Rapamycin sensitizes T-ALL cells to dexamethasone-induced apoptosis

<p>Abstract</p> <p>Background</p> <p>Glucocorticoid (GC) resistance is frequently seen in acute lymphoblastic leukemia of T-cell lineage (T-ALL). In this study we investigate the potential and mechanism of using rapamycin to restore the sensitivity of GC-resistant T-ALL cells to dexamethasone (Dex) treatment.</p> <p>Methods</p> <p>Cell proliferation was detected by 3-(4,5-dimethylthiazol-2-yl)- 2,5-diphenyltetrazolium bromide (MTT) assay. Fluorescence-activated cell sorting (FACS) analysis was used to analyze apoptosis and cell cycles. Western blot analysis was performed to test the expression of the downstream effector proteins of mammalian target of rapamycin (mTOR), the cell cycle regulatory proteins, and apoptosis associated proteins.</p> <p>Results</p> <p>10 nM rapamycin markedly increased GC sensitivity in GC-resistant T-ALL cells and this effect was mediated, at least in part, by inhibition of mTOR signaling pathway. Cell cycle arrest was associated with modulation of G₁-S phase regulators. Both rapamycin and Dex can induce up-regulation of cyclin-dependent kinase (CDK) inhibitors of p21 and p27 and co-treatment of rapamycin with Dex resulted in a synergistic induction of their expressions. Rapamycin did not obviously affect the expression of cyclin A, whereas Dex induced cyclin A expression. Rapamycin prevented Dex-induced expression of cyclin A. Rapamycin had a stronger inhibition of cyclin D1 expression than Dex. Rapamycin enhanced GC-induced apoptosis and this was not achieved by modulation of glucocorticoid receptor (GR) expression, but synergistically up-regulation of pro-apoptotic proteins like caspase-3, Bax, and Bim, and down-regulation of anti-apoptotic protein of Mcl-1.</p> <p>Conclusion</p> <p>Our data suggests that rapamycin can effectively reverse GC resistance in T-ALL and this effect is achieved by inducing cell cycles arrested at G₀/G₁phase and activating the intrinsic apoptotic program. Therefore, combination of mTOR inhibitor rapamycin with GC containing protocol might be an attracting new therapeutic approach for GC resistant T-ALL patients.</p

Towards Interpretable Natural Language Understanding with Explanations as Latent Variables

Recently generating natural language explanations has shown very promising results in not only offering interpretable explanations but also providing additional information and supervision for prediction. However, existing approaches usually require a large set of human annotated explanations for training while collecting a large set of explanations is not only time consuming but also expensive. In this paper, we develop a general framework for interpretable natural language understanding that requires only a small set of human annotated explanations for training. Our framework treats natural language explanations as latent variables that model the underlying reasoning process of a neural model. We develop a variational EM framework for optimization where an explanation generation module and an explanation-augmented prediction module are alternatively optimized and mutually enhance each other. Moreover, we further propose an explanation-based self-training method under this framework for semi-supervised learning. It alternates between assigning pseudo-labels to unlabeled data and generating new explanations to iteratively improve each other. Experiments on two natural language understanding tasks demonstrate that our framework can not only make effective predictions in both supervised and semi-supervised settings, but also generate good natural language explanation

Unlock Multi-Modal Capability of Dense Retrieval via Visual Module Plugin

This paper proposes Multi-modAl Retrieval model via Visual modulE pLugin (MARVEL) to learn an embedding space for queries and multi-modal documents to conduct retrieval. MARVEL encodes queries and multi-modal documents with a unified encoder model, which helps to alleviate the modality gap between images and texts. Specifically, we enable the image understanding ability of a well-trained dense retriever, T5-ANCE, by incorporating the image features encoded by the visual module as its inputs. To facilitate the multi-modal retrieval tasks, we build the ClueWeb22-MM dataset based on the ClueWeb22 dataset, which regards anchor texts as queries, and exact the related texts and image documents from anchor linked web pages. Our experiments show that MARVEL significantly outperforms the state-of-the-art methods on the multi-modal retrieval dataset WebQA and ClueWeb22-MM. Our further analyses show that the visual module plugin method is tailored to enable the image understanding ability for an existing dense retrieval model. Besides, we also show that the language model has the ability to extract image semantics from image encoders and adapt the image features in the input space of language models. All codes are available at https://github.com/OpenMatch/MARVEL

Purification and characterization of three laccase isozymes from the white rot fungus Trametes sp. HS-03

Three laccase isozymes (LacI, LacII and LacIII) were isolated from the culture supernatant solution of Trametes sp. HS-03. Diethylaminoethyl (DEAE)-sepharose fast flow anion exchange chromatography and Sephadex G-100 size-exclusion chromatography was performed to achieve electrophoretic homogeneity. The molecular masses (64.2, 60.7 and 38.9 kDa), isoelectric points [pIs (7.3, 4.7 and 3.5), and N-terminal amino acid sequences (G-I-G-P-V, A-I-G-P-T and S-I-G-P-V) were found to be different for the three laccase isozymes. LacI and II have similar thermostability, while LacIII showed better thermostability. LacIII also showed optimal activity at 80°C, with a half-life of 125 min at 70°C. The pI-value of LacI and the molecular mass of LacIII differ significantly from previously described fungal laccases.Keywords: Trametes sp. HS-03, laccase isozymes, purification, characterizatio

Training Socially Aligned Language Models on Simulated Social Interactions

Social alignment in AI systems aims to ensure that these models behave according to established societal values. However, unlike humans, who derive consensus on value judgments through social interaction, current language models (LMs) are trained to rigidly replicate their training corpus in isolation, leading to subpar generalization in unfamiliar scenarios and vulnerability to adversarial attacks. This work presents a novel training paradigm that permits LMs to learn from simulated social interactions. In comparison to existing methodologies, our approach is considerably more scalable and efficient, demonstrating superior performance in alignment benchmarks and human evaluations. This paradigm shift in the training of LMs brings us a step closer to developing AI systems that can robustly and accurately reflect societal norms and values.Comment: Code, data, and models can be downloaded via https://github.com/agi-templar/Stable-Alignmen

RNA interference in cytochrome P450 monooxygenase (CYP) gene results in reduced insecticide resistance in Megalurothrips usitatus Bagnall

Genes of the cytochrome P450 (CYP450) superfamily are known to be involved in the evolution of insecticide resistance. In this study, the transcriptomes of two Megalurothrips usitatus Bagnall (Thysanoptera: Thripidae) strains (resistant and susceptible) were screened for detoxification genes. MusiDN2722 encodes a protein composed of 504 amino acid residues with a relative molecular mass of 57.3 kDa. Multiple sequence alignment and phylogenetic analysis showed that MusiDN2722 is a member of the CYP450 family and has characteristics of the conserved CYP6 domain shared by typical CYP450 family members. RT-qPCR (real-time quantitative polymerase chain reaction) analysis showed that MusiDN2722 was upregulated in the acetamiprid-resistant strain compared with the susceptible strain (p &lt; 0.05), and the relative expression level was significantly higher at 48 h after exposure than at 24 h after exposure. The interference efficiency of the injection method was higher than that of the membrane-feeding method. Silencing of MusiDN2722 through RNA interference significantly increased the sensitivity of M. usitatus to acetamiprid. Overall, this study revealed that MusiDN2722 plays a crucial role in the resistance of M. usitatus to acetamiprid. The findings will not only advance our understanding of the role of P450s in insecticide resistance but also provide a potential target for the sustainable control of destructive pests such as thrips

Efficient photocatalytic degradation of Malachite Green in seawater by the hybrid of Zinc-Oxide Nanorods Grown on Three-Dimensional (3D) reduced graphene oxide(RGO)/Ni foam

A hybrid of ZnO nanorods grown onto three-dimensional (3D) reduced graphene oxide (RGO)@Ni foam (ZnO/RGO@NF) is synthesized by a facile hydrothermal method. The as-prepared hybrid material is physically characterized by SEM, XRD, Raman, and X-ray photoelectron spectroscopy (XPS).When the as-prepared 3D hybrid is investigated as a photocatalyst, it demonstrates significant high photocatalytic activity for the degradation of methylene blue (MB), rhodamine (RhB), and mixed MB/RhB as organic dye pollutants. In addition, the practical application and the durability of the as-prepared catalyst to degradation of malachite green (MG) in seawater are firstly assessed in a continuous flow system. The catalyst shows a high degradation efficiency and stable photocatalytic activity for 5 h continuous operation, which should be a promising catalyst for the degradation of organic dyes in seawater

Overexpression of MsSAG113 gene promotes leaf senescence in alfalfa via participating in the hormone regulatory network

IntroductionAlfalfa (Medicago sativa) is a kind of high quality leguminous forage species, which was widely cultivated in the world. Leaf senescence is an essential process in plant development and life cycle. Here, we reported the isolation and functional analysis of an alfalfa SENESCENCE-ASSOCIATED GENE113 (MsSAG113), which belongs to the PP2C family and mainly plays a role in promoting plant senescence.MethodsIn the study, Agrobacterium-mediated, gene expression analysis, next generation sequencing, DNA pull-down, yeast single hybridization and transient expression were used to identify the function of MsSAG113 gene.ResultsThe MsSAG113 gene was isolated from alfalfa, and the transgenic plants were obtained by Agrobacterium-mediated method. Compared with the wildtype, transgenic plants showed premature senescence in leaves, especially when cultivated under dark conditions. Meanwhile, application of exogenous hormones ABA, SA, MeJA, obviously acclerated leaf senescence of transgenic plants. Furthermore, the detached leaves from transgenic plants turned yellow earlier with lower chlorophyll content. Transcriptome analysis identified a total of 1,392 differentially expressed genes (DEGs), involving 13 transcription factor families. Of which, 234 genes were related to phytohormone synthesis, metabolism and transduction. Pull-down assay and yeast one-hybrid assay confirmed that alfalfa zinc finger CCCH domain-containing protein 39 (MsC3H-39) could directly bind the upstream of MsSAG113 gene. In conclusion, the MsSAG113 gene plays a crucial role in promoting leaf senescence in alfalfa via participating in the hormone regulatory network.DiscussionThis provides an essential basis for further analysis on the regulatory network involving senescence-associated genes in alfalfa

Application of quantitative real-time PCR to detect Mink Circovirus in minks, foxes and raccoon dogs in northern China

Mink circovirus disease caused by Mink Circovirus (MiCV) is a serious infectious disease of mink that has become prevalent in recent years in China, severely affecting the reproductive performance of mink and causing significant economic losses to farms. To date, there have been few studies on MiCV, its pathogenic mechanism is not clear, and there is no effective vaccine or drug to prevent and control the disease. Therefore, it is necessary to establish a rapid and reliable molecular diagnostic method, which would aid future studies of this novel virus. In our study, we developed a sensitive and specific TaqMan-based quantitative real-time PCR assay targeting the MiCV Cap gene. The assay showed no cross-reaction with other tested animal viruses. The assay is highly sensitive, with a detection limit of as low as 10 plasmid DNA copies and 2.38 × 10−2 pg of viral DNA. The intra and inter--assay coefficients of variation were both low. The positive detection rate of MiCV in clinical samples from minks, foxes, and raccoon dogs were 58.8% (133/226), 50.7% (72/142), and 42.2% (54/128), respectively, giving a total positive detection rate of 52.2% (259/496). Higher contamination levels were observed in samples from the environment in direct or indirect contact with animals, with a total positive detection rate of 75.1% (220/293). These epidemiological results showed that minks, foxes, and raccoon dogs had high infection rates of MiCV. This was also the first study to detect MiCV on the ground and equipment of fur-bearing animal farms. Our assay is highly sensitive and specific for the diagnosis and quantification of MiCV, and should provide a reliable real-time tool for epidemiological and pathogenetic study of MiCV infection

Analysis of COVID-19 Guideline Quality and Change of Recommendations: A Systematic Review.

Background Hundreds of coronavirus disease 2019 (COVID-19) clinical practice guidelines (CPGs) and expert consensus statements have been developed and published since the outbreak of the epidemic. However, these CPGs are of widely variable quality. So, this review is aimed at systematically evaluating the methodological and reporting qualities of COVID-19 CPGs, exploring factors that may influence their quality, and analyzing the change of recommendations in CPGs with evidence published. Methods We searched five electronic databases and five websites from 1 January to 31 December 2020 to retrieve all COVID-19 CPGs. The assessment of the methodological and reporting qualities of CPGs was performed using the AGREE II instrument and RIGHT checklist. Recommendations and evidence used to make recommendations in the CPGs regarding some treatments for COVID-19 (remdesivir, glucocorticoids, hydroxychloroquine/chloroquine, interferon, and lopinavir-ritonavir) were also systematically assessed. And the statistical inference was performed to identify factors associated with the quality of CPGs. Results We included a total of 92 COVID-19 CPGs developed by 19 countries. Overall, the RIGHT checklist reporting rate of COVID-19 CPGs was 33.0%, and the AGREE II domain score was 30.4%. The overall methodological and reporting qualities of COVID-19 CPGs gradually improved during the year 2020. Factors associated with high methodological and reporting qualities included the evidence-based development process, management of conflicts of interest, and use of established rating systems to assess the quality of evidence and strength of recommendations. The recommendations of only seven (7.6%) CPGs were informed by a systematic review of evidence, and these seven CPGs have relatively high methodological and reporting qualities, in which six of them fully meet the Institute of Medicine (IOM) criteria of guidelines. Besides, a rapid advice CPG developed by the World Health Organization (WHO) of the seven CPGs got the highest overall scores in methodological (72.8%) and reporting qualities (83.8%). Many CPGs covered the same clinical questions (it refers to the clinical questions on the effectiveness of treatments of remdesivir, glucocorticoids, hydroxychloroquine/chloroquine, interferon, and lopinavir-ritonavir in COVID-19 patients) and were published by different countries or organizations. Although randomized controlled trials and systematic reviews on the effectiveness of treatments of remdesivir, glucocorticoids, hydroxychloroquine/chloroquine, interferon, and lopinavir-ritonavir for patients with COVID-19 have been published, the recommendations on those treatments still varied greatly across COVID-19 CPGs published in different countries or regions, which may suggest that the CPGs do not make sufficient use of the latest evidence. Conclusions Both the methodological and reporting qualities of COVID-19 CPGs increased over time, but there is still room for further improvement. The lack of effective use of available evidence and management of conflicts of interest were the main reasons for the low quality of the CPGs. The use of formal rating systems for the quality of evidence and strength of recommendations may help to improve the quality of CPGs in the context of the COVID-19 pandemic. During the pandemic, we suggest developing a living guideline of which recommendations are supported by a systematic review for it can facilitate the timely translation of the latest research findings to clinical practice. We also suggest that CPG developers should register the guidelines in a registration platform at the beginning for it can reduce duplication development of guidelines on the same clinical question, increase the transparency of the development process, and promote cooperation among guideline developers all over the world. Since the International Practice Guideline Registry Platform has been created, developers could register guidelines prospectively and internationally on this platform