Synchronous Detection of BPV and BVDV with Duplex Taqman qPCR Method

Background: Bovine parvovirus (BPV) and bovine viral diarrhea virus (BVDV) are commonly etiologies causing diarrhea in dairy herds. BPV is a member of bocaparvovirus genus with a non-enveloped capsid. BVDV, belonging to Pestivirus genus in Flaviviridae, possesses a single-stranded RNA, and is classified into BVDV-1 and BVDV-2 genotypes according to the 5’UTR sequence. 21 genetic groups of BVDV-1 and four groups of BVDV-2 have been found. Diagnosis of viral diarrhea is often relied on virus detection by isolation or detection of serum antibody. The main objective of the present study was to establish a duplex real time PCR (qPCR) based on Taqman probe to detect synchronously BPV and BVDV. Materials, Methods & Results: TaqMan probe and primers were designed and synthesized from the sequences of conserved 5′ - untranslated regions (5′ UTR) of Haden strain of BPV and NADL strain of BVDV. The cDNAs were transcribed in vitro to make standard curves before optimizing the assay. DNA/PCR products were ligated into pMD18-T vector, and then used to transfer BL-21 competent cells to acquire the recombinant plasmids of pMD18-T-BPV and pMD18-T-BVDV. Optimum reaction conditions were comparatively selected. The sensitivity, specificity and reproducibility of TaqMan probe qRT-PCR were evaluated respectively. The results showed the concentrations of pMD18-T-BPV or pMD18-T-BVDV were 2.0 × 1010 DNA copies/μL, respectively. A duplex Taqman qPCR method was developed by optimizing the amplification conditions to simultaneously detect BPV and BVDV. The assay targets at highly conserved VP2 gene of BPV and 5′ UTR gene of BVDV. This qPCR assay was assessed for specificity and sensitivity using DNA of BPV and cDNA of BVDV. For clinical validation, 308 samples were tested from clinically diarrhea calves. The results showed that optimum annealing temperature was achieved in 43.2 ℃ fro duplex BPV and BPIV. Dynamic curves and standard curves were created following amplification of recombinant plasmids using the optimized duplex Taqman BPV and BVDV, with an amplification efficiency of 95.69%. Duplex Taqman qPCR could only detect DNA of BPV and cDNA of BVDV with a strong specificity. The detection limitation was as low as 2.0 × 102 copies/μL of pMD18-T-BPV plasmid and 2.0 × 101 copies/μL for pMD18-T-BVDV plasmid, respectively. Sensitivity of detection was 100-fold higher than conventional PCR. Duplex Taqman qPCR had excellent repeatability or stability with less than 1.2% of intra-assay and inter-assay. 35 and 47 positive feces samples were identified using duplex Taqman qPCR in comparison to 30 and 42 positives for universal PCR, respectively. Discussion: The bovine viral diarrhea virus (BVDV) is a key pathogenic factor in bovine diarrhea. Currently, few effective measures are available for the treatment or prevention for BVDV and BPV infections in animals. The technique was proven to be repeatable and linear over a range of at least 5 magnitudes, from 101 to 105 RNA/DNA copies, thus ensuring an accurate measurement of BPV DNA and BVDV RNA loads in clinical samples. In conclusion, a duplex Taqman qPCR was established for detecting simultaneously BPV and BVDV. Taqman qPCR method was rapid and specific assay. This assay was 100-fold sensitive than conventional PCR. It will be propitious to rapidly and differentially diagnose pathogens of viral diarrhea of dairy farms. Taqman qPCR method was rapid and specific assay and had a sensitivity of 2.0 copies/μL

Activating Transcription Factor 3 Deficiency Promotes Cardiac Hypertrophy, Dysfunction, and Fibrosis Induced by Pressure Overload

Activating transcription factor 3 (ATF3), which is encoded by an adaptive-response gene induced by various stimuli, plays an important role in the cardiovascular system. However, the effect of ATF3 on cardiac hypertrophy induced by a pathological stimulus has not been determined. Here, we investigated the effects of ATF3 deficiency on cardiac hypertrophy using in vitro and in vivo models. Aortic banding (AB) was performed to induce cardiac hypertrophy in mice. Cardiac hypertrophy was estimated by echocardiographic and hemodynamic measurements and by pathological and molecular analysis. ATF3 deficiency promoted cardiac hypertrophy, dysfunction and fibrosis after 4 weeks of AB compared to the wild type (WT) mice. Furthermore, enhanced activation of the MEK-ERK1/2 and JNK pathways was found in ATF3-knockout (KO) mice compared to WT mice. In vitro studies performed in cultured neonatal mouse cardiomyocytes confirmed that ATF3 deficiency promotes cardiomyocyte hypertrophy induced by angiotensin II, which was associated with the amplification of MEK-ERK1/2 and JNK signaling. Our results suggested that ATF3 plays a crucial role in the development of cardiac hypertrophy via negative regulation of the MEK-ERK1/2 and JNK pathways

Size-dependent in vivo toxicity of PEG-coated gold nanoparticles

Xiao-Dong Zhang, Di Wu, Xiu Shen, Pei-Xun Liu, Na Yang, Bin Zhao, Hao Zhang, Yuan-Ming Sun, Liang-An Zhang, Fei-Yue FanInstitute of Radiation Medicine, Chinese Academy of Medical Sciences and Peking Union Medical College, Tianjin Key Laboratory of Molecular Nuclear Medicine, Tianjin, People’s Republic of ChinaBackground: Gold nanoparticle toxicity research is currently leading towards the in vivo experiment. Most toxicology data show that the surface chemistry and physical dimensions of gold nanoparticles play an important role in toxicity. Here, we present the in vivo toxicity of 5, 10, 30, and 60 nm PEG-coated gold nanoparticles in mice.Methods: Animal survival, weight, hematology, morphology, organ index, and biochemistry were characterized at a concentration of 4000 µg/kg over 28 days.Results: The PEG-coated gold particles did not cause an obvious decrease in body weight or appreciable toxicity even after their breakdown in vivo. Biodistribution results show that 5 nm and 10 nm particles accumulated in the liver and that 30 nm particles accumulated in the spleen, while the 60 nm particles did not accumulate to an appreciable extent in either organ. Transmission electron microscopic observations showed that the 5, 10, 30, and 60 nm particles located in the blood and bone marrow cells, and that the 5 and 60 nm particles aggregated preferentially in the blood cells. The increase in spleen index and thymus index shows that the immune system can be affected by these small nanoparticles. The 10 nm gold particles induced an increase in white blood cells, while the 5 nm and 30 nm particles induced a decrease in white blood cells and red blood cells. The biochemistry results show that the 10 nm and 60 nm PEG-coated gold nanoparticles caused a significant increase in alanine transaminase and aspartate transaminase levels, indicating slight damage to the liver.Conclusion: The toxicity of PEG-coated gold particles is complex, and it cannot be concluded that the smaller particles have greater toxicity. The toxicity of the 10 nm and 60 nm particles was obviously higher than that of the 5 nm and 30 nm particles. The metabolism of these particles and protection of the liver will be more important issues for medical applications of gold-based nanomaterials in future.Keywords: gold nanoparticles, in vivo, toxicity, siz

Cellular repressor of E1A-stimulated genes attenuates cardiac hypertrophy and fibrosis

Cellular repressor of E1A-stimulated genes (CREG) is a secreted glycoprotein of 220 amino acids. It has been proposed that CREG acts as a ligand that enhances differentiation and/or reduces cell proliferation. CREG has been shown previously to attenuate cardiac hypertrophy in vitro. However, such a role has not been determined in vivo. In the present study, we tested the hypothesis that overexpression of CREG in the murine heart would protect against cardiac hypertrophy and fibrosis in vivo. The effects of constitutive human CREG expression on cardiac hypertrophy were investigated using both in vitro and in vivo models. Cardiac hypertrophy was produced by aortic banding and infusion of angiotensin II in CREG transgenic mice and control animals. The extent of cardiac hypertrophy was quantitated by two-dimensional and M-mode echocardiography as well as by molecular and pathological analyses of heart samples. Constitutive over-expression of human CREG in the murine heart attenuated the hypertrophic response, markedly reduced inflammation. Cardiac function was also preserved in hearts with increased CREG levels in response to hypertrophic stimuli. These beneficial effects were associated with attenuation of the mitogen-activated protein kinase (MAPK)-extracellular signal-regulated kinase 1 (MEK-ERK1)/2-dependent signalling cascade. In addition, CREG expression blocked fibrosis and collagen synthesis through blocking MEK-ERK1/2-dependent Smad 2/3 activation in vitro and in vivo. Therefore, the expression of CREG improves cardiac functions and inhibits cardiac hypertrophy, inflammation and fibrosis through blocking MEK-ERK1/2-dependent signalling

Uni-COAL: A Unified Framework for Cross-Modality Synthesis and Super-Resolution of MR Images

Cross-modality synthesis (CMS), super-resolution (SR), and their combination (CMSR) have been extensively studied for magnetic resonance imaging (MRI). Their primary goals are to enhance the imaging quality by synthesizing the desired modality and reducing the slice thickness. Despite the promising synthetic results, these techniques are often tailored to specific tasks, thereby limiting their adaptability to complex clinical scenarios. Therefore, it is crucial to build a unified network that can handle various image synthesis tasks with arbitrary requirements of modality and resolution settings, so that the resources for training and deploying the models can be greatly reduced. However, none of the previous works is capable of performing CMS, SR, and CMSR using a unified network. Moreover, these MRI reconstruction methods often treat alias frequencies improperly, resulting in suboptimal detail restoration. In this paper, we propose a Unified Co-Modulated Alias-free framework (Uni-COAL) to accomplish the aforementioned tasks with a single network. The co-modulation design of the image-conditioned and stochastic attribute representations ensures the consistency between CMS and SR, while simultaneously accommodating arbitrary combinations of input/output modalities and thickness. The generator of Uni-COAL is also designed to be alias-free based on the Shannon-Nyquist signal processing framework, ensuring effective suppression of alias frequencies. Additionally, we leverage the semantic prior of Segment Anything Model (SAM) to guide Uni-COAL, ensuring a more authentic preservation of anatomical structures during synthesis. Experiments on three datasets demonstrate that Uni-COAL outperforms the alternatives in CMS, SR, and CMSR tasks for MR images, which highlights its generalizability to wide-range applications

Integrative analysis of the role of BOLA2B in human pan-cancer

Objective:BOLA2B is a recently discovered protein-coding gene. Here, pan-cancer analysis was conducted to determine the expression patterns of BOLA2B and its impact on immune response, gene mutation, and possible molecular biological mechanisms in different tumors, together with investigating its potential usefulness for cancer prognosis.Methods: Data on BOLA2B expression and mutations were downloaded from TCGA and GTEx databases. Clinical survival data from TCGA were used to analyze the prognostic value of BOLA2B. TIMER and ESTIMATE algorithms were used to assess correlations between BOLA2B and tumor-infiltrating immune cells, immune cytokines, and immune scores.Results: BOLA2B was found to be highly expressed at both mRNA and protein levels in multiple tumors, where it was associated with worse overall survival (OS), disease-specific survival (DSS), and progression-free interval (PFI) in all cancers apart from ovarian cancer. BOLA2B was also found to be positively correlated with copy number variation (CNV), and mutations in TP53, TTN, and MUC16 were found to influence BOLA2B expression. Post-transcriptional modifications, including m5C, m1A, and m6A, were observed to regulate BOLA2B expression in all cancers. Functional analysis showed that BOLA2B was enriched in pathways associated with iron–sulfur cluster formation, mTOR-mediated autophagy, and cell cycle inhibition. Decreased BOLA2B expression induced the proliferation of breast cancer cells and G2/M cell cycle arrest.Conclusion:BOLA2B was found to be highly expressed in malignant tumors and could be used as a biomarker of poor prognosis in multiple cancers. Further investigation into BOLA2B’s role and molecular functions in cancer would provide new insights for cancer diagnosis and treatment

Physics-informed Deep Diffusion MRI Reconstruction with Synthetic Data: Break Training Data Bottleneck in Artificial Intelligence

Diffusion magnetic resonance imaging (MRI) is the only imaging modality for non-invasive movement detection of in vivo water molecules, with significant clinical and research applications. Diffusion MRI (DWI) acquired by multi-shot techniques can achieve higher resolution, better signal-to-noise ratio, and lower geometric distortion than single-shot, but suffers from inter-shot motion-induced artifacts. These artifacts cannot be removed prospectively, leading to the absence of artifact-free training labels. Thus, the potential of deep learning in multi-shot DWI reconstruction remains largely untapped. To break the training data bottleneck, here, we propose a Physics-Informed Deep DWI reconstruction method (PIDD) to synthesize high-quality paired training data by leveraging the physical diffusion model (magnitude synthesis) and inter-shot motion-induced phase model (motion phase synthesis). The network is trained only once with 100,000 synthetic samples, achieving encouraging results on multiple realistic in vivo data reconstructions. Advantages over conventional methods include: (a) Better motion artifact suppression and reconstruction stability; (b) Outstanding generalization to multi-scenario reconstructions, including multi-resolution, multi-b-value, multi-undersampling, multi-vendor, and multi-center; (c) Excellent clinical adaptability to patients with verifications by seven experienced doctors (p<0.001). In conclusion, PIDD presents a novel deep learning framework by exploiting the power of MRI physics, providing a cost-effective and explainable way to break the data bottleneck in deep learning medical imaging.Comment: 23 pages, 16 figure