Correspondence Estimation from Non-Rigid Motion Information

The DIET (Digital Image Elasto Tomography) system is a novel approach to screen for breast cancer using only optical imaging information of the surface of a vibrating breast. 3D tracking of skin surface motion without the requirement of external markers is desirable. A novel approach to establish point correspondences using pure skin images is presented here. Instead of the intensity, motion is used as the primary feature, which can be extracted using optical flow algorithms. Taking sequences of multiple frames into account, this motion information alone is accurate and unambiguous enough to allow for a 3D reconstruction of the breast surface. Two approaches, direct and probabilistic, for this correspondence estimation are presented here, suitable for different levels of calibration information accuracy. Reconstructions show that the results obtained using these methods are comparable in accuracy to marker-based methods while considerably increasing resolution. The presented method has high potential in optical tissue deformation and motion sensing

Automated Intelligent Monitoring and the Controlling Software System for Solar Panels

The inspection of the solar panels on a periodic basis is important to improve longevity and ensure performance of the solar system. To get the most solar potential of the photovoltaic (PV) system is possible through an intelligent monitoring & controlling system. The monitoring & controlling system has rapidly increased its popularity because of its user-friendly graphical interface for data acquisition, monitoring, controlling and measurements. In order to monitor the performance of the system especially for renewable energy source application such as solar photovoltaic (PV), data-acquisition systems had been used to collect all the data regarding the installed system. In this paper the development of a smart automated monitoring & controlling system for the solar panel is described, the core idea is based on IoT (the Internet of Things). The measurements of data are made using sensors, block management data acquisition modules, and a software system. Then, all the real-time data collection of the electrical output parameters of the PV plant such as voltage, current and generated electricity is displayed and stored in the block management. The proposed system is smart enough to make suggestions if the panel is not working properly, to display errors, to remind about maintenance of the system through email or SMS, and to rotate panels according to a sun position using the Ephemeral table that stored in the system. The advantages of the system are the performance of the solar panel system which can be monitored and analyzed

Quantitative model for inferring dynamic regulation of the tumour suppressor gene p53

Background: The availability of various "omics" datasets creates a prospect of performing the study of genome-wide genetic regulatory networks. However, one of the major challenges of using mathematical models to infer genetic regulation from microarray datasets is the lack of information for protein concentrations and activities. Most of the previous researches were based on an assumption that the mRNA levels of a gene are consistent with its protein activities, though it is not always the case. Therefore, a more sophisticated modelling framework together with the corresponding inference methods is needed to accurately estimate genetic regulation from "omics" datasets. Results: This work developed a novel approach, which is based on a nonlinear mathematical model, to infer genetic regulation from microarray gene expression data. By using the p53 network as a test system, we used the nonlinear model to estimate the activities of transcription factor (TF) p53 from the expression levels of its target genes, and to identify the activation/inhibition status of p53 to its target genes. The predicted top 317 putative p53 target genes were supported by DNA sequence analysis. A comparison between our prediction and the other published predictions of p53 targets suggests that most of putative p53 targets may share a common depleted or enriched sequence signal on their upstream non-coding region. Conclusions: The proposed quantitative model can not only be used to infer the regulatory relationship between TF and its down-stream genes, but also be applied to estimate the protein activities of TF from the expression levels of its target genes

Coronary angiography enhancement for visualization

High quality visualization on X-ray angiograms is of great significance both for the diagnosis of vessel abnormalities and for coronary interventions. Algorithms for improving the visualization of detailed vascular structures without significantly increasing image noise are currently demanded in the market. A new algorithm called stick-guided lateral inhibition (SGLI) is presented for increasing the visibility of coronary vascular structures. A validation study was set up to compare the SGLI algorithm with the conventional unsharp masking (UM) algorithm on 20 still frames of coronary angiographic images. Ten experienced QCA analysts and nine cardiologists from various centers participated in the validation. Sample scoring value (SSV) and observer agreement value (OAV) were defined to evaluate the validation result, in terms of enhancing performance and observer agreement, respectively. The mean of SSV was concluded to be 77.1 ± 11.9%, indicating that the SGLI algorithm performed significantly better than the UM algorithm (P-value < 0.001). The mean of the OAV was concluded to be 70.3%, indicating that the average agreement with respect to a senior cardiologist was 70.3%. In conclusion, this validation study clearly demonstrates the superiority of the SGLI algorithm in the visualization of coronary arteries from X-ray angiograms

Safety and efficacy of intrathecal antibodies to Nogo-A in patients with acute cervical spinal cord injury: A randomised, double-blind, multicentre, placebo-controlled, phase 2b trial

Background: Spinal cord injury results in permanent neurological impairment and disability due to the absence of spontaneous regeneration. NG101, a recombinant human antibody, neutralises the neurite growth-inhibiting protein Nogo-A, promoting neural repair and motor recovery in animal models of spinal cord injury. We aimed to evaluate the efficacy of intrathecal NG101 on recovery in patients with acute cervical traumatic spinal cord injury.Methods: This randomised, double-blind, placebo-controlled phase 2b clinical trial was done at 13 hospitals in the Czech Republic, Germany, Spain, and Switzerland. Patients aged 18-70 years with acute, complete or incomplete cervical spinal cord injury (neurological level of injury C1-C8) within 4-28 days of injury were eligible for inclusion. Participants were initially randomly assigned 1:1 to intrathecal treatment with 45 mg NG101 or placebo (phosphate-buffered saline); 18 months into the study, the ratio was adjusted to 3:1 to achieve a final distribution of 2:1 to improve enrolment and drug exposure. Randomisation was done using a centralised, computer-based randomisation system and was stratified according to nine distinct outcome categories with a validated upper extremity motor score (UEMS) prediction model based on clinical parameters at screening. Six intrathecal injections were administered every 5 days over 4 weeks, starting within 28 days of injury. Investigators, study personnel, and study participants were masked to treatment allocation. The primary outcome was change in UEMS at 6 months, analysed alongside safety in the full analysis set. The completed trial was registered at ClinicalTrials.gov, NCT03935321.Findings: From May 20, 2019, to July 20, 2022, 463 patients with acute traumatic cervical spinal cord injury were screened, 334 were deemed ineligible and excluded, and 129 were randomly assigned to an intervention (80 patients in the NG101 group and 49 in the placebo group). The full analysis set comprised 78 patients from the NG101 group and 48 patients from the placebo group. 107 (85%) patients were male and 19 (15%) patients were female, with a median age of 51·5 years (IQR 30·0-60·0). Across all patients, the primary endpoint showed no significant difference between groups (with UEMS change at 6 months 1·37 [95% CI -1·44 to 4·18]; placebo group mean 19·20 [SD 11·78] at baseline and 30·91 [SD 15·49] at day 168; NG101 group mean 18·23 [SD 15·14] at baseline and 31·31 [19·54] at day 168). Treatment-related adverse events were similar between groups (nine in the NG101 group and six in the placebo group). 25 severe adverse events were reported: 18 in 11 (14%) patients in the NG101 group and seven in six (13%) patients in the placebo group. Although no treatment-related fatalities were reported in the NG101 group, one fatality not related to treatment occurred in the placebo group. Infections were the most common adverse event affecting 44 (92%) patients in the placebo group and 65 (83%) patients in the NG101 group.Interpretation: NG101 did not improve UEMS in patients with acute spinal cord injury. Post-hoc subgroup analyses assessing UEMS and Spinal Cord Independence Measure of self-care in patients with motor-incomplete injury indicated potential beneficial effects that require investigation in future studies

Time warping of evolutionary distant temporal gene expression data based on noise suppression

<p>Abstract</p> <p>Background</p> <p>Comparative analysis of genome wide temporal gene expression data has a broad potential area of application, including evolutionary biology, developmental biology, and medicine. However, at large evolutionary distances, the construction of global alignments and the consequent comparison of the time-series data are difficult. The main reason is the accumulation of variability in expression profiles of orthologous genes, in the course of evolution.</p> <p>Results</p> <p>We applied Pearson distance matrices, in combination with other noise-suppression techniques and data filtering to improve alignments. This novel framework enhanced the capacity to capture the similarities between the temporal gene expression datasets separated by large evolutionary distances. We aligned and compared the temporal gene expression data in budding (<it>Saccharomyces cerevisiae</it>) and fission (<it>Schizosaccharomyces pombe</it>) yeast, which are separated by more then ~400 myr of evolution. We found that the global alignment (time warping) properly matched the duration of cell cycle phases in these distant organisms, which was measured in prior studies. At the same time, when applied to individual ortholog pairs, this alignment procedure revealed groups of genes with distinct alignments, different from the global alignment.</p> <p>Conclusion</p> <p>Our alignment-based predictions of differences in the cell cycle phases between the two yeast species were in a good agreement with the existing data, thus supporting the computational strategy adopted in this study. We propose that the existence of the alternative alignments, specific to distinct groups of genes, suggests presence of different synchronization modes between the two organisms and possible functional decoupling of particular physiological gene networks in the course of evolution.</p