This paper presents a robust and dynamic face recognition technique based on the extraction and m... more This paper presents a robust and dynamic face recognition technique based on the extraction and matching of devised probabilistic graphs drawn on SIFT features related to independent face areas. The face matching strategy is based on matching individual salient facial graph characterized by SIFT features as connected to facial landmarks such as the eyes and the mouth. In order to reduce the face matching errors, the Dempster-Shafer decision theory is applied to fuse the individual matching scores obtained from each pair of salient facial features. The proposed algorithm is evaluated with the ORL and the IITK face databases. The experimental results demonstrate the effectiveness and potential of the proposed face recognition technique also in case of partially occluded faces.
Proceedings of SPIE - The International Society for Optical Engineering
This paper presents a feature level fusion approach which uses the improved K-medoids clustering ... more This paper presents a feature level fusion approach which uses the improved K-medoids clustering algorithm and isomorphic graph for face and palmprint biometrics. Partitioning around medoids (PAM) algorithm is used to partition the set of n invariant feature points of the face and palmprint images into k clusters. By partitioning the face and palmprint images with scale invariant features SIFT points, a number of clusters is formed on both the images. Then on each cluster, an isomorphic graph is drawn. In the next step, the most probable pair of graphs is searched using iterative relaxation algorithm from all possible isomorphic graphs for a pair of corresponding face and palmprint images. Finally, graphs are fused by pairing the isomorphic graphs into augmented groups in terms of addition of invariant SIFT points and in terms of combining pair of keypoint descriptors by concatenation rule. Experimental results obtained from the extensive evaluation show that the proposed feature le...
This paper uses Support Vector Machines (SVM) to fuse multiple classifiers for an offline signatu... more This paper uses Support Vector Machines (SVM) to fuse multiple classifiers for an offline signature system. From the signature images, global and local features are extracted and the signatures are verified with the help of Gaussian empirical rule, Euclidean and Mahalanobis distance based classifiers. SVM is used to fuse matching scores of these matchers. Finally, recognition of query signatures is done by comparing it with all signatures of the database. The proposed system is tested on a signature database contains 5400 offline signatures of 600 individuals and the results are found to be promising. Comment: 11 pages, 3 figures, IJSIA 2010
This paper presents an intra-modal fusion environment to integrate multiple raw palm images at lo... more This paper presents an intra-modal fusion environment to integrate multiple raw palm images at low level. Fusion of palmprint instances is performed by wavelet transform and decomposition. To capture the palm characteristics, fused image is convolved with Gabor wavelet transform. The Gabor wavelet feature representation reflects very high dimensional space. To reduce the high dimensionality, ant colony optimization algorithm is applied to select relevant, distinctive and reduced feature set from Gabor responses. Finally, the reduced set of features is trained with support vector machines and accomplished user recognition tasks. For evaluation, CASIA multispectral palmprint database is used. The experimental results reveal that the system is found to be robust and encouraging while variations of classifiers are used. Also a comparative study is presented of the proposed system with a well-known method.
This paper uses Support Vector Machines (SVM) to fuse multiple classifiers for an offline signatu... more This paper uses Support Vector Machines (SVM) to fuse multiple classifiers for an offline signature system. From the signature images, global and local features are extracted and the signatures are verified with the help of Gaussian empirical rule, Euclidean and Mahalanobis distance based classifiers. SVM is used to fuse matching scores of these matchers. Finally, recognition of query signatures is done by comparing it with all signatures of the database. The proposed system is tested on a signature database contains 5400 offline signatures of 600 individuals and the results are found to be promising. Comment: 8 pages, 2 figures
Biometric systems are considered as human pattern recognition systems that can be used for indivi... more Biometric systems are considered as human pattern recognition systems that can be used for individual identification and verification. The decision on the authenticity is done with the help of some specific measurable physiological or behavioral characteristics possessed by the individuals. Robust architecture of any biometric system provides very good performance of the system against rotation, translation, scaling effect and deformation of the image on the image plane. Further, there is a need of development of real-time biometric system. There exist many graph matching techniques used to design robust and real-time biometrics systems. This paper discusses two graph matching techniques that have been successfully used in face biometric traits.
This paper presents a multimodal biometric system of fingerprint and ear biometrics. Scale Invari... more This paper presents a multimodal biometric system of fingerprint and ear biometrics. Scale Invariant Feature Transform (SIFT) descriptor based feature sets extracted from fingerprint and ear are fused. The fused set is encoded by K-medoids partitioning approach with less number of feature points in the set. K-medoids partition the whole dataset into clusters to minimize the error between data points belonging to the clusters and its center. Reduced feature set is used to match between two biometric sets. Matching scores are generated using wolf-lamb user-dependent feature weighting scheme introduced by Doddington. The technique is tested to exhibit its robust performance. Comment: 8 pages, 3 figures
Proceedings of SPIE - The International Society for Optical Engineering
This paper proposes a robust ear identification system which is developed by fusing SIFT features... more This paper proposes a robust ear identification system which is developed by fusing SIFT features of color segmented slice regions of an ear. The proposed ear identification method makes use of Gaussian mixture model (GMM) to build ear model with mixture of Gaussian using vector quantization algorithm and K-L divergence is applied to the GMM framework for recording the color similarity in the specified ranges by comparing color similarity between a pair of reference ear and probe ear. SIFT features are then detected and extracted from each color slice region as a part of invariant feature extraction. The extracted keypoints are then fused separately by the two fusion approaches, namely concatenation and the Dempster-Shafer theory. Finally, the fusion approaches generate two independent augmented feature vectors which are used for identification of individuals separately. The proposed identification technique is tested on IIT Kanpur ear database of 400 individuals and is found to ach...
This paper presents multi-appearance fusion of Principal Component Analysis (PCA) and generalizat... more This paper presents multi-appearance fusion of Principal Component Analysis (PCA) and generalization of Linear Discriminant Analysis (LDA) for multi-camera view offline face recognition (verification) system. The generalization of LDA has been extended to establish correlations between the face classes in the transformed representation and this is called canonical covariate. The proposed system uses Gabor filter banks for characterization of facial features by spatial frequency, spatial locality and orientation to make compensate to the variations of face instances occurred due to illumination, pose and facial expression changes. Convolution of Gabor filter bank to face images produces Gabor face representations with high dimensional feature vectors. PCA and canonical covariate are then applied on the Gabor face representations to reduce the high dimensional feature spaces into low dimensional Gabor eigenfaces and Gabor canonical faces. Reduced eigenface vector and canonical face ve...
This chapter presents a robust face recognition technique which is based on the extraction of Sca... more This chapter presents a robust face recognition technique which is based on the extraction of Scale Invariant Feature Transform (SIFT) features from the face areas. It uses both a global and local matching strategy. The local strategy is based on matching individual salient facial SIFT features as connected to facial landmarks such as the eyes and the mouth. As for the global matching strategy, all SIFT features are combined together to form a single feature. The Dempster–Shafer decision theory is applied to fuse the two matching strategies. The proposed technique has been evaluated with the Indian Institute of Technology Kanpur (IITK), Olivetti Research Laboratory (ORL) (formerly known as AT&T face database), and the Yale face databases. The experimental results demonstrate the effectiveness and potential of the proposed face recognition technique also in cases of partially occluded faces or with missing information. Besides this, some state-of-the-art face recognition techniques h...
This paper proposes a multimodal biometric system through Gaussian Mixture Model (GMM) for face a... more This paper proposes a multimodal biometric system through Gaussian Mixture Model (GMM) for face and ear biometrics with belief fusion of the estimated scores characterized by Gabor responses and the proposed fusion is accomplished by Dempster-Shafer (DS) decision theory. Face and ear images are convolved with Gabor wavelet filters to extracts spatially enhanced Gabor facial features and Gabor ear features. Further, GMM is applied to the high-dimensional Gabor face and Gabor ear responses separately for quantitive measurements. Expectation Maximization (EM) algorithm is used to estimate density parameters in GMM. This produces two sets of feature vectors which are then fused using Dempster-Shafer theory. Experiments are conducted on multimodal database containing face and ear images of 400 individuals. It is found that use of Gabor wavelet filters along with GMM and DS theory can provide robust and efficient multimodal fusion strategy.
Ear biometric is considered as one of the most reliable and invariant biometrics characteristics ... more Ear biometric is considered as one of the most reliable and invariant biometrics characteristics in line with iris and fingerprint characteristics. In many cases, ear biometrics can be compared with face biometrics regarding many physiological and texture characteristics. In this paper, a robust and efficient ear recognition system is presented, which uses Scale Invariant Feature Transform (SIFT) as feature descriptor for structural representation of ear images. In order to make it more robust to user authentication, only the regions having color probabilities in a certain ranges are considered for invariant SIFT feature extraction, where the K-L divergence is used for keeping color consistency. Ear skin color model is formed by Gaussian mixture model and clustering the ear color pattern using vector quantization. Finally, K-L divergence is applied to the GMM framework for recording the color similarity in the specified ranges by comparing color similarity between a pair of referenc...
Faces are highly deformable objects which may easily change their appearance over time. Not all f... more Faces are highly deformable objects which may easily change their appearance over time. Not all face areas are subject to the same variability. Therefore, decoupling of the information from independent areas of the face is of paramount importance to improve the robustness of any face recognition technique. The aim of this article is to present a robust face recognition technique based on the extraction and matching of probabilistic graphs drawn on scale invariant feature transform (SIFT) features related to independent face areas. The face matching strategy is based on matching individual salient facial graphs characterized by SIFT features as connected to facial landmarks such as the eyes and the mouth. In order to reduce the face matching errors, the Dempster–Shafer decision theory is applied to fuse the individual matching scores obtained from each pair of salient facial features. The proposed algorithm is evaluated with the Olivetti Research Lab (ORL) and the Indian Institute of...
RC-101, a cationic peptide retrocyclin analog, has in vitro activity against HIV-1. Peptide drugs... more RC-101, a cationic peptide retrocyclin analog, has in vitro activity against HIV-1. Peptide drugs are commonly prone to conformational changes, oxidation and hydrolysis when exposed to excipients in a formulation or biological fluids in the body, this can affect product efficacy. We aimed to investigate RC-101 stability under several conditions including the presence of human vaginal fluids (HVF), enabling the efficient design of a safe and effective microbicide product. Stability studies (temperature, pH, and oxidation) were performed by HPLC, Circular Dichroism, and Mass Spectrometry (LC-MS/MS). Additionally, the effect of HVF on formulated RC-101 was evaluated with fluids collected from healthy volunteers, or from subjects with bacterial vaginosis (BV). RC-101 was monitored by LC-MS/MS for up to 72 h. RC-101 was stable at pH 3, 4, and 7, at 25 and 37°C. High concentrations of hydrogen peroxide resulted in less than 10% RC-101 reduction over 24 h. RC-101 was detected 48 h after in...
The feasibility of using a liposome drug delivery system to formulate octylglycerol (OG) as a vag... more The feasibility of using a liposome drug delivery system to formulate octylglycerol (OG) as a vaginal microbicide product was explored. A liposome formulation was developed containing 1% OG and phosphatidyl choline in a ratio that demonstrated in vitro activity against Neisseria gonorrhoeae, HSV-1, HSV-2 and HIV-1 while sparing the innate vaginal flora, Lactobacillus. Two conventional gel formulations were prepared for comparison. The OG liposome formulation with the appropriate OG/lipid ratio and dosing level had greater efficacy than either conventional gel formulation and maintained this efficacy for at least 2 months. No toxicity was observed for the liposome formulation in ex vivo testing in a human ectocervical tissue model or in vivo testing in the macaque safety model. Furthermore, minimal toxicity was observed to lactobacilli in vitro or in vivo safety testing. The OG liposome formulation offers a promising microbicide product with efficacy against HSV, HIV and N. gonorrhoeae.
HIV/HCV co-infection provides a model to determine the role of immunity on HCV transmission and e... more HIV/HCV co-infection provides a model to determine the role of immunity on HCV transmission and evolution. In this study HCV transmission and evolution were evaluated in 6 HCV seroconverters in HIV-infected subjects with a wide range of CD4 cell count. The HCV envelope E1/E2 sequences were analyzed for transmission bottleneck, viral diversity/divergence, immune pressure, and mutations of HLA class I/II restricted epitopes. HCV infection started with transmission bottleneck in all HIV-infected individuals. During the 1.0–2.0 years of infection there was a shift of viral quasispecies in majority of the subjects from one to next visit. However, HCV diversity, divergence, mutations in HLA class I/II restricted and virus neutralizing epitopes were similar in all subjects regardless of CD4 cell count at the time of HCV infection. Our results suggest that HCV transmission and evolution in HIV-infected subjects may not be influenced by host CD4 cell count at the time of infection.
Clostridium perfringens type C isolates, which cause enteritis necroticans in humans and enteriti... more Clostridium perfringens type C isolates, which cause enteritis necroticans in humans and enteritis and enterotoxaemias of domestic animals, typically produce (at minimum) beta toxin (CPB), alpha toxin (CPA) and perfringolysin O (PFO) during log-phase growth. To assist development of improved vaccines and therapeutics, we evaluated the contribution of these three toxins to the intestinal virulence of type C disease isolate CN3685. Similar to natural type C infection, log-phase vegetative cultures of wild-type CN3685 caused haemorrhagic necrotizing enteritis in rabbit ileal loops. When isogenic toxin null mutants were prepared using TargeTron ® technology, even a double cpa/pfoA null mutant of CN3685 remained virulent in ileal loops. However, two independent cpb null mutants were completely attenuated for virulence in this animal model. Complementation of a cpb mutant restored its CPB production and intestinal virulence. Additionally, pre-incubation of wild-type CN3685 with a CPB-neutralizing monoclonal antibody rendered the strain avirulent for causing intestinal pathology. Finally, highly purified CPB reproduced the intestinal damage of wild-type CN3685 and that damage was prevented by pre-incubating purified CPB with a CPB monoclonal antibody. These results indicate that CPB is both required and sufficient for CN3685-induced enteric pathology, supporting a key role for this toxin in type C intestinal pathogenesis. , 15-30 agarose gel was then transferred onto a nylon membrane and hybridized with an intron-specific DIG-labelled probe. Lane 1: Wild-type CN3685; lane 2: BMC100; lane 3: BMC101; lane 4: BMC102; and lane 5: BMC103.
Replication ofvif-negative human immunodeficiency virus type 1 (HIV-1) is attenuated in certain c... more Replication ofvif-negative human immunodeficiency virus type 1 (HIV-1) is attenuated in certain cell lines and highly impaired in peripheral blood lymphocytes in vitro. To determine whether intact vif is positively selected during natural HIV-1 infection and to determinevifsequence variability, we employed PCR amplifi- cation, cloning, and sequencing to investigate thevifregion of replicating virus in short-term-passage HIV-1 primary isolates fromfive asymptomatic
This paper presents a robust and dynamic face recognition technique based on the extraction and m... more This paper presents a robust and dynamic face recognition technique based on the extraction and matching of devised probabilistic graphs drawn on SIFT features related to independent face areas. The face matching strategy is based on matching individual salient facial graph characterized by SIFT features as connected to facial landmarks such as the eyes and the mouth. In order to reduce the face matching errors, the Dempster-Shafer decision theory is applied to fuse the individual matching scores obtained from each pair of salient facial features. The proposed algorithm is evaluated with the ORL and the IITK face databases. The experimental results demonstrate the effectiveness and potential of the proposed face recognition technique also in case of partially occluded faces.
Proceedings of SPIE - The International Society for Optical Engineering
This paper presents a feature level fusion approach which uses the improved K-medoids clustering ... more This paper presents a feature level fusion approach which uses the improved K-medoids clustering algorithm and isomorphic graph for face and palmprint biometrics. Partitioning around medoids (PAM) algorithm is used to partition the set of n invariant feature points of the face and palmprint images into k clusters. By partitioning the face and palmprint images with scale invariant features SIFT points, a number of clusters is formed on both the images. Then on each cluster, an isomorphic graph is drawn. In the next step, the most probable pair of graphs is searched using iterative relaxation algorithm from all possible isomorphic graphs for a pair of corresponding face and palmprint images. Finally, graphs are fused by pairing the isomorphic graphs into augmented groups in terms of addition of invariant SIFT points and in terms of combining pair of keypoint descriptors by concatenation rule. Experimental results obtained from the extensive evaluation show that the proposed feature le...
This paper uses Support Vector Machines (SVM) to fuse multiple classifiers for an offline signatu... more This paper uses Support Vector Machines (SVM) to fuse multiple classifiers for an offline signature system. From the signature images, global and local features are extracted and the signatures are verified with the help of Gaussian empirical rule, Euclidean and Mahalanobis distance based classifiers. SVM is used to fuse matching scores of these matchers. Finally, recognition of query signatures is done by comparing it with all signatures of the database. The proposed system is tested on a signature database contains 5400 offline signatures of 600 individuals and the results are found to be promising. Comment: 11 pages, 3 figures, IJSIA 2010
This paper presents an intra-modal fusion environment to integrate multiple raw palm images at lo... more This paper presents an intra-modal fusion environment to integrate multiple raw palm images at low level. Fusion of palmprint instances is performed by wavelet transform and decomposition. To capture the palm characteristics, fused image is convolved with Gabor wavelet transform. The Gabor wavelet feature representation reflects very high dimensional space. To reduce the high dimensionality, ant colony optimization algorithm is applied to select relevant, distinctive and reduced feature set from Gabor responses. Finally, the reduced set of features is trained with support vector machines and accomplished user recognition tasks. For evaluation, CASIA multispectral palmprint database is used. The experimental results reveal that the system is found to be robust and encouraging while variations of classifiers are used. Also a comparative study is presented of the proposed system with a well-known method.
This paper uses Support Vector Machines (SVM) to fuse multiple classifiers for an offline signatu... more This paper uses Support Vector Machines (SVM) to fuse multiple classifiers for an offline signature system. From the signature images, global and local features are extracted and the signatures are verified with the help of Gaussian empirical rule, Euclidean and Mahalanobis distance based classifiers. SVM is used to fuse matching scores of these matchers. Finally, recognition of query signatures is done by comparing it with all signatures of the database. The proposed system is tested on a signature database contains 5400 offline signatures of 600 individuals and the results are found to be promising. Comment: 8 pages, 2 figures
Biometric systems are considered as human pattern recognition systems that can be used for indivi... more Biometric systems are considered as human pattern recognition systems that can be used for individual identification and verification. The decision on the authenticity is done with the help of some specific measurable physiological or behavioral characteristics possessed by the individuals. Robust architecture of any biometric system provides very good performance of the system against rotation, translation, scaling effect and deformation of the image on the image plane. Further, there is a need of development of real-time biometric system. There exist many graph matching techniques used to design robust and real-time biometrics systems. This paper discusses two graph matching techniques that have been successfully used in face biometric traits.
This paper presents a multimodal biometric system of fingerprint and ear biometrics. Scale Invari... more This paper presents a multimodal biometric system of fingerprint and ear biometrics. Scale Invariant Feature Transform (SIFT) descriptor based feature sets extracted from fingerprint and ear are fused. The fused set is encoded by K-medoids partitioning approach with less number of feature points in the set. K-medoids partition the whole dataset into clusters to minimize the error between data points belonging to the clusters and its center. Reduced feature set is used to match between two biometric sets. Matching scores are generated using wolf-lamb user-dependent feature weighting scheme introduced by Doddington. The technique is tested to exhibit its robust performance. Comment: 8 pages, 3 figures
Proceedings of SPIE - The International Society for Optical Engineering
This paper proposes a robust ear identification system which is developed by fusing SIFT features... more This paper proposes a robust ear identification system which is developed by fusing SIFT features of color segmented slice regions of an ear. The proposed ear identification method makes use of Gaussian mixture model (GMM) to build ear model with mixture of Gaussian using vector quantization algorithm and K-L divergence is applied to the GMM framework for recording the color similarity in the specified ranges by comparing color similarity between a pair of reference ear and probe ear. SIFT features are then detected and extracted from each color slice region as a part of invariant feature extraction. The extracted keypoints are then fused separately by the two fusion approaches, namely concatenation and the Dempster-Shafer theory. Finally, the fusion approaches generate two independent augmented feature vectors which are used for identification of individuals separately. The proposed identification technique is tested on IIT Kanpur ear database of 400 individuals and is found to ach...
This paper presents multi-appearance fusion of Principal Component Analysis (PCA) and generalizat... more This paper presents multi-appearance fusion of Principal Component Analysis (PCA) and generalization of Linear Discriminant Analysis (LDA) for multi-camera view offline face recognition (verification) system. The generalization of LDA has been extended to establish correlations between the face classes in the transformed representation and this is called canonical covariate. The proposed system uses Gabor filter banks for characterization of facial features by spatial frequency, spatial locality and orientation to make compensate to the variations of face instances occurred due to illumination, pose and facial expression changes. Convolution of Gabor filter bank to face images produces Gabor face representations with high dimensional feature vectors. PCA and canonical covariate are then applied on the Gabor face representations to reduce the high dimensional feature spaces into low dimensional Gabor eigenfaces and Gabor canonical faces. Reduced eigenface vector and canonical face ve...
This chapter presents a robust face recognition technique which is based on the extraction of Sca... more This chapter presents a robust face recognition technique which is based on the extraction of Scale Invariant Feature Transform (SIFT) features from the face areas. It uses both a global and local matching strategy. The local strategy is based on matching individual salient facial SIFT features as connected to facial landmarks such as the eyes and the mouth. As for the global matching strategy, all SIFT features are combined together to form a single feature. The Dempster–Shafer decision theory is applied to fuse the two matching strategies. The proposed technique has been evaluated with the Indian Institute of Technology Kanpur (IITK), Olivetti Research Laboratory (ORL) (formerly known as AT&T face database), and the Yale face databases. The experimental results demonstrate the effectiveness and potential of the proposed face recognition technique also in cases of partially occluded faces or with missing information. Besides this, some state-of-the-art face recognition techniques h...
This paper proposes a multimodal biometric system through Gaussian Mixture Model (GMM) for face a... more This paper proposes a multimodal biometric system through Gaussian Mixture Model (GMM) for face and ear biometrics with belief fusion of the estimated scores characterized by Gabor responses and the proposed fusion is accomplished by Dempster-Shafer (DS) decision theory. Face and ear images are convolved with Gabor wavelet filters to extracts spatially enhanced Gabor facial features and Gabor ear features. Further, GMM is applied to the high-dimensional Gabor face and Gabor ear responses separately for quantitive measurements. Expectation Maximization (EM) algorithm is used to estimate density parameters in GMM. This produces two sets of feature vectors which are then fused using Dempster-Shafer theory. Experiments are conducted on multimodal database containing face and ear images of 400 individuals. It is found that use of Gabor wavelet filters along with GMM and DS theory can provide robust and efficient multimodal fusion strategy.
Ear biometric is considered as one of the most reliable and invariant biometrics characteristics ... more Ear biometric is considered as one of the most reliable and invariant biometrics characteristics in line with iris and fingerprint characteristics. In many cases, ear biometrics can be compared with face biometrics regarding many physiological and texture characteristics. In this paper, a robust and efficient ear recognition system is presented, which uses Scale Invariant Feature Transform (SIFT) as feature descriptor for structural representation of ear images. In order to make it more robust to user authentication, only the regions having color probabilities in a certain ranges are considered for invariant SIFT feature extraction, where the K-L divergence is used for keeping color consistency. Ear skin color model is formed by Gaussian mixture model and clustering the ear color pattern using vector quantization. Finally, K-L divergence is applied to the GMM framework for recording the color similarity in the specified ranges by comparing color similarity between a pair of referenc...
Faces are highly deformable objects which may easily change their appearance over time. Not all f... more Faces are highly deformable objects which may easily change their appearance over time. Not all face areas are subject to the same variability. Therefore, decoupling of the information from independent areas of the face is of paramount importance to improve the robustness of any face recognition technique. The aim of this article is to present a robust face recognition technique based on the extraction and matching of probabilistic graphs drawn on scale invariant feature transform (SIFT) features related to independent face areas. The face matching strategy is based on matching individual salient facial graphs characterized by SIFT features as connected to facial landmarks such as the eyes and the mouth. In order to reduce the face matching errors, the Dempster–Shafer decision theory is applied to fuse the individual matching scores obtained from each pair of salient facial features. The proposed algorithm is evaluated with the Olivetti Research Lab (ORL) and the Indian Institute of...
RC-101, a cationic peptide retrocyclin analog, has in vitro activity against HIV-1. Peptide drugs... more RC-101, a cationic peptide retrocyclin analog, has in vitro activity against HIV-1. Peptide drugs are commonly prone to conformational changes, oxidation and hydrolysis when exposed to excipients in a formulation or biological fluids in the body, this can affect product efficacy. We aimed to investigate RC-101 stability under several conditions including the presence of human vaginal fluids (HVF), enabling the efficient design of a safe and effective microbicide product. Stability studies (temperature, pH, and oxidation) were performed by HPLC, Circular Dichroism, and Mass Spectrometry (LC-MS/MS). Additionally, the effect of HVF on formulated RC-101 was evaluated with fluids collected from healthy volunteers, or from subjects with bacterial vaginosis (BV). RC-101 was monitored by LC-MS/MS for up to 72 h. RC-101 was stable at pH 3, 4, and 7, at 25 and 37°C. High concentrations of hydrogen peroxide resulted in less than 10% RC-101 reduction over 24 h. RC-101 was detected 48 h after in...
The feasibility of using a liposome drug delivery system to formulate octylglycerol (OG) as a vag... more The feasibility of using a liposome drug delivery system to formulate octylglycerol (OG) as a vaginal microbicide product was explored. A liposome formulation was developed containing 1% OG and phosphatidyl choline in a ratio that demonstrated in vitro activity against Neisseria gonorrhoeae, HSV-1, HSV-2 and HIV-1 while sparing the innate vaginal flora, Lactobacillus. Two conventional gel formulations were prepared for comparison. The OG liposome formulation with the appropriate OG/lipid ratio and dosing level had greater efficacy than either conventional gel formulation and maintained this efficacy for at least 2 months. No toxicity was observed for the liposome formulation in ex vivo testing in a human ectocervical tissue model or in vivo testing in the macaque safety model. Furthermore, minimal toxicity was observed to lactobacilli in vitro or in vivo safety testing. The OG liposome formulation offers a promising microbicide product with efficacy against HSV, HIV and N. gonorrhoeae.
HIV/HCV co-infection provides a model to determine the role of immunity on HCV transmission and e... more HIV/HCV co-infection provides a model to determine the role of immunity on HCV transmission and evolution. In this study HCV transmission and evolution were evaluated in 6 HCV seroconverters in HIV-infected subjects with a wide range of CD4 cell count. The HCV envelope E1/E2 sequences were analyzed for transmission bottleneck, viral diversity/divergence, immune pressure, and mutations of HLA class I/II restricted epitopes. HCV infection started with transmission bottleneck in all HIV-infected individuals. During the 1.0–2.0 years of infection there was a shift of viral quasispecies in majority of the subjects from one to next visit. However, HCV diversity, divergence, mutations in HLA class I/II restricted and virus neutralizing epitopes were similar in all subjects regardless of CD4 cell count at the time of HCV infection. Our results suggest that HCV transmission and evolution in HIV-infected subjects may not be influenced by host CD4 cell count at the time of infection.
Clostridium perfringens type C isolates, which cause enteritis necroticans in humans and enteriti... more Clostridium perfringens type C isolates, which cause enteritis necroticans in humans and enteritis and enterotoxaemias of domestic animals, typically produce (at minimum) beta toxin (CPB), alpha toxin (CPA) and perfringolysin O (PFO) during log-phase growth. To assist development of improved vaccines and therapeutics, we evaluated the contribution of these three toxins to the intestinal virulence of type C disease isolate CN3685. Similar to natural type C infection, log-phase vegetative cultures of wild-type CN3685 caused haemorrhagic necrotizing enteritis in rabbit ileal loops. When isogenic toxin null mutants were prepared using TargeTron ® technology, even a double cpa/pfoA null mutant of CN3685 remained virulent in ileal loops. However, two independent cpb null mutants were completely attenuated for virulence in this animal model. Complementation of a cpb mutant restored its CPB production and intestinal virulence. Additionally, pre-incubation of wild-type CN3685 with a CPB-neutralizing monoclonal antibody rendered the strain avirulent for causing intestinal pathology. Finally, highly purified CPB reproduced the intestinal damage of wild-type CN3685 and that damage was prevented by pre-incubating purified CPB with a CPB monoclonal antibody. These results indicate that CPB is both required and sufficient for CN3685-induced enteric pathology, supporting a key role for this toxin in type C intestinal pathogenesis. , 15-30 agarose gel was then transferred onto a nylon membrane and hybridized with an intron-specific DIG-labelled probe. Lane 1: Wild-type CN3685; lane 2: BMC100; lane 3: BMC101; lane 4: BMC102; and lane 5: BMC103.
Replication ofvif-negative human immunodeficiency virus type 1 (HIV-1) is attenuated in certain c... more Replication ofvif-negative human immunodeficiency virus type 1 (HIV-1) is attenuated in certain cell lines and highly impaired in peripheral blood lymphocytes in vitro. To determine whether intact vif is positively selected during natural HIV-1 infection and to determinevifsequence variability, we employed PCR amplifi- cation, cloning, and sequencing to investigate thevifregion of replicating virus in short-term-passage HIV-1 primary isolates fromfive asymptomatic
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Papers by Phalguni Gupta