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.

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

Epitranscriptome studies have shown that critical RNA modifications drive tumorigenicity; however, the role of 5-methylcytosine (mC) RNA methylation remains poorly understood. We extracted 17 mC regulators and clustered distinct mC 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.

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.

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.

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.

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.

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.

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.

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.

[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.

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.

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.

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.

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.

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.

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.

[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.

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.

[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.

Application of empirical mode decomposition to remove the wall components in Doppler ultrasound signals: a simulation study.

Doppler ultrasound blood flow analysis systems normally use a high-pass filter to remove the large, low frequency components from the vessel wall from the blood flow signal. Unfortunately, the filter also removes the low frequency Doppler signals arising from slow moving blood. In this paper, we propose to use a novel technique, called the empirical mode decomposition (EMD), to remove the wall components from the mixed signals.

The removal of wall components in Doppler ultrasound signals by using the empirical mode decomposition algorithm.

Doppler ultrasound systems, used for the noninvasive detection of the vascular diseases, normally employ a high-pass filter (HPF) to remove the large, low-frequency components from the vessel wall from the blood flow signal. Unfortunately, the filter also removes the low-frequency Doppler signals arising from slow-moving blood. In this paper, we propose to use a novel technique, called the empirical mode decomposition (EMD), to remove the wall components from the mixed signals.

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.

Noise reduction in Doppler ultrasound signals using an adaptive decomposition algorithm.

A novel de-noising method for improving the signal-to-noise ratio (SNR) of Doppler ultrasound blood flow signals, called the matching pursuit method, has been proposed. Using this method, the Doppler ultrasound signal was first decomposed into a linear expansion of waveforms, called time-frequency atoms, which were selected from a redundant dictionary named Gabor functions. Subsequently, a decay parameter-based algorithm was employed to determine the decomposition times.

Correction for broadening in Doppler blood flow spectrum estimated using wavelet transform.

The conventionally used spectral estimation technique for Doppler blood flow signal analysis is short-time Fourier transform (STFT). But this method requires stationarity of the signal during the window interval. Wavelet transform (WT), which has a flexible time-frequency window, is particularly suitable for nonstationary signals.