Miracle-dz/UniFAR-FTUs huggingface dataset:
Translational profile of coding and non-coding RNAs revealed by genome wide profiling of ribosome footprints in grapevine

Translation is a crucial process during plant growth and morphogenesis. In grapevine (Vitis vinifera L.), many transcripts can be detected by RNA sequencing; however, their translational regulation is still largely unknown, and a great number of translation products have not yet been identified. Here, ribosome footprint sequencing was carried out to reveal the translational profile of RNAs in grapevine. A total of 8291 detected transcripts were divided into four parts, including the coding, untranslated regions (UTR), intron, and intergenic regions, and the 26 nt ribosome-protected fragments (RPFs) showed a 3 nt periodic distribution. Furthermore, the predicted proteins were identified and classified by GO analysis. More importantly, 7 heat shock-binding proteins were found to be involved in molecular chaperone DNA J families participating in abiotic stress responses. These 7 proteins have different expression patterns in grape tissues; one of them was significantly upregulated by heat stress according to bioinformatics research and was identified as DNA JA6. The subcellular localization results showed that VvDNA JA6 and VvHSP70 were both localized on the cell membrane. Therefore, we speculate that DNA JA6 may interact with HSP70. In addition, overexpression of VvDNA JA6 and VvHSP70, reduced the malondialdehyde (MDA) content, improved the antioxidant enzyme activity of superoxide dismutase (SOD), catalase (CAT) and peroxidase (POD), increased the content of proline, an osmolyte substance, and affected the expression of the high-temperature marker genes VvHsfB1, VvHsfB2A, VvHsfC and VvHSP100. In summary, our study proved that VvDNA JA6 and the heat shock protein VvHSP70 play a positive role in the response to heat stress. This study lays a foundation for further exploring the balance between gene expression and protein translation in grapevine under heat stress.
Bone quality changes as measured by Raman and FTIR spectroscopy in primiparous cows with humeral fracture from New Zealand

The occurrence of spontaneous humeral fractures in primiparous dairy cows from New Zealand prompted the study of bone material from affected cows to further characterize this condition and to outline a likely pathogenesis. Previous studies indicate that these cows developed osteoporosis due to periods of suboptimal bone formation followed by increased bone resorption during the period of lactation complicated by copper deficiency. We hypothesized that there are significant differences in the chemical composition/bone quality in bones from cows with spontaneous humeral fracture compared to cows without humeral fractures. In this study, Raman and Fourier transform infrared spectroscopy band ratios were, for the first time, measured, calculated, and compared in bone samples from 67 primiparous dairy cows that suffered a spontaneous fracture of the humerus and 14 age-matched post-calving cows without humeral fractures. Affected bone showed a significantly reduced mineral/matrix ratio, increased bone remodeling, newer bone tissue with lower mineralization and, lower carbonate substitution, and reduced crystallinity. As such, is likely that these have detrimentally impacted bone quality and strength in affected cows.
TOMM34 serves as a candidate therapeutic target associated with immune cell infiltration in colon cancer

Background Colon cancer represents one of the most pervasive digestive malignancies worldwide. Translocase of the outer mitochondrial membrane 34 (TOMM34) is considered an oncogene and is implicated in tumor proliferation. However, the correlation between TOMM34 and immune cell infiltration in colon cancer has not been investigated. Materials and methods Based on multiple open online databases, we performed integrated bioinformatics analysis of TOMM34 to evaluate the prognostic value of TOMM34 and its correlation with immune cell infiltration. Results TOMM34 gene and protein expression levels were elevated in tumor tissues compared with normal tissues. Survival analysis revealed that upregulation of TOMM34 was significantly associated with poorer survival time in colon cancer. High TOMM34 expression was dramatically related to low levels of B cells, CD8+ T cells, neutrophils, dendritic cells, PD-1, PD-L1 and CTLA-4. Conclusions Our results confirmed that high expression of TOMM34 in tumor tissue correlates with immune cell infiltration and worse prognosis in colon cancer patients. TOMM34 may serve as a potential prognostic biomarker for colon cancer diagnosis and prognosis prediction.
The impact of iron deposition on the fear circuit of the brain in patients with Parkinson’s disease and anxiety

Objective Anxiety is one of the most common psychiatric symptoms of Parkinson’s disease (PD), and brain iron deposition is considered to be one of the pathological mechanisms of PD. The objective of this study was to explore alterations in brain iron deposition in PD patients with anxiety compared to PD patients without anxiety, especially in the fear circuit. Methods Sixteen PD patients with anxiety, 23 PD patients without anxiety, and 26 healthy elderly controls were enrolled prospectively. All subjects underwent neuropsychological assessments and brain magnetic resonance imaging (MRI) examinations. Voxel-based morphometry (VBM) was used to study morphological brain differences between the groups. Quantitative susceptibility mapping (QSM), an MRI technique capable of quantifying susceptibility changes in brain tissue, was used to compare susceptibility changes in the whole brain among the three groups. The correlations between brain susceptibility changes and anxiety scores quantified using the Hamilton Anxiety Rating Scale (HAMA) were compared and analyzed. Results PD patients with anxiety had a longer duration of PD and higher HAMA scores than PD patients without anxiety. No morphological brain differences were observed between the groups. In contrast, voxel-based and ROI-based QSM analyses showed that PD patients with anxiety had significantly increased QSM values in the medial prefrontal cortex, anterior cingulate cortex, hippocampus, precuneus, and angular cortex. Furthermore, the QSM values of some of these brain regions were positively correlated with the HAMA scores (medial prefrontal cortex: r = 0.255, p = 0.04; anterior cingulate cortex: r = 0.381, p < 0.01; hippocampus: r = 0.496, p < 0.01). Conclusion Our findings support the idea that anxiety in PD is associated with iron burden in the brain fear circuit, providing a possible new approach to explaining the potential neural mechanism of anxiety in PD.
Hot water immersion as a potential substitute for strength training during the COVID-19 pandemic

Muscle strength and mass can impact the course of the disease in patients with coronavirus disease-2019 (COVID-19) (Grigioni et al., 2023; Kara et al., 2021; Pucci et al., 2022). Kara et al. (2021) measured handgrip strength at hospital admission of 312 COVID-19 patients and reported that patients with low handgrip strength had three times higher risk for developing pneumonia compared to those with high handgrip strength. The study by Pucci et al. (2022), conducted on 118 hospitalised COVID-19 patients, found that handgrip strength at admission to the hospital was 26% lower in patients who later needed endotracheal intubation versus those who did not. Grigioni et al. (2023) used computed tomography to measure skeletal muscle mass at the thoracic level in 244 hospitalised COVID-19 patients within 48 h of their hospital admission and reported that those with low muscle mass had longer hospital stay (25 days vs. 13 days) than their counterparts with normal muscle mass. Collectively, the cited studies suggest that increasing muscle strength and mass via strength training during the COVID-19 pandemic could be an effective prophylactic strategy to strengthen resilience to severe forms of the disease in case a person gets infected by severe acute respiratory syndrome coronavirus 2. While guidelines for strength training during the COVID-19 pandemic have been published (Gentil et al., 2021; Gentil et al., 2022; Rodríguez et al., 2020; Sá Filho et al., 2020), they failed to provide alternative strategies for those unable or unwilling to exercise. Clearly, there is a need to introduce a non-exercise intervention aimed at increasing muscle strength and mass in the COVID-19 literature. The current paper provides evidence that passive heat exposure could be an alternative to strength training in increasingmuscle strength andmass and proposes a homebased heating treatment.
The influence of growth hormone on pediatric body composition: A systematic review

Background Growth hormone (GH) affects metabolism and regulates growth in childhood. The most prominent feature of GH deficiency (GHD) in children is diminished height velocity that eventually leads to short stature. In adult-onset GHD, lean body mass (LBM) is reduced, and visceral fat mass (FM) increased. Beneficial effects of GH treatment on body composition in adults with GHD, including an increase in muscle mass and a decrease in FM, are well established. Relatively few studies have investigated the effects of GH treatment on the body composition of pediatric patients with idiopathic or hypothalamic-pituitary disease-associated GH deficiency. This systematic review aimed to summarize available evidence relating to the effects of GH treatment on body composition in children with GHD. Methods The PubMed, Science Direct, Cochrane Trials, and Embase databases, were searched with keywords including “GH”, “body composition”, “children”, and “growth hormone” for English-language articles, published between January 1999 and March 2021. Two reviewers independently evaluated the search results and identified studies for inclusion based on the following criteria: participants had a confirmed diagnosis of GHD (as defined in each study); participants were pediatric patients who were receiving GH or had stopped GH treatment, regardless of whether they were pre- or post-pubertal; the intervention was recombinant human GH (rhGH; somatropin); and outcomes included changes in body composition during or after stopping GH therapy. Data extracted from each study included study quality, study sample characteristics, study interventions, and body composition. Data on fat-free mass and LBM were combined into a single category of LBM. Results Sixteen studies reporting changes in body composition (i.e., FM and LBM) associated with GH treatment in children with GHD were identified and included in the review. Collectively, these studies demonstrated that FM decreased, and LBM increased in response to GH replacement therapy. Conclusion Despite study limitations (i.e., potential effects of diet and physical activity were not considered), we concluded that a periodic body composition assessment is required to ensure that a satisfactory body composition is achieved during GH replacement therapy in children with GHD.
How do people with chronic pain choose their music for pain management? Examining the external validity of the cognitive vitality model

Music interventions for pain are more successful when patients choose the music themselves. But little is known about the attentional strategies used by chronic pain patients when choosing or using music for pain management, and the degree to which these attentional strategies align with the cognitive mechanisms outlines in the cognitive vitality model (CVM, a recently developed theoretical framework that outlines five cognitive mechanisms that mediate the analgesic effects of music for pain management). To investigate this question, we used a sequential explanatory mixed method approach, which included a survey, online music listening experiment, and qualitative data collection, with chronic pain patients (n=70). First, we asked chronic pain patients to name a piece of music that they would use to manage their chronic pain, and answer 19 questions about why they chose that particular piece of music using a questionnaire based on the CVM. Next, we asked chronic pain patients to listen to high energy and low energy pieces of music, to understand aesthetic music preferences and emotional responses at the group level. Finally, participants were asked to qualitatively tell us how they used music to manage their pain. Factor Analysis was completed on the survey data, and identified a five-factor structure in participant responses that was consistent with five mechanisms identified in the CVM. Regression analysis indicated that chronic pain patients choose music for pain management if they think it will facilitate Musical Integration and Cognitive Agency. Musical Integration refers to the degree to which the music can provide an immersive and absorbing experience. Cognitive Agency refers to having an increased feeling of control. At the group level, participants reported a preference for low energy music, and reported that they found high energy music more irritating. However, is it important to note that individual people had different music preferences. Thematic synthesis of patient responses highlighted how these processes mediate the analgesic benefits of music listening from the perspective of chronic pain patients, and highlighted the wide range of music used by participants for chronic pain management including electronic dance music, heavy metal and Beethoven. These findings demonstrate that chronic pain patients use specific attentional strategies when using music for pain management, and these strategies align with the cognitive vitality model.
Considerations for designing trials targeting muscle dysfunction in exercise oncology

Individuals diagnosed with cancer commonly experience a significant decline in muscle mass and physical function collectively referred to as cancer related muscle dysfunction. This is concerning because impairments in functional capacity are associated with an increased risk for the development of disability and subsequent mortality. Notably, exercise offers a potential intervention to combat cancer related muscle dysfunction. Despite this, research is limited on the efficacy of exercise when implemented in such a population. Thus, the purpose of this mini review is to offer critical considerations for researchers seeking to design studies pertaining to cancer related muscle dysfunction. Namely, 1) defining the condition of interest, 2) determining the most appropriate outcome and methods of assessment, 3) establishing the best timepoint (along the cancer continuum) to intervene, and 4) understanding how exercise prescription can be configured to optimize outcomes.
Radix Rehmanniae Praeparata (Shu Dihuang) exerts neuroprotective effects on ICV-STZ-induced Alzheimer’s disease mice through modulation of INSR/IRS-1/AKT/GSK-3β signaling pathway and intestinal microbiota

Radix Rehmanniae Praeparata (RRP, Shu Dihuang in Cinese) is widely used as primal medicine in Chinese herbal formula for the treatment of Alzheimer’s disease (AD). However, the underlying mechanism of RRP for AD remains unclear. The aim of this study was to investigate the therapeutic effect of RRP on intracerebroventricular injection of streptozotocin (ICV-STZ)-induced AD model mice and its potential mechanism. ICV-STZ mice were continuously gavaged with RRP for 21 days. The pharmacological effects of RRP were evaluated by behavioral tests, brain tissue H&E staining and hippocampal tau protein phosphorylation levels. The expression levels of insulin receptor (INSR), IRS-1, pSer473-AKT/AKT and pSer9-GSK-3β/GSK-3β proteins in hippocampal and cortical tissues were detected by Western-blot method. The 16S rRNA gene sequencing was used to analyze the changes of intestinal microbiota in mice. The compounds in RRP were analyzed by mass spectrometry and their binding ability to INSR proteins was detected by molecular docking. The results showed that RRP ameliorated cognitive dysfunction and neuronal pathological changes of brain tissue in ICV-STZ mice, reduced tau protein hyperphosphorylation, INSR, IRS-1, pSer473-AKT/AKT, and pSer9-GSK-3β/GSK-3β levels in hippocampal and cortical tissues. Meanwhile, RRP reversed ICV-STZ-induced dysregulation of intestinal microbiota in AD mice. Mass spectrometry analysis showed that the RRP consisted mainly of seven compounds, namely Acteoside (Verbascoside), 5-Hydroxymethyl-2-furaldehyde (5-HMF), Apigenin7-O-glucuronide, Icariin, Gallic acid, Quercetin-3β-D-glucoside, and Geniposide. Molecular docking results further indicated that the compounds in RRP have binding ability to INSR protein and potential multiple synergistic effects. RRP ameliorates cognitive dysfunction and brain histopathological changes in AD mice. The mechanism of RRP ameliorating AD may be related to the regulation of INSR/IRS-1/AKT/GSK-3β signaling pathway and intestinal microbiota. This study supports the potential anti-AD efficacy of RRP and initially reveals the pharmacological mechanism of RRP, providing a theoretical basis for further clinical application of RRP.
Investigating brain cortical activity in patients with post-COVID-19 brain fog

Brain fog is a kind of mental problem, similar to chronic fatigue syndrome, and appears about 3 months after the infection with COVID-19 and lasts up to 9 months. The maximum magnitude of the third wave of COVID-19 in Poland was in April 2021. The research referred here aimed at carrying out the investigation comprising the electrophysiological analysis of the patients who suffered from COVID-19 and had symptoms of brain fog (sub-cohort A), suffered from COVID-19 and did not have symptoms of brain fog (sub-cohort B), and the control group that had no COVID-19 and no symptoms (sub-cohort C). The aim of this article was to examine whether there are differences in the brain cortical activity of these three sub-cohorts and, if possible differentiate and classify them using the machine-learning tools. he dense array electroencephalographic amplifier with 256 electrodes was used for recordings. The event-related potentials were chosen as we expected to find the differences in the patients' responses to three different mental tasks arranged in the experiments commonly known in experimental psychology: face recognition, digit span, and task switching. These potentials were plotted for all three patients' sub-cohorts and all three experiments. The cross-correlation method was used to find differences, and, in fact, such differences manifested themselves in the shape of event-related potentials on the cognitive electrodes. The discussion of such differences will be presented; however, an explanation of such differences would require the recruitment of a much larger cohort. In the classification problem, the avalanche analysis for feature extractions from the resting state signal and linear discriminant analysis for classification were used. The differences between sub-cohorts in such signals were expected to be found. Machine-learning tools were used, as finding the differences with eyes seemed impossible. Indeed, the A&B vs. C, B&C vs. A, A vs. B, A vs. C, and B vs. C classification tasks were performed, and the efficiency of around 60–70% was achieved. In future, probably there will be pandemics again due to the imbalance in the natural environment, resulting in the decreasing number of species, temperature increase, and climate change-generated migrations. The research can help to predict brain fog after the COVID-19 recovery and prepare the patients for better convalescence. Shortening the time of brain fog recovery will be beneficial not only for the patients but also for social conditions.
Perception and trust influence acceptance for black bears more than bear density or conflicts

Introduction To sustain black bear (Ursus americanus) populations, wildlife managers should understand the coupled socio-ecological systems that influence acceptance capacity for bears. Method In a study area encompassing a portion of New York State, we spatially matched datasets from three sources: human-bear conflict reports between 2006 and 2018, estimates of local bear density in 2017–2018, and responses to a 2018 property owner survey (n=1,772). We used structural equation modeling to test hypothesized relationships between local human-bear conflict, local bear density, and psychological variables. Results The final model explained 57% of the variance in acceptance. The effect of bear population density on acceptance capacity for bears was relatively small and was mediated by a third variable: perception of proximity to the effects of human-bear interactions. The variables that exerted a direct effect on acceptance were perception of bear-related benefits, perception of bear-related risks, perceived proximity to effects of human-bear interactions, and being a hunter. Perception of bear-related benefits had a greater effect on acceptance than perception of bear-related risks. Perceived proximity to effects of human-bear interactions was affected by local bear density, but also was affected by social trust. Increased social trust had nearly the same effect on perceived proximity as decreased bear density. Social trust had the greatest indirect effect on acceptance of any variable in the model. Discussion Findings suggest wildlife agencies could maintain public acceptance for bears through an integrated approach that combines actions to address bear-related perceptions and social trust along with active management of bear populations.
DualFlow: Generating imperceptible adversarial examples by flow field and normalize flow-based model

Recent adversarial attack research reveals the vulnerability of learning-based deep learning models (DNN) against well-designed perturbations. However, most existing attack methods have inherent limitations in image quality as they rely on a relatively loose noise budget, i.e., limit the perturbations by Lp-norm. Resulting that the perturbations generated by these methods can be easily detected by defense mechanisms and are easily perceptible to the human visual system (HVS). To circumvent the former problem, we propose a novel framework, called DualFlow, to craft adversarial examples by disturbing the image's latent representations with spatial transform techniques. In this way, we are able to fool classifiers with human imperceptible adversarial examples and step forward in exploring the existing DNN's fragility. For imperceptibility, we introduce the flow-based model and spatial transform strategy to ensure the calculated adversarial examples are perceptually distinguishable from the original clean images. Extensive experiments on three computer vision benchmark datasets (CIFAR-10, CIFAR-100 and ImageNet) indicate that our method can yield superior attack performance in most situations. Additionally, the visualization results and quantitative performance (in terms of six different metrics) show that the proposed method can generate more imperceptible adversarial examples than the existing imperceptible attack methods.