Miracle-dz/UniFAR-FTUs huggingface dataset:
Denoising Tc-99m DMSA images using Denoising Convolutional Neural Network with comparison to a Block Matching Filter

Introduction A DnCNN for image denoising trained with natural images is available in MATLAB. For Tc-99m DMSA images, any loss of clinical details during the denoising process will have serious consequences since denoised image is to be used for diagnosis. The objective of the study was to find whether this pre-trained DnCNN can be used for denoising Tc-99m DMSA images and compare its performance with block matching 3D (BM3D) filter. Materials and methods Two hundred forty-two Tc-99m DMSA images were denoised using BM3D filter (at sigma = 5, 10, 15, 20, and 25) and DnCNN. The original and denoised images were reviewed by two nuclear medicine physicians and also assessed objectively using the image quality metrics: SSIM, FSIM, MultiSSIM, PIQE, Blur, GCF, and Brightness. Wilcoxon signed-rank test was applied to find the statistically significant difference between the value of image quality metrics of the denoised images and the corresponding original images. Results Nuclear medicine physicians observed no loss of clinical information in DnCNN denoised image and superior image quality compared to its original and BM3D denoised images. Edges/boundaries of the scar were found to be well preserved, and doubtful scar became obvious in the denoised image. Objective assessment also showed that the quality of DnCNN denoised images was significantly better than that of original images at P-value <0.0001. Conclusion The pre-trained DnCNN available with MATLAB Deep Learning Toolbox can be used for denoising Tc-99m DMSA images, and the performance of DnCNN was found to be superior in comparison with BM3D filter.
Autonomous Control of Music to Retrain Walking After Stroke

Background Post-stroke care guidelines highlight continued rehabilitation as essential; however, many stroke survivors cannot participate in outpatient rehabilitation. Technological advances in wearable sensing, treatment algorithms, and care delivery interfaces have created new opportunities for high-efficacy rehabilitation interventions to be delivered autonomously in any setting (ie, clinic, community, or home). Methods We developed an autonomous rehabilitation system that combines the closed-loop control of music with real-time gait analysis to fully automate patient-tailored walking rehabilitation. Specifically, the mechanism-of-action of auditory-motor entrainment is applied to induce targeted changes in the post-stroke gait pattern by way of targeted changes in music. Using speed-controlled biomechanical and physiological assessments, we evaluate in 10 individuals with chronic post-stroke hemiparesis the effects of a fully-automated gait training session on gait asymmetry and the energetic cost of walking. Results Post-treatment reductions in step time (Δ: −12 ± 26%, P = .027), stance time (Δ: −22 ± 10%, P = .004), and swing time (Δ: −15 ± 10%, P = .006) asymmetries were observed together with a 9 ± 5% reduction (P = .027) in the energetic cost of walking. Changes in the energetic cost of walking were highly dependent on the degree of baseline energetic impairment (r =− .90, P < .001). Among the 7 individuals with a baseline energetic cost of walking larger than the normative value of healthy older adults, a 13 ± 4% reduction was observed after training. Conclusions The closed-loop control of music can fully automate walking rehabilitation that markedly improves walking after stroke. Autonomous rehabilitation delivery systems that can safely provide high-efficacy rehabilitation in any setting have the potential to alleviate access-related care gaps and improve long-term outcomes after stroke.
Congenital heart anomalies in the first trimester: From screening to diagnosis

Congenital heart defects occur in approximately 1% of liveborn children and represent the most common form of congenital malformation. Due to the small size and complexity of the heart structures, prenatal diagnosis is most often made in the second trimester of pregnancy. Early diagnosis however offers significant advantages regarding the timing of further investigations, prenatal counseling, and access to management options. In the last decade, advances in antenatal imaging have improved the detection of cardiac malformations with increasing emphasis on earlier pregnancy screening and diagnosis. We aim to summarize current “state of the art” imaging of the fetal heart in the first trimester.
In silico induced effect of N‐ε‐lysine acetylation on microtubule stability and subsequent interaction of microtubule‐associated proteins

Plant systems have been considered valuable models for addressing fundamental questions of microtubule (MT) organization due to their considerable practical utility. Protein acetylation is a very common protein modification, and therate of acetylation can be modulated in cells in different biological states, and these changes can be detected at a molecular level. Here, we focused on K40, K112, and K394 residues as putative acetylation sites, which were shown to exist in both plants and mammals. Such residual effect of acetylation causes critical but unclear effect on MT stability. In turn, it was shown that acetylation indirectly affects the probability of interaction with different MAPs (Microtubule‐associated proteins). In a multiscale study using an all‐atom force field to reproduce several lattice‐forming elements found on the surface the microtubule, we assembled a fragment of a plant microtubule composed of nine tubulins and used it as a model object along with the existing human complex. Triplets of tubulins assembled in a lattice cell were then simulated for both human and plant protein complexes, using a coarse‐grained force field. We then analyzed the trajectories and identified some critical deformations of the MAP interaction surface. The initial coordinates were used to investigate the structural scenario in which autophagy‐related protein 8 (ATG8) was able to interact with the MT fragment.
Mindfulness-based therapy for smoking cessation and mental health: a randomised controlled trial.

INTRODUCTION Effective smoking cessation programmes are essential for assisting smokers in quitting, indirectly lowering mortality and morbidity associated with smoking. Numerous studies have indicated positive outcomes when using mindfulness treatment (MT) to treat psychological or behavioural health issues. Although to date, no study has looked at the effectiveness of online MT for quitting smoking while addressing mental health, particularly among the Asian population. Therefore, this study compares the efficiency of online MT to traditional counselling therapy (CT) in aiding smoking cessation programmes while also addressing mental health. MATERIALS AND METHODS A randomised control study with a two-group, single-blind design and baseline evaluation was selected. Social media sites were used to advertise for participants, who were then admitted after meeting the requirements. Participants who met the eligibility requirements were randomly split into two groups. Each group received a total of three sessions of online therapy (MT or CT), once every two weeks, as well as one phone call per week as reinforcement. At the beginning and end of the intervention, participants completed questionnaires (1st week and 5th week). Generalized Estimating Equation (GEE) statistical analysis was used to analyse all the variables. RESULTS The MT group experienced a statistically significant decrease in cigarette consumption (β: -3.50, 95% Wald CI: - 4.62, -2.39) compared to the CT group over time. Furthermore, the MT group demonstrated significant improvements in their scores for the AAQ-2, anxiety, stress, depression and mindfulness compared to the CT group. CONCLUSION Online MT is more successful at assisting smokers in lowering their daily cigarette intake and supporting their mental health during the smoking cessation process. Further longitudinal comparisons of the effectiveness of online MT should be undertaken using online platforms in future studies.
Quaking regulates circular RNA production in cardiomyocytes

ABSTRACT Circular RNAs (circRNAs) are a class of non-coding RNA molecules that are gaining increasing attention for their roles in various pathophysiological processes. The RNA-binding protein quaking (QKI) has been identified as a regulator of circRNA formation. In this study, we investigate the role of QKI in the formation of circRNAs in the heart by performing RNA-sequencing on Qki-knockout mice. Loss of QKI resulted in the differential expression of 17% of the circRNAs in adult mouse hearts. Interestingly, the majority of the QKI-regulated circRNAs (58%) were derived from genes undergoing QKI-dependent splicing, indicating a relationship between back-splicing and linear splicing. We compared these QKI-dependent circRNAs with those regulated by RBM20, another cardiac splicing factor essential for circRNA formation. We found that QKI and RBM20 regulate the formation of a distinct, but partially overlapping set of circRNAs in the heart. Strikingly, many shared circRNAs were derived from the Ttn gene, and they were regulated in an opposite manner. Our findings indicate that QKI not only regulates alternative splicing in the heart but also the formation of circRNAs.
Draft Genome Sequence of Thermolongibacillus altinsuensis Strain B1-1, a Novel Hydrogenogenic CO Oxidizer Isolated from Sediment from Lake Biwa in Japan

A facultative anaerobic, thermophilic, hydrogenogenic CO-oxidizing bacterial strain, B1-1, was isolated from a sediment sample from Lake Biwa, a freshwater lake in Japan. B1-1, which is a novel strain of Thermolongibacillus altinsuensis, is capable of hydrogenogenic CO oxidation. Here, we report the draft genome sequence of B1-1 (2.92 Mbp, with a GC content of 41.3%). ABSTRACT A facultative anaerobic, thermophilic, hydrogenogenic CO-oxidizing bacterial strain, B1-1, was isolated from a sediment sample from Lake Biwa, a freshwater lake in Japan. B1-1, which is a novel strain of Thermolongibacillus altinsuensis, is capable of hydrogenogenic CO oxidation. Here, we report the draft genome sequence of B1-1 (2.92 Mbp, with a GC content of 41.3%).
Phosphorylation of E2 Serine Residue 402 Is Required for the Transcription and Replication of the HPV5 Genome

Human papillomavirus type 5 (HPV5) may play a role in the development of specific types of cutaneous and head and neck cancers. The persistence of the HPV genome in host cells depends on the activity of its proteins, namely, a helicase E1 and transcription/replication factor E2. ABSTRACT Cutaneous human papillomavirus type 5 (HPV5) belongs to the supposedly oncogenic β-HPVs associated with specific types of skin and oral cavity cancers. Three viral proteins, namely, helicase E1 and transcription factors E2 and E8^E2, are master regulators of the viral life cycle. HPV5 E2 is a transcriptional activator that also participates in the E1-dependent replication and nuclear retention of the viral genome, whereas E8^E2 counterbalances the activity of E2 and inhibits HPV transcription and replication. In the present study, we demonstrate that the HPV5 E2 protein is extensively phosphorylated by cellular protein kinases, and serine residue 402 (S402) is the highest scoring phosphoacceptor site. This residue is located within a motif conserved among many β-HPVs and in the oncogenic HPV31 α-type. Using the nonphosphorylatable and phosphomimetic mutants, we demonstrate that phosphorylation of the E2 S402 residue is required for the transcription and replication of the HPV5 genome in U2OS cells and human primary keratinocytes. Mechanistically, the E2-S402-phopshodeficient protein is unable to trigger viral gene transcription and has an impaired ability to support E1-dependent replication, but the respective E8^E2-S213 mutant displays no phenotype. However, phosphorylation of the E2 S402 residue has no impact on the E2 stability, subcellular localization, self-assembly, DNA-binding capacity, and affinity to the E1 and BRD4 proteins. Further studies are needed to identify the protein kinase(s) responsible for this phosphorylation. IMPORTANCE Human papillomavirus type 5 (HPV5) may play a role in the development of specific types of cutaneous and head and neck cancers. The persistence of the HPV genome in host cells depends on the activity of its proteins, namely, a helicase E1 and transcription/replication factor E2. The latter also facilitates the attachment of episomal viral genomes to host cell chromosomes. In the present study, we show that the HPV5 E2 protein is extensively phosphorylated by host cell protein kinases, and we identify serine residue 402 as the highest scoring phosphoacceptor site of E2. We demonstrate that the replication of the HPV5 genome may be blocked by a single point mutation that prevents phosphorylation of this serine residue and switches off the transcriptional activity of the E2 protein. The present study contributes to a better understanding of β-HPV5 replication and its regulation by host cell protein kinases.
Physical activity amongst culturally and linguistically diverse communities in Australia: a scoping review

ABSTRACT Background: Australia’s overseas-born population continues to grow. This population is disproportionately affected by chronic, non-communicable diseases. Physical activity is the cornerstone of all chronic disease management. Engaging people from culturally and linguistically diverse (CALD) backgrounds in physical activity is an important public health objective. The purpose of this scoping review was to examine the factors that shape physical activity participation among people from CALD backgrounds in Australia. Methods: This scoping review followed Arksey and O’Malley’s framework. Medline, Embase and CINAHL were searched with key words relating to ‘physical activity’, ‘CALD’ and ‘Australia’ in July 2021 and again in February 2022 for qualitative studies published in English since 2000. Exclusion criteria were: participants < 18 years old, studies specifically focusing on populations with health issues, pregnant or postpartum states. Methodological quality of included studies was evaluated using the Critical Appraisal Skills Programme with the purpose of informing future research. Data extracted from each study were analysed thematically and results were interpreted using Acculturation theory. Results: Of the 1130 studies, 17 met the inclusion criteria. Findings from each study were captured in three themes: Perceptions of physical activity; Acceptability and Appropriateness; and Access. Following migration, a decrease in physical activity, especially leisure-time activity, was reported. Common factors influencing physical activity engagement included perceptions of physical activity and wellbeing; language, financial and environmental barriers; as well as social, cultural, and religious considerations. Conclusion: This review identified several factors which may interact and contribute to the decline in self-reported physical activity upon migration. Findings from this review may be used to inform future health promotion initiatives targeting people from CALD backgrounds. Future research may benefit from devising a shared definition of physical activity and studying different CALD communities over time.
Meta-analysis of the efficacy and safety of sevelamer as hyperphosphatemia therapy for hemodialysis patients

Abstract This study was designed to examine the relative safety and efficacy of sevelamer in the treatment of chronic kidney disease (CKD) patients in comparison to placebo, calcium carbonate (CC), or lanthanum carbonate (LC). The PubMed, Embase, Cochrane Library, and China National Knowledge Infrastructure (CNKI) databases were searched for articles published through 18 June 2022. The quality of relevant studies was independently analyzed by two investigators who also extracted data from these manuscripts as per Cochrane Collaboration Handbook 5.3. The safety and efficacy of sevelamer as a treatment for hyperphosphatemia in CKD patients were then examined through a meta-analysis, with the primary patient-level outcomes of interest in this analysis being all-cause mortality and the incidence of gastrointestinal adverse effects. Vascular calcification score was also examined as an intermediate outcome, while serum biochemical parameters including levels of phosphate (P), calcium (Ca), intact parathyroid hormone (iPTH), lipids, C-reactive protein (CRP), or fibroblast growth factor-23 (FGF-23) were additionally assessed. In total, this meta-analysis incorporated data from 34 randomized controlled trials (RCTs) enrolling 2802 patients. Sevelamer was associated with reduced all-cause mortality (RR 0.28, CI 0.19 − 0.41, very low certainty) and Vessel calcification score (RR −0.58, CI −1.11 to −0.04, low certainty) and induced less hypercalcemia (MD −0.28, CI 0.40 to −0.16, low certainty) and hyperphosphatemia (MD −0.22, CI −0.32 to −0.13, low certainty) when compared with Ca-based binders in CKD5D individuals. No significant differences in gastrointestinal adverse events (GAEs) incidence were observed. These data suggest that sevelamer may represent a beneficial means of protecting CKD patients against death and vessel calcification when used to treat hyperphosphatemia, while we found no clinically important benefits in decreasing gastrointestinal adverse effects.
A Study on Effectiveness of Coherence for Monitoring Deforestation of Tropical Rain Forest Using JERS-1/SAR

竹 内 章 司* Shoji TAKEUCHI Abstract: We studied the effectiveness of coherence information for monitoring deforestation in tropical rain forests. First, the changing patterns of SAR backscattering intensity of JERS-1 SAR data in a tropical forest region in Sumatra island were investigated and it was found that the backscatter changes are rather complicated than those estimated from conventional studies. Then the coherence images by several JERS-1 SAR interferometric pairs were presented and the relationship between coherence and backscatter changing patterns was discussed. In addition, the accuracy for identifying deforested areas was assessed for the combined use of coherence with backscattering intensity. These results proved the effectiveness of the combined use of coherence for identifying deforested areas compared with the use of intensity only.
No detectable upper limit of mineral‐associated organic carbon in temperate agricultural soils

Soil organic carbon (SOC) sequestration is a promising climate change mitigation option. In this context, the formation of the relatively long‐lived mineral‐associated organic carbon (MAOC) is key. To date, soils are considered to be limited in their ability to accumulate MAOC, mainly by the amount of clay and silt particles present. Using the comprehensive German Agricultural Soil Inventory, we selected 189 samples with a wide range of SOC (5–118 g kg−1) and clay contents (30–770 g kg−1) to test whether there is a detectable upper limit of MAOC content. We found that the proportion of MAOC was surprisingly stable for soils under cropland and grassland use across the whole range of bulk SOC contents. Soil texture influenced the slope of the relationship between bulk SOC and MAOC, but no upper limit was observed in any texture class. Also, C content in the fine fraction (g C kg−1 fraction) was negatively correlated to fine fraction content (g kg−1 bulk soil). Both findings challenge the notion that MAOC accumulation is limited by soil fine fraction content per se.
Digital diaphanoscopy of maxillary sinus pathologies supported by machine learning

Maxillary sinus pathologies remain among the most common ENT diseases requiring timely diagnosis for successful treatment. Standard ENT inspection approaches indicate low sensitivity in detecting maxillary sinus pathologies. In this paper, we report on capabilities of digital diaphanoscopy combined with machine learning tools in the detection of such pathologies. We provide a comparative analysis of two machine learning approaches applied to digital diapahnoscopy data, namely, convolutional neural networks and linear discriminant analysis. The sensitivity and specificity values obtained for both employed approaches exceed the reported accuracy indicators for traditional screening diagnosis methods (such as nasal endoscopy or ultrasound), suggesting the prospects of their usage for screening maxillary sinuses alterations. The analysis of the obtained values showed that the linear discriminant analysis, being a simpler approach as compared to neural networks, allows one to detect the maxillary sinus pathologies with the sensitivity and specificity of 0.88 and 0.98, respectively.
Research and Implemention of One-Dimensional Maximum-Entropy Threshold Image Segmentation Based on Edge Features

In this paper,a new method of image segmentation is proposed.The new algorithm detects image edges first.Based on edge images,it processes binary conversions,reserving edge characteristics.And it can implement adaptive threshold selection, overcoming the shortcomings of the one dimensional maximum entropy threshold algorithm that loses the edge characteristics of the image.In addition,this algorithm is efficient in processing low quality images or fuzzy edge images.Many simulation results indicate that high performance is reached and this scheme is practical.
Computing nonlinear eigenvalues with spectral transformation Arnoldi

The Arnoldi algorithm is applied to a linearization of a nonlinear path following problem. A shift and invert spectral transformation gives fast convergence to those eigenvalues that predict turning points or bifurcations along the path, in such points the matrix of partial derivatives becomes singular. This approach is of special utility for very large matrices coming from systems with many degrees of freedom. The technique is demonstrated on a discretization of a Taylor vortex flow problem.
Noise-robust Graph Learning by Estimating and Leveraging Pairwise Interactions

Teaching Graph Neural Networks (GNNs) to accurately classify nodes under severely noisy labels is an important problem in real-world graph learning applications, but is currently underexplored. Although pairwise training methods have demonstrated promise in supervised metric learning and unsupervised contrastive learning, they remain less studied on noisy graphs, where the structural pairwise interactions (PI) between nodes are abundant and thus might benefit label noise learning rather than the pointwise methods. This paper bridges the gap by proposing a pairwise framework for noisy node classification on graphs, which relies on the PI as a primary learning proxy in addition to the pointwise learning from the noisy node class labels. Our proposed framework PI-GNN contributes two novel components: (1) a confidence-aware PI estimation model that adaptively estimates the PI labels, which are defined as whether the two nodes share the same node labels, and (2) a decoupled training approach that leverages the estimated PI labels to regularize a node classification model for robust node classification. Extensive experiments on different datasets and GNN architectures demonstrate the effectiveness of PI-GNN, yielding a promising improvement over the state-of-the-art methods. Code is publicly available at https://github.com/TianBian95/pi-gnn.
CoAIcoder: Examining the Effectiveness of AI-assisted Collaborative Qualitative Analysis

methods. We subsequently implemented a between-subject design involving 32 pairs of users who have undergone training in CQA across three commonly utilized phases under four methods. Our results suggest that CoAIcoder , which employs AI and a Shared Model, could potentially improve the efficiency of the coding process in CQA by fostering a quicker shared understanding and promoting early-stage discussions. However, this may come with the potential downside of reduced code diversity. We also underscored the existence of a trade-off between the level of independence and the coding outcome when humans collaborate during the early coding stages. Lastly, we identify design implications that could inspire and inform the future design of CQA systems.