Identification of Cuproptosis-related Gene Lipoyltransferase 1 as a Promising Biomarker in Oral Squamous Cell Carcinoma.

OBJECTIVE: To find efficient cuproptosis-related biomarkers to explore the oncogenesis and progression of oral squamous cell carcinoma (OSCC). METHODS: All the original data were downloaded from the Cancer Genome Atlas (TCGA) database. Univariate Cox analysis and Kaplan-Meier survival analysis were used to identify the gene related to survival. Tumor Immune Estimation Resource 2.0 (TIMER 2.0) was used to reveal the different expression of cuproptosis-related gene lipoyltransferase 1 (LIPT1) in various kinds of tumours. RESULTS: LIPT1, as a cuproptosis-related gene, was found to be differentially expressed in the OSCC group and the control group. It was also found to be related to the prognosis of OSCC. Pan cancer analysis showed LIPT1 was also involved in various kinds of tumours. CONCLUSION: All the results demonstrate that the cuproptosis-related gene LIPT1 is highly involved in the oncogenesis and progression of OSCC. These findings give new insight for further research into the cuproptosis-related biomarkers in OSCC.

Acoustic Imaging Method for Gas Leak Detection and Localization Using Virtual Ultrasonic Sensor Array.

An acoustic imaging method for detecting and locating gas leaks based on a virtual ultrasonic sensor array is proposed and experimentally demonstrated. A scanning sensor array of only two sensors is used to collect the acoustic signals generated by the leakage hole. The matrix of the leakage signal is processed by the cross-power spectrum method to achieve time consistency, afterward, the location of the leakage source can be calculated by the virtual beamforming method. The influence of the number of sensors and the distance between adjacent sensors on the effect of the proposed method are compared and discussed. To verify the effectiveness and operability of the detection and localization method, several experiments were carried out. Furthermore, a series of experiments were conducted to assess the accuracy and stability of this method. The experimental results demonstrate that the proposed method based on a virtual sensor array can achieve highly accurate localization of gas leaks and performs well regarding stability.

Brain connectomics improve prediction of 1-year decreased quality of life in breast cancer: A multi-voxel pattern analysis.

PURPOSE: Whether brain connectomics can predict 1-year decreased Quality of Life (QoL) in patients with breast cancer are unclear. A longitudinal study was utilized to explore their prediction abilities with a multi-center sample. METHODS: 232 breast cancer patients were consecutively enrolled and 214 completed the 1-year QoL assessment (92.2%). Resting state functional magnetic resonance imaging was collected before the treatment and a multivoxel pattern analysis (MVPA) was performed to differentiate whole-brain resting-state connectivity patterns. Net Reclassification Improvement (NRI) as well as Integrated Discrimination Improvement (IDI) were calculated to estimate the incremental value of brain connectomics over conventional risk factors. RESULTS: Paracingulate Gyrus, Superior Frontal Gyrus and Frontal Pole were three significant brain areas. Brain connectomics yielded 7.8-17.2% of AUC improvement in predicting 1-year decreased QoL. The NRI and IDI ranged from 20.27 to 54.05%, 13.21-33.34% respectively. CONCLUSION: Brain connectomics contribute to a more accurate prediction of 1-year decreased QoL in breast cancer. Significant brain areas in the prefrontal lobe could be used as potential intervention targets (i.e., Cognitive Behavioral Group Therapy) to improve long-term QoL outcomes in breast cancer.