Immune based therapies in cancer

Immunotherapy of cancer has become a more promising approach in the past decade. Developments in both basic immunology and tumor biology have increased our knowledge of the interactions between the tumor cells and the immune system. The molecular identification of tumor-associated antigens and understanding of immunological pathways have cleared the way for development of different strategies for anti-tumor vaccines. The success of any cancer vaccine relies on the induction of an effective tumor-specific immune response to break tolerance and to elicit a long lasting anti-tumor immunity. It is also increasingly clear that the interactions of host-tumor are quite complicated leading to tumor escape mechanisms, which add another level of difficulty to this interaction. This review will summarize the recent developments in tumor immunotherapy as well as the clinical trials addressing novel immunotherapeutic approaches to cancer.     

The role of physiologically based toxicokinetic models in biologically based risk assessment

Biologically-based cancer risk assessment relies on mathematical models that represent the toxicokinetics and toxicodynamics of the xenobiotic in the body. Physiologically-based toxicokinetic (PBTK) models are used as a tool for predicting the target tissue dose of a xenobiotic from different routes of exposure, extrapolating from high doses to low doses and extrapolating between species. This paper reviews the role of PBTK models and their limitations in biologically-based risk assessment.     

Recent advances in polyaniline based biosensors

The present paper contains a detailed overview of recent advances relating to polyaniline (PANI) as a transducer material for biosensor applications. This conducting polymer provides enormous opportunities for binding biomolecules, tuning their bio-catalytic properties, rapid electron transfer and direct communication to produce a range of analytical signals and new analytical applications. Merging the specific nature of different biomolecules (enzymes, nucleic acids, antibodies, etc.) and the key properties of this modern conducting matrix, possible biosensor designs and their biosensing characteristics have been discussed. Efforts have been made to discuss and explore various characteristics of PANI responsible for direct electron transfer leading towards fabrication of mediator-less biosensors.     

Pathophysiologically based treatment interventions in schizophrenia

Identifying the molecular alterations that underlie the pathophysiology of critical clinical features of schizophrenia is an essential step in the rational development of new therapeutic interventions for this devastating illness. Cognitive deficits, such as the impairments in working memory that arise from dysfunction of the dorsolateral prefrontal cortex, are a major determinant of functional outcome in schizophrenia. Here we consider the contributions of disturbances in glutamate, dopamine and GABA neurotransmission to the pathophysiology of working memory impairments in schizophrenia, suggest a cascade of molecular events that might link these disturbances, and argue that the molecular alterations most proximal to the pathophysiology of prefrontal dysfunction offer the most promise as targets for new drug development.     

Recent trends in antibody based sensors

This review details recent advances in the fields of immunosensors and closely related immunoassays in the past decade, together with a discussion of possible future trends. Immunosensors can be classified by the way in which they transduce the signal produced upon the formation of an antibody antigen complex. Recent advancements to these methods of detection and transduction are discussed in detail, with particular focus on electrochemical, optical, piezoelectric and magnetic based sensors. The varying applications of these sensors are also discussed. Some of the most significant advances include development of immunosensors for the continuous monitoring of analytes, point of care (PoC) devices, with lower unit costs, automation, reusability and ease of use. Immunosensor technology has advanced at a prolific rate since its conception and has grown into a diverse area of ongoing research.     

Ontology based document enrichment in bioinformatics

Controlled vocabularies are common within bioinformatics resources. They can be used to give a summary of the knowledge held about a particular entity. They are also used to constrain values given for particular attributes of an entity. This helps create a shared understanding of a domain and aids increased precision and recall during querying of resources. Ontologies can also provide such facilities, but can also enhance their utility. Controlled vocabularies are often simply lists of words, but may be viewed as a kind of ontology. Ideally ontologies are structurally enriched with relationships between terms within the vocabulary. Use of such rich forms of vocabularies in database annotation could enhance those resources usability by both humans and computers. The representation of the knowledge content of biological resources in a computationally accessible form opens the prospect of greater support for a biologist investigating new data.     

Multi-dimensional liquid phase based separations in proteomics

This review covers recent developments towards the implementation of multi-dimensional (MuD) liquid phase based systems for proteome investigations. Although two-dimensional polyacrylamide gel electrophoresis (2D-PAGE) has been used as a standard approach in proteomics, its drawbacks including the limited dynamic range and molecular mass range, together with lack of on-line integration with biological mass spectrometery (Bio-MS) have limited its widespread use and applications in proteomics. In the meantime, various liquid-phase based multi-dimensional separation techniques have been explored. Especially, with the emergence of the combination of nanoflow capillary high-performance liquid chromatography (cHPLC) and Bio-MS, attention is again refocused on utilizing multi-dimensional liquid-phase based separation of proteins. Some remarkable applications of on-line analysis of intact proteins and on-column digested proteins, and the emergence of approaches such as multiple HPLC-electrospray ionization tandem MS and capillary array electrophoresis-matrix assisted laser desorption ionization MS, have stimulated thinking towards developing a automated multi-dimensional system (MuDSy) that integrates liquid phase based separation, digestion and identification of proteins in complex biological mixtures.     

Novel biologically based therapeutic strategies in myeloma

Multiple myeloma remains incurable despite advances in conventional chemotherapy and wider applicability of high dose chemotherapy with single and/or tandem autologous peripheral blood stem cell transplantation. Although a complete remission rate of 41% and an event-free survival of 43 months have been reported after tandem transplantation, it is highly unlikely that further improvements in the outcome of multiple myeloma will be achieved by escalating cytotoxic chemotherapy alone. Novel biologically based therapies are therefore urgently required. Targeted therapeutic approaches based on: identification of genetic abnormalities in malignant plasma cells; interrupting growth of myeloma cells; triggering apoptotic signaling cascades in tumor cells; modulating growth and survival of multiple myeloma cells in the bone marrow microenvironment, i.e. angiogenesis and cytokine networks; enhancing allogeneic and autologous antimyeloma immunity; and characterizing newer myeloma antigens for serotherapy are under development. These therapies offer great promise, used alone/or in combination with conventional treatment approaches, to improve the outcome in this disease in newly diagnosed/refractory or relapsed patients with multiple myeloma.     

Temporal correlation based learning in neuron models

We study a learning rule based upon the temporal correlation (weighted by a learning kernel) between incoming spikes and the internal state of the postsynaptic neuron, building upon previous studies of spike timing dependent synaptic plasticity (Kempter, R., Gerstner, W., van Hemmen, J.L., Wagner, H., 1998. Extracting Oscillations: Neuronal coincidence detection with noisy periodic spike input. Neural computation 10, 1987–2017; Kempter, R., Gerstner, W., van Hemmen, J.L., 1999. Hebbian learning and spiking neurons. Physical Reviewm E59, 4498–4514; van Hemmen, J.L., 2001. Theory of synaptic plasticity. In: Moss, F., Gielen, S. (Eds.), Handbook of biological physics. vol. 4, Neuro Informatics, neural modelling, Elsevier, Amsterdam, pp. 771–823. Our learning rule for the synaptic weight w _ij is where the t _j,μ are the arrival times of spikes from the presynaptic neuron j and the function u(t) describes the state of the postsynaptic neuron i. Thus, the spike-triggered average contained in the inner integral is weighted by a kernel Γ(s), the learning window, positive for negative, negative for positive values of the time difference s between post- and presynaptic activity. An antisymmetry assumption for the learning window enables us to derive analytical expressions for a general class of neuron models and to study the changes in input-output relationships following from synaptic weight changes. This is a genuinely non-linear effect (Song, S., Miller, K., Abbott, L., 2000. Competitive Hebbian learning through spike timing dependent synaptic plasticity. Nature Neuroscience 3, 919–926).     

Polymorphism in Alnus based Frankia of Darjeeling

DNA samples extracted from the root nodules of Alnus nepalensis, collected from 10 different locations of Darjeeling hills, were used to assess the genetic diversity of Frankia. The DNA samples from the nodules of naturally growing plants were used as templates in PCR, targeting different genomic regions of Frankia, namely distal, middle and proximal parts of 16S rRNA gene and nifH-D IGS region with locus specific primers. The PCR products were digested with a number of frequent (4-base) cutter restriction endonucleases. Bands were scored as present (1) or absent (0) and the clustering was done using NTSYSpc. Distinct polymorphism was found among the nodules collected from different parts of the region and those of same geographic area. These results demonstrate that genetic diversity is indeed present among the naturally occurring Frankia of Darjeeling, India.     

Proximity based GPCRs prediction in transform domain

In this work, we predict G-protein coupled receptors (GPCRs) using hydrophobicity of amino acid sequences and Fast Fourier Transform for feature generation. We analyze whether the GPCRs classification strategy depends on the way the feature space may be exploited. Consequently, we show that the sequence pattern based information could easily be exploited in the frequency domain using proximity rather than increasing margin of separation between the classes. We thus develop a simple proximity based approach known as nearest neighbor (NN) for classifying the 17 GPCRs subfamilies. The NN classifier has outperformed the one against all implementation of support vector machine using both Jackknife and independent dataset. The results validate the importance of the understanding and efficient exploitation of the feature space. It also shows that simple classification strategies may outperform complex ones because of the efficient exploitation of the feature space.     

High-throughput PCR in silicon based microchamber array

Highly integrated hybridization assay and capillary electrophoresis have improved the throughput of DNA analysis. The shift to high throughput analysis requires a high speed DNA amplification system, and several rapid PCR systems have been developed. In these thermal cyclers, the temperature was controlled by effective methodology instead of a large heating/cooling block preventing rapid thermal cycling. In our research, high speed PCR was performed using a silicon-based microchamber array and three heat blocks. The highly integrated microchamber array was fabricated by semiconductor microfabrication techniques. The temperature of the PCR microchamber was controlled by alternating between three heat blocks of different temperature. In general, silicon has excellent thermal conductivity, and the heat capacity is small in the miniaturized sample volume. Hence, the heating/cooling rate was rapid, approximately 16 °C/s. The rapid PCR was therefore completed in 18 min for 40 cycles. The thermal cycle time was reduced to 1/10 of a commercial PCR instrument (Model 9600, PE Applied Biosystems-3 h).     

Phylogenetic relationships in theCampanulales based onrbcL sequences

Phylogenetic relationships within the angiosperm orderCampanulales were investigated by comparative sequencing of the chloroplast generbcL. CompleterbcL sequences were obtained for ten species in six families within the order. These data were analyzed along with previously publishedrbcL sequences from other taxa (for a total of 117 species) within the subclassAsteridae and outgroups, producing 32 equally parsimonious trees. A subset consisting of 44 of these taxa was then chosen and more rigorous analyses performed, resulting in four equally parsimonious trees. Results indicate that two major clades roughly corresponding to traditionally circumscribedAsterales andCampanulales exist as sister taxa. In particular, therbcL trees indicate thatSphenoclea is not a member ofCampanulales orAsterales, thatPentaphragma is more closely allied toAsterales thanCampanulales, that theCyphiaceae are not monophyletic, thatCampanulaceae andLobeliaceae are not sister taxa, and thatStylidiaceae are correctly placed withinCampanulales.     

Micro-economics based resource allocation in Grid-Federation environment

A Grid-Federation environment is composed of a collection of autonomous and selfish distributed cluster resource managers. These selfish managers participate in Grid-Federation to share their resources. Market models could be used to motivate the self-interested participants to share their resources. In this paper, firstly, a market for resource exchange in grid federation environment is established. Then, in order that the market reaches a Walrasian equilibrium, a computationally tractable mechanism is proposed. A Walrasian equilibrium problem consists of finding a set of prices and allocations of resources in such a way that the cluster resource managers could maximize their utilities and the market clears. Market clears when the resource supply equals to the demand. We show that in a Walrasian equilibrium, the Grid Federation market reaches an efficient resource allocation.     

生物学研究性教学的探索与实践

研究性教学将教师的探究性教学与学生的研究性学习有机地结合起来,激发学生自主学习和探究的动机,从而培养其能力和增强其社会竞争力。研究性教学要求生物教师有广泛的专业知识准备,积极收集国内外教学资料,重视学科交叉,对学生充满热情、爱心和奉献精神,坚持进行科学研究,坚持进行研究性教学理论与实践的探索并致力于立体化教材的建设,以促进开放、研究性的大学教学氛围的形成。