SINS/OD Integrated Navigation Algorithm Based on Body Frame Position Increment for Land Vehicles

It is a challenge to achieve high accuracy navigation for land vehicles without the aid of global navigation satellite systems (GNSS). Inertial measurement unit (IMU) and odometer (OD) are widely deployed due to their complementary properties. In this paper, SINS/OD integrated navigation algorithm based on body frame position increment is studied to improve the navigation performance. Taking the calibration errors of odometer scale factor, IMU installation angle, and lever arm into consideration, the odometer measurement model is derived. Then measurement equations based on body frame position increment are proposed to overcome the amplified random errors in the traditional velocity observation approach. Odometer fault detection and exception are conducted based on residual χ2 detection method, with the nonholonomic constraints of land vehicles applied to mitigate the standalone SINS error drift. Long distance real test is carried out using laser gyro SINS to assess the proposed algorithm, which shows that navigation performance can be effectively improved

A Large Genetic Causal Analysis of the Gut Microbiota and Urological Cancers: A Bidirectional Mendelian Randomization Study

Background: Several observational studies and clinical trials have shown that the gut microbiota is associated with urological cancers. However, the causal relationship between gut microbiota and urological cancers remains to be elucidated due to many confounding factors. Methods: In this study, we used two thresholds to identify gut microbiota GWAS from the MiBioGen consortium and obtained data for five urological cancers from the UK biobank and Finngen consortium, respectively. We then performed a two-sample Mendelian randomization (MR) analysis with Wald ratio or inverse variance weighted as the main method. We also performed comprehensive sensitivity analyses to verify the robustness of the results. In addition, we performed a reverse MR analysis to examine the direction of causality. Results: Our study found that family Rikenellaceae, genus Allisonella, genus Lachnospiraceae UCG001, genus Oscillibacter, genus Eubacterium coprostanoligenes group, genus Eubacterium ruminantium group, genus Ruminococcaceae UCG013, and genus Senegalimassilia were related to bladder cancer; genus Ruminococcus torques group, genus Oscillibacter, genus Barnesiella, genus Butyricicoccus, and genus Ruminococcaceae UCG005 were related to prostate cancer; class Alphaproteobacteria, class Bacilli, family Family XI, genus Coprococcus2, genus Intestinimonas, genus Lachnoclostridium, genus Lactococcus, genus Ruminococcus torques group, and genus Eubacterium brachy group were related to renal cell cancer; family Clostridiaceae 1, family Christensenellaceae, genus Eubacterium coprostanoligenes group, genus Clostridium sensu stricto 1, and genus Eubacterium eligens group were related to renal pelvis cancer; family Peptostreptococcaceae, genus Romboutsia, and genus Subdoligranulum were related to testicular cancer. Comprehensive sensitivity analyses proved that our results were reliable. Conclusions: Our study confirms the role of specific gut microbial taxa on urological cancers, explores the mechanism of gut microbiota on urological cancers from a macroscopic level, provides potential targets for the screening and treatment of urological cancers, and is dedicated to providing new ideas for clinical research

Assessment of an exhaled breath test using ultraviolet photoionization time-of-flight mass spectrometry for the monitoring of kidney transplant recipients

Abstract Continuous monitoring for immunosuppressive status, infection and complications are a must for kidney transplantation (KTx) recipients. Traditional monitoring including blood sampling and kidney biopsy, which caused tremendous medical cost and trauma. Therefore, a cheaper and less invasive approach was urgently needed. We thought that a breath test has the potential to become a feasible tool for KTx monitoring. A prospective-specimen collection, retrospective-blinded assessment strategy was used in this study. Exhaled breath samples from 175 KTx recipients were collected in West China Hospital and tested by online ultraviolet photoionization time-of-flight mass spectrometry (UVP-TOF–MS). The classification models based on breath test performed well in classifying normal and abnormal values of creatinine, estimated glomerular filtration rate (eGFR), blood urea nitrogen (BUN) and tacrolimus, with AUC values of 0.889, 0.850, 0.849 and 0.889, respectively. Regression analysis also demonstrated the predictive ability of breath test for clinical creatinine, eGFR, BUN, tacrolimus level, as the predicted values obtained from the regression model correlated well with the clinical true values (p < 0.05). The findings of this investigation implied that a breath test by using UVP-TOF–MS for KTx recipient monitoring is possible and accurate, which might be useful for future clinical screenings

A sensitive GRAB sensor for detecting extracellular ATP in vitro and in vivo

The purinergic transmitter ATP (adenosine 5'-triphosphate) plays an essential role in both the central and peripheral nervous systems, and the ability to directly measure extracellular ATP in real time will increase our understanding of its physiological functions. Here, we developed a sensitive GPCR activation-based ATP sensor called GRABATP1.0, with a robust fluorescence response to extracellular ATP when expressed in several cell types. This sensor has sub-second kinetics, has ATP affinity in the range of tens of nanomolar, and can be used to localize ATP release with subcellular resolution. Using this sensor, we monitored ATP release under a variety of in vitro and in vivo conditions, including stimuli-induced and spontaneous ATP release in primary hippocampal cultures, injury-induced ATP release in a zebrafish model, and lipopolysaccharides-induced ATP-release events in individual astrocytes in the mouse cortex. Thus, the GRABATP1.0 sensor is a sensitive, versatile tool for monitoring ATP release and dynamics under both physiological and pathophysiological conditions. Keywords: ATP; GPCR; GRAB; fluorescent sensors; genetically encoded; imaging; injury; neuroinflammation; purinergic signaling

Are medical record front page data suitable for risk adjustment in hospital performance measurement? Development and validation of a risk model of in-hospital mortality after acute myocardial infarction

Objectives To develop a model of in-hospital mortality using medical record front page (MRFP) data and assess its validity in case-mix standardisation by comparison with a model developed using the complete medical record data.Design A nationally representative retrospective study.Setting Representative hospitals in China, covering 161 hospitals in modelling cohort and 156 hospitals in validation cohort.Participants Representative patients admitted for acute myocardial infarction. 8370 patients in modelling cohort and 9704 patients in validation cohort.Primary outcome measures In-hospital mortality, which was defined explicitly as death that occurred during hospitalisation, and the hospital-level risk standardised mortality rate (RSMR).Results A total of 14 variables were included in the model predicting in-hospital mortality based on MRFP data, with the area under receiver operating characteristic curve of 0.78 among modelling cohort and 0.79 among validation cohort. The median of absolute difference between the hospital RSMR predicted by hierarchical generalised linear models established based on MRFP data and complete medical record data, which was built as ‘reference model’, was 0.08% (10th and 90th percentiles: −1.8% and 1.6%). In the regression model comparing the RSMR between two models, the slope and intercept of the regression equation is 0.90 and 0.007 in modelling cohort, while 0.85 and 0.010 in validation cohort, which indicated that the evaluation capability from two models were very similar.Conclusions The models based on MRFP data showed good discrimination and calibration capability, as well as similar risk prediction effect in comparison with the model based on complete medical record data, which proved that MRFP data could be suitable for risk adjustment in hospital performance measurement