Arbitrary Scale Super-Resolution for Brain MRI Images

Recent attempts at Super-Resolution for medical images used deep learning techniques such as Generative Adversarial Networks (GANs) to achieve perceptually realistic single image Super-Resolution. Yet, they are constrained by their inability to generalise to different scale factors. This involves high storage and energy costs as every integer scale factor involves a separate neural network. A recent paper has proposed a novel meta-learning technique that uses a Weight Prediction Network to enable Super-Resolution on arbitrary scale factors using only a single neural network. In this paper, we propose a new network that combines that technique with SRGAN, a state-of-the-art GAN-based architecture, to achieve arbitrary scale, high fidelity Super-Resolution for medical images. By using this network to perform arbitrary scale magnifications on images from the Multimodal Brain Tumor Segmentation Challenge (BraTS) dataset, we demonstrate that it is able to outperform traditional interpolation methods by up to 20$\%$ on SSIM scores whilst retaining generalisability on brain MRI images. We show that performance across scales is not compromised, and that it is able to achieve competitive results with other state-of-the-art methods such as EDSR whilst being fifty times smaller than them. Combining efficiency, performance, and generalisability, this can hopefully become a new foundation for tackling Super-Resolution on medical images. Check out the webapp here: https://metasrgan.herokuapp.com/ Check out the github tutorial here: https://github.com/pancakewaffles/metasrgan-tutorialComment: 12 pages, 8 figures, 1 table, to appear as a full paper with oral contribution in AIAI 202

Pressure Transient Analysis of Dual Fractal Reservoir

A dual fractal reservoir transient flow model was created by embedding a fracture system simulated by a tree-shaped fractal network into a matrix system simulated by fractal porous media. The dimensionless bottom hole pressure model was created using the Laplace transform and Stehfest numerical inversion methods. According to the model's solution, the bilogarithmic type curves of the dual fractal reservoirs are illustrated, and the influence of different fractal factors on pressure transient responses is discussed. This semianalytical model provides a practical and reliable method for empirical applications

Large fine‐scale spatiotemporal variations of CH4 diffusive fluxes from shrimp aquaculture ponds affected by organic matter supply and aeration in Southeast China

Mariculture shrimp ponds are important CH4 sources to the atmosphere. However, the spatiotemporal variations of CH4 concentration and flux at fine spatial scales in mariculture ponds are poorly known, particularly in China, worlds largest aquaculture producer. In this study, the plot‐scale spatiotemporal variations of water CH4 concentration and flux, both within and among ponds, were researched in shrimp ponds in Shanyutan wetland, Min River Estuary, Southeast China. The average water CH4 concentration and diffusion flux across the water‐air interface in the shrimp ponds over the shrimp aquaculture period varied from 2.29 ± 0.29 to 50.48 ± 20.91 μM and from 0.09 ± 0.01 to 2.32 ± 0.95 mmol·m−2·hr−1, respectively. The CH4 emissions from the estuarine ponds varied greatly between seasons, with peaks in August and September, which was similar to the trend of water temperature and dissolved oxygen concentrations. There was no remarkable difference in CH4 concentration and flux between shrimp ponds but significantly spatiotemporal differences in CH4 concentration and flux within the ponds. Significantly higher emissions occurred in the feeding zone, accounting for approximately 60% of total CH4 emission flux, while much lower CH4 emissions appeared in aeration zone, contributing 14% to total flux. This study suggests the importance of considering spatiotemporal variation in the whole‐pond estimates of CH4 concentration and flux. In light of such high spatial variation within ponds, improving aeration and feed utilization efficiency would help to mitigate CH4 emissions from mariculture ponds

Associations of Alzheimer's disease risk variants with gene expression, amyloidosis, tauopathy, and neurodegeneration.

BACKGROUND: Genome-wide association studies have identified more than 30 Alzheimer's disease (AD) risk genes, although the detailed mechanism through which all these genes are associated with AD pathogenesis remains unknown. We comprehensively evaluate the roles of the variants in top 30 non-APOE AD risk genes, based on whether these variants were associated with altered mRNA transcript levels, as well as brain amyloidosis, tauopathy, and neurodegeneration. METHODS: Human brain gene expression data were obtained from the UK Brain Expression Consortium (UKBEC), while other data used in our study were obtained from the Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort. We examined the association of AD risk allele carrier status with the levels of gene expression in blood and brain regions and tested the association with brain amyloidosis, tauopathy, and neurodegeneration at baseline, using a multivariable linear regression model. Next, we analyzed the longitudinal effects of these variants on the change rates of pathology using a mixed effect model. RESULTS: Altogether, 27 variants were detected to be associated with the altered expression of 21 nearby genes in blood and brain regions. Eleven variants (especially novel variants in ADAM10, IGHV1-68, and SLC24A4/RIN3) were associated with brain amyloidosis, 7 variants (especially in INPP5D, PTK2B) with brain tauopathy, and 8 variants (especially in ECHDC3, HS3ST1) with brain neurodegeneration. Variants in ADAMTS1, BZRAP1-AS1, CELF1, CD2AP, and SLC24A4/RIN3 participated in more than one cerebral pathological process. CONCLUSIONS: Genetic variants might play functional roles and suggest potential mechanisms in AD pathogenesis, which opens doors to uncover novel targets for AD treatment

Associations of Alzheimer's disease risk variants with gene expression, amyloidosis, tauopathy, and neurodegeneration.

BACKGROUND: Genome-wide association studies have identified more than 30 Alzheimer's disease (AD) risk genes, although the detailed mechanism through which all these genes are associated with AD pathogenesis remains unknown. We comprehensively evaluate the roles of the variants in top 30 non-APOE AD risk genes, based on whether these variants were associated with altered mRNA transcript levels, as well as brain amyloidosis, tauopathy, and neurodegeneration. METHODS: Human brain gene expression data were obtained from the UK Brain Expression Consortium (UKBEC), while other data used in our study were obtained from the Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort. We examined the association of AD risk allele carrier status with the levels of gene expression in blood and brain regions and tested the association with brain amyloidosis, tauopathy, and neurodegeneration at baseline, using a multivariable linear regression model. Next, we analyzed the longitudinal effects of these variants on the change rates of pathology using a mixed effect model. RESULTS: Altogether, 27 variants were detected to be associated with the altered expression of 21 nearby genes in blood and brain regions. Eleven variants (especially novel variants in ADAM10, IGHV1-68, and SLC24A4/RIN3) were associated with brain amyloidosis, 7 variants (especially in INPP5D, PTK2B) with brain tauopathy, and 8 variants (especially in ECHDC3, HS3ST1) with brain neurodegeneration. Variants in ADAMTS1, BZRAP1-AS1, CELF1, CD2AP, and SLC24A4/RIN3 participated in more than one cerebral pathological process. CONCLUSIONS: Genetic variants might play functional roles and suggest potential mechanisms in AD pathogenesis, which opens doors to uncover novel targets for AD treatment

Colorectal cancer screening using immunochemical fecal occult blood test

Fecal occult blood test (FOBT) screening has been shown to decrease the incidence and mortality of colorectal cancer (CRC). The sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of the immunochemical fecal occult blood test (i-FOBT) in diagnosing CRC were assessed among the patients in a tertiary referral hospital in Malaysia. A total sample of 814 patients aged 16 to 85 years old who performed i-FOBT and endoscopic screenings was obtained. The patients were recruited for a retrospective investigation. Sensitivity, specificity, PPV, and NPV were derived for the CRC screenees. Out of the 814 patients screened using i-FOBT, half of them were above 59 years old (49.6%), and 36% had positive i-FOBT. Gender distribution was almost equal, where 53.4% of the patients were female, and 46.6% were male. Majority of the patients were Malays (56.6%), followed by Chinese (24.0%), Indians (16.5%), and others (2.9%). Among the 71 patients referred for colonoscopy, 57.7% and 42.3% corresponded to positive and negative i-FOBT cases, respectively. Polyps were found to be most common among the patients (25.6%), 7.0% were found positive for invasive CRC, and 35.2% had normal colonoscopic findings. There was a significant association between colonoscopic finding and positive i-FOBT (p=0.001). The sensitivity, specificity, PPV, and NPV for CRC detection were 66.7%, 43.0%, 9.8%, and 93.3%, respectively. The results indicate that i-FOBT is a useful tool in the detection of abnormalities in the lower gastrointestinal tract and therefore serves as a cornerstone for potential large-scale screening programmes

An Epidemiological Study of Concomitant Use of Chinese Medicine and Antipsychotics in Schizophrenic Patients: Implication for Herb-Drug Interaction

Background: Herb-drug interactions are an important issue in drug safety and clinical practice. The aim of this epidemiological study was to characterize associations of clinical outcomes with concomitant herbal and antipsychotic use in patients with schizophrenia. Methods and Findings: In this retrospective, cross-sectional study, 1795 patients with schizophrenia who were randomly selected from 17 psychiatric hospitals in China were interviewed face-to-face using a structured questionnaire. Association analyses were conducted to examine correlates between Chinese medicine (CM) use and demographic, clinical variables, antipsychotic medication mode, and clinical outcomes. The prevalence of concomitant CM and antipsychotic treatment was 36.4% [95% confidence interval (95% CI) 34.2%-38.6%]. Patients using concomitant CM had a significantly greater chance of improved outcomes than non-CM use (61.1% vs. 34.3%, OR = 3.44, 95% CI 2.80-4.24). However, a small but significant number of patients treated concomitantly with CM had a greater risk of developing worse outcomes (7.2% vs. 4.4%, OR = 2.06, 95% CI 2.06-4.83). Significant predictors for concomitant CM treatment-associated outcomes were residence in urban areas, paranoid psychosis, and exceeding 3 months of CM use. Herbal medicine regimens containing Radix Bupleuri, Fructus Gardenia, Fructus Schisandrae, Radix Rehmanniae, Akebia Caulis, and Semen Plantaginis in concomitant use with quetiapine, clozapine, and olanzepine were associated with nearly 60% of the risk of adverse outcomes. Conclusions: Concomitant herbal and antipsychotic treatment could produce either beneficial or adverse clinical effects in schizophrenic population. Potential herb-drug pharmacokinetic interactions need to be further evaluated. © 2011 Zhang et al.published_or_final_versio