Cis-regulatory functions of overlapping HIF-1alpha/E-box/AP-1-like sequences of CD164

<p>Abstract</p> <p>Background</p> <p>CD164 (also known as MGC-24v or endolyn) is a sialomucin which has been suggested to participate in regulating the proliferation, cell adhesion and differentiation of hematopoietic stem and progenitor cells. CD164 is also involved in the development of cancer. The functions of cis-regulatory elements of CD164 remain relatively unknown.</p> <p>Methods</p> <p>In this study, we investigated the function of cis-regulatory elements within the promoter of CD164. We fused the 5'-flanking region of CD164 to a luciferase reporter vector. The minimal promoter region was confirmed by luciferase reporter assay. Using <it>in silico </it>analysis, we found the presence of one HIF-1alpha (HIF-1A) motif (5_-RCGTG-3_) overlapping E-box (CACGTG) and two AP-1-like binding sites (CGCTGTCCC, GTCTGTTG), one of which is also overlapped with HIF-1alpha sequence. Dual-luciferase assay was performed to examine the transcriptional activity of AP-1 and HIF-1alpha of CD164 promoter. Quantitative reverse transcriptase polymerase chain reaction (qRT-PCR) was performed to measure CD164 expression. Chromatin Immunoprecipitation was used to confirm the binding of HIF-1alpha and CD164.</p> <p>Results</p> <p>Co-transfection of c-jun, HIF-1alpha and minimal promoter region construct demonstrated that c-jun and HIF-1alpha bound the CD164 promoter and promoted CD164 expression. Hypoxia treatment also led to the up-regulation of CD164 expression. The mutation of overlapping sequences resulted in the reduced expression of CD164 induced by HIF-1alpha. Chromatin Immunoprecipitation demonstrated that the HIF-1alpha bound the minimal promoter region.</p> <p>Conclusions</p> <p>Determination of the optimal promoter region and transcription factors governing CD164 expression is useful in understanding CD164 functions. These results suggest that cis-regulatory elements of CD164 overlapping HIF-1alpha/E-box/AP-1-like sequences may play important regulatory roles.</p

UniDoc: A Universal Large Multimodal Model for Simultaneous Text Detection, Recognition, Spotting and Understanding

In the era of Large Language Models (LLMs), tremendous strides have been made in the field of multimodal understanding. However, existing advanced algorithms are limited to effectively utilizing the immense representation capabilities and rich world knowledge inherent to these large pre-trained models, and the beneficial connections among tasks within the context of text-rich scenarios have not been sufficiently explored. In this work, we introduce UniDoc, a novel multimodal model equipped with text detection and recognition capabilities, which are deficient in existing approaches. Moreover, UniDoc capitalizes on the beneficial interactions among tasks to enhance the performance of each individual task. To implement UniDoc, we perform unified multimodal instruct tuning on the contributed large-scale instruction following datasets. Quantitative and qualitative experimental results show that UniDoc sets state-of-the-art scores across multiple challenging benchmarks. To the best of our knowledge, this is the first large multimodal model capable of simultaneous text detection, recognition, spotting, and understanding

SPTS v2: Single-Point Scene Text Spotting

End-to-end scene text spotting has made significant progress due to its intrinsic synergy between text detection and recognition. Previous methods commonly regard manual annotations such as horizontal rectangles, rotated rectangles, quadrangles, and polygons as a prerequisite, which are much more expensive than using single-point. For the first time, we demonstrate that training scene text spotting models can be achieved with an extremely low-cost single-point annotation by the proposed framework, termed SPTS v2. SPTS v2 reserves the advantage of the auto-regressive Transformer with an Instance Assignment Decoder (IAD) through sequentially predicting the center points of all text instances inside the same predicting sequence, while with a Parallel Recognition Decoder (PRD) for text recognition in parallel. These two decoders share the same parameters and are interactively connected with a simple but effective information transmission process to pass the gradient and information. Comprehensive experiments on various existing benchmark datasets demonstrate the SPTS v2 can outperform previous state-of-the-art single-point text spotters with fewer parameters while achieving 19$\times$ faster inference speed. Most importantly, within the scope of our SPTS v2, extensive experiments further reveal an important phenomenon that single-point serves as the optimal setting for the scene text spotting compared to non-point, rectangular bounding box, and polygonal bounding box. Such an attempt provides a significant opportunity for scene text spotting applications beyond the realms of existing paradigms. Code will be available at https://github.com/bytedance/SPTSv2.Comment: arXiv admin note: text overlap with arXiv:2112.0791

Voxel-Mirrored Homotopic Connectivity of Resting-State Functional Magnetic Resonance Imaging in Blepharospasm

Objective: Several networks in human brain are involved in the development of blepharospasm. However, the underlying mechanisms for this disease are poorly understood. A voxel-mirrored homotopic connectivity (VMHC) method was used to quantify the changes in functional connectivity between two hemispheres of the brain in patients with blepharospasm.Methods: Twenty-four patients with blepharospasm and 24 healthy controls matched by age, sex, and education were recruited. The VMHC method was employed to analyze the fMRI data. The support vector machine (SVM) method was utilized to examine whether these abnormalities could be applied to distinguish the patients from the controls.Results: Compared with healthy controls, patients with blepharospasm showed significantly high VMHC in the inferior temporal gyrus, interior frontal gyrus, posterior cingulate cortex, and postcentral gyrus. No significant correlation was found between abnormal VMHC values and clinical variables. SVM analysis showed a combination of increased VMHC values in two brain areas with high sensitivities and specificities (83.33 and 91.67% in the combined inferior frontal gyrus and posterior cingulate cortex; and 83.33 and 87.50% in the combined inferior temporal gyrus and postcentral gyrus).Conclusion: Enhanced homotopic coordination in the brain regions associated with sensory integration networks and default-mode network may be underlying the pathophysiology of blepharospasm. This phenomenon may serve as potential image markers to distinguish patients with blepharospasm from healthy controls

Progressive Muscle Relaxation Improves Anxiety and Depression of Pulmonary Arterial Hypertension Patients

We explored the effects of progressive muscle relaxation (PMR) on anxiety, depression, and quality of life (QOL) in patients with pulmonary arterial hypertension (PAH). One hundred and thirty Han Chinese patients with PAH were randomly assigned to a PMR group (n=65) and a control group (n=65). In a 12-week study duration, the PMR group received hospital-based group and in-home PMR practice, while the control group received hospital-based mild group stretching and balance exercises. The control group and the PMR group were comparable at baseline. After 12 weeks of intervention, the PMR group showed significant improvement in anxiety, depression, overall QOL, and the mental component summary score of QOL (P<0.05) but not the physical component summary score of QOL or the 6-minute walking distance. In contrast, the control group showed no significant improvement in any of the variables. Moreover, the PMR group showed significant improvement in all QOL mental health domains (P<0.05) but not the physical health domains. In contrast, the control group showed no significant improvement in any QOL domain. In conclusion, this study suggests that PMR practice is effective in improving anxiety, depression, and the mental health components of QOL in patients with PAH

Hypoxic BMSC-derived exosomal miRNAs promote metastasis of lung cancer cells via STAT3-induced EMT

Abstract Background Metastasis is the main cause of lung cancer mortality. Bone marrow-derived mesenchymal stem cells (BMSCs) are a component of the cancer microenvironment and contribute to cancer progression. Intratumoral hypoxia affects both cancer and stromal cells. Exosomes are recognized as mediators of intercellular communication. Here, we aim to further elucidate the communication between BMSC-derived exosomes and cancer cells in the hypoxic niche. Methods Exosomal miRNA profiling was performed using a microRNA array. Lung cancer cells and an in vivo mouse syngeneic tumor model were used to evaluate the effects of select exosomal microRNAs. Hypoxic BMSC-derived plasma exosomal miRNAs were assessed for their capacity to discriminate between cancer patients and non-cancerous controls and between cancer patients with or without metastasis. Results We demonstrate that exosomes derived from hypoxic BMSCs are taken by neighboring cancer cells and promote cancer cell invasion and EMT. Exosome-mediated transfer of select microRNAs, including miR-193a-3p, miR-210-3p and miR-5100, from BMSCs to epithelial cancer cells activates STAT3 signaling and increases the expression of mesenchymal related molecules. The diagnostic accuracy of individual microRNA showed that plasma exosomal miR-193a-3p can discriminate cancer patients from non-cancerous controls. A panel of these three plasma exosomal microRNAs showed a better diagnostic accuracy to discriminate lung cancer patients with or without metastasis than individual exosomal microRNA. Conclusions Exosome-mediated transfer of miR-193a-3p, miR-210-3p and miR-5100, could promote invasion of lung cancer cells by activating STAT3 signalling-induced EMT. These exosomal miRNAs may be promising noninvasive biomarkers for cancer progression