study, a potential process is provided by copper ferrite catalyst (CuFe2O4) activated peroxymonosulfate (PMS, HSO5-) in the bicarbonate (HCO3-) enhanced system for efficient removal of Acid Orange 7 (AO7), 2,4-dichlorophenol, phenol and methyl orange (MO) in water. The impact of key reaction parameters, water quality components, main reactive oxygen species (ROS), probable degradation mechanism, rational degradation pathways and catalyst stability were systematically investigated. A 95.0% AO7 (C0 = 100 mg L-1) removal was achieved at initial pH (pH0) of 5.9 ± 0.1 (natural pH), CuFe2O4 dosage of 0.15 g L-1, PMS concentration of 0.98 mM, HCO3- concentration of 2 mM, and reaction time of 30 min. Both sulfate radical (SO4-•) and hydroxyl radical (•OH) on the surface of catalyst were proved as the predominant radical species through radical quenching experiments and electron paramagnetic resonance (EPR) analysis. The buffer nature of HCO3- was partially contributed for the enhanced degradation of AO7 under CuFe2O4/PMS/HCO3- system. Importantly, according to 13C nuclear magnetic resonance (NMR) and EPR analysis, the positive effect of bicarbonate may be mainly attributed to the formation of peroxymonocarbonate (HCO4-), which may enhance the generation of •OH. The magnetic CuFe2O4 particles can be well recycled and the leaching concentration of Cu was acceptable (<1 mg L-1). Considering the widespread presence of bicarbonate in water environment, this work may provide a safe, efficient, and sustainable technique for the elimination of ROCs from practical complex wastewater.

IAnimal: a cross-species omics knowledgebase for animals.

With the exponential growth of multi-omics data, its integration and utilization have brought unprecedented opportunities for the interpretation of gene regulation mechanisms and the comprehensive analyses of biological systems. IAnimal (https://ianimal.pro/), a cross-species, multi-omics knowledgebase, was developed to improve the utilization of massive public data and simplify the integration of multi-omics information to mine the genetic mechanisms of objective traits. Currently, IAnimal provides 61 191 individual omics data of genome (WGS), transcriptome (RNA-Seq), epigenome (ChIP-Seq, ATAC-Seq) and genome annotation information for 21 species, such as mice, pigs, cattle, chickens, and macaques. The scale of its total clean data has reached 846.46 TB. To better understand the biological significance of omics information, a deep learning model for IAnimal was built based on BioBERT and AutoNER to mine 'gene' and 'trait' entities from 2 794 237 abstracts, which has practical significance for comprehending how each omics layer regulates genes to affect traits. By means of user-friendly web interfaces, flexible data application programming interfaces, and abundant functional modules, IAnimal enables users to easily query, mine, and visualize characteristics in various omics, and to infer how genes play biological roles under the influence of various omics layers.

Ionizing radiation-induced "zombie" carcinoma-associated fibroblasts with suppressed pro-radioresistance on OSCC cells.

OBJECTIVES: This study was to investigate the effect of ionizing radiation (IR) on oral carcinoma-associated fibroblasts (CAFs) and to further explore subsequent effects of IR-induced "zombie" CAFs on oral squamous cell carcinoma (OSCC) cells. MATERIALS AND METHODS: Three primary CAFs and one primary normal-associated fibroblasts (NAFs) were separated from human OSCC and normal oral mucosa tissues, identified by immunocytochemistry. Cells were exposed to IR by X-ray irradiator under different doses. The DNA damage, proliferation, and migration of irradiated CAFs were, respectively, detected by immunofluorescence and wound healing assay, while senescence was detected by ß-galactosidase staining. Finally, the effect of irradiated CAFs on biological behavior and radioresistance of Cal-27 cells were determined via assays mentioned above. RESULTS: Oral CAFs were sensitive to IR with DNA damage increasing and proliferation decreasing. 18 Gy IR could not kill oral CAFs but induce them to "zombies," with arrested proliferation, increased senescence, and reduced migration. "Zombie" CAFs (zCAFs) could enhance proliferation, migration, and invasion of Cal-27 cells, and show suppressed pro-radioresistance by reducing DNA damage and facilitating survival. CONCLUSIONS: IR-induced zCAFs could continuously promote radioresistance of OSCC cells though being suppressed, suggesting the potential promoting effect on tumor relapse post-radiotherapy that needed further exploring.

A numerically stable constrained optimal filter design method for multichannel active noise control using dual conic formulation.

In practical active noise control (ANC) applications, various constraints are usually required, for example, the disturbance enhancement constraint, the robust stability constraint, and the controller output power constraint. One commonly used approach for designing a constrained ANC filter is to formulate a constrained optimization problem using an H / H framework, which requires significant computational power to solve. Recent work has shown that such an ANC filter design problem can be reformulated into a convex optimization problem and then further reformulated to a cone programming problem to reduce the required computational time by several orders. However, the standard cone programming reformulation procedure leads to a large number of free variables, which, in many applications, can adversely influence the numerical behavior of the optimization algorithm. In the current work, the ANC filter design problem structure is exploited in its dual conic form, which allows an elimination of free variables and can result in a numerically more stable solving process for the filter design problem while keeping the noise control performance unchanged. It is demonstrated that when compared with the reformulation using the standard procedure, the proposed formulation significantly improves its numerical stability and computational efficiency.

Genomic insights into the phylogeny and biomass-degrading enzymes of rumen ciliates.

Understanding the biodiversity and genetics of gut microbiomes has important implications for host physiology and industrial enzymes, whereas most studies have been focused on bacteria and archaea, and to a lesser extent on fungi and viruses. One group, still underexplored and elusive, is ciliated protozoa, despite its importance in shaping microbiota populations. Integrating single-cell sequencing and an assembly-and-identification pipeline, we acquired 52 high-quality ciliate genomes of 22 rumen morphospecies from 11 abundant morphogenera. With these genomes, we resolved the taxonomic and phylogenetic framework that revised the 22 morphospecies into 19 species spanning 13 genera and reassigned the genus Dasytricha from Isotrichidae to a new family Dasytrichidae. Comparative genomic analyses revealed that extensive horizontal gene transfers and gene family expansion provided rumen ciliate species with a broad array of carbohydrate-active enzymes (CAZymes) to degrade all major kinds of plant and microbial carbohydrates. In particular, the genomes of Diplodiniinae and Ophryoscolecinae species encode as many CAZymes as gut fungi, and ~80% of their degradative CAZymes act on plant cell-wall. The activities of horizontally transferred cellulase and xylanase of ciliates were experimentally verified and were 2-9 folds higher than those of the inferred corresponding bacterial donors. Additionally, the new ciliate dataset greatly facilitated rumen metagenomic analyses by allowing ~12% of the metagenomic sequencing reads to be classified as ciliate sequences.

Unraveling the Electronic Effect of Transition-Metal Dopants (M = Fe, Co, Ni, and Cu) and Graphene Substrate on Platinum-Transition Metal Dimers for Hydrogen Evolution Reaction.

As an extension of single-atom catalysts, despite the increased opportunities to optimize the hydrogen evolution reaction (HER) activity with the variation of the composition, dual-metal-atom catalysts, i.e., dimers, are deeply trapped in a design blind spot due to the lack of the essential recognition of the intrinsic catalytic mechanism at the atomic level. Herein, based on first-principles calculations, a series of platinum-transition metal dimers were constructed on nitrogen-doped graphene (PtM-NDG, M = Fe, Co, Ni, Cu) to reveal the effects of the internal (i.e., M atom) and external (i.e., NDG substrate) environments on the HER activity. Computational results show that the original over-adsorption of hydrogen intermediate (H*) of PtM dimer is weakened after the introduction of NDG, and the optimal active site migrates from the Pt in PtM dimer to the Pt-M bridge in PtM-NDG, triggered by the redistribution of the charge density of the metal atoms. In particular, the M atom switches from tuning the d-band center of the Pt atom to indirectly assist the adsorption behavior of Pt in the PtM dimer to the direct participation in the bonding with H* in PtM-NDG via its own d-band to regulate the distribution of σ and σ*, which enables fine modulation of the bond strength with H*. Moreover, the overall hydrogen evolution performance of PtM-NDG is mainly determined by the d-band center of the M atom. Furthermore, PtFe-NDG with the lowest energy barrier of the rate-determining step stands out in the process of H2 desorption and water dissociation. The present work deepens our understanding of the effects of the metal dopant and substrate on the catalytic performance of platinum.

Comparison of Conventional Logistic Regression and Machine Learning Methods for Predicting Delayed Cerebral Ischemia After Aneurysmal Subarachnoid Hemorrhage: A Multicentric Observational Cohort Study.

Background: Timely and accurate prediction of delayed cerebral ischemia is critical for improving the prognosis of patients with aneurysmal subarachnoid hemorrhage. Machine learning (ML) algorithms are increasingly regarded as having a higher prediction power than conventional logistic regression (LR). This study aims to construct LR and ML models and compare their prediction power on delayed cerebral ischemia (DCI) after aneurysmal subarachnoid hemorrhage (aSAH). Methods: This was a multicenter, retrospective, observational cohort study that enrolled patients with aneurysmal subarachnoid hemorrhage from five hospitals in China. A total of 404 aSAH patients were prospectively enrolled. We randomly divided the patients into training (N = 303) and validation cohorts (N = 101) according to a ratio of 75-25%. One LR and six popular ML algorithms were used to construct models. The area under the receiver operating characteristic curve (AUC), accuracy, balanced accuracy, confusion matrix, sensitivity, specificity, calibration curve, and Hosmer-Lemeshow test were used to assess and compare the model performance. Finally, we calculated each feature of importance. Results: A total of 112 (27.7%) patients developed DCI. Our results showed that conventional LR with an AUC value of 0.824 (95%CI: 0.73-0.91) in the validation cohort outperformed k-nearest neighbor, decision tree, support vector machine, and extreme gradient boosting model with the AUCs of 0.792 (95%CI: 0.68-0.9, P = 0.46), 0.675 (95%CI: 0.56-0.79, P < 0.01), 0.677 (95%CI: 0.57-0.77, P < 0.01), and 0.78 (95%CI: 0.68-0.87, P = 0.50). However, random forest (RF) and artificial neural network model with the same AUC (0.858, 95%CI: 0.78-0.93, P = 0.26) were better than the LR. The accuracy and the balanced accuracy of the RF were 20.8% and 11% higher than the latter, and the RF also showed good calibration in the validation cohort (Hosmer-Lemeshow: P = 0.203). We found that the CT value of subarachnoid hemorrhage, WBC count, neutrophil count, CT value of cerebral edema, and monocyte count were the five most important features for DCI prediction in the RF model. We then developed an online prediction tool (https://dynamic-nomogram.shinyapps.io/DynNomapp-DCI/) based on important features to calculate DCI risk precisely. Conclusions: In this multicenter study, we found that several ML methods, particularly RF, outperformed conventional LR. Furthermore, an online prediction tool based on the RF model was developed to identify patients at high risk for DCI after SAH and facilitate timely interventions. Clinical Trial Registration: http://www.chictr.org.cn, Unique identifier: ChiCTR2100044448.

Differential OAT methylation correlates with cell infiltration in tumor microenvironment and overall survival postradiotherapy in oral squamous cell carcinoma patient.

BACKGROUND: Given that DNA methylation and tumor microenvironment (TME) are susceptible to radiotherapy, we aimed to figure out specific differential DNA methylation to reflect oral squamous cell carcinoma (OSCC) prognosis and associated effect on TME changes postradiotherapy, performing as an efficient biomarker. MATERIALS AND METHODS: Differentially methylation analysis was performed using data from The Cancer Genome Atlas. Curves of Kaplan-Meier (K-M) survival, cumulative hazard and events, Cox proportional hazards, and linear regression model were conducted to screen and validate differential methylation genes, while multiple regression equation to analyze if ornithine aminotransferase (OAT) methylation correlates with radiotherapy. For correlation between OAT methylation and immune infiltrates, CIBERSORT and ESTIMATE algorithms were performed, following gene set enrichment analysis (GSEA) and ssGSEA analysis to evaluate biological process. RESULTS: Compared to normal tissues, only OAT in OSCC was differential significantly by K-M analysis (p = 0.0364). OAT hypermethylation was associated with increased overall survival (hazard ratio: 0.65, p = 0.0358). Radiotherapy correlated with OAT methylation (ß = -0.01, p = 0.0061); most patients with OAT hypermethylation were radiation-sensitive. Hypomethylated OAT correlated with higher cell infiltrations in TME. Neuroactive ligand-receptor interaction was most significantly related to OAT methylation (p = 9.2e-10). Sulfur metabolism was the most significantly in OAT hypermethylation group (p = 0.0041) and RIG-I-like receptor in OAT hypomethylation group (p = 0.0094). CONCLUSION: OAT methylation can serve as a predictor of OSCC prognosis postradiotherapy with potential mechanism by changing cell infiltrations in TME, but further experimental study deserves to carry out confirming the role and mechanism of OAT methylation in OSCC.

A Comparison of LASSO Regression and Tree-Based Models for Delayed Cerebral Ischemia in Elderly Patients With Subarachnoid Hemorrhage.

Backgrounds: As a most widely used machine learning method, tree-based algorithms have not been applied to predict delayed cerebral ischemia (DCI) in elderly patients with aneurysmal subarachnoid hemorrhage (aSAH). Hence, this study aims to develop the conventional regression and tree-based models and determine which model has better prediction performance for DCI development in hospitalized elderly patients after aSAH. Methods: This was a multicenter, retrospective, observational cohort study analyzing elderly patients with aSAH aged 60 years and older. We randomly divided the multicentral data into model training and validation cohort in a ratio of 70-30%. One conventional regression and tree-based model, such as least absolute shrinkage and selection operator (LASSO), decision tree (DT), random forest (RF), and eXtreme Gradient Boosting (XGBoost), was developed. Accuracy, sensitivity, specificity, area under the precision-recall curve (AUC-PR), and area under the receiver operating characteristic curve (AUC-ROC) with 95% CI were employed to evaluate the model prediction performance. A DeLong test was conducted to calculate the statistical differences among models. Finally, we figured the importance weight of each feature to visualize the contribution on DCI. Results: There were 111 and 42 patients in the model training and validation cohorts, and 53 cases developed DCI. According to AUC-ROC value in the model internal validation, DT of 0.836 (95% CI: 0.747-0.926, p = 0.15), RF of 1 (95% CI: 1-1, p < 0.05), and XGBoost of 0.931 (95% CI: 0.885-0.978, p = 0.01) outperformed LASSO of 0.793 (95% CI: 0.692-0.893). However, the LASSO scored a highest AUC-ROC value of 0.894 (95% CI: 0.8-0.989) than DT of 0.764 (95% CI: 0.6-0.928, p = 0.05), RF of 0.821 (95% CI: 0.683-0.959, p = 0.27), and XGBoost of 0.865 (95% CI: 0.751-0.979, p = 0.69) in independent external validation. Moreover, the LASSO had a highest AUC-PR value of 0.681 than DT of 0.615, RF of 0.667, and XGBoost of 0.622 in external validation. In addition, we found that CT values of subarachnoid clots, aneurysm therapy, and white blood cell counts were the most important features for DCI in elderly patients with aSAH. Conclusions: The LASSO had a superior prediction power than tree-based models in external validation. As a result, we recommend the conventional LASSO regression model to predict DCI in elderly patients with aSAH.

The Application Effect of Traditional Chinese Medicine Nursing on General Anesthesia Combined with Epidural Anesthesia and Electric Resection for the Treatment of Bladder Cancer and Its Influence on Tumor Markers.

OBJECTIVE: To explore the effects of traditional Chinese medicine nursing on general anesthesia combined with epidural anesthesia and electric resection to treat bladder cancer and its influence on tumor markers. METHODS: A total of 160 patients with non-muscle-invasive bladder cancer who underwent general anesthesia combined with epidural anesthesia and resection were included in this study. The patients were divided into control group (n = 80) and study group (n = 80) according to the random number table method. The control group received hydroxycamptothecin bladder perfusion therapy, and the study group received traditional Chinese medicine nursing combined with hydroxycamptothecin bladder perfusion therapy. The clinical efficacy, three-year cumulative survival rate, and postoperative recurrence rate of the two groups of patients were detected. The levels of tumor markers including vascular endothelial growth factor (VECF) and bladder tumor antigen (BTA) before and after treatment were also tested. The immune function, inflammatory factor levels, and quality of life of the two groups before and after treatment were evaluated. RESULTS: The total effective rate of the study group (83.75%) was significantly higher than that of the control group (58.75%). After treatment, the serum VEGF and BTA levels, inflammatory factors interleukin-6 (IL-6), C-reactive protein (CRP), and tumor necrosis factor-α (TNF-α) levels of the two groups of patients decreased, and the decrease in the study group was more significant than that in the control group (P < 0.05). After treatment, the levels of CD3+, CD4+, and CD4+/CD8+ in the two groups increased (P < 0.05), and the increase in the study group was more significant than that in the control group (P < 0.05). After treatment, the CD8+ levels of the two groups of patients decreased (P < 0.05), and the decrease in the study group was more significant than that in the control group (P < 0.05). After treatment, the quality-of-life scores in both groups increased (P < 0.05), and the increase in the study group was even more significant (P < 0.05). CONCLUSION: Traditional Chinese medicine nursing has significant clinical effects on the treatment of bladder cancer with general anesthesia combined with epidural anesthesia and electric resection. It can more effectively prevent the risk of recurrence of bladder cancer after surgery, significantly improve the quality of life, improve immune system function, regulate the levels of VECF and BTA, effectively reduce the level of serum inflammatory factors, inhibit tumor progression, and reduce tumor viability.