Comprehensive Modelling of the Neurospora Circadian Clock and Its Temperature Compensation

Circadian clocks provide an internal measure of external time allowing organisms to anticipate and exploit predictable daily changes in the environment. Rhythms driven by circadian clocks have a temperature compensated periodicity of approximately 24 hours that persists in constant conditions and can be reset by environmental time cues. Computational modelling has aided our understanding of the molecular mechanisms of circadian clocks, nevertheless it remains a major challenge to integrate the large number of clock components and their interactions into a single, comprehensive model that is able to account for the full breadth of clock phenotypes. Here we present a comprehensive dynamic model of the Neurospora crassa circadian clock that incorporates its key components and their transcriptional and post-transcriptional regulation. The model accounts for a wide range of clock characteristics including: a periodicity of 21.6 hours, persistent oscillation in constant conditions, arrhythmicity in constant light, resetting by brief light pulses, and entrainment to full photoperiods. Crucial components influencing the period and amplitude of oscillations were identified by control analysis. Furthermore, simulations enabled us to propose a mechanism for temperature compensation, which is achieved by simultaneously increasing the translation of frq RNA and decreasing the nuclear import of FRQ protein

Investigating casino event management integration: The case of East and South Asia casinos

The aim of this study is to investigate the gap of event management in East and South Asia’s casinos throughout the information provided by casinos on their websites. Main objective is to identify the differences and similarities of event holding in East and South Asia’s casinos and suggest future directions for casino managers and event organizers. Four research questions were developed to provide ourselves a goal, as well as to further our understanding of our investigation. There are two steps to structure our study. First is to evaluate the performance of 138 casino’s websites, which were obtained from worldcasinodirectory. com by using a website evaluation tool that we have constructed. In the second step, we conduct a content analysis for the website so we can identify what kind of events are organized in the area on our samples. The data of the content analysis provides a comparison of events in our sampling, such as the event’s size, type, and frequency of holding an event. We believe that our research would contribute to event organizers and large scale corporations to give them an insight on the overall efficiency of websites, as well as the frequency of events around East and South Asian casinos

Analysis of Resistance to Clarithromycin and Virulence Markers in Helicobacter pylori Clinical Isolates from Eastern Taiwan

AbstractObjectiveLittle information is available concerning the relationships between clarithromycin resistance and virulence marker genes (iceA, cagA and vacA) in Helicobacter pylori isolated in Taiwan. The aim of this study was to evaluate the possible association between clarithromycin resistance and genotypes of the virulence markers on clarithromycin-resistant H. pylori isolates obtained in eastern TaiwanMaterials and MethodsThe genotypes of the virulence marker genes (iceA, cagA and vacA) were analyzed by PCR, and the 23S rDNA region from 18 clarithromycin-resistant clinical isolates of H. pylori was amplified by PCR and sequenced.ResultsPoint mutations were found to occur in all isolates. Two isolates had A2143G, six had T2182C, one had C2227T, six had A2143G plus T2182C, and three had heterozygous alleles. The latter included a wild-type allele (A2143) plus (i) an A2143G, (ii) an A2143G plus an A2223G, and (iii) an A2143G plus a T2182C. The prevalence of the marker genes cagA, iceA1, iceA2, and both iceA1 and iceA2, in the isolates was 95.5%, 66.9%, 7.5%, and 25.6%, respectively. The vacAs1 allele was detected in all isolates, whereas the m1 and m2 alleles were found in 44.4% and 55.6% of the isolates, respectivelyConclusionThere were no significant associations between clarithromycin resistance and the presence of the cagA gene, vacA allele mosaicism, and the iceA genotypes. The most notable finding of our study was that the C2227T single mutation in 23S rDNA could also be related to the high clarithromycin minimal inhibitory concentrations in clinical isolates from eastern Taiwan

Self-supervised learning-based general laboratory progress pretrained model for cardiovascular event detection

The inherent nature of patient data poses several challenges. Prevalent cases amass substantial longitudinal data owing to their patient volume and consistent follow-ups, however, longitudinal laboratory data are renowned for their irregularity, temporality, absenteeism, and sparsity; In contrast, recruitment for rare or specific cases is often constrained due to their limited patient size and episodic observations. This study employed self-supervised learning (SSL) to pretrain a generalized laboratory progress (GLP) model that captures the overall progression of six common laboratory markers in prevalent cardiovascular cases, with the intention of transferring this knowledge to aid in the detection of specific cardiovascular event. GLP implemented a two-stage training approach, leveraging the information embedded within interpolated data and amplify the performance of SSL. After GLP pretraining, it is transferred for TVR detection. The proposed two-stage training improved the performance of pure SSL, and the transferability of GLP exhibited distinctiveness. After GLP processing, the classification exhibited a notable enhancement, with averaged accuracy rising from 0.63 to 0.90. All evaluated metrics demonstrated substantial superiority (p < 0.01) compared to prior GLP processing. Our study effectively engages in translational engineering by transferring patient progression of cardiovascular laboratory parameters from one patient group to another, transcending the limitations of data availability. The transferability of disease progression optimized the strategies of examinations and treatments, and improves patient prognosis while using commonly available laboratory parameters. The potential for expanding this approach to encompass other diseases holds great promise.Comment: published in IEEE Journal of Translational Engineering in Health & Medicin

Deploying Image Deblurring across Mobile Devices: A Perspective of Quality and Latency

Recently, image enhancement and restoration have become important applications on mobile devices, such as super-resolution and image deblurring. However, most state-of-the-art networks present extremely high computational complexity. This makes them difficult to be deployed on mobile devices with acceptable latency. Moreover, when deploying to different mobile devices, there is a large latency variation due to the difference and limitation of deep learning accelerators on mobile devices. In this paper, we conduct a search of portable network architectures for better quality-latency trade-off across mobile devices. We further present the effectiveness of widely used network optimizations for image deblurring task. This paper provides comprehensive experiments and comparisons to uncover the in-depth analysis for both latency and image quality. Through all the above works, we demonstrate the successful deployment of image deblurring application on mobile devices with the acceleration of deep learning accelerators. To the best of our knowledge, this is the first paper that addresses all the deployment issues of image deblurring task across mobile devices. This paper provides practical deployment-guidelines, and is adopted by the championship-winning team in NTIRE 2020 Image Deblurring Challenge on Smartphone Track.Comment: CVPR 2020 Workshop on New Trends in Image Restoration and Enhancement (NTIRE

New Plasma Separation Glucose Oxidase-based Glucometer in Monitoring of Blood With Different PO2 Levels

BackgroundThe PalmLab glucometer is a newly designed plasma separation glucose oxidase (GO)-based glucometer. Past studies have shown that the accuracy of GO-based glucometers is compromised when measurements are taken in patients with high PO2 levels. We performed a two-arm study comparing the fitness of the PalmLab blood glucometer with that of a standard glucose analyzer in monitoring blood glucose levels in pediatric patients, especially when arterial partial pressure of oxygen (PO2) was high.MethodsIn the first arm of the study, arterial blood samples from pediatric patients were measured by the PalmLab blood glucometer and the YSI 2302 Plus Glucose/Lactate analyzer. In the second arm of the study, venous blood samples from adult volunteers were spiked with glucose water to prepare three different levels of glucose (65, 150, and 300mg/dL) and then oxygenated to six levels of PO2 (range, 40–400mmHg). The biases of the PalmLab glucometer were calculated.ResultsA total of 162 samples were collected in the first arm of the study. Results of linear regression showed that the coefficient of determination (R2) between PalmLab glucometer and standard glucose analyzer was 0.9864. Error grid analysis revealed that all the results were within Zone A (clinically accurate estimate zone). The biases between the two systems were low at different PO2 levels. In the second arm of the study, the results were also unaffected by changes in PO2.ConclusionThe PalmLab glucometer provides accurate results in samples with high PO2 and is suitable for measuring arterial glucose levels in pediatric patients