Anonymization server system for DICOM images

We have developed an anonymization system for DICOM images. It requires consent from the patient to use the DICOM images for research or education. However, providing the DICOM image to the other facilities is not safe because it contains a lot of personal data. Our system is a server that provides anonymization service of DICOM images for users in the facility. The distinctive features of the system are, input interface, flexible anonymization policy, and automatic body part identification. In the first feature, we can use the anonymization service on the existing DICOM workstations. In the second feature, we can select a best policy fitting for the Protection of personal data that is ruled by each medical facility. In the third feature, we can identify the body parts that are included in the input image set, even if the set lacks the body part tag in DICOM header. We installed the system for the first time to a hospital in December 2005. Currently, the system is working in other four facilities. In this paper we describe the system and how it works

Prolonged oxidative stress and delayed tissue repair exacerbate acetaminophen-induced liver injury in aged mice

マウスにアセトアミノフェンを投与して急性劇症肝炎を誘導すると，中心静脈域にネクローシスによる大量の肝細胞死が誘導される．障害後は，速やかに障害が解消され，障害後48 時間後には活発な肝細胞増殖が誘導され，組織再生が進行する．老齢マウスでは，アセトアミノフェン代謝産物の処理能力低下による障害の持続，障害部位へのマクロファージ集積低下による死細胞の残存，肝細胞増殖能の低下，などによって障害の持続と再生の遅延が認められた．本研究の結果は，加齢が薬剤の肝毒性を高めるリスクファクターとなる場合があることを示している

An automated distinction of DICOM image for lung cancer CAD system

Automated distinction of medical images is an important preprocessing in Computer-Aided Diagnosis (CAD) systems. The CAD systems have been developed using medical image sets with specific scan conditions and body parts. However, varied examinations are performed in medical sites. The specification of the examination is contained into DICOM textual meta information. Most DICOM textual meta information can be considered reliable, however the body part information cannot always be considered reliable. In this paper, we describe an automated distinction of DICOM images as a preprocessing for lung cancer CAD system. Our approach uses DICOM textual meta information and low cost image processing. Firstly, the textual meta information such as scan conditions of DICOM image is distinguished. Secondly, the DICOM image is set to distinguish the body parts which are identified by image processing. The identification of body parts is based on anatomical structure which is represented by features of three regions, body tissue, bone, and air. The method is effective to the practical use of lung cancer CAD system in medical sites

Analysis of the anti-tumor mechanism of BRD4 inhibition in hepatocellular carcinoma

Bromodomain and extra terminal (BET) family proteins, which include BRD4, are readers of histone acetyl-lysines and key regulators of gene transcription. BRD4 inhibitors exert anti-tumor effects in various cancers, including hepatocellular carcinoma (HCC). We investigated the mechanism underlying the antitumor effects of BRD4 inhibition in HCC. We first tested the effects of the BRD4 inhibitor JQ1 in a series of 9 HCC cell lines and found that it strongly suppressed HCC cell proliferation by inducing cell cycle arrest and apoptosis. Gene expression microarray analysis revealed that JQ1 also induced marked changes in the gene expression profiles of HCC cells, and genes associated with cell cycle and apoptosis were significantly enriched among the affected genes. Notably, a number of cancer-related genes, including BCAT1, DDR1, GDF15, FANCD2, SENP1 and TYRO3, were strongly suppressed by JQ1 in HCC cells. We also confirmed BRD4 bound within the promoter regions of these genes, which suggests they are targets of BRD4 in HCC cells. JQ1 thus appears to exert its anti-tumor effects in HCC by suppressing multiple BRD4 target genes

Выращивание ремонтного молодняка кур при использовании пробиотических препаратов «Бацелл» и «Моноспорин»

Применение пробиотических препаратов с первых дней жизни цыплят позволит получить в дальнейшем здоровую птицу с высокой реализацией генетического потенциала

Epigenetic biomarkers for prediction of sensitivity to chemotherapeutic drugs in multiple myeloma

Multiple myeloma continues to be a lethal malignancy despite the development of treatments such as high-dose chemotherapy combined with stem cell transplantation. Multiple myeloma arises through an accumulation of multiple genetic anges, including immunoglobulin gene rearrangements involved in Cyclin D. The main difficulties in multiple myeloma treatments are drug-resistance. DNA methylation of the5\u27 CpG islands of genes is often found in multiple myeloma. To screen for he genes involved in tumorigenesis of multiple myeloma, which are silenced by DNA methylation, we performed cDNA microarray analysis using multiple myeloma cell lines treated with demethylating agent5-aza-2-deoxycytidine (DAC), and entified RASD1, a dexamethasone (Dex)-inducible gene, as one of the targets of epigenetic changes. Inactivation of RASD1 was found to correlate with resistance to Dex, and treatment of multiple myeloma cells with DAC restored sensitivity to Dex. These findings suggest the involvement of epigenetic gene silencing in multiple myeloma progression and drug-resistance, and the usefulness of demethylation therapy for multiple myeloma treatment. Furthermore, DNA methylation can be an epigenetic biomarker for multiple myeloma

Prediction of p53 target genes based on integrative analysis of chromatin immunoprecipitated and sequenced tags，by using Galaxy，a web-based interactive platform for large-scale genome analysis

Chromatin immunoprecipitation (ChIP) followed by sequencing of immunoprecipitated DNA fragments is the high throughput method for identifying transcription factor binding sites. In one such method, ChIP PET, paired end ditags (PETs) derived from both ends of the immunoprecipitated DNA fragments are sequenced and mapped to the genome. We report here the prediction of p53 target genes by meta analyzing tags of p53 ChIP PET and by combining with other genomic annotations, using Galaxy, a web based platform for large scale genome analysis. We found 327 of p53 binding sites on the genome of 5-fluorouracil (5-FU)-treated HCT116 colon cancer cells by searching the total 65,509 PETs for PET clusters. The search for p53 target gene, which focused on PET clusters with computationally-predicted p53 binding motif, identified 20 of putative p53 target genes as well as 11 of known p53 targets. Another search for p53 target genes, which focused on PET clusters located within 50-kb flanking regions of transcription start sites of genes, identified 278 of Refseq genes, 79 of non-coding RNAs and 5 of microRNAs as p53 targets which included lots of known validated targets. Our results indicate that sequencing-based ChIP analysis combined with the existing genome annotation is effective method to predict p53 binding loci and target genes, and also show that the Galaxy platform is well-suited for multiple-type analyses and visualization of ChIP data, leading to functional annotation of transcription factor binding sites