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Abstract Objective This study seeks to investigate independent risk factors affecting the prognoses of patients with bladder pain syndrome/interstitial cystitis (BPS/IC) following hydrodistention surgery and to develop a column chart model and a random forest model to help predict clinical outcomes. Method A retrospective analysis was conducted on the clinical data of 1006 BPS/IC patients who visited the urology department of the Fifth Hospital of Shanxi Medical University (Shanxi Provincial People's Hospital) between June 2012 and June 2022. The patients were randomly divided into a model group (n = 704) and a validation group (n = 302). In the model group, logistic regression analysis was used to identify independent risk factors, which were used to construct a prognostic nomogram. The nomogram was evaluated by analyzing the area under the curve (AUC), calibration curve, and decision curve. These results were subsequently validated via consistency analysis (n = 302). And based on the random forest algorithm, we calculate the same data and construct a random forest model. Result Multivariate logistic regression analysis revealed that age and the expression of the biomarkers CD117, P2X3R, NGF, and TrkA were independent prognostic factors for patients with BPS/IC (P

Blade wear is the critical problem in the operation of multiphase pump. This paper presents a numerical study of the multiphase flow of multiphase pump. The trajectory of particles in the pump is calculated by the discrete phase model. Then, the simulation results are compared with the model test results of the pump to verify the correctness of the simulation method. The results show that the particles in the impeller domain are mainly near the hub, and the particles in the diffuser domain form a agglomerated area in the middle of the flow channel. The average wear rate of the impeller is more affected by the particle size than that of the diffuser. The maximum wear rate of blade surface increases first and then decreases with the increase of particle size. According to the wear data under different particle sizes, the regression model between particle size and wear rate is fitted to predict the wear of mixed transport pump in actual operation. The research results have important reference value for the prediction of the wear performance of the multiphase pump.

To explore the causal relationship between maternal smoking around birth and childhood asthma using Mendelian randomization (MR). Using the data from large-scale genome-wide association studies, we selected independent genetic loci closely related to maternal smoking around birth and maternal diseases as instrumental variables and used MR methods. In this study, we considered the inverse variance weighted method (MR-IVW), weighted median method, and MR-Egger regression. We investigated the causal relationship between maternal smoking around birth and maternal diseases in childhood asthma using the odds ratio (OR) as an evaluation index. Multivariable MR (MVMR) included maternal history of Alzheimer's disease, illnesses of the mother: high blood pressure and illnesses of the mother: heart diseaseas covariates to address potential confounding. Sensitivity analyses were evaluated for weak instrument bias and pleiotropic effects. It was shown with the MR-IVW results that maternal smoking around birth increased the risk of childhood asthma by 1.5% (OR = 1.0150, 95% CI: 1.0018–1.0283). After the multivariable MR method was used to correct for relevant covariates, the association effect between maternal smoking around birth and childhood asthma was still statistically significant (P < 0.05). Maternal smoking around birth increases the risk of childhood asthma.

As a medium and low pressure gear machine without automatic compensation structure for axial and radial clearances, the friction pairs in the straight conjugate internal gear pumps (SCIGPs) depend on the fixed small clearances to seal, lubricate and transfer the force. The oil film design of the friction pairs has become an important part of gear pump design. However, there has never been a publicly published research on the oil film design of the SCIGP in past literature. This paper applies orthogonal test to the oil film design of the SCIGP for the first time to determine the best working clearances. With this goal, the paper first provides the mathematical models for analyzing the internal leakage flow and the viscous friction loss, which elucidate the relationships between the leakage and the friction loss with working conditions. After that, the orthogonal test scheme for numerical simulation was designed on the basis of determining the range of oil film thickness. The paper also propounds the viewpoints of using the range-method to estimate the primary and secondary relationship of factors and determining the optimal combination according to the test target. Based on this concept, the main factors affecting the target are procured and the optimal working clearances of the friction pairs are determined. For the purpose of verifying the model, the redesigned prototype was tested and compared with the simulation results. The results validate the applicability of the simulation model and the correctness of the simulation method. Finally, the paper summarizes the ways to improve the total efficiency and the working conditions at the highest efficiency.

As a precision mechanical component to reduce friction between components, the rolling bearing is widely used in many fields because of its slight friction loss, strong bearing capacity, high precision, low power consumption, and high mechanical efficiency. This paper reviews several excellent kinds of study and their relevance to the fault detection of rolling bearings. We summarize the fault location, sensor types, bearing fault types, and fault signal analysis of rolling bearings. The fault signal types are divided into one-dimensional and two-dimensional images, which account for 40.14% and 31.69%, respectively, and their classification is clarified and discussed. We counted the proportions of various methods in the references cited in this paper. Among them, the method of one-dimensional signal detection with external sensors accounted for 3.52%, the method of one-dimensional signal detection with internal sensors accounted for 36.62%, and the method of two-dimensional signal detection with external sensors accounted for 19.72%. The method of two-dimensional signal detection with internal sensors accounted for 11.97%. Among these methods, the highest detection rate is 100%, and the lowest detection rate is more than 70%. The similarities between the different methods are compared. The research results summarized in this paper show that with the progress of the times, a variety of new and better research methods have emerged, which have sped up the detection and diagnosis of rolling bearing faults. For example, the technology using artificial intelligence is still developing rapidly, such as artificial neural networks, convolutional neural networks, and machine learning. Although there are still defects, such methods can quickly discover a fault and its cause, enrich the database, and accumulate experience. More and more advanced techniques are applied in this field, and the detection method has better robustness and superiority.

Studies have suggested that the progress of most kidney diseases from occurrence to course and subsequent related complications are closely related to inflammatory reaction. Increased common leukocytes count in the family (neutrophils, eosinophils, basophils, lymphocytes, etc.) are also involved in the tissue damage of kidney diseases. However, these studies are only traditional observational studies, which cannot prove whether there is a causal relationship between these four kinds of leukocytes count and kidney diseases. We aim to explore the causal relationship between these four kinds of leukocytes count and kidney diseases by Mendelian randomization (MR). Large sample size of the genome-wide association database of four cell traits (neutrophil, basophil, lymphocyte, and eosinophil cell counts) in the leukocyte family were used as exposure variables. The outcome variables were various renal diseases (including chronic renal failure, acute renal failure, hypertensive heart or/and kidney disease, hypertensive renal disease, disorders resulting from impaired renal tubular function, and type 1 diabetes with renal complications). The covariates used in multivariable MR are also four cell traits related to blood cells (neutrophil, basophil, lymphocyte, and eosinophil cell counts). Instrumental variables and single nucleotide polymorphic loci were identified (P < 5 × 10−8. Linkage disequilibrium R2 < 0.001). The causal relationships were studied by inverse variance weighted (IVW), weighted median, and MR-Egger regression. Sensitivity analysis was also performed. In our study, IVW analysis results showed that increased neutrophil cell count was a risk factor for chronic renal failure (OR = 2.0245861, 95% CI = 1.1231207–3.649606, P = 0.01896524), increased basophil cell count was a risk factor for chronic renal failure (OR = 3.975935, 95% CI = 1.4871198–10.62998, P = 0.005942755). Basophil cell count was not a risk factor for acute renal failure (OR = 1.160434, 95% CI = 0.9455132–1.424207, P = 0.15448828). Increased basophil cell count was a protective factor for hypertensive heart and/or renal disease (OR = 0.7716065, 95% CI = 0.6484979–0.9180856, P = 0.003458707). Increased basophil cell count was a risk factor for disorders resulting from impaired renal tubular function (OR = 1.648131, 95% CI = 1.010116–2.689133, P = 0.04546835). Increased lymphocyte cell count was a risk factor for hypertensive renal disease (OR = 1.372961, 95% CI = 1.0189772–1.849915, P = 0.03719874). Increased eosinophil cell count was a risk factor for type 1 diabetes with renal complications (OR = 1.516454, 95% CI = 1.1826453–1.944482, P = 0.001028964). Macrophage inflammatory protein 1b levels was a protective factor for renal failure (OR = 0.9381862, 95% CI = 0.8860402–0.9934013, P = 0.02874872). After multivariable MR was used to correct covariates (neutrophil, basophil, and lymphocyte cell counts), the correlation effect between increased eosinophil cell counts and type 1 diabetes with renal complications was still statistically significant (P = 0.02201152). After adjusting covariates (neutrophil, basophil, and eosinophil cell counts) with multivariable MR, the correlation effect between increased lymphocyte cell counts and hypertensive renal disease was still statistically significant (P = 0.02050226). This study shows that increased basophils can increase the relative risk of chronic renal failure and renal tubular dysfunction, and reduce the risk of hypertensive heart disease and/or hypertensive nephropathy, while increased basophil cell count will not increase the relative risk of acute renal failure, increased neutrophil cell count can increase the risk of chronic renal failure, increased lymphocyte cell count can increase the relative risk of hypertensive nephropathy, and increased eosinophil cell count can increase the relative risk of type 1 diabetes with renal complications. Macrophage inflammatory protein 1b levels was a protective factor for renal failure. [ABSTRACT FROM AUTHOR]