The RNA m6A writer METTL3 in tumor microenvironment: emerging roles and therapeutic implications

The tumor microenvironment (TME) is a heterogeneous ecosystem comprising cancer cells, immune cells, stromal cells, and various non-cellular components, all of which play critical roles in controlling tumor progression and response to immunotherapies. Methyltransferase-like 3 (METTL3), the core component of N6-methyladenosine (m6A) writer, is frequently associated with abnormalities in the m6A epitranscriptome in different cancer types, impacting both cancer cells and the surrounding TME. While the impact of METTL3 on cancer cells has been extensively reviewed, its roles in TME and anti-cancer immunity have not been comprehensively summarized. This review aims to systematically summarize the functions of METTL3 in TME, particularly its effects on tumor-infiltrating immune cells. We also elaborate on the underlying m6A-dependent mechanism. Additionally, we discuss ongoing endeavors towards developing METTL3 inhibitors, as well as the potential of targeting METTL3 to bolster the efficacy of immunotherapy

Metabonomic Profiles Delineate the Effect of Traditional Chinese Medicine Sini Decoction on Myocardial Infarction in Rats

Background: In spite of great advances in target-oriented Western medicine for treating myocardial infarction (MI), it is still a leading cause of death in a worldwide epidemic. In contrast to Western medicine, Traditional Chinese medicine (TCM) uses a holistic and synergistic approach to restore the balance of Yin-Yang of body energy so the body’s normal function can be restored. Sini decoction (SND) is a well-known formula of TCM which has been used to treat MI for many years. However, its holistic activity evaluation and mechanistic understanding are still lacking due to its complex components. Methodology/Principal Findings: A urinary metabonomic method based on nuclear magnetic resonance and ultra highperformance liquid chromatography coupled to mass spectrometry was developed to characterize MI-related metabolic profiles and delineate the effect of SND on MI. With Elastic Net for classification and selection of biomarkers, nineteen potential biomarkers in rat urine were screened out, primarily related to myocardial energy metabolism, including the glycolysis, citrate cycle, amino acid metabolism, purine metabolism and pyrimidine metabolism. With the altered metabolism pathways as possible drug targets, we systematically analyze the therapeutic effect of SND, which demonstrated that SND administration could provide satisfactory effect on MI through partially regulating the perturbed myocardial energy metabolism. Conclusions/Significance: Our results showed that metabonomic approach offers a useful tool to identify MI-relate

A POLYMER-BASED MICROFLUIDIC RESISTIVE SENSOR FOR DETECTING DISTRIBUTED LOADS

ABSTRACT This paper reports on a polymer-based microfluidic resistive sensor for detecting distributed loads. The sensor is comprised of a polymer rectangular microstructure with an embedded electrolyte-filled microchannel and an array of electrodes aligned along the microchannel length. Electrolyte solution in the microchannel serves as impedance transduction. Distributed loads acting on the polymer microstructure give rise to different deflection along the microstructure length, which is recorded as the resistance change in electrolyte solution. This sensor can detect distributed loads by monitoring the resistance change at each pair of electrodes. A sensor with an in-plane dimension of ~20mm10mm and five pairs of electrodes is fabricated using a CNC machine. 1M KCl solution is used as the electrolyte. Using a custom built electronic circuit on breadboard and a custom LabVIEW program, the static and dynamic performance of the sensor is characterized, demonstrating the feasibility of employing this sensor to detect distributed loads

Potential Biomarkers in Mouse Myocardium of Doxorubicin-Induced Cardiomyopathy: A Metabonomic Method and Its Application

BACKGROUND: Doxorubicin (DOX) is one of the most potent antitumor agents available; however, its clinical use is limited because of the risk of severe cardiotoxicity. Though numerous studies have ascribed DOX cardiomyopathy to specific cellular pathways, the precise mechanism remains obscure. Sini decoction (SND) is a well-known formula of Traditional Chinese Medicine (TCM) and is considered as efficient agents against DOX-induced cardiomyopathy. However, its action mechanisms are not well known due to its complex components. METHODOLOGY/PRINCIPAL FINDINGS: A tissue-targeted metabonomic method using gas chromatography-mass spectrometry was developed to characterize the metabolic profile of DOX-induced cardiomyopathy in mice. With Elastic Net for classification and selection of biomarkers, twenty-four metabolites corresponding to DOX-induced cardiomyopathy were screened out, primarily involving glycolysis, lipid metabolism, citrate cycle, and some amino acids metabolism. With these altered metabolic pathways as possible drug targets, we systematically analyzed the protective effect of TCM SND, which showed that SND administration could provide satisfactory effect on DOX-induced cardiomyopathy through partially regulating the perturbed metabolic pathways. CONCLUSIONS/SIGNIFICANCE: The results of the present study not only gave rise to a systematic view of the development of DOX-induced cardiomyopathy but also provided the theoretical basis to prevent or modify expected damage

In Search of the Long-Tail: Systematic Generation of Long-Tail Knowledge via Logical Rule Guided Search

Since large language models have approached human-level performance on many tasks, it has become increasingly harder for researchers to find tasks that are still challenging to the models. Failure cases usually come from the long-tail distribution - data that an oracle language model could assign a probability on the lower end of its distribution. Current methodology such as prompt engineering or crowdsourcing are insufficient for creating long-tail examples because humans are constrained by cognitive bias. We propose a Logic-Induced-Knowledge-Search (LINK) framework for systematically generating long-tail knowledge statements. Grounded by a symbolic rule, we search for long-tail values for each variable of the rule by first prompting a LLM, then verifying the correctness of the values with a critic, and lastly pushing for the long-tail distribution with a reranker. With this framework we construct a dataset, Logic-Induced-Long-Tail (LINT), consisting of 200 symbolic rules and 50K knowledge statements spanning across four domains. Human annotations find that 84% of the statements in LINT are factually correct. In contrast, ChatGPT and GPT4 struggle with directly generating long-tail statements under the guidance of logic rules, each only getting 56% and 78% of their statements correct. Moreover, their "long-tail" generations in fact fall into the higher likelihood range, and thus are not really long-tail. Our findings suggest that LINK is effective for generating data in the long-tail distribution while enforcing quality. LINT can be useful for systematically evaluating LLMs' capabilities in the long-tail distribution. We challenge the models with a simple entailment classification task using samples from LINT. We find that ChatGPT and GPT4's capability in identifying incorrect knowledge drop by ~3% in the long-tail distribution compared to head distribution

Polysaccharides from Enteromorpha prolifera Improve Glucose Metabolism in Diabetic Rats

This study investigated the effects of polysaccharides from Enteromorpha prolifera (PEP) on glucose metabolism in a rat model of diabetes mellitus (DM). PEP (0, 150, 300, and 600 mg/kg) was administered intragastrically to rats for four weeks. After treatment, fasting blood glucose (FBG) and insulin (INS) levels were measured, and the insulin sensitivity index (ISI) was calculated. The morphopathological changes in the pancreas were observed. Serum samples were collected to measure the oxidant-antioxidant status. The mRNA expression levels of glucokinase (GCK) and insulin receptor (InsR) in liver tissue and glucose transporter type 4 (GLUT-4) and adiponectin (APN) in adipose tissue were determined. Compared with the model group, the FBG and INS levels were lower, the ISI was higher, and the number of islet β-cells was significantly increased in all the PEP groups. In the medium- and high-dose PEP groups, MDA levels decreased, and the enzymatic activities of SOD and GSH-Px increased. The mRNA expression of InsR and GCK increased in all the PEP groups; APN mRNA expression increased in the high-dose PEP group, and GLUT-4 mRNA expression increased in adipose tissue. These findings suggest that PEP is a potential therapeutic agent that can be utilized to treat DM

Pressured HIV testing "in the name of love": a mixed methods analysis of pressured HIV testing among men who have sex with men in China.

INTRODUCTION: HIV testing has rapidly expanded into diverse, decentralized settings. While increasing accessibility to HIV testing is beneficial, it may lead to unintended consequences such as being pressured to test. We examined the frequency, correlates and contexts of pressured HIV testing among Chinese men who have sex with men (MSM) using mixed methods. METHODS: We conducted an online survey of MSM (N = 1044) in May 2017. Pressured HIV testing was defined as being forced to test for HIV. We conducted logistic regression analysis to determine the associations between pressured HIV testing and socio-demographic and sexual behavioural factors. Follow-up interviews (n = 17) were conducted with men who reported pressured testing and we analysed qualitative data using a thematic analysis approach. RESULTS: Ninety-six men (9.2%) reported experiencing pressure to test for HIV. Regular male sex partners were the most common source of pressure (61%, 59/96), and the most common form of pressure was a threat to end a relationship with the one who was being pressured (39%, 37/96). We found a higher risk of pressured testing in men who had only used HIV self-testing compared to men who had never self-tested (AOR 2.39 (95%CI: 1.38 to 4.14)). However, this relationship was only significant among men with low education (AOR 5.88 (95% CI: 1.92 to 17.99)) and not among men with high education (AOR 1.62 (95% CI: 0.85 to 3.10)). After pressured testing, about half of men subsequently tested for HIV (55%, 53/96) without pressure - none reported being diagnosed with HIV. Consistent with this finding, qualitative data suggest that perceptions of pressure existed on a continuum and depended on the relationship status of the one who pressured them. Although being pressured to test was accompanied by negative feelings, men who were pressured into testing often changed their attitude towards HIV testing, testing behaviours, sexual behaviours and relationship with the one who pressured them to test. CONCLUSION: Pressured HIV testing was reported among Chinese MSM, especially from men with low education levels and men who received HIV self-testing. However, in some circumstances, pressure to test helped MSM in several ways, challenging our understanding of the role of agency in the setting of HIV testing

Advances of MnO2 nanomaterials as novel agonists for the development of cGAS-STING-mediated therapeutics

As an essential micronutrient, manganese plays an important role in the physiological process and immune process. In recent decades, cGAS-STING pathway, which can congenitally recognize exogenous and endogenous DNA for activation, has been widely reported to play critical roles in the innate immunity against some important diseases, such as infections and tumor. Manganese ion (Mn2+) has been recently proved to specifically bind with cGAS and activate cGAS-STING pathway as a potential cGAS agonist, however, is significantly restricted by the low stability of Mn2+ for further medical application. As one of the most stable forms of manganese, manganese dioxide (MnO2) nanomaterials have been reported to show multiple promising functions, such as drug delivery, anti-tumor and anti-infection activities. More importantly, MnO2 nanomaterials are also found to be a potential candidate as cGAS agonist by transforming into Mn2+, which indicates their potential for cGAS-STING regulations in different diseased conditions. In this review, we introduced the methods for the preparation of MnO2 nanomaterials as well as their biological activities. Moreover, we emphatically introduced the cGAS-STING pathway and discussed the detailed mechanisms of MnO2 nanomaterials for cGAS activation by converting into Mn2+. And we also discussed the application of MnO2 nanomaterials for disease treatment by regulating cGAS-STING pathway, which might benefit the future development of novel cGAS-STING targeted treatments based on MnO2 nanoplatforms

Histone demethylase KDM5D drives sex-specific differences in colorectal cancer

View full abstracthttps://openworks.mdanderson.org/leading-edge/1011/thumbnail.jp

CodeFuse-13B: A Pretrained Multi-lingual Code Large Language Model

Code Large Language Models (Code LLMs) have gained significant attention in the industry due to their wide applications in the full lifecycle of software engineering. However, the effectiveness of existing models in understanding non-English inputs for multi-lingual code-related tasks is still far from well studied. This paper introduces CodeFuse-13B, an open-sourced pre-trained code LLM. It is specifically designed for code-related tasks with both English and Chinese prompts and supports over 40 programming languages. CodeFuse achieves its effectiveness by utilizing a high quality pre-training dataset that is carefully filtered by program analyzers and optimized during the training process. Extensive experiments are conducted using real-world usage scenarios, the industry-standard benchmark HumanEval-x, and the specially designed CodeFuseEval for Chinese prompts. To assess the effectiveness of CodeFuse, we actively collected valuable human feedback from the AntGroup's software development process where CodeFuse has been successfully deployed. The results demonstrate that CodeFuse-13B achieves a HumanEval pass@1 score of 37.10%, positioning it as one of the top multi-lingual code LLMs with similar parameter sizes. In practical scenarios, such as code generation, code translation, code comments, and testcase generation, CodeFuse performs better than other models when confronted with Chinese prompts.Comment: 10 pages with 2 pages for reference