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Cardiac macrophage contributes to the development of cardiac fibrosis, but factors that regulate cardiac macrophages transition and activation during this process remains elusive. Here we show, by single-cell transcriptomics, lineage tracing and parabiosis, that cardiac macrophages from circulating monocytes preferentially commit to macrophage-to-myofibroblast transition (MMT) under angiotensin II (Ang II)-induced hypertension, with accompanying increased expression of the RNA N6-methyladenosine demethylases, ALKBH5. Meanwhile, macrophage-specific knockout of ALKBH5 inhibits Ang II-induced MMT, and subsequently ameliorates cardiac fibrosis and dysfunction. Mechanistically, RNA immunoprecipitation sequencing identifies interlukin-11 (IL-11) mRNA as a target for ALKBH5-mediated m6A demethylation, leading to increased IL-11 mRNA stability and protein levels. By contrast, overexpression of IL11 in circulating macrophages reverses the phenotype in ALKBH5-deficient mice and macrophage. Lastly, targeted delivery of ALKBH5 or IL-11 receptor α (IL11RA1) siRNA to monocytes/macrophages attenuates MMT and cardiac fibrosis under hypertensive stress. Our results thus suggest that the ALKBH5/IL-11/IL11RA1/MMT axis alters cardiac macrophage and contributes to hypertensive cardiac fibrosis and dysfunction in mice, and thereby identify potential targets for cardiac fibrosis therapy in patients. Cardiac macrophage contributes to the onset of cardiac fibrosis, but the underneath mechanisms remain unclear. Here the authors show that mouse cardiac macrophages from circulating monocytes may trans-differentiate into myofibroblast under hypertensive conditions for fibrosis development, with an AKLBH5/IL11 molecular axis modulating this macrophage-to-myofibroblast transition.

Ischemic stroke (IS) is a common neurological disorder associated with high disability rates and mortality rates. At present, recombinant tissue plasminogen activator (r-tPA) is the only US(FDA)-approved drug for IS. However, due to the narrow therapeutic window and risk of intracerebral hemorrhage, r-tPA is currently used in less than 5% of stroke patients. Natural compounds have been widely used in the treatment of IS in China and have a wide range of therapeutic effects on IS by regulating multiple targets and signaling pathways. The keywords “ischemia stroke, traditional Chinese Medicine, Chinese herbal medicine, natural compounds” were used to search the relevant literature in PubMed and other databases over the past five years. The results showed that JAK/STAT, NF-κB, MAPK, Notch, Nrf2, and PI3K/Akt are the key pathways, and SIRT1, MMP9, TLR4, HIF-α are the key targets for the natural compounds from traditional Chinese medicine in treating IS. This study aims to update and summarize the signaling pathways and targets of natural compounds in the treatment of IS, and provide a base of information for the future development of effective treatments for IS.

Audio-visual learning, aimed at exploiting the relationship between audio and visual modalities, has drawn considerable attention since deep learning started to be used successfully. Researchers tend to leverage these two modalities to improve the performance of previously considered single-modality tasks or address new challenging problems. In this paper, we provide a comprehensive survey of recent audio-visual learning development. We divide the current audio-visual learning tasks into four different subfields: audio-visual separation and localization, audio-visual correspondence learning, audio-visual generation, and audio-visual representation learning. State-of-the-art methods, as well as the remaining challenges of each subfield, are further discussed. Finally, we summarize the commonly used datasets and challenges.

To provide a complete toxicity profile, toxicity spectrum, and a safety ranking of immune checkpoint inhibitor (ICI) drugs for treatment of cancer. Systematic review and network meta-analysis. Electronic databases (PubMed, Embase, Cochrane Library, and Web of Science) were systematically searched to include relevant studies published in English between January 2007 and February 2018. Only head-to-head phase II and III randomised controlled trials comparing any two or three of the following treatments or different doses of the same ICI drug were included: nivolumab, pembrolizumab, ipilimumab, tremelimumab, atezolizumab, conventional therapy (chemotherapy, targeted therapy, and their combinations), two ICI drugs, or one ICI drug with conventional therapy. Eligible studies must have reported site, organ, or system level data on treatment related adverse events. High quality, single arm trials and placebo controlled trials on ICI drugs were selected to establish a validation group. 36 head-to-head phase II and III randomised trials (n=15 370) were included. The general safety of ICI drugs ranked from high to low for all adverse events was as follows: atezolizumab (probability 76%, pooled incidence 66.4%), nivolumab (56%, 71.8%), pembrolizumab (55%, 75.1%), ipilimumab (55%, 86.8%), and tremelimumab (54%, not applicable). The general safety of ICI drugs ranked from high to low for severe or life threatening adverse events was as follows: atezolizumab (49%, 15.1%), nivolumab (46%, 14.1%), pembrolizumab (72%, 19.8%), ipilimumab (51%, 28.6%), and tremelimumab (28%, not applicable). Compared with conventional therapy, treatment-related adverse events for ICI drugs occurred mainly in the skin, endocrine, hepatic, and pulmonary systems. Taking one ICI drug was generally safer than taking two ICI drugs or one ICI drug with conventional therapy. Among the five ICI drugs, atezolizumab had the highest risk of hypothyroidism, nausea, and vomiting. The predominant treatment-related adverse events for pembrolizumab were arthralgia, pneumonitis, and hepatic toxicities. The main treatment-related adverse events for ipilimumab were skin, gastrointestinal, and renal toxicities. Nivolumab had a narrow and mild toxicity spectrum, mainly causing endocrine toxicities. Integrated evidence from the pooled incidences, subgroup, and sensitivity analyses implied that nivolumab is the best option in terms of safety, especially for the treatment of lung cancer. Compared with other ICI drugs used to treat cancer, atezolizumab had the best safety profile in general, and nivolumab had the best safety profile in lung cancer when taking an integrated approach. The safety ranking of treatments based on ICI drugs is modulated by specific treatment-related adverse events. PROSPERO CRD42017082553.

Background The prognostic values of staging parameters require continual re‐assessment amid changes in diagnostic and therapeutic methods. This study aimed to identify the prognostic factors and failure patterns of non‐metastatic nasopharyngeal carcinoma (NPC) in the intensity‐modulated radiotherapy (IMRT) era. Methods We reviewed the data from 749 patients with newly diagnosed, biopsy‐proven, non‐metastatic NPC in our cancer center (South China, an NPC endemic area) between January 2003 and December 2007. All patients underwent magnetic resonance imaging (MRI) before receiving IMRT. The actuarial survival rates were estimated using the Kaplan–Meier method, and survival curves were compared using the log‐rank test. Multivariate analyses with the Cox proportional hazards model were used to test for the independent prognostic factors by backward eliminating insignificant explanatory variables. Results The 5‐year occurrence rates of local failure, regional failure, locoregional failure, and distant failure were 5.4, 3.0, 7.4, and 17.4%, respectively. The 5‐year survival rates were as follows: local relapse‐free survival, 94.6%; nodal relapse‐free survival, 97.0%; distant metastasis‐free survival, 82.6%; disease‐free survival, 75.1%; and overall survival, 82.0%. Multivariate Cox regression analysis revealed that orbit involvement was the only significant prognostic factor for local failure (P = 0.011). Parapharyngeal tumor extension, retropharyngeal lymph node involvement, and the laterality, longest diameter, and Ho's location of the cervical lymph nodes were significant prognostic factors for both distant failure and disease failure (all P < 0.05). Intracranial extension had significant prognostic value for distant failure (P = 0.040). Conclusions The key failure pattern for NPC was distant metastasis in the IMRT era. With changes in diagnostic and therapeutic technologies as well as treatment modalities, the significant prognostic parameters for local control have also been altered substantially.

Macrophages are a subset of mononuclear phagocytes of the innate immune system with high plasticity and heterogeneity. At the maternal-fetal interface, macrophages are present in all stages of pregnancy and involved in a variety of activities, including regulation of immune cell activities, decidualization, placental cell invasion, angiogenesis, parturition, and postpartum uterine involution. The activation state and function of uterine-placental macrophages are largely dependent on the local tissue microenvironment. However, disruption of the uterine microenvironment can have profound effects on macrophage activity and subsequently impact pregnancy outcome. Thus, appropriately and timely regulated macrophage polarization has been considered a key determinant of successful pregnancy. Targeting macrophage polarization might be an efficient strategy for maintaining maternal-fetal immune homeostasis and a normal pregnancy. Here, we will review the latest findings regarding the modulators regulating macrophage polarization in healthy pregnancies and pregnancy complications, which might provide a basis for macrophage-centered therapeutic strategies.

Adverse Drug Reactions (ADRs) stand out as a pressing challenge in public health and a critical aspect of drug discovery. The dilemma arises from the inherent impossibility of conducting a comprehensive evaluation of a drug before its market release, constrained by the limitations in scale and duration of clinical trials. Therefore, the post-marketing detection of ADRs in a timely and accurate manner becomes imperative. Adding to the complexity, a multitude of tweets harbor concealed information about adverse drug reactions, creating difficulties due to their concise, sporadic, and noisy content. To solve the problem, we regard ADR detection as a question-answer problem and introduces an innovative neural network framework with multiple GRU layers designed for extracting ADR-related information from tweets. The Von Mises-Fisher distribution is applied to derive keyword vectors through tweet sampling. An attention mechanism is employed to enhance the interaction between these keyword vectors and the word sequences within tweets. The credibility of word sequences is systematically evaluated based on the reliability of answer factors. To address concerns related to background information and training speed, we propose a quality assurance mechanism utilizing a GRU network due to its straightforward structure and efficient training capabilities. As a result of the training process, word sequences are mapped to a low-latitude vector space, generating corresponding answers. Experimental results obtained from two Twitter ADR datasets affirm that our Question-Answer Mechanism, leveraging multi-GRU architecture, significantly improves the accuracy of ADR detection in tweets. Our method achieved F1-scores of 81.3% and 73.3% on the two datasets, respectively, while consistently maintaining a higher recall.

Background Ferroptosis has been implicated in the pathological process of type 2 diabetic osteoporosis (T2DOP), although the specific underlying mechanisms remain largely unknown. This study aimed to clarify the role and possible mechanism of acid sphingomyelinase (ASM)-mediated osteoblast ferroptosis in T2DOP. Methods We treated hFob1.19 cells with normal glucose (NG) and different concentrations of high glucose (HG, 26.25 mM, 35 mM, or 43.75 mM) for 48 h. We then measured cell viability and osteogenic function, quantified ferroptosis and autophagy levels, and measured the levels of ASM and ceramide in the cells. To further investigate the specific mechanism, we examined these indicators by knocking down ASM expression, hydroxychloroquine (HCQ) treatment, or N -acetylcysteine (NAC) treatment. Moreover, a T2DOP rat model was induced and microcomputed tomography was used to observe the bone microstructure. We also evaluated the serum levels of iron metabolism-associated factors, ceramide and lipid peroxidation (LPO) and measured the expression of ASM, LC3 and GPX4 in bone tissues. Results HG inhibited the viability and osteogenic function of osteoblasts by inducing ferroptosis in a concentration-dependent manner. Furthermore, the expression of ASM and ceramide and autophagy levels were increased by HG treatment, and these factors were required for the HG-induced reactive oxygen species (ROS) generation and LPO. Similarly, inhibiting intracellular ROS also reduced HG-induced ASM activation and autophagy. ASM-mediated activation of autophagy was crucial for HG-induced degradation of GPX4, and inhibiting ASM improved osteogenic function by decreasing HG-induced autophagy, GPX4 degradation, LPO and subsequent ferroptosis. We also found that inhibiting ASM could alleviated ferroptosis and autophagy and improved osteogenic function in a T2DOP rat model. Conclusion ASM-mediated autophagy activation induces osteoblast ferroptosis under HG conditions through the degradation of GPX4, providing a novel mechanistic insight into the treatment and prevention of T2DOP.

Background Identifying molecular subtypes of ovarian cancer is important. Compared to identify subtypes using single omics data, the multi-omics data analysis can utilize more information. Autoencoder has been widely used to construct lower dimensional representation for multi-omics feature integration. However, learning in the deep architectures in Autoencoder is difficult for achieving satisfied generalization performance. To solve this problem, we proposed a novel deep learning-based framework to robustly identify ovarian cancer subtypes by using denoising Autoencoder. Results In proposed method, the composite features of multi-omics data in the Cancer Genome Atlas were produced by denoising Autoencoder, and then the generated low-dimensional features were input into k -means for clustering. At last based on the clustering results, we built the light-weighted classification model with L1-penalized logistic regression method. Furthermore, we applied the differential expression analysis and WGCNA analysis to select target genes related to molecular subtypes. We identified 34 biomarkers and 19 KEGG pathways associated with ovarian cancer. Conclusions The independent test results in three GEO datasets proved the robustness of our model. The literature reviewing show 19 (56%) biomarkers and 8(42.1%) KEGG pathways identified based on the classification subtypes have been proved to be associated with ovarian cancer. The outcomes indicate that our proposed method is feasible and can provide reliable results.

Background The conversion from estrogen-dependent to estrogen-independent state of ER+ breast cancer cells is the key step to promote resistance to endocrine therapies. Although the crucial role of MAPK/ERK signaling pathway in estrogen-independent breast cancer cell growth is well established, the underlying mechanism is not fully understood. Methods In this study, we profiled lncRNA expression against a focused group of lncRNAs selected from lncRNA database. CRISPR/Cas9 was employed to knockout (KO) linc-RoR in MCF-7 cells, while rescue experiments were carried out to re-express linc-RoR in KO cells. Colony formation and MTT assays were used to examine the role of linc-RoR in estrogen-independent growth and tamoxifen resistance. Western blot and qRT-PCR were used to determine the change of protein and lncRNA levels, respectively. The expression of DUSP7 in clinical specimens was downloaded from Oncomine ( www.oncomine.org ) and the dataset from Kaplan-Meier Plotter ( http://kmplot.com ) was used to analyze the clinical outcomes in relation to DUSP7. Results We identified that linc-RoR functions as an onco-lncRNA to promote estrogen-independent growth of ER+ breast cancer. Under estrogen deprivation, linc-RoR causes the upregulation of phosphorylated MAPK/ERK pathway which in turn activates ER signaling. Knockout of linc-RoR abrogates estrogen deprivation-induced ERK activation as well as ER phosphorylation, whereas re-expression of linc-RoR restores all above phenotypes. Moreover, we show that the ERK-specific phosphatase Dual Specificity Phosphatase 7 (DUSP7), also known as MKP-X, is involved in linc-RoR KO-induced repression of MAPK/ERK signaling. Interestingly, linc-RoR KO increases the protein stability of DUSP7, resulting in repression of ERK phosphorylation. Clinical data analysis reveal that DUSP7 expression is lower in ER+ breast cancer samples than that in ER- breast cancer. Moreover, downregulation of DUSP7 expression is associated with poor patient survival. Conclusion Taken together, these results suggest that linc-RoR promotes estrogen-independent growth and activation of MAPK/ERK pathway of breast cancer cells by regulating the ERK-specific phosphatase DUSP7. Thus, this study might help not only in establishing a role for linc-RoR in estrogen-independent and tamoxifen resistance of ER+ breast cancer, but also suggesting a link between linc-RoR and MAPK/ERK pathway.