Miracle-dz/UniFAR-FTUs huggingface dataset:
Potential methylation-regulated genes and pathways in hepatocellular neoplasm, not otherwise specified

Background and Aims The molecular basis of hepatocellular neoplasm, not otherwise specified (HCN-NOS) is unknown. We aimed to identify gene expression patterns, potential methylation-regulated genes and pathways that characterize the tumor, and its possible relationship to hepatoblastoma and hepatocellular carcinoma (HCC). Approach & Results Parallel genome-wide profiling of gene expression (RNAseq) and DNA methylation (EPIC850) was performed on 4 pairs of pre-treatment HCN-NOS tumors and adjacent non-tumor controls. 2530 significantly differentially expressed genes (DEGs) were identified between tumors and controls. Many of these DEGs were associated with hepatoblastoma and/or HCC. Analysis Match in Ingenuity Pathway Analysis determined that the gene expression profile of HCN-NOS was unique but significantly similar to that of both hepatoblastoma and HCC. A total of 27,195 CpG sites (CpGs) were significantly differentially methylated (DM) between tumors and controls, with a global hypomethylation pattern and predominant CpG island hypermethylation in promotor regions. Aberrant DNA methylation predominated in Developmental Process and Molecular Function Regulator pathways. Embryonic stem cell pathways were significantly enriched. In total, 1055 aberrantly methylated (at CpGs) and differentially expressed genes were identified, including 25 upstream regulators and sixty-one potential CpG island methylation-regulated genes. Eight methylation-regulated genes (TCF3, MYBL2, SRC, HMGA2, PPARGC1A, SLC22A1, COL2A1 and MYCN) had highly consistent gene expression patterns and prognostic value in patients with HCC, based on comparison to publicly available datasets. Conclusions HCN-NOS has a unique, stem-cell like gene expression and DNA methylation profile related to both hepatoblastoma and HCC but distinct therefrom. Further, 8 methylation-regulated genes associated with prognosis in HCC were identified.
The core genes of cuproptosis assists in discerning prognostic and immunological traits of clear cell renal cell carcinoma

Objective Cuproptosis, a nascent and unique pattern of cell death, is poised to spark a new rush of biological research. Yet, the subsumed mechanism of cuproptosis in carcinoma is not wholly clarified. The exclusive aim of this work is to define a novel classification algorithm and risk-prognosis scoring framework based on the expression modalities of cuproptosis genes to monitor clear cell renal cell carcinoma (ccRCC) patients’ prognosis and immunotherapeutic response. Methods We pooled ccRCC data from three large-scale databases as the training subset and gathered a panel of clinical queues, termed the Taizhou cohort, which served as the validation setup. Wilcox test was conducted for comparison of expression variation, while the cox analysis and KM curves were utilized to visualize prognosis. Unsupervised clustering analysis was used to identify cuproptosis phenotypes in ccRCC. Concurrently, LASSO regression-based computational scoring model. A step further, gene set enrichment analysis (GSEA) was performed to check potential biological processes and the “CIBERSORT” R package was used to estimate the proportion of immune cells. To last, immunohistochemistry and qRT-PCR were carried out for the assay of critical genes for cuproptosis. Results Here, we glimpse the prognostic power of cuproptosis genes in pan-cancer by investigating 33 cancers with multi-omics data to map their genetic heterogeneity landscape. In parallel, we devoted extra attention to their strategic potential role in ccRCC, identifying two phenotypes of cuproptosis with different immune microenvironmental characteristics by pooling ccRCC data from three large-scale databases. Additionally, we compiled a cuproptosis scoring system for clinicians to determine the prognosis, immunotherapy response, and chemosensitivity of ccRCC patients. Notably, we assembled a clinical cohort sample to validate the pivotal gene for cuproptosis, FDX1, to supply more clues to translate the biological significance of cuproptosis in ccRCC. Conclusion In all, our investigations highlight that cuproptosis is involved in various components of ccRCC and assists in the formation of the tumor immune microenvironment. These results provide partial insights to further comprehend the molecular mechanisms of cuproptosis in ccRCC and could be helpful for the development of personalized therapeutic strategies targeting copper or cuproptosis.
Cost-effectiveness of ensartinib, crizotinib, ceritinib, alectinib, brigatinib and lorlatinib in patients with anaplastic lymphoma kinase-positive non-small cell lung cancer in China

Objective Six anaplastic lymphoma kinase-tyrosine kinase inhibitors (ALK-TKIs), including one domestic (ensartinib) and five imported ALK-TKIs (crizotinib, ceritinib, alectinib, brigatinib, and lorlatinib), have been recommended as first-line treatments for advanced ALK-positive NSCLC in China. This study sought to examine the cost-effectiveness of these six novel therapies in Chinese patients. Material and methods We constructed a Markov model to compare the cost-effectiveness of the six ALK-TKIs as a first-line treatment for patients with advanced ALK-positive NSCLC from the perspective of the Chinese healthcare system. Transition probabilities were estimated by synthesizing data from the PROFILE 1,029 trial and a network meta-analysis. Health state utilities and costs were sourced from published literature, publicly available national databases, and local general hospitals. The robustness of model was assessed via deterministic sensitivity analyses and probabilistic sensitivity analyses. Results Compared with crizotinib, ensartinib achieved additional 0.12 quality-adjusted life-year (QALY) with marginal costs of $3,249, resulting in an incremental cost-effectiveness ratio (ICER) of $27,553/ QALY. When compared with ceritinib and brigatinib, ensartinib achieved additional 0.06 and 0.03 QALYs with substantially reduced costs. When compared with lorlatinib and alectinib, ensartinib was associated with a lower QALY and decreased total costs; the ICERs for lorlatinib and alectinib were $934,101/ QALY and $164,888/ QALY, respectively. Conclusion For Chinese patients with advanced ALK-positive NSCLC, ensartinib was a cost-effective option compared with crizotinib, and was a dominant alternative to ceritinib and brigatinib. Although lorlatinib and alectinib were associated with prolonged survival compared with ensartinib, they were less cost-effective than ensartinib due to the overwhelming total costs.
Aging-friendly cities: Investigating the effects of street usage on the psychological satisfaction of older adults in megacities

The psychological satisfaction of older adults is an important evaluation standard for the construction of elder-friendly cities. Meanwhile, as important space carriers carrying the travel activities and social participation of older adults, streets are also of great significance to improve psychological wellbeing. However, few studies pay attention to the street usage of aging population, especially in the context of megacities. Moreover, the previous literature rarely distinguishes the types of streets. Thus, employing a mixed approach, we investigate the relationships between street usage and psychological satisfaction for older adults. Based on the survey in Shanghai, we find that a clear role for different usage indicators in the determination of subjective psychological satisfaction of older adults. More specially, the street usage and psychological satisfaction for older adults are strongly correlated, especially for living streets. Psychological satisfaction for older adults in different types of streets is not always positively related to the positive perception of street usage. The psychological satisfaction of different streets depends on different factors. By focusing on the case of a megacity, our study emphasizes the differences between different types of streets, which will be conducive to the proposal of practical planning policies. In addition, employing mixed research methods not only explains how different street usage affects the psychological welfare of older adults on a macro scale, but also emphasizes the inner world of respondents.
Parsimonious genotype by environment interaction covariance models for cassava (Manihot esculenta)

The assessment of cassava clones across multiple environments is often carried out at the uniform yield trial, a late evaluation stage, before variety release. This is to assess the differential response of the varieties across the testing environments, a phenomenon referred to as genotype-by-environment interaction (GEI). This phenomenon is considered a critical challenge confronted by plant breeders in developing crop varieties. This study used the data from variety trials established as randomized complete block design (RCBD) in three replicates across 11 locations in different agro-ecological zones in Nigeria over four cropping seasons (2016–2017, 2017–2018, 2018–2019, and 2019–2020). We evaluated a total of 96 varieties, including five checks, across 48 trials. We exploited the intricate pattern of GEI by fitting variance–covariance structure models on fresh root yield. The goodness-of-fit statistics revealed that the factor analytic model of order 3 (FA3) is the most parsimonious model based on Akaike Information Criterion (AIC). The three-factor loadings from the FA3 model explained, on average across the 27 environments, 53.5% [FA (1)], 14.0% [FA (2)], and 11.5% [FA (3)] of the genetic effect, and altogether accounted for 79.0% of total genetic variability. The association of factor loadings with weather covariates using partial least squares regression (PLSR) revealed that minimum temperature, precipitation and relative humidity are weather conditions influencing the genotypic response across the testing environments in the southern region and maximum temperature, wind speed, and temperature range for those in the northern region of Nigeria. We conclude that the FA3 model identified the common latent factors to dissect and account for complex interaction in multi-environment field trials, and the PLSR is an effective approach for describing GEI variability in the context of multi-environment trials where external environmental covariables are included in modeling.
Role of transversity in spin effects in meson leptoproduction

We analyze the light meson leptoproduction within the handbag approach. We show that effects determined by the transversity Generalized Parton Distributions (GPDs), $H_T$ and $\bar E_T$ are essential in the description of pseudoscalar and vector meson leptoproduction.
Determination of phage susceptibility as a clinical diagnostic tool: A routine perspective

As the global burden of disease caused by multidrug resistant bacteria is a major source of concern, credible clinical alternatives to antibiotic therapy, such as personalized phage therapy, are actively explored. Although phage therapy has been used for more than a century, the issue of an easy to implement diagnostic tool for determining phage susceptibility that meets current routine clinical needs is still open. In this Review, we summarize the existing methods used for determining phage activity on bacteria, including the three reference methods: the spot test, the double agar overlay plaque assay, and the Appelmans method. The first two methods rely on the principle of challenging the overnight growth of a lawn of bacteria in an agar matrix to a known relative phage to bacteria concentration and represent good screening tools to determine if the tested phage can be used for a “passive” and or “active” treatment. Beside these methods, several techniques, based on “real-time” growth kinetics assays (GKA) have been developed or are under development. They all monitor the growth of clinical isolates in the presence of phages, but use various detection methods, from classical optical density to more sophisticated techniques such as computer-assisted imagery, flow-cytometry, quantitative real-time polymerase chain reaction (qPCR) or metabolic indicators. Practical considerations as well as information provided about phage activity are reviewed for each technique. Finally, we also discuss the analytical and interpretative requirements for the implementation of a phage susceptibility testing tool in routine clinical microbiology.
Exploration of the regulatory mechanisms of regeneration, anti-oxidation, anti-aging and the immune response at the post-molt stage of Eriocheir sinensis

Eriocheir sinensis is widely appreciated by the surrounding population due to its culinary delicacy and rich nutrients. The E. sinensis breeding industry is very prosperous and molting is one of the important growth characteristics. Research on the regulation of molting in E. sinensis is still in the initial stages. There is currently no relevant information on the regulatory mechanisms of heart development following molting. Comparative transcriptome analysis was used to study developmental regulation mechanisms in the heart of E. sinensis at the post-molt and inter-molt stages. The results indicated that many regulatory pathways and genes involved in regeneration, anti-oxidation, anti-aging and the immune response were significantly upregulated after molting in E. sinensis. Aside from cardiac development, the differentially expressed genes (DEGs) were relevant to myocardial movement and neuronal signal transduction. DEGs were also related to the regulation of glutathione homeostasis and biological rhythms in regard to anti-oxidation and anti-aging, and to the regulation of immune cell development and the immune response. This study provides a theoretical framework for understanding the regulation of molting in E. sinensis and in other economically important crustaceans.
Detecting COVID-19 infection status from chest X-ray and CT scan via single transfer learning-driven approach

COVID-19 has caused over 528 million infected cases and over 6.25 million deaths since its outbreak in 2019. The uncontrolled transmission of the SARS-CoV-2 virus has caused human suffering and the death of uncountable people. Despite the continuous effort by the researchers and laboratories, it has been difficult to develop reliable efficient and stable vaccines to fight against the rapidly evolving virus strains. Therefore, effectively preventing the transmission in the community and globally has remained an urgent task since its outbreak. To avoid the rapid spread of infection, we first need to identify the infected individuals and isolate them. Therefore, screening computed tomography (CT scan) and X-ray can better separate the COVID-19 infected patients from others. However, one of the main challenges is to accurately identify infection from a medical image. Even experienced radiologists often have failed to do it accurately. On the other hand, deep learning algorithms can tackle this task much easier, faster, and more accurately. In this research, we adopt the transfer learning method to identify the COVID-19 patients from normal individuals when there is an inadequacy of medical image data to save time by generating reliable results promptly. Furthermore, our model can perform both X-rays and CT scan. The experimental results found that the introduced model can achieve 99.59% accuracy for X-rays and 99.95% for CT scan images. In summary, the proposed method can effectively identify COVID-19 infected patients, could be a great way which will help to classify COVID-19 patients quickly and prevent the viral transmission in the community.
Exergy Decrease in Shock Waves and Boundary Layers of Space Launch Vehicles

Abstract : The exergy method of analysis uses both the First and Second laws of Thermodynamics to determine where losses occur. This method has been shown to be superior to conventional heat balance analyzes. A primary contributor to the exergy decrease is the production of entropy. Entropy is produced in shock waves and boundary layers, as well as in other regions of the flowfield. A method of analysis is presented to quantify the entropy that is produced in the bow shock wave and the boundary layer of a space launch vehicle for Mach numbers between 1.1 and 10. Exergy,
Amaranth as a natural food colorant source: Survey of germplasm and optimization of extraction methods for betalain pigments

Growing consumer demands for healthier foods have evoked trends in the food industry to replace synthetically produced colorants with naturally derived alternatives. Anthocyanins currently comprise the bulk of the natural colorant market, but betalains offer advantages where anthocyanins have limits. Amaranthus species are appealing betalain sources given their extensive pigmentation patterns and recognized food status around the world. An advantage of amaranths as natural food colorants is that, when grown as leafy vegetables, water extracts would be compliant with U.S. Food and Drug Administration guidelines as “vegetable juice” colorants. Thus, we developed a methodology based on U.S. FDA guidelines to investigate betalain diversity among forty-eight amaranth accessions grown as leafy vegetables. Total betacyanin concentrations ranged from 4.7 to 478.8 mg/100 g dry weight, with amaranthin and isoamaranthin identified as major constituents. Our findings will guide future research on amaranths to determine economic viability and suitability for growing natural colorant markets.
A harmonic suppression strategy for grid-connected inverters based on quadrature sinewave extractor

Grid-connected inverters need to reduce current harmonics as much as possible. After introducing the input signal’s fundamental and main harmonic quadrature components, a discrete state model is created, and the discrete observer design method is used to propose a harmonic extraction algorithm called quadrature sinewave extractor (QSE). The QSE is a stable recursive operator with the advantages of no phase displacement and the ability to eliminate mutual influence between harmonic components. Compared to the widely used proportional multi-resonant controller, QSE can reduce current harmonics and improve system stable performance by using it in the current control of grid-connected inverters. Finally, comparative experiments on a three-phase grid-connected inverter are used to verify the proposed method’s effectiveness.
Believing processes around COVID-19 vaccination: An exploratory study investigating workers in the health sector

Background The processes underlying believing have been labeled “creditions”, which are important brain functions between emotion and cognition. Creditions are influenced by both internal and external factors, one of which is the coronavirus disease 2019 (COVID-19) pandemic and the vaccination against the disease. Methods To investigate believing processes shortly before the implementation of a mandatory vaccination in Austria, both vaccinated and unvaccinated workers in the health sector (WHS) were surveyed in December 2021/January 2022. In total, 1,062 vaccinated and 97 unvaccinated WHS (920 females) completed the online survey. Beliefs were assessed using the parameters of the credition model (narrative, certainty, emotion, and mightiness) with regard to (1) the COVID-19 pandemic in general, and (2) the vaccination. Type of emotion and narrative were divided into positive, negative, and indifferent. Moreover, the congruence between emotion and narrative was calculated. Results The vaccination rate of the sample was 91.6%, with a significantly higher percentage of men being in the group of vaccinated (21.1%) as compared to unvaccinated individuals (12.4%). Pertaining beliefs about the COVID-19 vaccination, unvaccinated WHS reported more negative and less positive emotions as well as content of narrative than vaccinated WHS. In addition, they showed higher levels of certainty as well as mightiness while believing and felt less sufficiently informed about governmental and workplace-related COVID-19 measures. The groups did not differ in the type of emotion or content of narrative in their beliefs about the pandemic in general. Conclusion In conclusion, unvaccinated WHS had more negative and less positive emotions and thoughts than vaccinated WHS in their beliefs about the COVID-19 vaccination and their motivations for not having received it. They were more certain about their beliefs and felt stronger negative emotions in their beliefs compared to vaccinated individuals. Providing unvaccinated WHS with adequate information might be helpful in reducing their mental burden.
Small secreted peptides encoded on the wheat (Triticum aestivum L.) genome and their potential roles in stress responses

Small secreted peptides (SSPs) are important signals for cell-to-cell communication in plant, involved in a variety of growth and developmental processes, as well as responses to stresses. While a large number of SSPs have been identified and characterized in various plant species, little is known about SSPs in wheat, one of the most important cereal crops. In this study, 4,981 putative SSPs were identified on the wheat genome, among which 1,790 TaSSPs were grouped into 38 known SSP families. The result also suggested that a large number of the putaitive wheat SSPs, Cys-rich peptides in particular, remained to be characterized. Several TaSSP genes were found to encode multiple SSP domains, including CLE, HEVEIN and HAIRPININ domains, and two potentially novel TaSSP family DYY and CRP8CI were identified manually among unpredicted TaSSPs. Analysis on the transcriptomic data showed that a great proportion of TaSSPs were expressed in response to abiotic stresses. Exogenous application of the TaCEPID peptide encoded by TraesCS1D02G130700 enhanced the tolerance of wheat plants to drought and salinity, suggesting porential roles of SSPs in regulating stress responses in wheat.
Lung microbiome in children with hematological malignancies and lower respiratory tract infections

Background Respiratory infectious complications remain a major cause of morbidity and mortality in children with hematological malignancies. Knowledge regarding the lung microbiome in aforementioned children is limited. Methods A prospective cohort was conducted, enrolling 16 children with hematological malignancies complicated with moderate-to-severe lower respiratory tract infections (LRTIs) versus 21 LRTI children with age, gender, weight, and infection severity matched, with no underlying malignancies, to evaluate the lung microbiome from bronchoalveolar lavage fluid samples in different groups. Results The lung microbiome from children with hematological malignancies and LRTIs showed obviously decreased α and β diversity; increased microbial function in infectious disease:bacteria/parasite; drug resistance:antimicrobial and human pathogenesis than the control group; a significantly reduced proportion of Firmicutes, Bacteroidota, Actinobacteriota; increased Proteobacteria at the phylum level; and distinctly elevated Parabacteroides, Klebsiella, Grimontia, Escherichia_Shigella, unclassified_Enterobacteriaceae at the genus level than the control group. Furthermore, it was revealed that α diversity (Shannon), β diversity (Bray–Curtis dissimilarity), Proteobacteria at the phylum level, and unclassified_Enterobacteriaceae and Escherichia_Shigella at the genus level were significantly negatively associated with hospitalization course whereas Firmicutes at the phylum level was established positively correlated with the hospitalization course. Conclusions Children with hematological malignancies and LRTIs showed obviously decreased α and β diversity, significantly increased function in infectious disease pathogenesis, antimicrobial drug resistance, and unfavorable environment tolerance. Moreover, α diversity (Shannon), β diversity (Bray–Curtis dissimilarity), and Proteobacteria may be used as negative correlated predictors for hospitalization course in these children whereas Firmicutes may be utilized as a positive correlated predictor.