Epidemiological and clinical characteristics of craniofacial soft tissue injuries in a plastic emergency department in Xi'an, China: a retrospective study of 22887 patients from 2019 to 2023.

Objective: This study aims to describe the epidemiological features of craniofacial soft tissue injuries in a major plastic emergency department in northwest China.

Methods: A retrospective review of emergency medical records (2019-2023) was conducted for craniofacial soft tissue injury patients. Demographic and clinical data were collected and analyzed, stratified by age and with consideration of the COVID-19 period.

DNA methylation variations of DNA damage response correlate survival and local immune status in melanomas.

Aim: We aimed to explore the impact of DNA methylation alterations on the DNA damage response (DDR) in melanoma prognosis and immunity. MATERIAL & METHODS: Different melanoma cohorts with molecular and clinical data were included.

Results: Hierarchical clustering utilizing different combinations of DDR-relevant CpGs yielded distinct melanoma subtypes, which were characteristic of different prognoses, transcriptional function profiles of DDR, and immunity and immunotherapy responses but were associated with similar tumor mutation burdens.

A new method to orient a 3-dimensional facial model to natural head position: A preliminary report on accuracy and reproducibility.

Objectives: To establish and validate a novel method to orient a 3-dimensional (3D) facial model to natural head position (NHP) in a stereophotogrammetric system using a 2-dimensional frontal full-face photograph of NHP.

Material And Methods: Specific technique procedure was reported for our method, and in vitro model experiment was performed for accuracy test. A preliminary volunteer study was then planned for reproducibility test.

Machine learning prediction models for in-hospital postoperative functional outcome after moderate-to-severe traumatic brain injury.

Aim: This study aims to utilize machine learning (ML) and logistic regression (LR) models to predict surgical outcomes among patients with traumatic brain injury (TBI) based on admission examination, assisting in making optimal surgical treatment decision for these patients.

Method: We conducted a retrospective review of patients hospitalized in our department for moderate-to-severe TBI. Patients admitted between October 2011 and October 2022 were assigned to the training set, while patients admitted between November 2022 and May 2023 were designated as the external validation set.

Machine learning models for predicting in-hospital outcomes after non-surgical treatment among patients with moderate-to-severe traumatic brain injury.

Aim: This study aims to develop prediction models for in-hospital outcomes after non-surgical treatment among patients with moderate-to-severe traumatic brain injury (TBI).

Method: We conducted a retrospective review of patients hospitalized for moderate-to-severe TBI in our department from 2011 to 2020. Five machine learning (ML) algorithms and the conventional logistic regression (LR) model were employed to predict in-hospital mortality and the Glasgow Outcome Scale (GOS) functional outcomes.

Correlation between intraosseous thermal change and drilling impulse data during osteotomy within autonomous dental implant robotic system: An in vitro study.

Objectives: This study aims at examining the correlation of intraosseous temperature change with drilling impulse data during osteotomy and establishing real-time temperature prediction models.

Materials And Methods: A combination of in vitro bovine rib model and Autonomous Dental Implant Robotic System (ADIR) was set up, in which intraosseous temperature and drilling impulse data were measured using an infrared camera and a six-axis force/torque sensor respectively. A total of 800 drills with different parameters (e.

Genome-wide DNA methylation analysis identifies potent CpG signature for temzolomide response in non-G-CIMP glioblastomas with unmethylated MGMT promoter: MGMT-dependent roles of GPR81.

Purposes: To identify potent DNA methylation candidates that could predict response to temozolomide (TMZ) in glioblastomas (GBMs) that do not have glioma-CpGs island methylator phenotype (G-CIMP) but have an unmethylated promoter of O-6-methylguanine-DNA methyltransferase (unMGMT).

Methods: The discovery-validation approach was planned incorporating a series of G-CIMP-/unMGMT GBM cohorts with DNA methylation microarray data and clinical information, to construct multi-CpG prediction models. Different bioinformatic and experimental analyses were performed for biological exploration.

Machine learning algorithms for improved prediction of in-hospital outcomes after moderate-to-severe traumatic brain injury: a Chinese retrospective cohort study.

Aim: Controversy remains high over the superiority of advanced machine learning (ML) algorithms to conventional logistic regression (LR) in the prediction of prognosis after traumatic brain injury (TBI). This study aimed to compare the performance of ML and LR models in predicting in-hospital prognosis after TBI.

Method: In a single-center retrospective cohort of adult patients hospitalized for moderate-to-severe TBI (Glasgow coma score ≤12) in our hospital from 2011 to 2020, LR and three ML algorithms (XGboost, lightGBM, and FT-transformer) were run to build prediction models for in-hospital mortality and the Glasgow Outcome Scale (GOS) functional outcomes using either all 19 clinical and laboratory features or the 10 non-laboratory ones collected at admission to the neurological intensive care unit.

Novel predictive epigenetic signature for temozolomide in non-G-CIMP glioblastomas.

Objective: To identify novel epigenetic signatures that could provide predictive information that is complementary to promoter methylation status of the O-6-methylguanine-DNA methyltransferase (MGMT) gene for predicting temozolomide (TMZ) response, among glioblastomas (GBMs) without glioma-CpGs island methylator phenotype (G-CIMP) METHODS: Different cohorts of primary non-G-CIMP GBMs with genome-wide DNA methylation microarray data were included for discovery and validation of a multimarker signature, combined using a RISK score model. Different statistical analyses and functional experiments were performed for clinical and biological validation.

Results: By employing discovery cohorts with radiotherapy (RT) and TMZ versus RT alone and a strict multistep selection strategy, we identified seven CpGs, each of which was significantly correlated with overall survival (OS) of non-G-CIMP GBMs with RT/TMZ, independent of age, MGMT promoter methylation status, and other identified CpGs.

A five-CpG signature of microRNA methylation in non-G-CIMP glioblastoma.

Aims: DNA methylation has been found to regulate microRNAs (miRNAs) expression, but the prognostic value of miRNA-related DNA methylation aberration remained largely elusive in cancers including glioblastomas (GBMs). This study aimed to investigate the clinical and biological feature of miRNA methylation in GBMs of non-glioma-CpG island methylator phenotype (non-G-CIMP).

Methods: Prognostic miRNA methylation loci were analyzed, with TCGA and Rennes cohort as training sets, and independent datasets of GBMs and low-grade gliomas (LGGs) were obtained as validation sets.

A novel prognostic six-CpG signature in glioblastomas.

Aims: We aimed to identify a clinically useful biomarker using DNA methylation-based information to optimize individual treatment of patients with glioblastoma (GBM).

Methods: A six-CpG panel was identified by incorporating genome-wide DNA methylation data and clinical information of three distinct discovery sets and was combined using a risk-score model. Different validation sets of GBMs and lower-grade gliomas and different statistical methods were implemented for prognostic evaluation.

Dec1 expression predicts prognosis and the response to temozolomide chemotherapy in patients with glioma.

Differentiated embryo chondrocyte expressed gene 1 (Dec1), a crucial cell differentiation mediator and apoptosis inhibitor, is abundantly expressed in various types of human cancer and is associated with malignant tumor progression. As poor differentiation and low apoptosis are closely associated with poor survival rates and a poor response to radio/chemotherapy in patients with cancer, the prognostic value of Dec1 expression was examined in the present study and its correlation with response to temozolomide (TMZ) chemotherapy was analyzed in patients with glioma. Dec1 expression was analyzed by immunohistochemistry in 157 samples of newly diagnosed glioma and 63 recurrent glioblastoma cases that relapsed during TMZ chemotherapy.

New way to achieve frontal facial photographs of the head in its natural position.

Frontal photographs of the head in its natural position are not as easy to achieve as lateral ones. We describe a new way to obtain standard 2-dimensional images of its natural position in full-face frontal view using a customised photographic system, which may provide supplementary information for traditional lateral facial imaging, and be helpful for standard assessment of 3-dimensional facial images.

The predictive but not prognostic value of MGMT promoter methylation status in elderly glioblastoma patients: a meta-analysis.

Background: The clinical implication of O6-methylguanine-DNA methyltransferase (MGMT) promoter status is ill-defined in elderly glioblastoma patients. Here we report a meta-analysis to seek valid evidence for its clinical relevance in this subpopulation.

Methods: Literature were searched and reviewed in a systematic manner using the PubMed, EMBASE and Cochrane databases.

A meta-analysis of temozolomide versus radiotherapy in elderly glioblastoma patients.

Temozolomide (TMZ) alone has been proposed as a promising alternative to radiotherapy (RT) in elderly glioblastoma (GBM) patients. We report a meta-analysis to systematically evaluate TMZ monotherapy in older GBM patients. A systematic literature search was performed using PubMed, EMBASE and the Cochrane database.

Radiotherapy plus concurrent or sequential temozolomide for glioblastoma in the elderly: a meta-analysis.

Background: Many physicians are reluctant to treat elderly glioblastoma (GBM) patients as aggressively as younger patients, which is not evidence based due to the absence of validated data from primary studies. We conducted a meta-analysis to provide valid evidence for the use of the aggressive combination of radiotherapy (RT) and temozolomide (TMZ) in elderly GBM patients.

Methods: A systematic literature search was conducted using the PubMed, EMBASE and Cochrane databases.

The treatment of glioblastomas: a systematic update on clinical Phase III trials.

Glioblastomas (GBMs) are invariably associated with unavoidable tumor recurrence and overall poor prognosis. The present study is to summarize the results of clinical Phase III studies on GBMs over the past seven years. A systematic literature search was performed using major electronic databases and by screening meeting abstracts.