Miracle-dz/UniFAR-FTUs huggingface dataset:
Ferroptosis Modulation: Potential Therapeutic Target for Glioblastoma Treatment

Glioblastoma multiforme is a lethal disease and represents the most common and severe type of glioma. Drug resistance and the evasion of cell death are the main characteristics of its malignancy, leading to a high percentage of disease recurrence and the patients’ low survival rate. Exploiting the modulation of cell death mechanisms could be an important strategy to prevent tumor development and reverse the high mortality and morbidity rates in glioblastoma patients. Ferroptosis is a recently described type of cell death, which is characterized by iron accumulation, high levels of polyunsaturated fatty acid (PUFA)-containing phospholipids, and deficiency in lipid peroxidation repair. Several studies have demonstrated that ferroptosis has a potential role in cancer treatment and could be a promising approach for glioblastoma patients. Thus, here, we present an overview of the mechanisms of the iron-dependent cell death and summarize the current findings of ferroptosis modulation on glioblastoma including its non-canonical pathway. Moreover, we focused on new ferroptosis-inducing compounds for glioma treatment, and we highlight the key ferroptosis-related genes to glioma prognosis, which could be further explored. Thereby, understanding how to trigger ferroptosis in glioblastoma may provide promising pharmacological targets and indicate new therapeutic approaches to increase the survival of glioblastoma patients.
A unique insight for Xiaoyao San exerts antidepressant effects by modulating hippocampal glucose catabolism using stable isotope-resolved metabolomics.

ETHNOPHARMACOLOGICAL RELEVANCE In traditional Chinese medicine (TCM) theory, depression is an emotional disease, which is thought to be related to stagnation of liver qi and dysfunction of the spleen in transport. Xiaoyao San (XYS) is considered to have the effects of soothing liver-qi stagnation and invigorating the spleen. The spleen has the function to transport and transform nutrients. The liver has also termed the center of energy metabolism in the body. Therefore, exploring the antidepressant effects of XYS from the perspective of energy metabolism may reveal new findings. AIM OF THE STUDY Glucose catabolism is an important part of energy metabolism. In recent years, several researchers have found that XYS can exert antidepressant effects by modulating abnormalities in glucose catabolism-related metabolites. The previous research of our research group found that the hippocampus glucose catabolism was disordered in depression. However, the antidepressant potential of XYS through the modulation of hippocampal glucose catabolism and the specific metabolic pathways and targets of XYS action were still unknown. The aim of this study was to address the above scientific questions. MATERIALS AND METHODS In this research, the CUMS (chronic unpredictable mild stress) model was used as the animal model of depression. The antidepressant effect of XYS was evaluated by behavioral indicators. The specific pathways and targets of XYS modulation of glucose catabolism in the hippocampus of CUMS rats were obtained by stable isotope-resolved metabolomics. Further, the isotope tracing results were also verified by molecular biology and electron transmission electron microscopy. RESULTS The results demonstrated that XYS pretreatment could significantly improve the depressive symptom induced by CUMS. More importantly, it was found that XYS could modulate glucose catabolism in the hippocampus of CUMS rats. Stable isotope-resolved metabolomics and enzyme activity tests showed that Lactate dehydrogenase (LDH), Pyruvate carboxylase (PC), and Pyruvate dehydrogenase (PDH) were targets of XYS for modulating glucose catabolism in the hippocampus of CUMS rats. The Succinate dehydrogenase (SDH) and mitochondrial respiratory chain complex V (MRCC-Ⅴ) were targets of XYS to improve abnormal mitochondrial oxidative phosphorylation in the hippocampus of CUMS rats. XYS was also found to have the ability to improve the structural damage of mitochondria and nuclei in the hippocampal caused by CUMS. CONCLUSIONS This study was to explore the antidepressant effect of XYS from the perspective of glucose catabolism based on a strategy combining stable isotope tracing, molecular biology techniques, and transmission electron microscopy. We not only obtained the specific pathways and targets of XYS to improve the disorder of glucose catabolism in the hippocampus of CUMS rats, but also revealed the specific targets of the pathways of XYS compared with VLF.
Midgut Bacterial Communities of Vespa velutina Lepeletier (Hymenoptera: Vespidae)

Vespa velutina nigrithorax and Vespa velutina auraria are two subspecies of Vespa velutina Lepeletier. V. velutina preys managed honey bees, other pollinators, and insects. However, the Vespa midgut microbiota of three forms, namely queens, workers, and males have not been reported, thus the objective of this study was to analyze the midgut bacterial diversity of the three forms of V. v. nigrithorax and V. v. auraria. Our results showed that Proteobacteria, Firmicutes, Bacteroidetes, Tenericutes, and Actinobacteria were the most abundant phyla, and Lactobacillus (17.21%) and Sphingomonas (11.39%) were the most abundant genera in the midgut of V. v. nigrithorax and V. v. auraria. We found that the midgut bacterial compositions of the V. velutina males were special, in terms of richness and diversity of bacterial communities, as well as the content of lactic acid bacteria. By comparing the gut bacterial compositions of Vespa from different regions (Japan, South Korea, Italy, and China), it was discovered that the gut bacterial compositions were very similar at the phylum and class level, and Gammaproteobacteria, Bacilli, and Alphaproteobacteria were the most abundant classes of bacteria and consistent in the genus Vespa. Besides, though Vespa from different regions had quite different gut bacterial communities at the genus level, Lactobacillus and other lactic acid bacteria were abundant and played important roles in protection and metabolism in V. velutina collected from different regions. This is the first report of midgut bacterial diversity of three forms queens, workers, and males of V. velutina. Our findings provide insight that Proteobacteria and Firmicutes (especially Lactobacillus and other lactic acid bacteria) are consistent and may play important roles in the genus Vespa. The understanding of the microbiome in the midgut of Vespa and the discovery of the vital bacteria would provide useful information to design pest biological control agents. Thus, the significance of this study is to provide a basis for the study of the relationship between gut microbiota and physiology and health of Vespa, as well as the control of Vespa.
Adoption of Innovations: Comparing the Imitation and the Threshold Models

This monograph introduces and compares the two leading frameworks for analyzing the adoption and diﬀusion of innovations – the imitation and threshold models. Imitation models perceive the diﬀusion process as being driven pri-marily by communication, whether initiated by the ﬁrm or between existing and potential customers, and are partic-ularly useful when aggregate data is available, and allows the incorporation of some economic variables. By contrast, the threshold model emphasizes individual micro-economic decision making and explains the diﬀerences in the timing of adoption by heterogeneity among individuals or ﬁrms while the dynamic processes of learning aﬀect costs as well as perceptions of value that drive the diﬀusion process. The threshold model provides a foundation to use cross section and panel data to estimate factors that aﬀect diﬀerences We show how to incorporate multiple marketing tools into both models. We ﬁnd that the threshold model aﬀords a more reﬁned consideration of risk to optimize the choice of marketing tools because the threshold model can explicitly incorporate various economic frameworks such as expected utility, loss aversion and disappointment models, the safety-rule approach, and real-option theory. We illustrate how to manage marketing risk reduction tools in this context, including money back guarantees and demonstrations. Our review suggests that the two models should be treated as complementary models rather than as substitutes for each other. Our analysis expands on the analysis and design of marketing tools in promoting diﬀusion and discusses how to enhance their relevance and eﬀectiveness. It also provides a bridge between marketing tools and the economic analysis of diﬀusion.
Drug-food Interactions in the Era of Molecular Big Data, Machine Intelligence, and Personalized Health

The drug-food interaction brings forth changes in the clinical effects of drugs. While favourable interactions bring positive clinical outcomes, unfavourable interactions may lead to toxicity. This article reviews the impact of food intake on drug-food interactions, the clinical effects of drugs, and the effect of drug-food in correlation with diet and precision medicine. Emerging areas in drug-food interactions are the food-genome interface (nutrigenomics) and nutrigenetics. Understanding the molecular basis of food ingredients, including genomic sequencing and pharmacological implications of food molecules, helps to reduce the impact of drug-food interactions. Various strategies are being leveraged to alleviate drug-food interactions; measures including patient engagement, digital health, approaches involving machine intelligence, and big data are a few of them. Furthermore, delineating the molecular communications across diet-microbiome-drug-food-drug interactions in a pharmacomicrobiome framework may also play a vital role in personalized nutrition. Determining nutrient-gene interactions aids in making nutrition deeply personalized and helps mitigate unwanted drug-food interactions, chronic diseases, and adverse events from their onset. Translational bioinformatics approaches could play an essential role in the next generation of drug-food interaction research. In this landscape review, we discuss important tools, databases, and approaches along with key challenges and opportunities in drug-food interaction and its immediate impact on precision medicine.
FCFusion: Fractal Componentwise Modeling With Group Sparsity for Medical Image Fusion

Multimodal image fusion is the process of combing relevant biological information that can be used for automated industrial application. In this article, we present a novel framework combining fractal constraint with group sparsity to achieve the optimal fusion quality. First, we adopt the idea of patch division and componentwise separation to perceive the fractal characteristics across multimodality sources. Then, to preserve the spatial information against the redundancy of component-entanglement, the group sparsity is proposed. A dual variable weighting rule is inherently embedded to mitigate the overfitting across the component penalty. Furthermore, the alternating direction method of multipliers is conducted to the proposed model optimization. The experiments show that our model has a better performance in quantitative visual quality and qualitative evaluation analysis. Finally, a real segmentation application of positron emission tomography/computed tomography image fusion proves the effectiveness of our algorithm.
Value of Literature Review to Inform Development and Use of Biologics in Juvenile Idiopathic Arthritis

Background Juvenile idiopathic arthritis (JIA) is one of the most common pediatric inflammatory rheumatic diseases (PiRDs). Uncontrolled disease activity is associated with decreased quality of life and chronic morbidity. Biologic disease-modifying antirheumatic drugs (bDMARDs) and Janus kinase inhibitors (JAKi) have considerably improved clinical outcomes. For optimized patient care, understanding the efficacy-safety profile of biologics in subgroups of JIA is crucial. This systematic review based on published randomized controlled trials (RCTs) aims to assess efficacy and safety data for bDMARDs and JAKi with various JIA subgroups after 3 months of treatment. Methods Data for American College of Rheumatology (ACR) pediatric (Pedi) 30, 50, and/or 70 responses after 3 months of treatment were selected from RCTs investigating bDMARDs or JAKi in JIA according to predefined inclusion/exclusion criteria. Treatment and control arms were compared by calculating risk ratios (RRs) with 95% confidence intervals (CIs), and proportions of overall, serious adverse events (AEs) and infections were analyzed. Forest plots were generated to summarize efficacy and safety endpoints across studies, JIA subgroups, and type of biologics. Results Twenty-eight out of 41 PiRD RCTs investigated bDMARD or JAKi treatments in JIA. 9 parallel RCTs reported ACR Pedi 30, 50, and/or 70 responses 3 months after treatment initiation. All treatment arms showed improved ACR Pedi responses over controls. RRs ranged from 1.05 to 3.73 in ACR Pedi 30, from 1.20 to 7.90 in ACR Pedi 50, and from 1.19 to 8.73 in ACR Pedi 70. An enhanced effect for ACR Pedi 70 was observed with infliximab combined with methotrexate in PJIA vs. methotrexate monotherapy. A slightly higher risk of gastrointestinal AEs and infections was observed with treatment arms compared to placebo or methotrexate monotherapy. Conclusion Investigated bDMARDs and JAKi showed superior treatment responses compared to controls after 3 months of treatment, which were more pronounced in ACR Pedi 50 and 70 than in ACR Pedi 30. Higher susceptibility to infections associated with bDMARDs or JAKi vs. control arms must be weighed against efficacious treatment of the underlying disease and prevention of disease-related damage. Additional RCTs are warranted to further inform development and utilization of biologics in JIA.
Elephants and Sirenians: A Comparative Review across Related Taxa in Regard to Learned Vocal Behavior

Vocal production learning is the ability to modify a vocal output in response to auditory experience. It is essential for human speech production and language acquisition. Vocal learning evolved independently several times in vertebrates, indicating evolutionary pressure in favor of this trait. This enables cross-species comparative analysis to be used to test evolutionary hypotheses. Humans share this ability with a versatile but limited group of species: songbirds, parrots and hummingbirds, bats, cetaceans, seals, and elephants. Although case studies demonstrate that African savanna and Asian elephants are capable of heterospecific imitation, including imitation of human words, our under standing of both the underlying mechanisms and the adaptive relevance within the elephant’s natural communication system is limited. Even though comparing phylogenetically distant species is intriguing, it is also worthwhile to investigate whether and to what extent learned vocal behavior is apparent in species phylogenetically close to an established vocal learner. For elephants, this entails determining whether their living relatives share their special ability for (complex) vocal learning. In this review, we address vocal learning in Elephantidea and Sirenia, sister groups within the Paenungulata. So far, no research has been done on vocal learning in Sirenians. Because of their aquatic lifestyle, vocalization structure, and evolutionary relationship to elephants, we believe Sirenians are a particularly interesting group to study. This review covers the most important acoustic aspects related to vocal learning in elephants, manatees, and dugongs, as well as knowledge gaps that must be filled for one to fully comprehend why vocal learning evolved (or did not) in these distinctive but phylogenetically related taxa. intellectual into the design of Figure 5, illustrating the manatee and elephant vocal apparatus.
Accounts from the backwoods: The role of accounting in an early Upper Canada settlement

The founding of the town of Guelph, Ontario, was uncommon in that the town was established prior to the development of surrounding agricultural lands. This was done through an arrangement between the British government and a private, for-profit company. Grounded in agency theory, this study examines the establishment of the town and the role of accounting in its early development. The results show how the absence of accounting created a space in which the company's agent could operate in a way that promoted the well-being of the local population while adopting a long-term approach to shareholder wealth creation. This study highlights the insights that can be gained by investigating where accounting is absent and the importance of aligning accounting techniques with organisational and social objectives, particularly in the context of private companies acting on behalf of governments.
Premature Greying of Hair and Role of Oiling in Indian Perspective

Hairs are said to grey prematurely only if greying occurs before the age of 20 years in Whites, 25 years in Asians and 30 years in Africans [3]. Caucasian people will begin to grey in their mid-thirties, AfricanAmerican people can retain their original hair colour until their midforties, Asian people begin greying in their late thirties, however as compared to South Indian population, North Indians begin to grey in their early thirties. Premature greying of hairs has significant effect on self-esteem and social acceptance of the individual as it is viewed as a sign of old age and loss of health and vigor.
Transcriptomic and Metabolomic Analysis of Seedling-Stage Soybean Responses to PEG-Simulated Drought Stress

Soybean is an important crop grown worldwide, and drought stress seriously affects the yield and quality of soybean. Therefore, it is necessary to elucidate the molecular mechanisms underlying soybean resistance to drought stress. In this study, RNA-seq technology and ultra-performance liquid chromatography–tandem mass spectrometry were used to analyze the transcriptome and metabolome changes in soybean leaves at the seedling stage under drought stress. The results showed that there were 4790 and 3483 DEGs (differentially expressed genes) and 156 and 124 DAMs (differentially expressed metabolites), respectively, in the HN65CK vs. HN65S0 and HN44CK vs. HN44S0 comparison groups. Comprehensive analysis of transcriptomic and metabolomic data reveals metabolic regulation of seedling soybean in response to drought stress. Some candidate genes such as LOC100802571, LOC100814585, LOC100777350 and LOC100787920, LOC100800547, and LOC100785313 showed different expression trends between the two cultivars, which may cause differences in drought resistance. Secondly, a large number of flavonoids were identified, and the expression of Monohydroxy-trimethoxyflavone-O-(6″-malonyl)glucoside was upregulated between the two varieties. Finally, several key candidate genes and metabolites involved in isoflavone biosynthesis and the TCA cycle were identified, suggesting that these metabolic pathways play important roles in soybean response to drought. Our study deepens the understanding of soybean drought resistance mechanisms and provides references for soybean drought resistance breeding.
Multiscale Adaptive Convolution for Hyperspectral Image Classification

Convolutional neural network (CNN) is widely used in hyperspectral image (HSI) classification owing to their advantages of spatial-spectral features capture capability and learning depth features as well as their structural flexibility. Nevertheless, the shape of the convolution kernel is fixed, a limitation that leads to shape fixation when modeling different features in CNN, especially in the edge regions between classes. A multiscale adaptive convolution (MSAC) model is proposed in this article to overcome this shortcoming. Combining superpixels with the traditional convolutional kernels to form adaptive kernels automatically adjusts the receptive field, suppresses edge noise, and enhances feature learning for different classes. On the basis of adaptive convolution, adaptive convolution units (AConvUs) are constructed. The hierarchical residual structure is constructed by superimposing multiple AConvUs to learn the spatial spectral features of different receptive fields of the HSI, reduce the gradient disappearance and enhance the robustness. The proposed multiscale convolution adjusts the shape of the convolution kernel according to the spatial distribution of different superpixels in HSI. Finally, the MSAC classification framework is constructed by the decision fusion of multiscale adaptive convolution at different superpixel scales, which helps to extract the complementary information of the HSI. The MSAC method’s experimental performance on several HSI datasets, including Indian Pines, University of Pavia, Salinas and Gaofen-5, to verify the validity and practically.
Do indigenous territories sustain the standing Amazon forest? The case of the Sete de Setembro Indigenous Land

This work presents a spatiotemporal analysis of deforestation and vegetation fires in the Sete de Setembro Indigenous Land (SSIL), located between the states of Rondônia and Mato Grosso, a region known as “Arc of Deforestation” in the Brazilian Legal Amazon. The distribution of the occurrence of fires and deforestation in the SSIL and its surroundings were evaluated, considering five buffer zones in relation to its perimeter: 1) Core: the innermost area of the SSIL; 2) internal buffer 0 to 5 km; 3) internal buffer 5 – 10km; 4) external buffer 0 to 5 km; 5) external buffer 5 to 10 km. For the spatio-temporal analysis of forest fires, we considered the reference satellite data from 2000 to 2020 available at Queimadas Program. PRODES data were analyzed to quantify deforestation, considering the clear cut from 2008 onwards. Vegetation fires on SSLI occur predominantly on the borders and presented a considerable reduction since 2004, when the Action Plan for the Prevention and Control of Deforestation in the Legal Amazon (PPCDAm) was created. Less than 1% of SSLI has been clear cut since 2008; however, considering the Legal Amazon, there is a trend towards an increase in forest removal since 2018. This increase is mainly associated with cattle in the municipalities where SSLI is located. SSIL has been efficient in holding deforestation and fires in its interior, although it is exposed and vulnerable to anthropization in its surroundings, mainly resulting from the dense network of highways and roads in that region. seu entorno, considerando cinco zonas de amortecimento em relação ao seu perímetro: 1) Núcleo: a área mais interna da TISS; 2) buffer interno de 0 a 5 km; 3) buffer interno 5 – 10km; 4) buffer externo de 0 a 5 km; 5) buffer externo de 5 a 10 km. Para a análise espaço-temporal dos incêndios florestais, foram considerados os dados do satélite de referência de 2000 a 2020 disponíveis no Programa Queimadas. Os dados do PRODES foram analisados para quantificar o desmatamento, considerando o corte raso a partir de 2008. As queimadas na TISS ocorrem predominantemente nas fronteiras e apresentaram uma redução considerável desde 2004, quando foi criado o Plano de Ação para Prevenção e Controle do Desmatamento na Amazônia Legal (PPCDAm). Menos de 1% da TISS foi desmatado desde 2008; no entanto, considerando a Amazônia Legal, há uma tendência de aumento da remoção florestal desde 2018. Esse aumento está associado principalmente ao gado nos municípios onde a TISS está localizada. A TISS tem se mostrado eficiente na contenção de desmatamentos e queimadas em seu interior, embora esteja exposta e vulnerável à antropização em seu entorno, decorrente principalmente da densa rede de rodovias e estradas naquela região. desmatamento, queimadas, conservação, floresta tropical.