Serial optical coherence microscopy for label-free volumetric histopathology

The observation of histopathology using optical microscope is an essential procedure for examination of tissue biopsies or surgically excised specimens in biological and clinical laboratories. However, slide-based microscopic pathology is not suitable for visualizing the large-scale tissue and native 3D organ structure due to its sampling limitation and shallow imaging depth. Here, we demonstrate serial optical coherence microscopy (SOCM) technique that offers label-free, high-throughput, and large-volume imaging of ex vivo mouse organs. A 3D histopathology of whole mouse brain and kidney including blood vessel structure is reconstructed by deep tissue optical imaging in serial sectioning techniques. Our results demonstrate that SOCM has unique advantages as it can visualize both native 3D structures and quantitative regional volume without introduction of any contrast agents

Characterisation of feline renal cortical fibroblast cultures and their transcriptional response to transforming growth factor beta 1

Chronic kidney disease (CKD) is common in geriatric cats, and the most prevalent pathology is chronic tubulointerstitial inflammation and fibrosis. The cell type predominantly responsible for the production of extra-cellular matrix in renal fibrosis is the myofibroblast, and fibroblast to myofibroblast differentiation is probably a crucial event. The cytokine TGF-β1 is reportedly the most important regulator of myofibroblastic differentiation in other species. The aim of this study was to isolate and characterise renal fibroblasts from cadaverous kidney tissue of cats with and without CKD, and to investigate the transcriptional response to TGF-β1

Use of neoadjuvant chemotherapy prior to radical hysterectomy in cervical cancer: monitoring tumour shrinkage and molecular profile on magnetic resonance and assessment of 3-year outcome

Use of neoadjuvant chemotherapy prior to radical hysterectomy in cervical cancer: monitoring tumour shrinkage and molecular profile on magnetic resonance and assessment of 3-year outcome The objective of this study is to assess tumour response to neoadjuvant chemotherapy prior to radical hysterectomy in cervical cancer using magnetic resonance (MR) to monitor tumour volume and changes in molecular profile and to compare the survival to that of a control group. Eligibility included Stage Ib-IIb previously untreated cervical tumours >10 cm(3). Neoadjuvant chemotherapy in 22 patients ( methotrexate 300 mg m(-2) (with folinic acid rescue), bleomycin 30 mg m(-2), cisplatin 60 mg m(-2)) was repeated twice weekly for three courses and followed by radical hysterectomy. Post-operative radiotherapy was given in 14 cases. A total of 23 patients treated either with radical surgery or chemoradiotherapy over the same time period comprised the nonrandomised control group. MR scans before and after neoadjuvant chemotherapy and in the control group documented tumour volume on imaging and metabolites on in vivo spectroscopy. Changes were compared using a paired t-test. Survival was calculated using the Kaplan-Meier method. There were no significant differences between the neoadjuvant chemotherapy and control groups in age ( mean, s.d. 43.3 +/- 10, 44.7 +/- 8.5 years, respectively, P = 0.63) or tumour volume (medians, quartiles 35.8, 17.8, 57.7 cm(3) vs 23.0, 15.0, 37.0 cm(3), respectively, P = 0.068). The reduction in tumour volume post-chemotherapy (median, quartiles 7.5, 3.0, 19.0 cm(3)) was significant ( P = 0.002). The reduction in - CH2 triglyceride approached significance ( P = 0.05), but other metabolites were unchanged. The 3-year survival in the chemotherapy group (49.1%) was not significantly different from the control group (46%, P = 0.94). There is a significant reduction in tumour volume and - CH2 triglyceride levels after neoadjuvant chemotherapy, but there is no survival advantage

Cognitive impairment induced by delta9-tetrahydrocannabinol occurs through heteromers between cannabinoid CB1 and serotonin 5-HT2A receptors

Delta-9-tetrahydrocannabinol (THC), the main psychoactive compound of marijuana, induces numerous undesirable effects, including memory impairments, anxiety, and dependence. Conversely, THC also has potentially therapeutic effects, including analgesia, muscle relaxation, and neuroprotection. However, the mechanisms that dissociate these responses are still not known. Using mice lacking the serotonin receptor 5-HT2A, we revealed that the analgesic and amnesic effects of THC are independent of each other: while amnesia induced by THC disappears in the mutant mice, THC can still promote analgesia in these animals. In subsequent molecular studies, we showed that in specific brain regions involved in memory formation, the receptors for THC and the 5-HT2A receptors work together by physically interacting with each other. Experimentally interfering with this interaction prevented the memory deficits induced by THC, but not its analgesic properties. Our results highlight a novel mechanism by which the beneficial analgesic properties of THC can be dissociated from its cognitive side effects

Development and application of a Japanese model of the WHO fracture risk assessment tool (FRAX™)

SUMMARY: The present study estimated the 10-year probability using the Japanese version of WHO fracture risk assessment tool (FRAX) in order to determine fracture probabilities that correspond to intervention thresholds currently used in Japan and to resolve some issues for its use in Japan. INTRODUCTION: The objective of the present study was to evaluate a Japanese version of the WHO fracture risk assessment (FRAX) tool to compute 10-year probabilities of osteoporotic fracture in Japanese men and women. Since lumbar spine bone mineral density (BMD) is used preferentially as a site for assessment, and densitometers use Japanese reference data, a second aim was to investigate the suitability and impact of this practice in Japan. METHODS: Fracture probabilities were computed from published data on the fracture and death hazards in Japan. Probabilities took account of age, sex, the presence of clinical risk factors and femoral neck BMD. Fracture probabilities were determined that were equivalent to intervention thresholds currently used in Japan. The difference between T-scores derived from international reference data and that using Japanese-specific normal ranges was estimated from published sources. The gradient of risk of BMD for fracture in Japan was compared to that for BMD at the lumbar spine in the Hiroshima cohort. RESULTS: The 10-year probabilities of a major osteoporosis-related fracture that corresponded to current intervention thresholds ranged from approximately 5% at the age of 50 years to more than 20% at the age of 80 years. The use of femoral neck BMD predicts fracture as well as or better than BMD tests at the lumbar spine. There were small differences in T-scores between those used for the model and those derived from a Japanese reference population. CONCLUSIONS: The FRAX mark tool has been used to determine possible thresholds for therapeutic intervention, based on equivalence of risk with current guidelines. The approach will need to be supported by appropriate health economic analyses. Femoral neck BMD is suitable for the prediction of fracture risk among Japanese. However, when applying the FRAX model to Japan, T-scores and Z-scores should be converted to those derived from the international reference

Analysis and comparison of very large metagenomes with fast clustering and functional annotation

<p>Abstract</p> <p>Background</p> <p>The remarkable advance of metagenomics presents significant new challenges in data analysis. Metagenomic datasets (metagenomes) are large collections of sequencing reads from anonymous species within particular environments. Computational analyses for very large metagenomes are extremely time-consuming, and there are often many novel sequences in these metagenomes that are not fully utilized. The number of available metagenomes is rapidly increasing, so fast and efficient metagenome comparison methods are in great demand.</p> <p>Results</p> <p>The new metagenomic data analysis method Rapid Analysis of Multiple Metagenomes with a Clustering and Annotation Pipeline (<b>RAMMCAP</b>) was developed using an ultra-fast sequence clustering algorithm, fast protein family annotation tools, and a novel statistical metagenome comparison method that employs a unique graphic interface. RAMMCAP processes extremely large datasets with only moderate computational effort. It identifies raw read clusters and protein clusters that may include novel gene families, and compares metagenomes using clusters or functional annotations calculated by RAMMCAP. In this study, RAMMCAP was applied to the two largest available metagenomic collections, the "Global Ocean Sampling" and the "Metagenomic Profiling of Nine Biomes".</p> <p>Conclusion</p> <p>RAMMCAP is a very fast method that can cluster and annotate one million metagenomic reads in only hundreds of CPU hours. It is available from <url>http://tools.camera.calit2.net/camera/rammcap/</url>.</p

WebCARMA: a web application for the functional and taxonomic classification of unassembled metagenomic reads

Gerlach W, Jünemann S, Tille F, Goesmann A, Stoye J. WebCARMA: a web application for the functional and taxonomic classification of unassembled metagenomic reads. BMC Bioinformatics. 2009;10(1):430.Background Metagenomics is a new field of research on natural microbial communities. High-throughput sequencing techniques like 454 or Solexa-Illumina promise new possibilities as they are able to produce huge amounts of data in much shorter time and with less efforts and costs than the traditional Sanger technique. But the data produced comes in even shorter reads (35-100 basepairs with Illumina, 100-500 basepairs with 454-sequencing). CARMA is a new software pipeline for the characterisation of species composition and the genetic potential of microbial samples using short, unassembled reads. Results In this paper, we introduce WebCARMA, a refined version of CARMA available as a web application for the taxonomic and functional classification of unassembled (ultra-)short reads from metagenomic communities. In addition, we have analysed the applicability of ultra-short reads in metagenomics. Conclusions We show that unassembled reads as short as 35 bp can be used for the taxonomic classification of a metagenome. The web application is freely available at http://webcarma.cebitec.uni-bielefeld.d

Probing Metagenomics by Rapid Cluster Analysis of Very Large Datasets

BACKGROUND: The scale and diversity of metagenomic sequencing projects challenge both our technical and conceptual approaches in gene and genome annotations. The recent Sorcerer II Global Ocean Sampling (GOS) expedition yielded millions of predicted protein sequences, which significantly altered the landscape of known protein space by more than doubling its size and adding thousands of new families (Yooseph et al., 2007 PLoS Biol 5, e16). Such datasets, not only by their sheer size, but also by many other features, defy conventional analysis and annotation methods. METHODOLOGY/PRINCIPAL FINDINGS: In this study, we describe an approach for rapid analysis of the sequence diversity and the internal structure of such very large datasets by advanced clustering strategies using the newly modified CD-HIT algorithm. We performed a hierarchical clustering analysis on the 17.4 million Open Reading Frames (ORFs) identified from the GOS study and found over 33 thousand large predicted protein clusters comprising nearly 6 million sequences. Twenty percent of these clusters did not match known protein families by sequence similarity search and might represent novel protein families. Distributions of the large clusters were illustrated on organism composition, functional class, and sample locations. CONCLUSION/SIGNIFICANCE: Our clustering took about two orders of magnitude less computational effort than the similar protein family analysis of original GOS study. This approach will help to analyze other large metagenomic datasets in the future. A Web server with our clustering results and annotations of predicted protein clusters is available online at http://tools.camera.calit2.net/gos under the CAMERA project