Photoacoustic tomography of the human finger: towards the assessment of inflammatory joint diseases

Inflammatory arthritis is often manifested in finger joints. The growth of new or withdrawal of old blood vessels can be a sensitive marker for these diseases. Photoacoustic (PA) imaging has great potential in this respect since it allows the sensitive and highly resolved visualization of blood. We systematically investigated PA imaging of finger vasculature in healthy volunteers using a newly developed PA tomographic system. We present the PA results which show excellent detail of the vasculature. Vessels with diameters ranging between 100 mu m and 1.5 mm are visible along with details of the skin, including the epidermis and the subpapillary plexus. The focus of all the studies is at the proximal and distal interphalangeal joints, and in the context of ultimately visualizing the inflamed synovial membrane in patients. This work is important in laying the foundation for detailed research into PA imaging of the phalangeal vasculature in patients suffering from rheumatoid arthritis.

Regulation of oxidative-stress responsive genes by arecoline in human keratinocytes

Background and Objective: Arecoline, an arecanut alkaloid present in the saliva of betel quid chewers, has been implicated in the pathogenesis of a variety of inflammatory oral diseases, including oral submucous fibrosis and periodontitis. To understand the molecular b asis of arecoline action in epithelial changes associated with these diseases, we investigated the effects of arecoline on human keratinocytes with respect to cell growth regulation and the expression of stress-responsive genes.Material and Methods:Human keratinocyte cells (of the HaCaT cell line) were treated with arecoline, following which cell viability was assessed using the Trypan Blue dye-exclusion assay, cell growth and proliferation were analyzed using the MTT (3-[4,5-dimethylthiazol-2-yl]-2,5-diphenyltetrazolium bromide) and 5-bromo-2-deoxyuridine incorporation assays, cell cycle arrest and generation of reactive oxygen species were examined using flow cytometry, and gene expression changes were investigated using the reverse transcription-polymerase chain reaction technique. The role of oxidative stress, muscarinic acetylcholine receptor and mitogen-activated protein kinase (MAPK) pathways were studied using specific inhibitors. Western blot analysis was performed to study p38 MAPK activation.Results:Arecoline induced the generation of reactive oxygen species and cell cycle arrest at the G1/G0 phase in HaCaT cells without affecting the expression of p21/Cip1. Arecoline-induced epithelial cell death at higher concentrations was caused by oxidative trauma without eliciting apoptosis. Sublethal concentrations of arecoline upregulated the expression of the following stress-responsive genes: heme oxygenase-1; ferritin light chain; glucose-6-phosphate dehydrogenase; glutamate-cysteine ligase catalytic subunit; and glutathione reductase.Additionally, there was a dose-dependent induction of interleukin-1alfa mRNA by arecoline via oxidative stress and p38 MAPK activation. Conclusion:our data highlight the role of oxidative stress in arecoline-mediated cell death, gene regulation and inflammatory processes in human keratinocytes.

DC-SIGN and alpha 2,6-sialylated IgG Fc interaction is dispensable for the anti-inflammatory activity of IVIg on human dendritic cells

Intravenous immunoglobulin (IVIg) is widely used to treat autoimmune diseases. Several mutually nonexclusive mechanisms are proposed to explain the beneficial effects of IVIg in patients (1, 2). Lately, Ravetch and colleagues (3) demonstrate that anti-inflammatory activity of IVIg is mediated mainly by antibodies that contain terminal _2,6-sialic acid linkages at the Asn297-linked glycan of Fc region.

An ethnobotanical study of traditional anti-inflammatory plants used by the Lohit community of Arunachal Pradesh, India

Aim of the study: Most people especially in rural areas depend on herbal medicines to treat many diseases including inflammation-related ailments such as rheumatism, muscle swelling, cut wound, accidental bone fracture, insect bites, pains and burn by fire and hot water. The objectives of this study were: to catalog ethno-medicinal plants of Lohit community, ecological status, indigenous folk medicinal uses, morphological parts used and to determine their reported pharmacological studies. Materials and methods: The ethnobotanical information on traditional medicinal plants exclusively used for management of inflammation-related ailments by the Khampti community of Arunachal Pradesh, India was based on first-hand field survey work through semi-structured interviews. Results and conclusion: A total of 34 species in 32 genera and 22 families were encountered during the field survey. Botanical families such as Asteraceae, Euphorbiaceae, Zingiberaceae and Lamiaceae were represented by the highest numbers of species reported in this study. Thirteen plant species, namely: Bombax ceiba, Canarium strictum, Chloranthus erectus, Xanthium indicum, Lycopodium clavatum, Coleus blumei, Batrachospermum atrum, Chlorella vulgaris, Marchantia palmata, Marchantia polymorpha, Eria pannea, Sterculia villosa and Alpinia galanga are reported for the first time for the treatment of inflammation-related diseases.

Evaluation of anti-inflammatory potential of Chloranthus erectus (Buch.-Ham.) Verd. leaf extract in rats

Aim of the study: Chloranthus erectus (Buch.-Ham.) Verdcourt (Chloranthaceae) is a shrub native to tropical and temperate zone of Eastern Himalaya of India and South-East Asia and have traditionally been used as a folklore medicine to treat localised swelling, joint pain, skin inflammation, fever and bodyache. In this study, an attempthas been made to demonstrate the anti-inflammatory activity of methanol extract obtained from Chloranthus erectus leaves (MECEL) in acute, sub-acute and chronic mouse models. Materials and methods: Inflammation in the hind paw of Wistar albino rat was induced by carrageenan, histamine and serotonin, and tissue granuloma pouch was induced by cotton pellet method. Antiinflammatory drug-phenylbutazone was used as standard drug for comparison. Results: In acute carrageenan-induced rat hind paw edema, oral administration of MECEL at 200 mg/kg produced significant inhibition of edema by 38.34 % (p<0.01) while the histamine- and serotonin-induced sub-acute model, the inhibition of paw edema reached 52.54 % (p < 0.001) and 25.5 % (p < 0.01), respectively. in a 7-day study, MECEL at 20 and 50 mg/kg produced significant suppression of cotton pellet-induced tissue granuloma formation in rats. Conclusions: This preliminary study revealed that the methanol extract of Chloranthus erectus exhibited significant anti-inflammatory activity in the tested models, and may provide the scientific rationale for its popular folk medicine as anti-inflammatory agent.

Anti-inflammatory activity of the ethanol extract of Dictamnus dasycarpus leaf in lipopolysaccharide-activated macrophages

Background: Dictamnus dasycarpus is widely used as a traditional remedy for the treatment of eczema, rheumatism, and other inflammatory diseases in Asia. The current study investigates the molecular mechanism of anti-inflammatory action of the ethanol extract of Dictamnus dasycarpus leaf (DE) in lipopolysaccharide (LPS)-stimulated RAW 264.7 cells. Methods: Nitric oxide (NO) production was assessed by Griess reaction and the mRNA and protein expressions of pro inflammatory cytokines, transcription factor, and enzymes were determined by real-time RT-PCR and immunoblotting analysis. Results: DE (0.5 and 1 mg/mL) suppressed the NO production by 10 and 33%, respectively, compared to the untreated group in LPS-stimulated RAW 264.7 cells. DE (0.5 and 1 mg/mL) reduced the mRNA expression of key transcription factor nuclear factor-kappa B by 7 and 24%, respectively compared to the untreated group in LPS activated macrophage. The pro inflammatory cytokines such as tumor necrosis factor a and interleukin 1 beta were also decreased by DE treatment. Moreover, the protein expression of pro inflammatory enzymes, inducible nitric oxide synthase and cyclooxygenase 2 were also dramatically attenuated by DE in a dose dependent manner. Conclusions: These results suggest that Dictamnus dasycarpus leaf has a potent anti-inflammatory activity and can be used for the development of new anti-inflammatory agents.

Improved assessment of aerosol absorption using OMI-MODIS joint retrieval

The Ozone Monitoring Instrument (OMI) aboard EOS-Aura and the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard EOS-Aqua fly in formation as part of the A-train. Though OMI retrieves aerosol optical depth (AOD) and aerosol absorption, it must assume aerosol layer height. The MODIS cannot retrieve aerosol absorption, but MODIS aerosol retrieval is not sensitive to aerosol layer height and with its smaller pixel size is less affected by subpixel clouds. Here we demonstrate an approach that uses MODIS-retrieved AOD to constrain the OMI retrieval, freeing OMI from making an a priori estimate of aerosol height and allowing a more direct retrieval of aerosol absorption. To predict near-UV optical depths using MODIS data we rely on the spectral curvature of the MODIS-retrieved visible and near-IR spectral AODs. Application of an OMI-MODIS joint retrieval over the north tropical Atlantic shows good agreement between OMI and MODIS-predicted AODs in the UV, which implies that the aerosol height assumed in the OMI-standard algorithm is probably correct. In contrast, over the Arabian Sea, MODIS-predicted AOD deviated from the OMI-standard retrieval, but combined OMI-MODIS retrievals substantially improved information on aerosol layer height (on the basis of validation against airborne lidar measurements). This implies an improvement in the aerosol absorption retrieval, but lack of UV absorption measurements prevents a true validation. Our study demonstrates the potential of multisatellite analysis of A-train data to improve the accuracy of retrieved aerosol products and suggests that a combined OMI-MODIS-CALIPSO retrieval has large potential to further improve assessments of aerosol absorption.

Influence of Joint Thickness and Mortar-Block Elastic Properties on the Strength and Stresses Developed in Soil-Cement Block Masonry

Soil-cement blocks are employed for load bearing masonry buildings. This paper deals with the study on the influence of bed joint thickness and elastic properties of the soil-cement blocks, and the mortar on the strength and behavior of soil-cement block masonry prisms. Influence of joint thickness on compressive strength has been examined through an experimental program. The nature of stresses developed and their distribution, in the block and the mortar of the soil-cement block masonry prism under compression, has been analyzed by an elastic analysis using FEM. Influence of various parameters like joint thickness, ratio of block to mortar modulus, and Poisson's ratio of the block and the mortar are considered in FEM analysis. Some of the major conclusions of the study are: (1) masonry compressive strength is sensitive to the ratio of modulus of block to that of the mortar (Eb/Em) and masonry compressive strength decreases as the mortar joint thickness is increased for the case where the ratio of block to mortar modulus is more than 1; (2) the lateral tensile stresses developed in the masonry unit are sensitive to the Eb/Em ratio and the Poisson's ratio of mortar and the masonry unit; and (3) lateral stresses developed in the masonry unit are more sensitive to the Poisson's ratio of the mortar than the Poisson's ratio of the masonry unit.

Joint evaluation of multiple speech patterns for speech recognition and training

We are addressing the novel problem of jointly evaluating multiple speech patterns for automatic speech recognition and training. We propose solutions based on both the non-parametric dynamic time warping (DTW) algorithm, and the parametric hidden Markov model (HMM). We show that a hybrid approach is quite effective for the application of noisy speech recognition. We extend the concept to HMM training wherein some patterns may be noisy or distorted. Utilizing the concept of ``virtual pattern'' developed for joint evaluation, we propose selective iterative training of HMMs. Evaluating these algorithms for burst/transient noisy speech and isolated word recognition, significant improvement in recognition accuracy is obtained using the new algorithms over those which do not utilize the joint evaluation strategy.

Temperature independent mixing rules to correlate the solubilities of antibiotics and anti-inflammatory drugs in SCCO2

The accurate experimental determination of the solubilities of antibiotics and anti-inflammatory drugs in supercritical fluids (SCFs) and correlations are essential for the development of supercritical technologies for the pharmaceuticals industry. In this work, the solubilities of penicillinG, penicillinV, flurbiprofen, ketoprofen, naproxen, ibuprofen, aspirin and diflunisal in supercritical carbon dioxide (SCCO2) were correlated using Peng-Robinson equation of state (PR EOS) with the modified Kwak and Mansoori mixing rules (mKM) and with Bartle model. The ability of mKM rules was compared against the conventional mixing rules of van der Waals in correlating the solubilities. In the present model, vapor pressure was considered as an adjustable parameter along with binary interactions parameters. In the proposed model, the constants used in the mixing rule, and vapor pressure expression coefficients are temperature independent. The optimization of these constants with experimental data gives binary interaction parameters along with vapor pressure correlations. Sublimation enthalpies were estimated with both the models compared with literature reported experimental values.

A Joint Source-Channel Coding Scheme for Transmission of Correlated Discrete Sources over a Gaussian Multiple Access Channel

We consider the problem of transmission of correlated discrete alphabet sources over a Gaussian Multiple Access Channel (GMAC). A distributed bit-to-Gaussian mapping is proposed which yields jointly Gaussian codewords. This can guarantee lossless transmission or lossy transmission with given distortions, if possible. The technique can be extended to the system with side information at the encoders and decoder.

An adaptive drug delivery design using neural networks for effective treatment of infectious diseases: A simulation study

An adaptive drug delivery design is presented in this paper using neural networks for effective treatment of infectious diseases. The generic mathematical model used describes the coupled evolution of concentration of pathogens, plasma cells, antibodies and a numerical value that indicates the relative characteristic of a damaged organ due to the disease under the influence of external drugs. From a system theoretic point of view, the external drugs can be interpreted as control inputs, which can be designed based on control theoretic concepts. In this study, assuming a set of nominal parameters in the mathematical model, first a nonlinear controller (drug administration) is designed based on the principle of dynamic inversion. This nominal drug administration plan was found to be effective in curing "nominal model patients" (patients whose immunological dynamics conform to the mathematical model used for the control design exactly. However, it was found to be ineffective in curing "realistic model patients" (patients whose immunological dynamics may have off-nominal parameter values and possibly unwanted inputs) in general. Hence, to make the drug delivery dosage design more effective for realistic model patients, a model-following adaptive control design is carried out next by taking the help of neural networks, that are trained online. Simulation studies indicate that the adaptive controller proposed in this paper holds promise in killing the invading pathogens and healing the damaged organ even in the presence of parameter uncertainties and continued pathogen attack. Note that the computational requirements for computing the control are very minimal and all associated computations (including the training of neural networks) can be carried out online. However it assumes that the required diagnosis process can be carried out at a sufficient faster rate so that all the states are available for control computation.

A Slotted Aloha joint MAC-cum-Routing protocol for data gathering sensor network applications

In this paper we have proposed and implemented a joint Medium Access Control (MAC) -cum- Routing scheme for environment data gathering sensor networks. The design principle uses node 'battery lifetime' maximization to be traded against a network that is capable of tolerating: A known percentage of combined packet losses due to packet collisions, network synchronization mismatch and channel impairments Significant end-to-end delay of an order of few seconds We have achieved this with a loosely synchronized network of sensor nodes that implement Slotted-Aloha MAC state machine together with route information. The scheme has given encouraging results in terms of energy savings compared to other popular implementations. The overall packet loss is about 12%. The battery life time increase compared to B-MAC varies from a minimum of 30% to about 90% depending on the duty cycle.

Distributed joint source channel coding on a multiple access channel with side information

We consider the problem of transmission of several discrete sources over a multiple access channel (MAC) with side information at the sources and the decoder. Source-channel separation does not hold for this channel. Sufficient conditions are provided for transmission of sources with a given distortion. The channel could have continuous alphabets (Gaussian MAC is a special case). Various previous results are obtained as special cases.

Joint decoding of multiple speech patterns for robust speech recognition

We are addressing a new problem of improving automatic speech recognition performance, given multiple utterances of patterns from the same class. We have formulated the problem of jointly decoding K multiple patterns given a single Hidden Markov Model. It is shown that such a solution is possible by aligning the K patterns using the proposed Multi Pattern Dynamic Time Warping algorithm followed by the Constrained Multi Pattern Viterbi Algorithm The new formulation is tested in the context of speaker independent isolated word recognition for both clean and noisy patterns. When 10 percent of speech is affected by a burst noise at -5 dB Signal to Noise Ratio (local), it is shown that joint decoding using only two noisy patterns reduces the noisy speech recognition error rate to about 51 percent, when compared to the single pattern decoding using the Viterbi Algorithm. In contrast a simple maximization of individual pattern likelihoods, provides only about 7 percent reduction in error rate.