Protection of the Extracts of Lentinus edodes Mycelia against Carbon-Tetrachloride-Induced Hepatic Injury in Rats

Lentinus edodes is the medicinal macrofungus showing potential for therapeutic applications in infectious disorders including hepatitis. In an attempt to develop the agent for handling hepatic injury, we used the extracts of Lentinus edodes mycelia (LEM) to screen the effect on hepatic injury in rats induced by carbon tetrachloride (CCl4). Intraperitoneal administration of CCl4 not only increased plasma glutamic oxaloacetic transaminase (GOT) and glutamic pyruvic transaminase (GPT) but also decreased hepatic superoxide dismutase (SOD) and glutathione peroxidase (GPx) levels in rats. Similar to the positive control silymarin, oral administration (three times daily) of this product (LEM) for 8 weeks significantly reduced plasma GOT and GPT. Also, the activities of antioxidant enzymes of SOD and GPx were elevated by LEM. in liver from CCl4-treated rats, indicating that mycelium can increase antioxidant-like activity. Moreover, the hepatic mRNA and protein levels of SOD and GPx were both markedly raised by LEM. The obtained results suggest that oral administration of the extracts of Lentinus edodes mycelia (LEM) has the protective effect against CCl4-induced hepatic injury in rats, mainly due to an increase in antioxidant-like action

Circadian Alterations Increase with Progression in a Patient-Derived Cell Culture Model of Breast Cancer

Circadian rhythm disruption can elicit the development of various diseases, including breast cancer. While studies have used cell lines to study correlations between altered circadian rhythms and cancer, these models have different genetic backgrounds and do not mirror the changes that occur with disease development. Isogenic cell models can recapitulate changes across cancer progression. Hence, in this study, a patient-derived breast cancer model, the 21T series, was used to evaluate changes to circadian oscillations of core clock protein transcription as cells progress from normal to malignant states. Three cell lines were used: H16N2 (normal breast epithelium), 21PT (atypical ductal hyperplasia), and 21MT-1 (invasive metastatic carcinoma). The cancerous cells are both HER2+. We assessed the transcriptional profiles of two core clock proteins, BMAL1 and PER2, which represent a positive and negative component of the molecular oscillator. In the normal H16N2 cells, both genes possessed rhythmic mRNA oscillations with close to standard periods and phases. However, in the cancerous cells, consistent changes were observed: both genes had periods that deviated farther from normal and did not have an anti-phase relationship. In the future, mechanistic studies should be undertaken to determine the oncogenic changes responsible for the circadian alterations found

PRS-Net: planar reflective symmetry detection net for 3D models

In geometry processing, symmetry is a universal type of high-level structural information of 3D models and benefits many geometry processing tasks including shape segmentation, alignment, matching, and completion. Thus it is an important problem to analyze various symmetry forms of 3D shapes. Planar reflective symmetry is the most fundamental one. Traditional methods based on spatial sampling can be time-consuming and may not be able to identify all the symmetry planes. In this paper, we present a novel learning framework to automatically discover global planar reflective symmetry of a 3D shape. Our framework trains an unsupervised 3D convolutional neural network to extract global model features and then outputs possible global symmetry parameters, where input shapes are represented using voxels. We introduce a dedicated symmetry distance loss along with a regularization loss to avoid generating duplicated symmetry planes. Our network can also identify generalized cylinders by predicting their rotation axes. We further provide a method to remove invalid and duplicated planes and axes. We demonstrate that our method is able to produce reliable and accurate results. Our neural network based method is hundreds of times faster than the state-of-the-art methods, which are based on sampling. Our method is also robust even with noisy or incomplete input surfaces

PRS-Net: Planar Reflective Symmetry Detection Net for 3D Models

In geometry processing, symmetry is a universal type of high-level structural information of 3D models and benefits many geometry processing tasks including shape segmentation, alignment, matching, and completion. Thus it is an important problem to analyze various symmetry forms of 3D shapes. Planar reflective symmetry is the most fundamental one. Traditional methods based on spatial sampling can be time-consuming and may not be able to identify all the symmetry planes. In this paper, we present a novel learning framework to automatically discover global planar reflective symmetry of a 3D shape. Our framework trains an unsupervised 3D convolutional neural network to extract global model features and then outputs possible global symmetry parameters, where input shapes are represented using voxels. We introduce a dedicated symmetry distance loss along with a regularization loss to avoid generating duplicated symmetry planes. Our network can also identify generalized cylinders by predicting their rotation axes. We further provide a method to remove invalid and duplicated planes and axes. We demonstrate that our method is able to produce reliable and accurate results. Our neural network based method is hundreds of times faster than the state-of-the-art methods, which are based on sampling. Our method is also robust even with noisy or incomplete input surfaces.Comment: Corrected typo

Fusion of Diffusion Weighted MRI and Clinical Data for Predicting Functional Outcome after Acute Ischemic Stroke with Deep Contrastive Learning

Stroke is a common disabling neurological condition that affects about one-quarter of the adult population over age 25; more than half of patients still have poor outcomes, such as permanent functional dependence or even death, after the onset of acute stroke. The aim of this study is to investigate the efficacy of diffusion-weighted MRI modalities combining with structured health profile on predicting the functional outcome to facilitate early intervention. A deep fusion learning network is proposed with two-stage training: the first stage focuses on cross-modality representation learning and the second stage on classification. Supervised contrastive learning is exploited to learn discriminative features that separate the two classes of patients from embeddings of individual modalities and from the fused multimodal embedding. The network takes as the input DWI and ADC images, and structured health profile data. The outcome is the prediction of the patient needing long-term care at 3 months after the onset of stroke. Trained and evaluated with a dataset of 3297 patients, our proposed fusion model achieves 0.87, 0.80 and 80.45% for AUC, F1-score and accuracy, respectively, outperforming existing models that consolidate both imaging and structured data in the medical domain. If trained with comprehensive clinical variables, including NIHSS and comorbidities, the gain from images on making accurate prediction is not considered substantial, but significant. However, diffusion-weighted MRI can replace NIHSS to achieve comparable level of accuracy combining with other readily available clinical variables for better generalization.Comment: 12 pages, 5 figures, 5 table

Altered neuronatin expression in the rat dorsal root ganglion after sciatic nerve transection

<p>Abstract</p> <p>Background</p> <p>Several molecular changes occur following axotomy, such as gene up-regulation and down-regulation. In our previous study using Affymetrix arrays, it was found that after the axotomy of sciatic nerve, there were many novel genes with significant expression changes. Among them, neuronatin (Nnat) was the one which expression was significantly up-regulated. Nnat was identified as a gene selectively expressed in neonatal brains and markedly reduced in adult brains. The present study investigated whether the expression of Nnat correlates with symptoms of neuropathic pain in adult rats with transected sciatic nerve.</p> <p>Methods</p> <p>Western blotting, immunohistochemistry, and the Randall and Selitto test were used to study the protein content, and subcellular localization of Nnat in correlation with pain-related animal behavior.</p> <p>Results</p> <p>It was found that after nerve injury, the expression of Nnat was increased in total protein extracts. Unmyelinated C-fiber and thinly myelinated A-δ fiber in adult dorsal root ganglions (DRGs) were the principal sub-population of primary afferent neurons with distributed Nnat. The increased expression of Nnat and its subcellular localization were related to mechanical hyperalgesia.</p> <p>Conclusions</p> <p>The results indicated that there was significant correlation between mechanical hyperalgesia in axotomy of sciatic nerve and the increased expression of Nnat in C-fiber and A-δ fiber of adult DRG neurons.</p

Mineralization of Progenitor Cells with Different Implant Topographies

AbstractThe major challenge for dental implants is achieving an optimal osteoregeneration. Different levels of roughness processed through sand-blasting/ acid-etching (SLA) then further treated with silane and peptide were measured. Peptide bonded with silane on the SLA and machine ground titanium (Ti) surface were used as a culture substitute. The sample properties on the osteogenic abilities were compared by testing the interaction with mesenchymal stem cells (MSCs, D1). When comparing to the SLA only group, the silane treated Ti surface with peptide bonded had smaller wetting angle and the cell proliferative ability did differ with statistical significance (p<0.05). A rougher surface binding with peptide provided higher hydrophilic ability and had the potential ability to enhance the proliferation and mineralization of the progenitor cell D1. Accordingly, a novel implant surface treatment method having tissues integrated was obtained through the supplement of peptide on the surfaces through SLA treatment of titanium

Molecular Imaging, Pharmacokinetics, and Dosimetry of 111In-AMBA in Human Prostate Tumor-Bearing Mice

Molecular imaging with promise of personalized medicine can provide patient-specific information noninvasively, thus enabling treatment to be tailored to the specific biological attributes of both the disease and the patient. This study was to investigate the characterization of DO3A-CH2CO-G-4-aminobenzoyl-Q-W-A-V-G-H-L-M-NH2 (AMBA) in vitro, MicroSPECT/CT imaging, and biological activities of 111In-AMBA in PC-3 prostate tumor-bearing SCID mice. The uptake of 111In-AMBA reached highest with 3.87 ± 0.65% ID/g at 8 h. MicroSPECT/CT imaging studies suggested that the uptake of 111In-AMBA was clearly visualized between 8 and 48 h postinjection. The distribution half-life (t1/2α) and the elimination half-life (t1/2β) of 111In-AMBA in mice were 1.53 h and 30.7 h, respectively. The Cmax and AUC of 111In-AMBA were 7.57% ID/g and 66.39 h∗% ID/g, respectively. The effective dose appeared to be 0.11 mSv/MBq−1. We demonstrated a good uptake of 111In-AMBA in the GRPR-overexpressed PC-3 tumor-bearing SCID mice. 111In-AMBA is a safe, potential molecular image-guided diagnostic agent for human GRPR-positive tumors, ranging from simple and straightforward biodistribution studies to improve the efficacy of combined modality anticancer therapy

Overview of the Reporting Sources of Developmentallydelayed Children in Taiwan Between 2011 and 2012

Early Intervention (EI) services, as defined in The Bye-laws of Children and Youth Welfare Law, provided for 1.2 % of the nation’s infants, toddlers and preschool children between 2011 and 2012; however, the proportion was higher in some counties or cities and lower in others. In order to elucidate factors that may influence reporting rates, we analyzed the reporting sources from 23 counties/cities between 2011 and 2012. We analyzed registry data of newly reported cases between 2011 and 2012, published by the Department of Statistics, Ministry of Interior of Taiwan. The reporting sources were categorized into eight types, and the percentage of cases reported by each source was calculated. The statistical relationship between these variables and the reporting rates were analyzed with suitable methods. P value < 0.05 was regarded as statistically significant. The estimated 2-year average reporting rate of new cases was 11.97‰. The reporting rate was significantly higher among children living in counties compared with children living in cities (P = 0.0007). The reporting rate was also significantly higher among children living in low urbanized areas as compared with children living in highly urbanized areas (P = 0.0067). The proportion of medical organization reported cases was the highest of all the reporting sources (39.99%). Higher reporting rates from householders, guardians and health centers positively affected the total reporting rates (P = 0.0499 and P=0.0151, respectively). In conclusion our study shows that many sources contribute to the notification of children at risk or with developmental delay, with implications for regular surveillance and screening children development by people involved with them. Incorporating more efficient developmental screening tools, including parent-concerned based screening questionnaires during health screening, with additional staff to do the screening, may increase the proportion of children with possible developmental delay being notified