Impacts of heavy smoking on non-coding RNA expression for patients with esophageal carcinoma.

BACKGROUND: Smoking is a well-recognized risk factor for esophageal carcinoma, but the underlying molecular mechanism remains unclear. Previous studies have demonstrated the predictive value of non-coding RNA (ncRNA) for the prognosis of esophageal carcinoma; however, the expression of smoking-related ncRNAs has not been systematically characterized. Herein, we comprehensively assessed the hazard of heavy smoking and its impact on ncRNA expression patterns in patients with esophageal carcinoma. METHODS: Transcriptome and clinical features of patients with esophageal carcinoma were acquired from The Cancer Genome Atlas (TCGA) database. Cox regression analysis was employed to calculate the hazard ratio (HR) of smoking behavior. Differential expression analysis was conducted with the "edgeR" package. The smoking-related RNA regulatory network was based on lncRNA‒miRNA and miRNA‒mRNA pairs and visualized by Cytoscape 3.7.1. We applied Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses for functional annotation. Univariate and least absolute shrinkage and selection operator (LASSO) Cox regression analyses were used for model construction. We applied Kaplan‒Meier analysis with a log-rank test for survival analysis, with group comparison by the Wilcoxon signed ranked test. RESULTS: Heavy smoking contributed to the poor overall survival of esophageal carcinoma, with an HR of 3.167 (95% CI: 1.077-9.312). A total of 195 lncRNAs and 73 miRNAs were differentially expressed between patients with or without smoking behavior. We constructed smoking-related RNA regulatory networks, and functional annotation enriched a series of cancer-related pathways. We generated a smoking-related prognostic risk score and found that patients with a high score had a poor prognosis. Fourteen out of 23 immune cell types differentially infiltrated into a distinct risk group, while no correlation was observed between the risk score and immune cells. CONCLUSION: Altogether, we profiled smoking-related ncRNA expression patterns and constructed an RNA regulatory network, providing a landscape of smoking-related molecular mechanisms of esophageal carcinoma. The smoking-related risk score, which was related to prognosis, revealed that tobacco smoking could suppress tumor immunity via the ncRNA mechanism.

Molecular features, biological behaviors and clinical implications of m5C RNA methylation modification regulators in gastrointestinal cancers.

Epitranscriptome studies have shown that critical RNA modifications drive tumorigenicity; however, the role of 5-methylcytosine (m5C) RNA methylation remains poorly understood. We extracted 17 m5C regulators and clustered distinct m5C modification patterns by consensus clustering analysis. Gene set variation and single-sample gene set enrichment analysis were applied to quantify functional analysis and immune infiltration. The least absolute shrinkage and selection operator was employed to develop a prognostic risk score. Kaplan-Meier with log-rank test was used for survival analysis. Differential expression analysis was performed with the "limma" R package. Wilcoxon signed ranked test or Kruskal-Wallis test was used to compare groups. We observed that m5C RNA methylation was commonly upregulated in gastrointestinal cancer and related to prognosis. Clusters were identified for m5C patterns, with distinct immune infiltrations and functional pathways. The risk scores of m5C regulators were independent risk factors. Differentially expressed mRNAs (DEmRNAs) in m5C clusters were involved in cancer-related pathways. The methylation-based m5Cscore showed a significant effect on the prognosis. Patients with a lower m5Cscore exhibited more therapeutic efficiency on anti-CTLA4 therapy in liver cancer, while the combination of anti-CTLA4 therapy and pd1 was more efficient for patients with a lower m5Cscore in pancreatic cancer. We uncovered dysregulations of m5C-related regulators in gastrointestinal cancer and their associations with overall survival. Some immune cells were differently infiltrated in distinct m5C modification patterns, indicating their potential impacts on gastrointestinal cancer cell-immune. Moreover, an m5Cscore, derived from DEmRNAs in specific clusters, can serve as a classifier for immunotherapy.

Inactivated COVID-19 vaccine booster dose shortened the viral shedding time of patients infected with the Omicron variant BA.2.

OBJECTIVES: We assessed the effect of inactivated COVID-19 vaccine boosting immunization on the viral shedding time for patients infected with the Omicron variant BA.2. METHODS: We performed a real-world study by analyzing the outbreak data of patients infected with the COVID-19 Omicron variant BA.2 from March to May 2022 in Shanghai, China. Patients were categorized into three groups, including not fully vaccinated (zero and one dose), fully vaccinated (two doses), and booster-vaccinated (three doses). RESULTS: A total of 4443 patients infected with COVID-19 were included in the analysis. The proportion of viral shedding within 14 days in the three groups was 94.7%, 95.5%, and 96.7%, respectively (P <0.001). After adjusting for sex, age, underlying conditions, and clinical symptoms, the booster vaccination had a 29% increased possibility (hazard ratio: 1.29, 95% confidence interval: 1.18-1.41) of no detectable viral shedding within 14 days, whereas the fully vaccinated group had an 11% increased possibility of no detectable viral shedding (hazard ratio: 1.11, 95% confidence interval: 1.01-1.23). The effect of booster vaccination was more significant in males, the elderly, and people with underlying conditions or symptomatic infections. CONCLUSION: Our study confirmed that the booster vaccination could significantly shorten the viral shedding time of patients infected with the Omicron variant BA.2.

Environment pollutants exposure affects the endogenous activation of within-host Mycobacterium tuberculosis.

OBJECTIVE: Epidemiological studies have linked ambient pollutants with tuberculosis (TB) risk, but the association has not been fully understood. Here, for the first time, we applied whole-genome sequencing (WGS) to assess the reproductive state of Mycobacterium tuberculosis (MTB) by profiling the mutation rate of MTB (MTBMR) during within-host endogenous reactivated progression, intending to dissect the actual effects of ambient pollutants on the endogenous reactivation. METHODS: We conducted a retrospective cohort study on bacteriologically confirmed TB patients and followed them for relapse in Jiangsu and Sichuan Province, China. Endogenous and exogenous activation were distinguished by WGS of the pathogen. The average concentration of air pollution was estimated by considering a lag of 0-1 to 0-12 months. We applied a generalized additive model with a Poisson function to evaluate the relationships between ambient pollutants exposure and MTBMR. RESULTS: In the single-pollutant adjusted models, the maximum effect for PM10 (MTBMR increase: 81.87%, 95% CI: 38.38, 139.03) and PM2.5 (MTBMR increase: 73.91%, 95% CI: 22.17, 147.55) was observed at a lag of 0-12 months for every 10 µg/m³ increase. For SO2, the maximum effect was observed at lag 0-8 months, with MTBMR increasing by 128.06% (95% CI: 45.92, 256.44); and for NO2, the maximum effect was observed at lag 0-9 months, with MTBMR increasing by 124.02% (95% CI: 34.5, 273.14). In contrast, the O3 concentration was inversely associated with MTBMR, and the maximum reduction of MTBMR was 6.18% (95% CI: -9.24, -3.02) at a lag of 0-9 months. Similar results were observed for multi-pollutant models. CONCLUSIONS: Increased exposure to ambient pollutants (PM10, PM2.5, SO2, and NO2) contributed to a faster MTBMR, indicating that MTB exhibits increased reproductive activity, thus accelerating within-host endogenous reactivation. O3 exposure could decrease the MTBMR, suggesting that MTB exerts low reproductive activity by inhibiting within-host endogenous activation.

A clinical indicator-based prognostic model predicting treatment outcomes of pulmonary tuberculosis: a prospective cohort study.

OBJECTIVES: Identifying prognostic factors helps optimize the treatment regimen and promote favorable outcomes. We conducted a prospective cohort study on patients with pulmonary tuberculosis to construct a clinical indicator-based model and estimate its performance. METHODS: We performed a two-stage study by recruiting 346 pulmonary tuberculosis patients diagnosed between 2016 and 2018 in Dafeng city as the training cohort and 132 patients diagnosed between 2018 and 2019 in Nanjing city as the external validation population. We generated a risk score based on blood and biochemistry examination indicators by the least absolute shrinkage and selection operator (LASSO) Cox regression. Univariate and multivariate Cox regression models were used to assess the risk score, and the strength of association was expressed as the hazard ratio (HR) and 95% confidence interval (CI). We plotted the receiver operating characteristic (ROC) curve and calculated the area under the curve (AUC). Internal validation was conducted by 10-fold cross-validation. RESULTS: Ten significant indicators (PLT, PCV, LYMPH, MONO%, NEUT, NEUT%, TBTL, ALT, UA, and Cys-C) were selected to generate the risk score. Clinical indicator-based score (HR: 10.018, 95% CI: 4.904-20.468, P < 0.001), symptom-based score (HR: 1.356, 95% CI: 1.079-1.704, P = 0.009), pulmonary cavity (HR: 0.242, 95% CI: 0.087-0.674, P = 0.007), treatment history (HR: 2.810, 95% CI: 1.137-6.948, P = 0.025), and tobacco smoking (HR: 2.499, 95% CI: 1.097-5.691, P = 0.029) were significantly related to the treatment outcomes. The AUC was 0.766 (95% CI: 0.649-0.863) in the training cohort and 0.796 (95% CI: 0.630-0.928) in the validation dataset. CONCLUSION: In addition to the traditional predictive factors, the clinical indicator-based risk score determined in this study has a good prediction effect on the prognosis of tuberculosis.

Application of Computer-Aided Diagnosis to the Sonographic Evaluation of Cervical Lymph Nodes.

We initiated an observer study to evaluate a computerized system developed in our previous study for automatic extraction of 10 features and estimation of the malignancy probability of cervical nodes in sonograms. In the present study, five expert radiologists and five resident radiologists interpreted the sonograms of 178 nodes. The malignancy rating and patient management recommendation (biopsy or follow-up) were made without and then with the computer aid. Under these two reading conditions, the performances of radiologists and agreement among a group of radiologists were evaluated by using the receiver operating characteristic (ROC) analysis and the κ statistic, respectively. With the computer aid, the performances of radiologists improved significantly, as indicated by the increase in the area under the ROC curve (Az) from 0.843 to 0.896 (p = 0.031) and from 0.705 to 0.822 (p < 0.001), for the expert and resident groups, respectively. Agreement among all 10 radiologists improved from slight to moderate as indicated by an increase in the κ value from 0.195 to 0.421 (p < 0.001). The average performance of residents with aid (Az = 0.822) was close to that of experts without aid (Az = 0.843). Results indicate that computer-aided diagnosis is useful to improve radiologist performance (especially that of inexperienced radiologists) in the ultrasonographic evaluation of cervical nodes and to reduce variability among radiologists.

Intelligent speckle reducing anisotropic diffusion algorithm for automated 3-D ultrasound images.

A novel 3-D filtering method is presented for speckle reduction and detail preservation in automated 3-D ultrasound images. First, texture features of an image are analyzed by using the improved quadtree (QT) decomposition. Then, the optimal homogeneous and the obvious heterogeneous regions are selected from QT decomposition results. Finally, diffusion parameters and diffusion process are automatically decided based on the properties of these two selected regions. The computing time needed for 2-D speckle reduction is very short. However, the computing time required for 3-D speckle reduction is often hundreds of times longer than 2-D speckle reduction. This may limit its potential application in practice. Because this new filter can adaptively adjust the time step of iteration, the computation time is reduced effectively. Both synthetic and real 3-D ultrasound images are used to evaluate the proposed filter. It is shown that this filter is superior to other methods in both practicality and efficiency.

Computer-aided King classification of scoliosis.

OBJECTIVE: Surgical planning for scoliosis relies on the classification of spinal curve pattern. The widely used King classification is subject to human measurement and judgment errors. To reduce the variability of King classification, a computer-aided method is proposed and its reliability is evaluated in this study. METHODS: At the first step, endplate inclination and position of each vertebra are measured by a computerized system on the posteroanterior radiograph. Based on these measurements, the apical and end vertebrae are identified and then the Cobb angles are calculated automatically. The system subsequently classifies the curve types automatically based on the computerized Cobb measurements, the vertebral inclination, and the analysis of the relationship between the center sacral vertical line, and the apical lumbar vertebra. Five observers participated in the experiments. The kappa statistic was used to evaluate the variability. RESULTS: Classifications of 105 scoliotic cases by the five observers showed that with the aid of our system, the average intraobserver and interobserver kappa values improved from 0.75 to 0.90 and from 0.66 to 0.86, respectively. CONCLUSION: Results indicate that the proposed computerized system can assist a surgeon with the King classification of scoliosis.

Multivariable time series prediction for the icing process on overhead power transmission line.

The design of monitoring and predictive alarm systems is necessary for successful overhead power transmission line icing. Given the characteristics of complexity, nonlinearity, and fitfulness in the line icing process, a model based on a multivariable time series is presented here to predict the icing load of a transmission line. In this model, the time effects of micrometeorology parameters for the icing process have been analyzed. The phase-space reconstruction theory and machine learning method were then applied to establish the prediction model, which fully utilized the history of multivariable time series data in local monitoring systems to represent the mapping relationship between icing load and micrometeorology factors. Relevant to the characteristic of fitfulness in line icing, the simulations were carried out during the same icing process or different process to test the model's prediction precision and robustness. According to the simulation results for the Tao-Luo-Xiong Transmission Line, this model demonstrates a good accuracy of prediction in different process, if the prediction length is less than two hours, and would be helpful for power grid departments when deciding to take action in advance to address potential icing disasters.

Computerized Lenke classification of scoliotic spine.

A computer-aided approach was proposed to reduce the variability in the Lenke classification. At the first step, endplate inclination of each vertebra on both the coronal and sagittal radiographs was measured by a computerized system. The Cobb angles of the proximal thoracic, the main thoracic, and the thoracolumbar/lumbar curves were then automatically calculated in the standing and side-bending coronal planes and the standing sagittal plane. A computerized algorithm automatically classified the spinal type. The classification results of 37 scoliotic patients by five observers showed that with the computer aid, the average interobserver and intraobserver kappa values were improved from 0.77 to 0.88 and from 0.68 to 0.83, respectively. This computerized tool can assist in the Lenke classification of scoliosis.

3-D reconstruction of the spine from biplanar radiographs based on contour matching using the Hough transform.

The purpose of this study was to develop and evaluate a method for three-dimensional (3-D) reconstruction of the spine from biplanar radiographs. The approach was based on vertebral contour matching for estimating vertebral orientations and locations. Vertebral primitives were initially positioned under constraint of the 3-D spine midline, which was estimated from manually identified control points. Vertebral orientations and locations were automatically adjusted by matching projections of 3-D primitives with vertebral edges on biplanar radiographs based on the generalized Hough transform technique with a deformation tolerant matching strategy. We used graphics processing unit to accelerate reconstruction. Accuracy and precision were evaluated using radiographs from 15 scoliotic patients and a spine model in 24 poses. On in vivo radiographs, accuracy was within 2.8° for orientation and 2.4 mm for location; precision was within 2.3° for orientation and 2.1 mm for location. results were slightly better on model radiographs than on in vivo radiographs but without significance (p>0.05). The duration for user intervention was less than 2 min, and the computation time was within 3 min. Results indicated the method's reliability. It is a promising tool to determine 3-D spinal geometry with acceptable user interaction.

[An approach for the measurement of the surface area of scalp flap over the cranial defect after decompressive craniectomy].

OBJECTIVE: To introduce a simple, fast and universal measuring method used in measurement of the surface area of scalp flap over the cranial defect after decompressive craniectomy. METHODS: The first step: CT images of the patient with craniocerebral trauma after decompressive craniectomy were obtained and imported into Mimics. The second step: based on the defined threshold, the 3D geometric models of brain and skull were reconstructed after the original Dicom format pictures three-dimensional processed by Mimics. The third step: based on the two builded 3D models, utilizing the segmentation and measurement tools of Mimics to conduct cutting, splitting and measuring operations for the 3D model of brain. The forth step: estimating the surface area of scalp flap over the removed bone flap by using mathematical computation methods. RESULTS: The application of the introduced method estimated the surface area of scalp flap over the cranial defect of different people with different position of craniocerebral trauma. CONCLUSIONS: This paper introduces a simple, fast and universal new measuring method. We can conveniently estimate the surface area of scalp flap by using the introduced method.

A computer simulation model for Doppler ultrasound signals from pulsatile blood flow in stenosed vessels.

A computer simulation model based on an analytic flow velocity distribution is proposed to generate Doppler ultrasound signals from pulsatile blood flow in the vessels with various stenosis degrees. The model takes into account the velocity field from pulsatile blood flow in the stenosed vessels, sample volume shape and acoustic factors that affect the Doppler signals. By analytically solving the Navier-Stokes equations, the velocity distributions of pulsatile blood flow in the vessels with various stenosis degrees are firstly calculated according to the velocity at the axis of the circular tube. Secondly, power spectral density (PSD) of the Doppler signals is estimated by summing the contribution of all scatterers passing through the sample volume grouped into elemental volumes. Finally, Doppler signals are generated using cosine-superposed components that are modulated by the PSD functions that vary over the cardiac cycle. The results show that the model generates Doppler blood flow signals with characteristics similar to those found in practice. It could be concluded that the proposed approach offers the advantages of computational simplicity and practicality for simulating Doppler ultrasound signals from pulsatile blood flow in stenosed vessels.

A computer-aided Cobb angle measurement method and its reliability.

STUDY DESIGN: Development of a computer-aided Cobb measurement method and evaluation of its reliability. OBJECTIVES: To reduce the variability of Cobb angle measurement by developing the computer-aided method and to investigate if the developed method is sensitive to observer skill levels or experiences. SUMMARY OF BACKGROUND DATA: Therapeutic decisions for scoliosis heavily rely on the Cobb angle measured from consecutive radiographs. The manual Cobb measurement is subject to human errors. The observer error is 3 to 10 degrees resulted from different end-vertebrae selection and/or manually drawing variable best-fit lines to the endplates of the end-vertebrae. METHODS: A fussy Hough transform technique was used to develop a computer-aided method to detect the vertebral endplates. The Cobb angle, upper end-vertebra, and lower end-vertebra were then measured automatically. The computer-aided method was tested twice by each of 3 observers in 84 posteroanterior radiographs from patients with adolescent idiopathic scoliosis. The intraobserver and interobserver errors were analyzed. RESULTS: Both the intraobserver and interobserver reliability analyses resulted in the intraclass correlation coefficients higher than 0.9 for the Cobb angle. The average intraobserver and interobserver errors were less than 3 degree for the Cobb angle, and less than 0.3 levels for both the upper and lower end-vertebral identification. There were no significant differences in the measurement variability between groups of curve location (thoracic, thoracolumbar, and lumbar), curve direction (right and left), curve magnitude (curves less than 25 degree, between 25 and 45 degrees, and more than 45 degree), and observer experience (experienced observer and inexperienced observers). CONCLUSIONS: Compared with the documented results, variability of the Cobb measurement is reduced by using the developed computer-aided method. This method can help orthopedic surgeons measure the Cobb angle more reliably during scoliosis clinics.

Computer-aided assessment of scoliosis on posteroanterior radiographs.

In order to reduce the observer variability in radiographic scoliosis assessment, a computer-aided system was developed. The system semi-automatically measured the Cobb angle and vertebral rotation on posteroanterior radiographs based on Hough transform and snake model, respectively. Both algorithms were integrated with the shape priors to improve the performance. The system was tested twice by each of three observers. The intraobserver and interobserver reliability analyses resulted in the intraclass correlation coefficients higher than 0.9 and 0.8 for Cobb measurement on 70 radiographs and rotation measurement on 156 vertebrae, respectively. Both the Cobb and rotation measurements resulted in the average intraobserver and interobserver errors less than 2 degrees and 3 degrees , respectively. There were no significant differences in the measurement variability between groups of curve location, curve magnitude, observer experience, and vertebra location. Compared with the documented results, measurement variability is reduced by using the developed system. This system can help orthopedic surgeons assess scoliosis more reliably.

An improved graph cut segmentation method for cervical lymph nodes on sonograms and its relationship with node's shape assessment.

A modified graph cut was proposed under the elliptical shape constraint to segment cervical lymph nodes on sonograms, and its effect on the measurement of short axis to long axis ratio (S/L) was investigated by using the relative ultimate measurement accuracy (RUMA). Under the same user inputs, the proposed algorithm successfully segmented all 60 sonograms tested, while the traditional graph cut failed. The mean RUMA resulted from the developed method was comparable to that resulted from the manual segmentation. Results indicated that utilizing the elliptical shape prior could appreciably improve the graph cut for nodes segmentation, and the proposed method satisfied the accuracy requirement of S/L measurement.

[Using CTS and PK-PD models to predict the effect of uncertainty about population parameters on clinical trial power].

The traditional clinical trail designs always depend on expert opinions and lack statistical evaluations. In this article, we present a method and illustrate how population parameter uncertainty may be incorporated in the overall simulation model. Using the techniques of clinical trail simulation (CTS) and setting up predictions on the basis of pharmacokinetics-pharmacodynamics (PK-PD) models, we advance the modeling methods for simulation, for treatment effects, and for the clinical trail power under the given PK-PD conditions. Then we discuss the model of uncertainty, suggest an ANOVA-based method, add eta2 statistics for sensitivity analysis, and canvass the effect of uncertainty about population parameters on clinical trail power. The results from simulations and the indices derived from this type of sensitivity analysis may be used for grading the influence on the prediction quality of uncertainty about different population parameters. The experiment results are satisfactory and the approach presented has practical value in clinical trails.

Preservation of quadrature Doppler signals from bidirectional slow blood flow close to the vessel wall using an adaptive decomposition algorithm.

A novel approach based on the phasing-filter (PF) technique and the empirical mode decomposition (EMD) algorithm is proposed to preserve quadrature Doppler signal components from bidirectional slow blood flow close to the vessel wall. Bidirectional mixed Doppler ultrasound signals, which were echoed from the forward and reverse moving blood and vessel wall, were initially separated to avoid the phase distortion of quadrature Doppler signals (which is induced from direct decomposition by the nonlinear EMD processing). Separated unidirectional mixed Doppler signals were decomposed into intrinsic mode functions (IMFs) using the EMD algorithm and the relevant IMFs that contribute to blood flow components were identified and summed to give the blood flow signals, whereby only the components from the bidirectional slow blood flow close to the vessel wall were retained independently. The complex quadrature Doppler blood flow signal was reconstructed from a combination of the extracted unidirectional Doppler blood flow signals. The proposed approach was applied to simulated and clinical Doppler signals. It is concluded from the experimental results that this approach is practical for the preservation of quadrature Doppler signal components from the bidirectional slow blood flow close to the vessel wall, and may provide more diagnostic information for the diagnosis and treatment of vascular diseases.

[Evaluation studies of ultrasonic image features extraction for cervical lymph nodes].

Abstract Ultrasonic image features of cervical lymph nodes were extracted by a computerized scheme. The scheme quantified the parameters of shape, border, cortex to medulla ratio, distributing of medulla, long axis to short axis ratio, vascular density and vascular pattern features. Then correlations between the experts andthe computerized scheme for assessing parameters in corresponding categories were computed to evaluate the validity of the parameters extracted by the computer. 106 cervical lymph nodes were studied, and the results showed that good agreement was seen in NRL (normalized radial length) zero crossing count, convex hull depth, long axis to short axis ratio, the vascular density and the entropy of the blood mapping boundary points' distribution.

ECG compression using uniform scalar dead-zone quantization and conditional entropy coding.

A new wavelet-based method for the compression of electrocardiogram (ECG) data is presented. A discrete wavelet transform (DWT) is applied to the digitized ECG signal. The DWT coefficients are first quantized with a uniform scalar dead-zone quantizer, and then the quantized coefficients are decomposed into four symbol streams, representing a binary significance stream, the signs, the positions of the most significant bits, and the residual bits. An adaptive arithmetic coder with several different context models is employed for the entropy coding of these symbol streams. Simulation results on several records from the MIT-BIH arrhythmia database show that the proposed coding algorithm outperforms some recently developed ECG compression algorithms.