A near-zero quiescent power breeze wake-up anemometer based on a rolling-bearing triboelectric nanogenerator.

Wind sensors have always played an irreplaceable role in environmental information monitoring and are expected to operate with lower power consumption to extend service lifetime. Here, we propose a breeze wake-up anemometer (B-WA) based on a rolling-bearing triboelectric nanogenerator (RB-TENG) with extremely low static power. The B-WA consists of two RB-TENGs, a self-waking-up module (SWM), a signal processing module (SPM), and a wireless transmission unit. The two RB-TENGs are employed for system activation and wind-speed sensing. Once the ambient wind-speed exceeds 2 m/s, the wake TENG (W-TENG) and the SWM can wake up the system within 0.96 s. At the same time, the SPM starts to calculate the signal frequency from the measured TENG (M-TENG) to monitor the wind speed with a sensitivity of 9.45 Hz/(m/s). After the wind stops, the SWM can switch off the B-WA within 0.52 s to decrease the system energy loss. In quiescent on-duty mode, the operating power of the B-WA is less than 30 nW, which can greatly extend the service lifetime of the B-WA. By integrating triboelectric devices and rolling bearings, this work has realized an ultralow quiescent power and self-waked-up wireless wind-speed monitoring system, which has foreseeable applications in remote weather monitoring, IoT nodes, and so on.

A stratification system of ferroptosis and iron-metabolism related LncRNAs guides the prediction of the survival of patients with esophageal squamous cell carcinoma.

Ferroptosis and iron-metabolism have been widely reported to play an important role in cancer. Long non-coding RNAs (lncRNAs) are increasingly recognized as the crucial mediators in the regulation of ferroptosis and iron metabolism. A systematic understanding of ferroptosis and iron-metabolism related lncRNAs (FIRLs) in esophageal squamous cell carcinoma (ESCC) is essential for prognosis prediction. Herein, Pearson's correlation analysis was carried out between ferroptosis and iron-metabolism-related genes (FIRGs) and all lncRNAs to derive the FIRLs. Based on weighted gene co-expression network exploration (WCGNA), least absolute shrinkage and selection operator (LASSO) regression and Cox regression analysis, a risk stratification system, including 3 FIRLs (LINC01068, TMEM92-AS1, AC243967.2), was established. According to Kaplan-Meier analysis, receiver operating characteristic (ROC) curve analysis, and univariate and multivariate Cox regression analyses, the risk stratification system had excellent predictive ability and clinical relevance. The validity of the established prognostic signature was further examined in TCGA (training set) and GEO (validation set) cohorts. A nomogram with enhanced precision for forecasting OS was set up on basis of the independent prognostic elements. Functional enrichment analysis revealed that three FIRLs took part in various cellular functions and signaling pathways, and the immune status was varied in the high-risk and low-risk groups. In the end, the oncogenic effects of LINC01068 was explored using in vitro researches. Overall, a risk stratification system of three FIRLs was found to have significant prognostic value for ESCC and may serve as a ferroptosis-associated therapeutic target in the clinic.

Comprehensive Analysis of Molecular Clusters and Prognostic Signature Based on m7G-related LncRNAs in Esophageal Squamous Cell Carcinoma.

N7-Methylguanosine (m7G) and long non-coding RNAs (lncRNAs) have been widely reported to play an important role in cancer. However, there is little known about the relationship between m7G-related lncRNAs and esophageal squamous cell carcinoma (ESCC). In this study, we aimed to find new potential biomarkers and construct an m7G-related lncRNA prognostic signature for ESCC. Three molecular clusters were identified by consensus clustering of 963 m7G-related lncRNAs, of which cluster B is preferentially related to poorer prognosis, higher immune and stromal scores, higher mRNA levels of immune checkpoints, and higher immune infiltrate level. We constructed a robust and effective m7G-related lncRNA prognostic signature (m7G-LPS, including 7 m7G-related prognostic lncRNAs) and demonstrated its prognostic value and predictive ability in the GEO and TCGA cohorts. The risk score was able to serve as an independent risk factor for patients with ESCC and showed better prediction than the traditional clinical risk factors. The immune score, stromal score, the infiltration level of immune cells and expression of immune checkpoints were significantly higher in the high-risk subgroup compared to the low-risk subgroup. The establishment of nomogram further improved the performance of m7G-LPS and facilitated its clinical application. Finally, we used GTEx RNA-seq data and qRT-PCR experiments to verify the expression levels of 7 m7G-related lncRNAs. To a certain degree, m7G-lncRNAs can be used as prognostic markers and therapeutic targets for ESCC patients.

Exploring the Potential of Exosome-Related LncRNA Pairs as Predictors for Immune Microenvironment, Survival Outcome, and Microbiotain Landscape in Esophageal Squamous Cell Carcinoma.

Accumulating studies have demonstrated the indispensable roles of exosomes and long non-coding RNAs (lncRNAs) in cancer progression and the tumor microenvironment (TME). However, the clinical relevance of exosome-related lncRNAs (ER-lncRNAs) in esophageal squamous cell carcinoma (ESCC) remains unclear. Three subtypes were identified by consensus clustering of 3459 valid ER-lncRNA pairs, of which subtype A is preferentially related to favorable prognosis, lower stromal and immune scores, and higher tumor purity scores. Higher immune cell infiltration, higher mRNA levels of immune checkpoints, higher stromal and immune scores, and lower tumor purity were found in subtype C, which presented a poor prognosis. We developed a prognostic risk score model based on 8 ER-lncRNA pairs in the GEO cohort using univariate Cox regression analysis and LASSO Cox regression analysis. Patients were divided into a high risk-score group and low risk-score group by the cut-off values of the 1-year ROC curves in the training set (GEO cohort) and the validation set (TCGA cohort). Receiver operating characteristic (ROC) curves, Decision curve analysis (DCA), clinical correlation analysis, and univariate and multivariate Cox regression all confirmed that the prognostic model has good predictive power and that the risk score can be used as an independent prognostic factor in different cohorts. By further analyzing the TME based on the risk model, higher immune cell infiltration and more active TME were found in the high-risk group, which presented a poor prognosis. Patients with high risk scores also exhibited higher mRNA levels of immune checkpoints and lower IC50 values, indicating that these patients may be more prone to profit from chemotherapy and immunotherapy. The top five most abundant microbial phyla in ESCC was also identified. The best ER-lncRNAs (AC082651.3, AP000487.1, PLA2G4E-AS1, C8orf49 and AL356056.2) were identified based on machine learning algorithms. Subsequently, the expression levels of the above ER-lncRNAs were analyzed by combining the GTEx and TCGA databases. In addition, qRT-PCR analysis based on clinical samples from our hospital showed a high degree of consistency. This study fills the gap of ER-lncRNA model in predicting the prognosis of patients with ESCC and the risk score-based risk stratification could facilitate the determination of therapeutic option to improve prognoses.

Identification of A Risk Signature Based on Lactic Acid Metabolism-Related LncRNAs in Patients With Esophageal Squamous Cell Carcinoma.

Lactic acid, formerly thought of as a byproduct of glycolysis or a metabolic waste produced, has now been identified as a key regulator of cancer growth, maintenance, and progression. However, the results of investigations on lactic acid metabolism-related long non-coding RNAs (LRLs) in esophageal squamous cell carcinoma (ESCC) remain inconclusive. In this study, univariate Cox regression analysis was carried out in the TCGA cohort, and 9 lncRNAs were shown to be significantly associated with prognosis. Least absolute shrinkage and selection operator (LASSO) regression analysis and multivariate Cox regression analysis were then used in the GEO cohort. 6 LRLs were identified as independent prognostic factors for ESCC patients used to construct a prognostic risk-related signature subsequently. Two groups were formed based on the middle value of risk scores: a low-risk group and a high-risk group. Following that, we conducted Kaplan-Meier survival analysis, which revealed that the high-risk group had a lower survival probability than the low-risk group in both GEO and TCGA cohorts. On multivariate Cox regression analysis, the prognostic signature was shown to be independent prognostic factor, and it was found to be a better predictor of the prognosis of ESCC patients than the currently widely used grading and staging approaches. The established nomogram can be conveniently applied in the clinic to predict the 1-, 3-, and 5- year survival rates of patients. There was a significant link found between the 6 LRLs-based prognostic signature and immune-cell infiltration, tumor microenvironment (TME), tumor somatic mutational status, and chemotherapeutic treatment sensitivity in the study population. Finally, we used GTEx RNA-seq data and qRT-PCR experiments to verify the expression levels of 6 LRLs. In conclusion, we constructed a prognostic signature which could predict the prognosis and immunotherapy response of ESCC patients.

Pro-Angiogenesis Role of LINC00662 From Esophageal Squamous Cell Carcinoma Cells-Derived Extracellular Vehicles.

Objective: LINC00662 is oncogenic in some human cancers, but no much was revealed concerning to its specific action in tumor angiogenesis. Given that, our study investigated the role of LINC00662 from esophageal squamous cell carcinoma (ESCC) cells-derived extracellular vehicles (EVs) in angiogenesis through microRNA (miR)-195-5p/vascular endothelial growth factor A (VEGFA) axis. Methods: Clinical tissue samples were collected from patients with ESCC, in which LINC00662, miR-195-5p and VEGFA expression was analyzed. ESCC cells were transfected, from which EVs were isolated. Human umbilical vein endothelial cells (HUVECs) were co-cultured with the pretreated EVs. After that, viability, colony formation ability, invasion, migration and tube formation ability of HUVECs were observed. Tumor xenograft in nude mice was performed to detect the effect of LINC00662, miR-195-5p or EV specific inhibitor GW4869 on tumor development. Results: LINC00662 and VEGFA were upregulated while miR-195-5p was downregulated in the cancer tissue of patients with ESCC. EVs derived from ESCC cells promoted viability, colony formation ability, invasion and tube formation ability of HUVECs. Downregulation of LINC00662 or upregulation of miR-195-5p reversed the promotion of EVs derived from ESCC cells on the viability, colony formation ability, invasion and tube formation ability of HUVECs in vitro and in vivo. VEGFA overexpression reversed EVs carrying restored miR-195-5p induced effects on HUVECs in vitro. Conclusion: In summary, elevated LINC00662 transferred by ESCC cells-derived EVs induces angiogenesis through downregulating miR-195-5p and upregulating VEGFA.

Risk Factors Analysis of Thoracic Trauma Complicated With Acute Respiratory Distress Syndrome and Observation of Curative Effect of Lung-Protective Ventilation.

PURPOSE: To explore the risk factors of acute respiratory distress syndrome (ARDS) secondary to thoracic trauma and the therapeutic effect of protective lung ventilation in patients with acute respiratory distress syndrome complicated with thoracic trauma. METHODS: We collected 206 patients with thoracic trauma admitted to our hospital from September 2017 to March 2021, counted the incidence of ARDS and analyzed the risk factors of ARDS. To observe the clinical efficacy of the application of lung-protective ventilation therapy in patients with thoracic trauma combined with ARDS. RESULTS: Among 206 patients with thoracic trauma, there were 82 cases of combined ARDS, and its incidence was 39.81%. The 82 patients with ARDS were randomly divided into the control group and the observation group with 42 cases each, and different ventilation methods were used for treatment. The results showed that the mechanical ventilation time (MVT) was shorter in the observation group than in the control group, and the incidence of ventilator-associated lung injury (VALI) and case fatality rate (CFR) were lower than those in the control group (P < 0.05). Arterial partial pressure of oxygen (Pa02), arterial blood carbon dioxide partial pressure (PaCO2), and Oxygenation index (arterial partial pressure of oxygen/Fraction of inspiration O2, PaO2/FiO2) were significantly improved better in both groups after treatment; compared with the control group, patients in the observation group had higher Pa02 levels and lower PaCO2 levels at 8 h and 24 h after ventilation (P < 0.05). Multivariate analysis revealed that blunt trauma, massive blood transfusion, procalcitonin (PCT) level, tumor necrosis factor-α (TNF-α) level, and acute physiology and chronic health score (APACHE II) were all risk factors for Thoracic trauma with ARDS. CONCLUSION: Risk factors for the development of ARDS after thoracic trauma are blunt injuries, massive blood transfusion, high PCT and TNF-α levels, and high APACHE II scores, which can be given active interventions in the early stage of clinical practice to improve patient prognosis. The use of protective lung ventilation therapy can improve the clinical outcome of patients with thoracic trauma combined with ARDS, which is important for improving the ventilation effect and respiratory function of patients.