STAT1: a novel candidate biomarker and potential therapeutic target of the recurrent aphthous stomatitis.

BACKGROUND: The recurrent aphthous stomatitis (RAS) frequently affects patient quality of life as a result of long lasting and recurrent episodes of burning pain. However, there were temporarily few available effective medical therapies currently. Drug target identification was the first step in drug discovery, was usually finding the best interaction mode between the potential target candidates and probe small molecules. Therefore, elucidating the molecular mechanism of RAS pathogenesis and exploring the potential molecular targets of medical therapies for RAS was of vital importance. METHODS: Bioinformatics data mining techniques were applied to explore potential novel targets, weighted gene co-expression network analysis (WGCNA) was used to construct a co-expression module of the gene chip data from GSE37265, and the hub genes were identified by the Molecular Complex Detection (MCODE) plugin. RESULTS: A total of 16 co-expression modules were identified, and 30 hub genes in the turquoise module were identified. In addition, functional analysis of Hub genes in modules of interest was performed, which indicated that such hub genes were mainly involved in pathways related to immune response, virus infection, epithelial cell, signal transduction. Two clusters (highly interconnected regions) were determined in the network, with score = 17.647 and 10, respectively, cluster 1 and cluster 2 are linked by STAT1 and ICAM1, it is speculated that STAT1 may be a primary gene of RAS. Finally, genistein, daidzein, kaempferol, resveratrol, rosmarinic acid, triptolide, quercetin and (-)-epigallocatechin-3-gallate were selected from the TCMSP database, and both of them is the STAT-1 inhibitor. The results of reverse molecular docking suggest that in addition to triptolide, (-)-Epigallocatechin-3-gallate and resveratrol, the other 5 compounds (flavonoids) with similar structures may bind to the same position of STAT1 protein with different docking score. CONCLUSIONS: Our study identified STAT1 as the potential biomarkers that might contribute to the diagnosis and potential therapeutic target of RAS, and we can also screen RAS therapeutic drugs from STAT-1 inhibitors.

A risk factor-based predictive model for linezolid-induced anaemia: A 7-year retrospective study.

WHAT IS KNOWN AND OBJECTIVE: The primary adverse reaction of linezolid is haematological toxicity, leading to thrombocytopenia and anaemia. This study aimed to investigate the risk factors of linezolid-induced anaemia (LI-AN) and establish a predictive model by multivariate logistic regression model analysis to predict LI-AN risks in Chinese adult patients. METHODS: Demographic and clinical data of patients who underwent linezolid therapy for more than three days between January 2014 and December 2020 in Zhongshan Hospital, Fudan University, were retrieved from the hospital's electronic medical record for analysis. Multivariate logistic regression analysis was employed to establish a predictive model, whose predictability was further evaluated by the area under the receiver operating characteristic (ROC) curve. RESULTS AND DISCUSSION: The study comprised 298 patients among the 2322 patients who underwent linezolid treatment between 2014 and 2020. Among the 298 patients, 32 (10.7%) developed anaemia with an average of 11.4 (SD 6.2) days after the initiation of linezolid therapy. Multivariate logistic analysis revealed that age ≥60 years (odds ratio [OR] 2.815, 95% confidence interval [CI] 1.242-6.379), higher total bilirubin (TBi) (OR 1.031, 95% CI 1.011-1.051), eGFR < 60 ml/(min·1.73 m2 ) (OR 2.537, 95% CI 1.054-6.106), duration of linezolid therapy (DLT) (OR 1.091, 95% CI 1.023-1.163) and intensive care unit (ICU) admittance (OR 2.664, 95% CI 1.150-6.174) were the independent risk factors for anaemia occurrence among patients receiving linezolid therapy. A logistic regression equation based on the five risk factors was subsequently established and transformed to obtain the calculation formula of the combined predictor: Y(Combined predictor)  = XTBi  + 34.5 × XAge≥60  + 31.1 × XeGFR<60  + 32.7 × XICU  + 2.9 × XDLT , (where Age ≥60 years, yes = 1, no = 0; eGFR < 60 ml/(min·1.73 m2 ), yes = 1, no = 0; ICU admittance, yes = 1, no = 0). The area under the ROC curve of the combined predictors equation was 0.773 with an optimal cut-off point value of 92.4, corresponding to a 75.0% sensitivity and 76.7% specificity. WHAT IS NEW AND CONCLUSION: LI-AN is associated with age (≥60 years), higher TBi, eGFR < 60 ml/(min·1.73 m2 ), DLT and ICU admittance. Physicians should thus calculate the combined predictor value at the beginning of linezolid treatment to predict and evaluate the risk of LI-AN. An optimal cut-off value larger than 92.4 indicates that the patient has a higher LI-AN risk. As such, Hb levels should be monitored regularly, and dosage regimens adjusted accordingly to prevent anaemia occurrence. This study provides an evidence-based logistic model that reduces LI-AN incidences and promotes the safe clinical use of linezolid.

Enhancing parameter design for full-aperture rapid planar polishing based on fuzzy optimization.

Full-aperture rapid planar polishing (RPP) has been widely used in optics manufacturing for high-power laser systems. A new, to the best of our knowledge, fuzzy optimization method was presented to assess the precision and productivity of RPP. Unlike the traditional method that can only set one objective, the proposed method can combine different objectives for RPP into one overall indicator. The material removal rate, material removal uniformity, and synthetical fuzzy indicator of RPP (SFIRPP) were selected as the objectives to prove the validity of fuzzy optimization. The rotational speed of optics, polishing pressure, and swing speed were set as the optimized parameters. The orthogonal design was introduced to simplify the operations of experiments. A semi-gamma distribution was used to fit the curve of SFIRPP. The experimental results indicated that the optimized parameters under SFIRPP obtained better manufacturing precision and productivity for flat optics simultaneously. The proposed fuzzy optimization provides the potential for enhancing the optimal parameters of RPP.

Detection of Single Steel Strand Distribution in Grouting Duct Based on Capacitive Sensing Technique.

Grouting ducts (containing steel strands) are widely used to increase the structural strengths of infrastructures. The determination of the steel strand's integrity inside of ducts and the grouting quality are important for a strength evaluation of the structure. In this study, a capacitive sensing technique was applied to identify the cross-sectional distribution of the steel strands. The distribution was expressed in polar coordinates in an external post-tensioned pre-stressed duct model. An improved capacitive sensor structure was designed, which consisted of four electrodes, and different electrode-pairs were used to determine various locations' information of the steel strands. Two rounds of measurements were conducted using the designed sensor to detect the angle (θ) and center distance (r) of the steel strand in the duct. The simulated and experimental results are presented and analyzed. In general, it is difficult to locate the angle of a steel strand directly from first-round capacitance measurements by analyzing the experimental results. Our method based on Q-factor analysis was presented for the position detection of a steel bar in an external post-tensioned pre-stressed duct. The center distance of the steel bar could be identified by second-round capacitance measurements. The processed results verified the effectiveness of the proposed capacitive sensor structure. Thus, the capacitive sensing technique exhibited potential for steel strand cross-section distribution detection in external post-tensioned pre-stressed ducts.

Ultrasonic Transmission Tomography Sensor Design for Bubble Identification in Gas-Liquid Bubble Column Reactors.

Scientists require methods to monitor the distribution of gas bubbles in gas-liquid bubble column reactors. One non-destructive method that can potential satisfy this requirement in industrial situations is ultrasonic transmission tomography (UTT). In this paper, an ultrasonic transmission tomography sensor is designed for measuring bubble distribution in a reactor. Factors that influence the transducer design include transmission energy loss, the resonance characteristics and vibration modes of the transducer, and diffusion angles of the transducers, which are discussed. For practical application, it was found that an excitation frequency of 300 kHz could identify the location and size of gas bubbles. The vibration mode and diffusion also directly affect the quality of the imaging. The geometric parameters of the transducer (a cylinder transducer with a 10 mm diameter and 6.7 mm thickness) are designed to achieve the performance requirements. A UTT system, based on these parameters, was built in order to verify the effectiveness of the designed ultrasonic transducer array. A Sector-diffusion-matrix based Linear Back Projection (SLBP) was used to reconstruct the gas/liquid two-phase flow from the obtained measurements. Two other image processing methods, based on SLBP algorithm named SLBP-HR (SLBP-Hybrid Reconstruction) and SLBP-ATF (SLBP-Adaptive Threshold Filtering), were introduced, and the imaging results are presented. The imaging results indicate that a gas bubble with a 3 mm radius can be identified from reconstructed images, and that three different flow patterns, namely, single gas bubble, double gas bubble with different diameters, and eccentric flow, can be identified from reconstructed images. This demonstrates that the designed UTT sensor can effectively measure bubble distribution in gas-liquid bubble column reactors.

Determination of optimized removal functions for imprinting continuous phase plates using fuzzy theory.

A new evaluation method based on fuzzy theory was proposed to assess the manufacturing efficiency and accuracy of continuous phase plates (CPPs) with magnetorheological finishing imprinting. Two-dimensional sinusoidal waves were employed to verify the effectiveness of the proposed method theoretically and experimentally in terms of two parameters, error root mean square and processing time, which indicate the accuracy and efficiency of CPP manufacture. The weight factor was used for balancing the priorities of processing time and accuracy in our method. The simulations and experiments were compared based on our proposed method. The results show that the optimum removal functions for various spatial periods result in good agreement between simulations and experiments, and furthermore, relative errors are 6.07%, 2.62%, and 6.00% for CPPs with spatial periods of 12 mm, 18 mm, and 30 mm, respectively. All the results indicate that the method provides a valid and feasible way to select an optimized removal function for imprinting the patterns of CPPs.