Show and Write: Entity-aware Article Generation with Image Information

Many vision-language applications contain long articles of text paired with images (e.g., news or Wikipedia articles). Prior work learning to encode and/or generate these articles has primarily focused on understanding the article itself and some related metadata like the title or date it was written. However, the images and their captions or alt-text often contain crucial information such as named entities that are difficult to be correctly recognized and predicted by language models. To address this shortcoming, this paper introduces an ENtity-aware article Generation method with Image iNformation, ENGIN, to incorporate an article's image information into language models. ENGIN represents articles that can be conditioned on metadata used by prior work and information such as captions and named entities extracted from images. Our key contribution is a novel Entity-aware mechanism to help our model better recognize and predict the entity names in articles. We perform experiments on three public datasets, GoodNews, VisualNews, and WikiText. Quantitative results show that our approach improves generated article perplexity by 4-5 points over the base models. Qualitative results demonstrate the text generated by ENGIN is more consistent with embedded article images. We also perform article quality annotation experiments on the generated articles to validate that our model produces higher-quality articles. Finally, we investigate the effect ENGIN has on methods that automatically detect machine-generated articles

Manufacture of IRDye800CW-coupled Fe3O4 nanoparticles and their applications in cell labeling and in vivo imaging

BackgroundIn recent years, near-infrared fluorescence (NIRF)-labeled iron nanoparticles have been synthesized and applied in a number of applications, including the labeling of human cells for monitoring the engraftment process, imaging tumors, sensoring the in vivo molecular environment surrounding nanoparticles and tracing their in vivo biodistribution. These studies demonstrate that NIRF-labeled iron nanoparticles provide an efficient probe for cell labeling. Furthermore, the in vivo imaging studies show excellent performance of the NIR fluorophores. However, there is a limited selection of NIRF-labeled iron nanoparticles with an optimal wavelength for imaging around 800 nm, where tissue autofluorescence is minimal. Therefore, it is necessary to develop additional alternative NIRF-labeled iron nanoparticles for application in this area.ResultsThis study manufactured 12-nm DMSA-coated Fe3O4 nanoparticles labeled with a near-infrared fluorophore, IRDye800CW (excitation/emission, 774/789 nm), to investigate their applicability in cell labeling and in vivo imaging. The mouse macrophage RAW264.7 was labeled with IRDye800CW-labeled Fe3O4 nanoparticles at concentrations of 20, 30, 40, 50, 60, 80 and 100 μg/ml for 24 h. The results revealed that the cells were efficiently labeled by the nanoparticles, without any significant effect on cell viability. The nanoparticles were injected into the mouse via the tail vein, at dosages of 2 or 5 mg/kg body weight, and the mouse was discontinuously imaged for 24 h. The results demonstrated that the nanoparticles gradually accumulated in liver and kidney regions following injection, reaching maximum concentrations at 6 h post-injection, following which they were gradually removed from these regions. After tracing the nanoparticles throughout the body it was revealed that they mainly distributed in three organs, the liver, spleen and kidney. Real-time live-body imaging effectively reported the dynamic process of the biodistribution and clearance of the nanoparticles in vivo.ConclusionIRDye800CW-labeled Fe3O4 nanoparticles provide an effective probe for cell-labeling and in vivo imaging

Irisin attenuates angiotensin II-induced atrial fibrillation and atrial fibrosis via LOXL2 and TGFβ1/Smad2/3 signaling pathways

Objective(s): Irisin was reported as a cardioprotective and anti-oxidative effector, while the effect on atrial fibrosis is unknown. The current research examined irisin’s function in atrial fibrillation (AF); atrial fibrosis brought on by Ang II can be suppressed, thus lessening the risk of developing AF. Materials and Methods: 246 individuals were enrolled in the present case-control study. Chinese AF patients (n=126), 83 of whom were paroxysmal AF (PAF), 43 patients with persistent AF (PeAF), and 120 healthy controls. Saline or Ang II (2.0 mg/kg/day) was subcutaneously injected into healthy male C57BL/6 mice for four weeks. Once daily for four weeks, intraperitoneal injections of exogenous irisin (500 g/kg/day) were administered. Results: In comparison to PAF patients and healthy controls (all P<0.05), PeAF patients had significantly higher rates of heart failure (HF), large left atrial size (LAD), hypertrophic protein B-type natriuretic peptide (BNP), malondialdehyde (MDA), tumor necrosis factor-α (TNF-α), interleukin-6 (IL-6), C-terminal telopeptide of type I collagen (CTX-I), and transforming growth factor beta-1 (TGF-β1), while superoxide dismutase (SOD) level was low. Expression of irisin was decreased in AF patients’ serum and Ang II-infused mice. Exogenous irisin dramatically reduced apoptosis, atrial fibrosis, atrial inflammation, and the susceptibility to AF caused by Ang II. In the atrial tissue, irisin inhibited Ang II-induced fibroblast transdifferentiation, LOXL2, TGF-β1, collagen production, and phosphorylation of Smad2/3. Conclusion: The study results speculated that irisin could be a potential AF target, and it inhibited atrial fibrosis and significantly impaired increased AF susceptibility through inactivation of LOXL2 and the TGF-β/Smad pathway

In vivo optical coherence tomography–based scoring of oral mucositis in human subjects: a pilot study

A preliminary study to assess noninvasive optical coherence tomography (OCT) for early detection and evaluation of chemotherapy-induced oral mucositis in five patients. In five patients receiving neoadjuvant chemotherapy for primary breast cancer, oral mucositis was assessed clinically, and imaged using noninvasive OCT. Imaging was scored using a novel imaging-based scoring system. Conventional clinical assessment using the Oral Mucositis Assessment Scale was used as the gold standard. Patients were evaluated on days 0, 2, 4, 7, and 11 after commencement of chemotherapy. OCT images were visually examined by one blinded investigator. The following events were identified using OCT: (1) change in epithelial thickness and subepithelial tissue integrity (beginning on day 2), (2) loss of surface keratinized layer continuity (beginning on day 4), (3) loss of epithelial integrity (beginning on day 4). Imaging data gave higher scores compared to clinical scores earlier in treatment, suggesting that the imaging-based diagnostic scoring was more sensitive to early mucositic change than the clinical scoring system. Once mucositis was established, imaging and clinical scores converged. Chemotherapy-induced oral changes were identified prior to their clinical manifestation using OCT, and the proposed scoring system for oral mucositis was validated for the semiquantification of mucositic change

Predicting Transcriptional Activity of Multiple Site p53 Mutants Based on Hybrid Properties

As an important tumor suppressor protein, reactivate mutated p53 was found in many kinds of human cancers and that restoring active p53 would lead to tumor regression. In this work, we developed a new computational method to predict the transcriptional activity for one-, two-, three- and four-site p53 mutants, respectively. With the approach from the general form of pseudo amino acid composition, we used eight types of features to represent the mutation and then selected the optimal prediction features based on the maximum relevance, minimum redundancy, and incremental feature selection methods. The Mathew's correlation coefficients (MCC) obtained by using nearest neighbor algorithm and jackknife cross validation for one-, two-, three- and four-site p53 mutants were 0.678, 0.314, 0.705, and 0.907, respectively. It was revealed by the further optimal feature set analysis that the 2D (two-dimensional) structure features composed the largest part of the optimal feature set and maybe played the most important roles in all four types of p53 mutant active status prediction. It was also demonstrated by the optimal feature sets, especially those at the top level, that the 3D structure features, conservation, physicochemical and biochemical properties of amino acid near the mutation site, also played quite important roles for p53 mutant active status prediction. Our study has provided a new and promising approach for finding functionally important sites and the relevant features for in-depth study of p53 protein and its action mechanism

Recent advances on extracellular vesicles in central nervous system diseases

Extracellular vesicles (EVs) are particles released by multiple cells, encapsulated by lipid bilayers and containing a variety of biological materials, including proteins, nucleic acids, lipids and metabolites. With the advancement of separation and characterization methods, EV subtypes and their complex and diverse functions have been recognized. In the central nervous system (CNS), EVs are involved in various physiological and pathological processes, such as regulation of neuronal firing, synaptic plasticity, formation and maintenance of myelin sheath, propagation of neuroinflammation, neuroprotection, and spread and removal of toxic protein aggregates. Activity-dependent alteration of constituents enables EVs to reflect the change of cell and tissue states, and the wide distribution of EVs in biological fluids endows them with potential as diagnostic and prognostic biomarkers for CNS diseases, including neurodegenerative disease, cerebrovascular disease, traumatic brain disease, and brain tumor. Favorable biocompatibility, ability of crossing the blood-brain barrier and protecting contents from degradation, give promising therapeutic effects of EVs, either collected from mesenchymal stem cells culture conditioned media, or designed as drug delivery vehicles loaded with specific agents. In this review, we summarized EVs\u27 basic biological properties, and mainly focused on their applications in CNS diseases

Nuclear transport signals control cellular localization and function of androgen receptor cofactor p44/WDR77.

The androgen receptor (AR) cofactor p44/WDR77, which regulates expression of a set of androgen target genes, is required for differentiation of prostate epithelium. Aberrant localization of p44/WDR77 in the cytoplasm is associated with prostate tumorigenesis. Here, we describe studies that used the mouse prostate and human prostate cancer cells as model systems to investigate signals that control subcellular localization of p44/WDR77. We observed distinct subcellular location of p44/WDR77 during prostate development. p44/WDR77 localizes in the cytoplasm at the early stage of prostate development, when prostate epithelial cells are rapidly proliferating, and in the nucleus in adult prostate, when epithelial cells are fully differentiated. Subcellular localization assays designed to span the entire open-reading frame of p44/WDR77 protein revealed the presence of two nuclear exclusion signal (NES) and three nuclear localization signal (NLS) sequences in the p44/WDR77 protein. Site-directed mutagenesis of critical residues within an NLS led to loss of nuclear localization and transcriptional activity of p44/WDR77, suggesting that nuclear localization of p44/WDR77 is essential for its function as a transcriptional cofactor for AR. Three identified NLS were not functional in AR-positive prostate cancer (LNCaP and 22RV1) cells, which led to localization of p44/WDR77 in cytoplasm. The function of NLS in LNCaP cells could be restored by factor(s) from Cos 7 or PC3 cells. Mass spectrometric (MALDI-TOF/TOF) analysis identified proteins associated with an NLS and an NES in prostate cancer cells. These results provide a basis for understanding subcellular transport of p44/WDR77 during prostate development and tumorigenesis