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PubMed2026

DORSSAA: Drug-Target interactOmics Resource Based on Stability/Solubility Alteration Assay.

Advancements in high-throughput techniques such as Thermal Proteome Profiling and the high-throughput Proteome Integral Solubility Alteration assay have revolutionized our understanding of drug-protein interactions. Despite these innovations, the absence of an integrative platform for cross-study analysis of stability and solubility alteration data represents a significant bottleneck. To address this gap, we introduce Drug-target interactOmics Resource based on Stability/Solubility Alteration Assay (DORSSAA), an interactive and expandable web-based platform for the systematic analysis and visualization of proteome stability and solubility alteration assay datasets. Currently, DORSSAA features 1,135,985 records spanning 38 cell lines and organisms, 135 compounds, and 40,742 protein targets. Through its user-friendly interface, the resource supports comparative drug-protein interaction analysis and facilitates the discovery of actionable therapeutic targets. Through two case studies, methotrexate target profiling in A549 cells and combinatorial-therapy drug-target interactions in leukemia cell lines, we demonstrate DORSSAA's utility for identifying protein-drug interactions across diverse experimental contexts. This resource empowers researchers to accelerate drug discovery and enhance our understanding of protein behavior. Compared with data repositories and interaction databases, DORSSAA provides direct protein-level evidence of mechanisms of action with strict statistical control for each study. This enables more reliable identification of drug targets, off-target effects, and potential drug combinations.

Humans↗
PubMed2004

Ice as a reservoir for pathogenic human viruses: specifically, caliciviruses, influenza viruses, and enteroviruses.

Hundreds of isolates of viable bacteria and fungi have been recovered from ancient ice and permafrost. Evidence supports the hypothesis that viral pathogens also are preserved in ice repositories, such as glaciers, ice sheets, and lake ice. Proof may depend upon narrowing the search by applying specific criteria, which would target candidate viruses. Such criteria include viral pathogens likely to occur in great abundance, likely to be readily transported into ice, and then participate in ongoing disease cycles suggestive of their having been deposited in and subsequently released from ice. Caliciviruses, influenza A, and some enteroviruses appear to satisfy all three criteria. Environmental ice appears to be an important abiotic reservoir for pathogenic microbes. World health and eradication of specific pathogens could be affected by this huge reservoir.

Caliciviridae↗
PubMed2005

The role and effectiveness of bone marrow in osseous regeneration.

Autologous bone marrow serves as the richest and most readily available repository of progenitor cells capable of differentiating into mature bone forming cells. Numerous studies have demonstrated that bone marrow alone or cell suspensions of marrow usually diluted in culture medium affect de novo bone formation when implanted in soft tissue sites. Consequently, when bone marrow is used to enrich orthopaedic grafting matrices such as xenograft, demineralized bone matrix, or ceramic materials it almost invariably produces faster and more consistent defect healing compared to bone marrow or the carrier matrix alone and, in some cases, equivalent healing to autograft. This article evaluates the clinical effectiveness of these grafting materials for various orthopaedic applications such as healing long bone defects and enhancing spinal fusion procedures, and hypothesizes that enrichment with bone marrow is integral to timely and satisfactory graft incorporation. Methods such as centrifugation, culture expansion and selective cell retention that concentrate and deliver marrow-derived osteoprogenitor cells to the graft site as a means of mimicking more closely the consistent bone forming potential of autologous bone graft are also discussed.

Animals↗
PubMed2004

Electron energy-loss spectroscopy of anomalous plutonium behavior in nuclear waste materials.

Plutonium-enriched layer has been observed in corroded spent uranium oxide fuel (CSNF). These Pu-enriched regions were examined with analytical transmission electron microscopy combined with electron energy-loss spectroscopy (EELS). The enriched region also contained U, Am, Ru, Zr, but only minor enrichment of rare earth elements. The Pu, possibly as Pu(V) according to EELS measurements, was dispersed within re-precipitated uranium oxide (identified as U3O8) nano-crystals between U(VI) secondary phases and the CSNF surface. The U, Pu, and Am enrichment was observed in the corrosion products with tests on different nuclear fuels. This may have implications for the long-term behavior of CSNF under storage in a geologic waste repository. Furthermore, there may be an increased potential for the generation of Pu-bearing colloids from this type of weathered CSNF.

Journal Article↗
PubMed2005

DNA metabolism and genetic diversity in Trypanosomes.

Trypanosomes are protozoan parasites that cause major diseases in humans and other animals. Trypanosoma brucei and Trypanosoma cruzi are the etiologic agents of African and American Trypanosomiasis, respectively. In spite of large amounts of information regarding various aspects of their biology, including the essentially complete sequences of their genomes, studies directed towards an understanding of mechanisms related to DNA metabolism have been very limited. Recent reports, however, describing genes involved with DNA recombination and repair in T. brucei and T. cruzi, indicated the importance of these processes in the generation of genetic variability, which is crucial to the success of these parasites. Here, we review these data and discuss how the DNA repair and recombination machineries may contribute to strikingly different strategies evolved by the two Trypanosomes to create genetic variability that is needed for survival in their hosts. In T. brucei, two genetic components are critical to the success of antigenic variation, a strategy that allows the parasite to evade the host immune system by periodically changing the expression of a group of variant surface glycoproteins (VSGs). One component is a mechanism that provides for the exclusive expression of a single VSG at any one time, and the second is a large repository of antigenically distinct VSGs. Work from various groups showing the importance of recombination reactions in T. brucei, primarily to move a silent VSG into an active VSG expression site, is discussed. T. cruzi does not use the strategy of antigenic variation for host immune evasion but counts on the extreme heterogeneity of their population for parasite adaptation to different hosts. We discuss recent evidence indicating the existence of major differences in the levels of genomic heterogeneity among T. cruzi strains, and suggest that metabolic changes in the mismatch repair pathway could be an important source of antigenic diversity found within the T. cruzi population.

Animals↗
PubMed2005

Data-partitioning using the Hilbert space filling curves: effect on the speed of convergence of Fuzzy ARTMAP for large database problems.

The Fuzzy ARTMAP algorithm has been proven to be one of the premier neural network architectures for classification problems. One of the properties of Fuzzy ARTMAP, which can be both an asset and a liability, is its capacity to produce new nodes (templates) on demand to represent classification categories. This property allows Fuzzy ARTMAP to automatically adapt to the database without having to a priori specify its network size. On the other hand, it has the undesirable side effect that large databases might produce a large network size (node proliferation) that can dramatically slow down the training speed of the algorithm. To address the slow convergence speed of Fuzzy ARTMAP for large database problems, we propose the use of space-filling curves, specifically the Hilbert space-filling curves (HSFC). Hilbert space-filling curves allow us to divide the problem into smaller sub-problems, each focusing on a smaller than the original dataset. For learning each partition of data, a different Fuzzy ARTMAP network is used. Through this divide-and-conquer approach we are avoiding the node proliferation problem, and consequently we speedup Fuzzy ARTMAP's training. Results have been produced for a two-class, 16-dimensional Gaussian data, and on the Forest database, available at the UCI repository. Our results indicate that the Hilbert space-filling curve approach reduces the time that it takes to train Fuzzy ARTMAP without affecting the generalization performance attained by Fuzzy ARTMAP trained on the original large dataset. Given that the resulting smaller datasets that the HSFC approach produces can independently be learned by different Fuzzy ARTMAP networks, we have also implemented and tested a parallel implementation of this approach on a Beowulf cluster of workstations that further speeds up Fuzzy ARTMAP's convergence to a solution for large database problems.

Algorithms↗
PubMed2005

Graph kernels for chemical informatics.

Increased availability of large repositories of chemical compounds is creating new challenges and opportunities for the application of machine learning methods to problems in computational chemistry and chemical informatics. Because chemical compounds are often represented by the graph of their covalent bonds, machine learning methods in this domain must be capable of processing graphical structures with variable size. Here, we first briefly review the literature on graph kernels and then introduce three new kernels (Tanimoto, MinMax, Hybrid) based on the idea of molecular fingerprints and counting labeled paths of depth up to d using depth-first search from each possible vertex. The kernels are applied to three classification problems to predict mutagenicity, toxicity, and anti-cancer activity on three publicly available data sets. The kernels achieve performances at least comparable, and most often superior, to those previously reported in the literature reaching accuracies of 91.5% on the Mutag dataset, 65-67% on the PTC (Predictive Toxicology Challenge) dataset, and 72% on the NCI (National Cancer Institute) dataset. Properties and tradeoffs of these kernels, as well as other proposed kernels that leverage 1D or 3D representations of molecules, are briefly discussed.

Anticarcinogenic Agents↗
PubMed2006

Pipelining of Fuzzy ARTMAP without matchtracking: correctness, performance bound, and Beowulf evaluation.

Fuzzy ARTMAP neural networks have been proven to be good classifiers on a variety of classification problems. However, the time that Fuzzy ARTMAP takes to converge to a solution increases rapidly as the number of patterns used for training is increased. In this paper we examine the time Fuzzy ARTMAP takes to converge to a solution and we propose a coarse grain parallelization technique, based on a pipeline approach, to speed-up the training process. In particular, we have parallelized Fuzzy ARTMAP without the match-tracking mechanism. We provide a series of theorems and associated proofs that show the characteristics of Fuzzy ARTMAP's, without matchtracking, parallel implementation. Results run on a BEOWULF cluster with three large databases show linear speedup as a function of the number of processors used in the pipeline. The databases used for our experiments are the Forrest CoverType database from the UCI Machine Learning repository and two artificial databases, where the data generated were 16-dimensional Gaussian distributed data belonging to two distinct classes, with different amounts of overlap (5% and 15%).

Databases as Topic↗
PubMed2005

BioVision: an application for the automated image analysis of histological sections.

We describe a computer application, "BioVision", that can be trained to quickly and effectively classify and quantify user definable histological objects (e.g., senile plaques, neurofibrillary tangles) within single or double-labeled immunocytochemically stained sections. For a given image population, BioVision is interactively trained (in Independent User Mode) by an investigator to perform the desired classifications. This training yields a statistical model of the different types of objects occurring in the target image population. The resulting model can then be used (in Automated User Mode) to classify all objects in any image or images from the target population. BioVision simplifies the quantification of complex visual objects and improves inter-rater reliability. The program accomplishes classification in two major stages: pixel classification and blob classification. In pixel classification, each pixel is assigned to one of some number of substance classes, based on its chromatic properties and local context, reflecting basic histological distinctions of interest. In the blob classification phase, the image's pixels are first partitioned into "blobs": maximal connected sets of pixels assigned to the same substance class. Then, based on its size, shape, textural and contextual properties, each blob is assigned to a histological object class. A Bayesian classifier is used in each of the pixel and blob classification stages. We report several tests of BioVision. First, we applied BioVision to classify senile plaques and neurofibrillary tangles in several test cases of Alzheimer's brain immunostained for beta-amyloid and PHF-tau and compared the results to those produced by experienced investigators. BioVision was trained to classify Plaque-type blobs as either plaques or plaque-type nonentities, and tangle-type blobs as either tangles or tangle-type nonentities. BioVision classified the objects with an accuracy comparable to the trained investigator. Next, we applied BioVision to the task of counting all the tangles in hippocampal images from 22 Alzheimer's disease (AD) cases selected to span a broad range of dementia levels from the tissue repository of UC Irvine's Center for the study of Brain Aging and Dementia. The tangle counts produced by BioVision proved to be significantly better predictors of the cases' adjusted MMSE scores than any of tangle load, age at death, post mortem interval or the interval between the last MMSE score and death.

Alzheimer Disease↗
PubMed2026

Individual Differences in Cognitive Aging Rodent Datasets (ID-CARD): A collaborative platform for behavioral analysis across the lifespan.

Understanding cognitive aging requires approaches that capture individual variability while enabling integration across studies. In rodent models, behavioral data are central to this effort, yet cross-laboratory differences in experimental design limit comparability and constrain secondary analysis. To address this gap, we developed the Individual Differences in Cognitive Aging Rodent Datasets (ID-CARD), a first-of-its-kind collaborative repository aggregating trial-level Morris water maze data from multiple laboratories. ID-CARD is designed to support large-scale, integrative analyses and to facilitate secondary use of existing behavioral data in alignment with emerging data-sharing and transparency initiatives. Rather than imposing retrospective harmonization of experimental protocols, we implemented a normalization and modeling framework that enables comparison of learning trajectories while preserving meaningful variation across studies. Behavioral data from > 5000 rats spanning common strains, both sexes, and multiple ages were normalized in training and performance domains and fit with a logarithmic function to derive an error accumulation rate coefficient (EARC) as a measure of spatial learning. Age was strongly associated with increased EARC, indicating attenuated learning, even after adjusting for non-spatial cue performance. Analyses of goodness of fit revealed systematic structure in learning dynamics, where age was associated with reduced learning-curve conformity after accounting for overall performance. Inter-individual variability in spatial learning also increased with age, with strain-specific interactions. These findings demonstrate that integrated analysis of heterogeneous behavioral datasets can yield robust, individual-level insights into cognitive aging. ID-CARD provides a scalable resource and analytic framework to advance discovery in behavioral neuroscience by enabling reuse, integration, and comparative analysis of existing data.

Cognitive aging↗
PubMed2004

A knowledge-driven algorithm for a rapid and automatic extraction of the human cerebral ventricular system from MR neuroimages.

A knowledge-driven algorithm for a rapid, robust, accurate, and automatic extraction of the human cerebral ventricular system from MR neuroimages is proposed. Its novelty is in combination of neuroanatomy, radiological properties, and variability of the ventricular system with image processing techniques. The ventricular system is divided into six 3D regions: bodies and inferior horns of the lateral ventricles, third ventricle, and fourth ventricle. Within each ventricular region, a 2D region of interest (ROI) is defined based on anatomy and variability. Each ventricular region is further subdivided into subregions, and conditions detecting and preventing leakage into the extra-ventricular space are specified for each subregion. The algorithm extracts the ventricular system by (1) processing each ROI (to calculate its local statistics, determine local intensity ranges of cerebrospinal fluid and gray and white matters, set a seed point within the ROI, grow region directionally in 3D, check anti-leakage conditions, and correct growing if leakage occurred) and (2) connecting all unconnected regions grown by relaxing growing conditions. The algorithm was validated qualitatively on 68 and quantitatively on 38 MRI normal and pathological cases (30 clinical, 20 MGH Brain Repository, and 18 MNI BrainWeb data sets). It runs successfully for normal and pathological cases provided that the slice thickness is less than 3.0 mm in axial and less than 2.0 mm in coronal directions, and the data do not have a high inter-slice intensity variability. The algorithm also works satisfactorily in the presence of up to 9% noise and up to 40% RF inhomogeneity for the BrainWeb data. The running time is less than 5 s on a Pentium 4, 2.0 GHz PC. The best overlap metric between the results of a radiology expert and the algorithm is 0.9879 and the worst 0.9527; the mean and standard deviation of the overlap metric are 0.9723 and 0.01087, respectively.

Adolescent↗
PubMed2006

Skull-stripping magnetic resonance brain images using a model-based level set.

The segmentation of brain tissue from nonbrain tissue in magnetic resonance (MR) images, commonly referred to as skull stripping, is an important image processing step in many neuroimage studies. A new mathematical algorithm, a model-based level set (MLS), was developed for controlling the evolution of the zero level curve that is implicitly embedded in the level set function. The evolution of the curve was controlled using two terms in the level set equation, whose values represented the forces that determined the speed of the evolving curve. The first force was derived from the mean curvature of the curve, and the second was designed to model the intensity characteristics of the cortex in MR images. The combination of these forces in a level set framework pushed or pulled the curve toward the brain surface. Quantitative evaluation of the MLS algorithm was performed by comparing the results of the MLS algorithm to those obtained using expert segmentation in 29 sets of pediatric brain MR images and 20 sets of young adult MR images. Another 48 sets of elderly adult MR images were used for qualitatively evaluating the algorithm. The MLS algorithm was also compared to two existing methods, the brain extraction tool (BET) and the brain surface extractor (BSE), using the data from the Internet brain segmentation repository (IBSR). The MLS algorithm provides robust skull-stripping results, making it a promising tool for use in large, multi-institutional, population-based neuroimaging studies.

Aged↗
PubMed2006

CaMKII activation in the entorhinal cortex disrupts previously encoded spatial memory.

To investigate the role of the entorhinal cortex in memory at a molecular level, we developed transgenic mice in which transgene expression was inducible and limited to the superficial layers of the medial entorhinal cortex, pre- and parasubiculum. We found that expression of a constitutively active mutant form of CaMKII in these structures disrupted spatial memory formation. Immediate post-training activation of the transgene disrupted previously established memory while transgene activation 3 weeks following the training was ineffective. These results demonstrate that, similar to the hippocampus, the entorhinal cortex plays a time-limited role in spatial memory formation but is not a final cortical repository of long-term memory. Moreover, these results suggest that the indiscriminate activation of CaMKII is able to disrupt preexisting memories, possibly by altering the pattern of synaptic weight changes that are thought to form the basis of the memory trace.

Animals↗
PubMed2005

REFOLD: an analytical database of protein refolding methods.

The expression and harvesting of proteins from insoluble inclusion bodies by solubilization and refolding is a technique commonly used in the production of recombinant proteins. To bring clarity to the large and widespread quantity of published protein refolding data, we have recently established the REFOLD database (http://refold.med.monash.edu.au), which is a freely available, open repository for protocols describing the refolding and purification of recombinant proteins. Refolding methods are currently published in many different formats and resources--REFOLD provides a standardized system for the structured reporting and presentation of these data. Furthermore, data in REFOLD are readily accessible using a simple search function, and the database also enables analyses which identify and highlight particular trends between suitable refolding and purification conditions and specific protein properties. This information may in turn serve to facilitate the rational design and development of new refolding protocols for novel proteins. There are approximately 200 proteins currently listed in REFOLD, and it is anticipated that with the continued contribution of data by researchers this number will grow significantly, thus strengthening the emerging trends and patterns and making this database a valuable tool for the scientific community.

Databases, Protein↗
PubMed2004

Evidence for stanniocalcin and a related receptor in annelids.

Stanniocalcin (STC) is a prime example of a hormone whose discovery in fish led to its subsequent discovery in mammals. STC is considered to be first and foremost a vertebrate polypeptide hormone with regulatory effects on ion transport, mitochondrial function and steroid hormone synthesis. The gene is widely expressed in both fishes and mammals, and the hormone can operate via both local and endocrine signaling pathways. In spite of the growing catalogue of vertebrate hormones and receptors with homologues in invertebrates, the notion that there might be an invertebrate STC homolog has received scant attention to date. In the present study, we have provided evidence for STC in annelid worms (freshwater leeches). Western blot analysis revealed the presence of two STC immunoreactive (STCir) proteins in leech tissue extracts of 100 and 193 kDa. These same extracts significantly lowered the rate of gill calcium transport upon injection into fish. Similarly, fish STC increased the rate of whole body calcium uptake when administered to leeches, and STC receptors of high affinity were identified on isolated leech plasma membranes. Two discrete populations of STC-positive cells were also identified in leeches using antibodies to fish STC and fish STC cRNA probes. One of the cell types was confined to the skin. The second cell type was confined to the coelomic cavity and identified as an adipose cell, which in leeches is a major repository of fat. Collectively, the data constitutes compelling evidence for the existence of STC-related proteins and receptors in annelids that share structural and functional similarities with those in vertebrates.

Animals↗
PubMed2006

Neural and hormonal control of muscular activity of the spermatheca in the locust, Locusta migratoria.

The spermatheca in insects is a tubular structure within the female that acts as a repository for spermatozoa deposited by the male during copulation. The spermatozoa remain viable within the spermatheca for extended periods of time, and are then delivered to the site of fertilization during oviposition (egg-laying). Thus, the production of viable offspring is dependent upon the coordination of events associated with fertilization, including the passage of the egg through the lateral and common oviducts and the passage of spermatozoa along the spermathecal duct. The egg and the spermatozoa are propelled along their respective tracts by contractions of the visceral muscles intrinsic to the oviduct and spermatheca. The neural and hormonal control of muscular activity of the locust oviducts has been well reviewed, with more recent studies examining the control over the spermatheca. This review highlights more recent literature, including new data, for neural and hormonal control of muscular activity of the spermatheca of the locust, Locusta migratoria, making reference to examples in other insects where relevant. A variety of neuronal types project to the spermatheca in L. migratoria, and a variety of neuroactive chemicals, including neuropeptides and amines, influence contraction. A comparison is made between the control of oviducts and spermatheca in L. migratoria with regard to their neural substrate and the composition of neuroactive chemicals.

Animals↗
PubMed2004

NMRShiftDB -- compound identification and structure elucidation support through a free community-built web database.

Compound identification and support for computer-assisted structure elucidation via a free community-built web database for organic structures and their NMR data is described. The new database NMRShiftDB is available on . As the first NMR database, NMRShiftDB allows not only open access to the database but also open and peer reviewed submission of datasets, enabling the natural products community to build its first free repository of assigned 1H and 13C NMR spectra. In addition to the open access, the underlying database software is built solely from free software and is available under an open source license. This allows collaborating laboratories to fully replicate the database and to create a highly available network of NMRShiftDB mirrors. The database contains about 10,000 structures and assigned spectra, with new datasets constantly added. Its functionality includes (sub-) spectra and (sub-) structure searches as well as shift prediction of 13C spectra based on the current database material.

Databases, Factual↗
PubMed2006

PeroxiBase: a class III plant peroxidase database.

Class III plant peroxidases (EC 1.11.1.7), which are encoded by multigenic families in land plants, are involved in several important physiological and developmental processes. Their varied functions are not yet clearly determined, but their characterization will certainly lead to a better understanding of plant growth, differentiation and interaction with the environment, and hence to many exciting applications. Since there is currently no central database for plant peroxidase sequences and many plant sequences are not deposited in the EMBL/GenBank/DDBJ repository or the UniProt KnowledgeBase, this prevents researchers from easily accessing all peroxidase sequences. Furthermore, gene expression data are poorly covered and annotations are inconsistent. In this rapidly moving field, there is a need for continual updating and correction of the peroxidase superfamily in plants. Moreover, consolidating information about peroxidases will allow for comparison of peroxidases between species and thus significantly help making correlations of function, structure or phylogeny. We report a new database (PeroxiBase) accessible through a web server with specific tools dedicated to facilitate query, classification and submission of peroxidase sequences. Recent developments in the field of plant peroxidase are also mentioned.

Databases, Genetic↗