Continuous respiratory monitoring is an important tool for clinical monitoring. Associated with the development of biomedical technology, it has become more and more important, especially in the measuring of gas flow and CO2 concentration, which can reflect the status of the patient. In this paper, a new type of biomedical device is presented, which uses low-power sensors with a piezoresistive silicon differential pressure sensor to measure gas flow and with a pyroelectric sensor to measure CO2 concentration simultaneously. For the portability of the biomedical device, the sensors and low-power measurement circuits are integrated together, and the airway tube also needs to be miniaturized. Circuits are designed to ensure the stability of the power source and to filter out the existing noise. Modulation technology is used to eliminate the fluctuations at the trough of the waveform of the CO2 concentration signal. Statistical analysis with the coefficient of variation was performed to find out the optimal driving voltage of the pressure transducer. Through targeted experiments, the biomedical device showed a high accuracy, with a measuring precision of 0.23 mmHg, and it worked continuously and stably, thus realizing the real-time monitoring of the status of patients.

BackgroundStudies investigating the association between the apolipoprotein E (APOE) gene polymorphism and the risk of intracerebral hemorrhage (ICH) have reported conflicting results. We here performed a meta-analysis based on the evidence currently available from the literature to make a more precise estimation of this relationship.MethodsPublished literature from the National Library of Medline and Embase databases were retrieved. Odds ratio (OR) and 95% confidence interval (CI) were calculated in fixed- or random-effects models when appropriate. Subgroup analyses were performed by race.ResultsThis meta-analysis included 11 case–control studies, which included 1,238 ICH cases and 3,575 controls. The combined results based on all studies showed that ICH cases had a significantly higher frequency of APOE ϵ4 allele (OR= 1.42, 95% CI= 1.21,1.67, P<0.001). In the subgroup analysis by race, we also found that ICH cases had a significantly higher frequency of APOE ϵ4 allele in Asians (OR= 1.52, 95% CI= 1.20,1.93, P<0.001) and in Caucasians (OR= 1.34, 95% CI= 1.07,1.66, P=0.009). There was no significant relationship between APOE ϵ2 allele and the risk of ICH.ConclusionOur meta-analysis suggested that APOE ϵ4 allele was associated with a higher risk of ICH.

Pancreatic adenocarcinoma (PAAD) remains an extremely fatal malignancy with a high mortality rate worldwide. This study focuses on the roles of ubiquitin‐specific peptidase 10 (USP10) and cysteine rich angiogenic inducer 61 (Cyr61) in macrophage polarization, immune escape, and metastasis of PAAD. USP10 showed a positive correlation with Yes1 associated transcriptional regulator (YAP1), which, according to the TCGA‐PAAD database, is highly expressed in PAAD and indicates poor patient prognosis. USP10 knockdown increased ubiquitination and degradation of YAP1, which further decreased the programmed cell death ligand 1 (PD‐L1) and Galectin‐9 expression, suppressed immune escape, and reduced the proliferation and metastasis of PAAD cells in vitro and in vivo. Cyr61, a downstream factor of YAP1, was overexpressed in PAAD cells after USP10 silencing for rescue experiments. Overexpression of Cyr61 restored the PD‐L1 and Galectin‐9 expression in cells and triggered M2 polarization of macrophages, which enhanced the immune escape and maintained the proliferation and metastasis ability of PAAD cells. In conclusion, this work demonstrates that USP10 inhibits YAP1 ubiquitination and degradation to promote Cyr61 expression, which induces immune escape and promotes growth and metastasis of PAAD.

Background Gene mutations play critical roles in tumorigenesis and cancer development. Our study aimed to screen survival-related mutations and explore a novel gene signature to predict the overall survival in pancreatic cancer. Methods Somatic mutation data from three cohorts were used to identify the common survival-related gene mutation with Kaplan-Meier curves. RNA-sequencing data were used to explore the signature for survival prediction. First, Weighted Gene Co-expression Network Analysis was conducted to identify candidate genes. Then, the ICGC-PACA-CA cohort was applied as the training set and the TCGA-PAAD cohort was used as the external validation set. A TP53-associated signature calculating the risk score of every patient was developed with univariate Cox, least absolute shrinkage and selection operator, and stepwise regression analysis. Kaplan-Meier and receiver operating characteristic curves were plotted to verify the accuracy. The independence of the signature was confirmed by the multivariate Cox regression analysis. Finally, a prognostic nomogram including 359 patients was constructed based on the combined expression data and the risk scores. Results TP53 mutation was screened to be the robust and survival-related mutation type, and was associated with immune cell infiltration. Two thousand, four hundred fifty-five genes included in the six modules generated in the WGCNA were screened as candidate survival related TP53-associated genes. A seven-gene signature was constructed: Risk score = (0.1254 × ERRFI1) - (0.1365 × IL6R) - (0.4400 × PPP1R10) - (0.3397 × PTOV1-AS2) + (0.1544 × SCEL) - (0.4412 × SSX2IP) – (0.2231 × TXNL4A). Area Under Curves of 1-, 3-, and 5-year ROC curves were 0.731, 0.808, and 0.873 in the training set and 0.703, 0.677, and 0.737 in the validation set. A prognostic nomogram including 359 patients was constructed and well-calibrated, with the Area Under Curves of 1-, 3-, and 5-year ROC curves as 0.713, 0.753, and 0.823. Conclusions The TP53-associated signature exhibited good prognostic efficacy in predicting the overall survival of PC patients.

Continuous respiratory gas monitoring is an important tool for clinical monitoring. In particular, measurement of respiratory [Formula: see text] concentration and gasflow can reflect the status of a patient by providing parameters such as volume of carbon dioxide, end-tidal [Formula: see text] respiratory rate and alveolar deadspace. However, in the majority of previous work, [Formula: see text] concentration and gasflow have been studied separately. This study focuses on a mainstream system which simultaneously measures respiratory [Formula: see text] concentration and gasflow at the same location, allowing for volumetric capnography to be implemented. A non-dispersive infrared monitor is used to measure [Formula: see text] concentration and a differential pressure sensor is used to measure gasflow. In developing this new device, we designed a custom airway adapter which can be placed in line with the breathing circuit and accurately monitor relevant respiratory parameters. Because the airway adapter is used both for capnography and gasflow, our system reduces mechanical deadspace. The finite element method was used to design the airway adapter which can provide a strong differential pressure while reducing airway resistance. Statistical analysis using the coefficient of variation was performed to find the optimal driving voltage of the pressure transducer. Calibration between variations and flows was used to avoid pressure signal drift. We carried out targeted experiments using the proposed device and confirmed that the device can produce stable signals.