Empirical evidence of effects of stringency amid Covid-19 pandemic spread

The objective of this paper is to provide an insight on effect of stringency in Covid-19 spread in India especially in Chennai, a city were more lockdown, and restrictions was imposed to control the infection. Even though the restriction was imposed in the country by the end of March 2020, the growth reduction was seen in the mid of June as the awareness was increased. The average Covid-19 case growth was got reduce from 3.43 to 2.62% by July mid. To analysis the impact of stringency, a detailed analysis was done on Chennai city which was imposed with more repeated lockdowns to flatten the curve. We tried to fit a regression line with three difference scenario of data. The results show a promising R-squared and p value, with a right skewed distribution normal probability plot. The impact of lockdown in people's lives in different sectors were also discussed in this paper.

Using Technology to Overcome the Challenges of COVID-19 Pandemic in India: The DEMCARES Model of Virtual Intervention Delivery

BACKGROUND

The COVID-19 pandemic and associated restrictions have greatly affected the delivery of treatment and access to in-person interventions for dementia, especially in low- and middle-income countries such as India. Technology use could potentially help bring the above-mentioned services to persons with dementia (PwD) and their caregivers in the safety of their homes. The aim of this study is to evaluate the dementia care services delivered by the Dementia Care in SCARF (DEMCARES) team in the densely populated city of Chennai in South India during the COVID-19 pandemic.

METHODS

We reviewed teleconsultation logs, records of dementia-related services and interventions offered to both PwD and their caregivers at the DEMCARES clinic between July 2020 and December 2021 during the COVID-19 pandemic. Moreover, we collected feedback from PwD and caregivers regarding virtually delivered dementia interventions and analyzed them to understand benefits, barriers, and facilitators.

RESULTS

In addition to in-person outpatient clinic, teleconsultation for PwD and behavioral and psychological symptoms of dementia management training for caregivers through audio/videoconferencing was provided to those with access to technology. Interventions, such as STrAtegies for RelaTives (START) and Cognitive Stimulation Therapy (CST) that were originally delivered face-to-face, were adapted for virtual delivery to cater to the needs of persons with dementia and their caregivers in Chennai, India. Furthermore, dementia awareness course for caregivers and caregiver support groups were also conducted online. Feedback from PwD and their caregivers were largely positive, and the numbers reached were higher during the pandemic than before.

CONCLUSION

Being situated in an urban setting, the DEMCARES team of professionals were able to reach many PwD and their caregivers who had access to technology. Despite some of its limitations, technology holds a great potential for providing uninterrupted treatment and interventions for dementia in addition to considerably improving access to care, especially during the pandemic.

A Statistical Non-Parametric data analysis for COVID-19 incidence data

BACKGROUND

The impact of COVID-19 on the Global scale is tremendously drastic. There are several types of research going on across the world simultaneously to understand and overcome this dire pandemic outbreak. This paper is purely a statistical study on a distinct set of datasets regarding COVID-19 in India. The motivation of this study is to provide an insight into the rapid growth of confirmed COVID-19 cases in India.

METHODS

The rapid growth of COVID-19 cases in India started in March 2020. The main objective of this paper is to provide a solid statistical model for the policymaker to handle this kind of pandemic situation in the near future with nonlinear data. In this paper, the data was got from 1st April to 29th November 2020. To come up with a solid statistical model, various nonlinear data such as confirmed COVID-19 cases, maximum temperature, minimum temperature, the total population (state-wise), the total area in km2 (state-wise), and the total rural and urban population count (state-wise) have been analyzed. In this paper, six different Generalized Additive Models (GAM) was identified after a thorough analysis of other researchers' (Xie and Zhu, 2020; Prata et al., 2020) findings.

RESULTS

In all perspectives, the results were identified and analyzed. The GAM model regarding total COVID-19 confirmed cases, total population, and the total rural population provides the best average fit of R2 value of 0.934. As the population value is quite high, the author has concise it using logarithm to provide the best p-value of 0.000542 and 0.001407 for a relation between the total number of COVID-19 cases regarding the total population and total rural population respectively.

Cultural adaptation of Alzheimer's disease assessment scale-cognitive subscale for use in India and validation of the Tamil version for South Indian population

OBJECTIVE

Currently no standardized tools are available in the Indian languages to assess changes in cognition. Our objectives are to culturally adapt the Alzheimer's disease Assessment Scale-Cognitive Subscale (ADAS-Cog) for use in India and to validate the Tamil version in an urban Tamil-speaking older adult population.

METHODS

Two panels of key stakeholders and a series of qualitative interviews informed the cultural and linguistic adaptation of the ADAS-Cog-Tamil. Issues related to levels of literacy were considered during the adaptation. Validation of the ADAS-Cog-Tamil was completed with 107 participants - 54 cases with a confirmed diagnosis of mild-moderate dementia, and 53 age, gender and education matched controls. Concurrent validity was examined with the Vellore Screening Instrument for Dementia (VSID) in Tamil. Internal consistency using Cronbach's alpha, sensitivity and specificity data using the Area under the Receiver Operating Characteristics (AUROC) curve values were computed. Inter-rater reliability was established in a subsample.

RESULTS

The ADAS-Cog-Tamil shows good internal consistency (α = 0.91), inter-rater reliability and concurrent validity (with VSID-Patient version: r = -0.84 and with VSID-Caregiver version: r = -0.79). A cut-off score of 13, has a specificity of 89% and sensitivity of 90% for the diagnosis of dementia.

CONCLUSION

ADAS-Cog-Tamil, derived from a rigorous, replicable linguistic and cultural adaptation process involving service users and experts, shows good psychometric properties despite the limitations of the study. It shows potential for use in clinical settings with urban Tamil speaking populations. The English version of the tool derived from the cultural adaptation process could be used for further linguistic adaptation across South Asia.

Network attack classification using LSTM with XGBoost feature selection

The evolving new and modern technologies raise the risks in the network which will be affected by several attacks and thus give rise to developing efficient network attack detection and classification methods. Here in this article for predicting and classifying the network attacks, the LSTM neural network with XGBoost is suggested in which the NSL-KDD dataset was utilized to train the LSTM in the study. In the beginning, the unnecessary data and the noisy data will be eliminated using the dataset and the feature subset with the most compelling features will be selected using the feature selection. By utilizing the essential data, the proposed system will be trained and the training parameter values will be modified for maximizing the functionality of the proposed system. Then, the result of the proposed system will be evaluated with some of the existing machine learning and deep learning algorithms such as SVM, LR, RF, DNN, and CNN with the performance metrics like Accuracy, F1 score, Recall, and Precision. It was found that the proposed model outperforms better than the other algorithms as this model is trained with the most important features and due to this, the training time and overfitting of the learning model was reduced thereby increasing the model effectiveness

Missing data imputation on biomedical data using deeply learned clustering and L2 regularized regression based on symmetric uncertainty

Big data era in healthcare led to the generation of high dimensional datasets like genomic datasets, electronic health records etc. One among the critical issues to be addressed in such datasets is handling incomplete data that may yield misleading results if not handled properly. Imputation is considered to be an effective way when the missing data rate is high. While imputation accuracy and classification accuracy are the two important metrics generally considered by most of the imputation techniques, high dimensional datasets such as genomic datasets motivated the need for imputation techniques that are also computationally efficient and preserves the structure of the dataset. This paper proposes a novel approach to missing data imputation in biomedical datasets using an ensemble of deeply learned clustering and L2 regularized regression based on symmetric uncertainty. The experiments are conducted with different proportion of missing data on both genomic and non-genomic biomedical datasets for different types of missingness pattern. Our proposed approach is compared with seven proven baseline imputation methods and two recently proposed imputation approaches. The results show that the proposed approach outperforms the other approaches considered in our experimentation in terms of imputation accuracy and computational efficiency despite preserving the structure of the dataset. Thus, the overall classification accuracy of the biomedical classification tasks is also improved when our proposed missing data imputation technique is used.

A hybrid feature selection model based on improved squirrel search algorithm and rank aggregation using fuzzy techniques for biomedical data classification

Feature selection has gained its importance due to the voluminous nature of the data. Owing to the computational complexity of wrapper approaches, the poor performance of filtering techniques, and the classifier dependency of embedded approaches, hybrid approaches are more commonly used in feature selection. Hybrid approaches use filtering metrics to reduce the computational complexity of wrapper algorithms and are proved to yield better feature subset. Though filtering metrics select the features based on their significance, most of them are unstable and biased towards the metric used. Moreover, the choice of filtering metrics depends largely on the distribution of data and data types. Biomedical datasets contain features with different distribution and types adding to the complexity in the choice of filtering metric. We address this problem by proposing a stable filtering method based on rank aggregation in hybrid feature selection model with Improved Squirrel search algorithm for biomedical datasets. Our proposed model is compared with other well-known and state-of-the-art methods and the results prove that our model exhibited superior performance in terms of classification accuracy and computational time. The robustness of our proposed model is proved by conducting experiments on nine biomedical datasets and with three different classifiers.

Patient and Public Involvement for Dementia Research in Low- and Middle-Income Countries: Developing Capacity and Capability in South Asia

Background: Patient and public involvement (PPI) is an active partnership between the public and researchers in the research process. In dementia research, PPI ensures that the perspectives of the person with "lived experience" of dementia are considered. To date, in many lower- and middle-income countries (LMIC), where dementia research is still developing, PPI is not well-known nor regularly undertaken. Thus, here, we describe PPI activities undertaken in seven research sites across South Asia as exemplars of introducing PPI into dementia research for the first time. Objective: Through a range of PPI exemplar activities, our objectives were to: (1) inform the feasibility of a dementia-related study; and (2) develop capacity and capability for PPI for dementia research in South Asia. Methods: Our approach had two parts. Part 1 involved co-developing new PPI groups at seven clinical research sites in India, Pakistan and Bangladesh to undertake different PPI activities. Mapping onto different "rings" of the Wellcome Trust's "Public Engagement Onion" model. The PPI activities included planning for public engagement events, consultation on the study protocol and conduct, the adaptation of a study screening checklist, development and delivery of dementia training for professionals, and a dementia training programme for public contributors. Part 2 involved an online survey with local researchers to gain insight on their experience of applying PPI in dementia research. Results: Overall, capacity and capability to include PPI in dementia research was significantly enhanced across the sites. Researchers reported that engaging in PPI activities had enhanced their understanding of dementia research and increased the meaningfulness of the work. Moreover, each site reported their own PPI activity-related outcomes, including: (1) changes in attitudes and behavior to dementia and research involvement; (2) best methods to inform participants about the dementia study; (3) increased opportunities to share knowledge and study outcomes; and (4) adaptations to the study protocol through co-production. Conclusions: Introducing PPI for dementia research in LMIC settings, using a range of activity types is important for meaningful and impactful dementia research. To our knowledge, this is the first example of PPI for dementia research in South Asia.

Molecular characterization of Orf virus isolates from Kodai hills, Tamil Nadu, India

Aim:

The present study was carried out to find out the causative agent of exanthematous skin lesions in sheep maintained by Southern Regional Research Centre, Mannavanur, Kodai hills, Tamil Nadu.

Materials and Methods:

Polymerase chain reaction (PCR) with Orf virus (ORFV) B2L gene-specific primers was carried out by employing the total genomic DNA isolated from the scabs as the template. The ORFV isolates from Kodai hills were characterized by the use of bioinformatics tools.

Results:

The amino acid identity of ORFV isolate 1 from Kodai hills is having 98.14%, 96.29%, and 83.59% identity with reference strains of ORFV, Pseudocowpox virus, and bovine papular stomatitis virus, respectively. Phylogenetic analysis revealed that ORFV isolates from Kodai hills clustered with the other ORFV isolates from different geographical areas of India.

Conclusion:

The etiological agent of exanthematous skin lesion among sheep of Kodai hills is ORFV.

Co-thermal liquefaction of Prosopis juliflora biomass with paint sludge for liquid hydrocarbons production

In this study, Prosopis juliflora biomass was co-liquefied with hydrocarbons rich paint waste for next generation fuel (bio-oil) production. Co-liquefaction (HTL) was performed at varying biomass to paint waste ratios (1:0, 0:1, 1:1, 2:1 and 1:2) at different temperatures from 340 to 440 °C for a holding time of 60 min. Bentonite catalyst was added from 1 to 5% wt. to the HTL reactor. Gas Chromatography-Mass Spectroscopy (GC-MS) and Fourier Transform Infrared Spectroscopy (FTIR) analysis were carried out for bio-oil and HTL aqueous phase. Maximum bio-oil yield was around 49.26% wt. at 420 °C, 2:1 blend and 4% wt. of bentonite catalyst. Energy and carbon recovery of bio-oil was around 70% and 96% respectively. Additionally, HTL aqueous phase was analysed and it showed presence of acids molecules in it. The gas from HTL process contained Carbon dioxide (46.25%), Carbon monoxide (6.38%), Methane (9.35%) and hydrogen (24.53%).

A hybrid of whale optimization and late acceptance hill climbing based imputation to enhance classification performance in electronic health records

Electronic health records (EHR) are a major source of information in biomedical informatics. Yet, missing values are prominent characteristics of EHR. Prediction on dataset with missing values results in inaccurate inferences. Nearest neighbour imputation based on lazy learning approach is a proven technique for missing data imputation and is recognized as one among the top ten data mining algorithms due to its simplicity and understandability. But its performance is deteriorated due to the curse of dimensionality as unimportant features are likely to dominate. We address this problem by proposing a novel approach for feature weighting based on a hybrid of metaheuristic whale optimization algorithm (WOA) and local search late acceptance hill climbing algorithm (LAHCA) on nearest neighbour imputation method. Our proposed approach Metaheuristic and Local Search based Feature Weighted Nearest Neighbour Imputation (kNN+LAHCAWOA) also learns different k values for different test points. Our approach is tested on benchmark EHR datasets with three proven classifiers Support Vector Machines(SVM), Random forest(RF) and Deep neural networks(DNN). The results prove that kNN+LAHCAWOA is an effective imputation strategy and aids in improving the classification performance when compared with its competitor methods.

Anatomical and functional implications of corticotrophin-releasing hormone neurones in a septal nucleus of the avian brain: an emphasis on glial-neuronal interaction via V1a receptors in vitro

Previously, we showed that corticotrophin-releasing hormone immunoreactive (CRH-IR) neurones in a septal structure are associated with stress and the hypothalamic-pituitary-adrenal axis in birds. In the present study, we focused upon CRH-IR neurones located within the septal structure called the nucleus of the hippocampal commissure (NHpC). Immunocytochemical and gene expression analyses were used to identify the anatomical and functional characteristics of cells within the NHpC. A comparative morphometry analysis showed that CRH-IR neurones in the NHpC were significantly larger than CRH-IR parvocellular neurones in the paraventricular nucleus of the hypothalamus (PVN) and lateral bed nucleus of the stria terminalis. Furthermore, these large neurones in the NHpC usually have more than two processes, showing characteristics of multipolar neurones. Utilisation of an organotypic slice culture method enabled testing of how CRH-IR neurones could be regulated within the NHpC. Similar to the PVN, CRH mRNA levels in the NHpC were increased following forskolin treatment. However, dexamethasone decreased forskolin-induced CRH gene expression only in the PVN and not in the NHpC, indicating differential inhibitory mechanisms in the PVN and the NHpC of the avian brain. Moreover, immunocytochemical evidence also showed that CRH-IR neurones reside in the NHpC along with the vasotocinergic system, comprising arginine vasotocin (AVT) nerve terminals and immunoreactive vasotocin V1a receptors (V1aR) in glia. Hence, we hypothesised that AVT acts as a neuromodulator within the NHpC to modulate activity of CRH neurones via glial V1aR. Gene expression analysis of cultured slices revealed that AVT treatment increased CRH mRNA levels, whereas a combination of AVT and a V1aR antagonist treatment decreased CRH mRNA expression. Furthermore, an attempt to identify an intercellular mechanism in glial-neuronal communication in the NHpC revealed that brain-derived neurotrophic factor (BDNF) and its receptor (TrkB) could be involved in the signalling mechanism. Immunocytochemical results further showed that both BDNF and TrkB receptors were found in glia of the NHpC. Interestingly, in cultured brain slices containing the NHpC, the use of a selective TrkB antagonist decreased the AVT-induced increase in CRH gene expression levels. The results from the present study collectively suggest that CRH neuronal activity is modulated by AVT via V1aR involving BDNF and TrkB glia in the NHpC.

Genetic trend for growth and wool performance in a closed flock of Bharat Merino sheep at sub temperate region of Kodai hills, Tamil Nadu

Aim:

The study was conducted at Southern Regional Research Center, ICAR-Central Sheep and Wool Research Institute (CSWRI), Mannavanur, Kodaikanal, Tamil Nadu to estimate genetic trends for birth weight (BWT), weaning weight (3WT), 6 months weight (6WT), and greasy fleece weight (GFY) in a Bharat Merino (BM) flock, where selection was practiced for 6WT and GFY.

Materials and Methods:

The data for this study represents a total of 1652 BM lambs; progeny of 144 sires spread over 15 years starting from 2000 to 2014, obtained from the BM flock of ICAR-SRRC (CSWRI), Mannavanur, Kodaikanal, Tamil Nadu, India. The genetic trends were calculated by regression of average predicted breeding values using software WOMBAT for the traits BWT, 3WT, 6WT and GFY versus the animal’s birth year.

Results:

The least square means were 3.28±0.02 kg, 19.08±0.23 kg, 25.00±0.35 kg and 2.13±0.07 kg for BWT, 3WT, 6WT and GFY, respectively. Genetic trends were positive and highly significant (p<0.01) for BWT, while the values for 3WT, 6WT and GFY though positive, were not significant. The estimates of genetic trends in BWT, 3WT, 6WT and GFY were 5 g, 0.8 g, 7 g and 0.3 g/year gain and the fit of the regression shows 55%, 22%, 42% and 12% coefficient of determination with the regressed value, respectively. In this study, estimated mean predicted breeding value (kg) in BWT and 3WT, 6WT and GFY were 0.067, 0.008, 0.036 and −0.003, respectively.

Conclusion:

Estimates of genetic trends indicated that there was a positive genetic improvement in all studied traits and selection would be effective for the improvement of body weight traits and GFY of BM sheep.

Neuropeptide Arginine Vasotocin Positively Affects Neurosteroidogenesis in the Early Brain of Grouper, Epinephelus coioides

The neuropeptide arginine vasotocin (AVT) has versatile physiological functions in non-mammalian vertebrates. However, the functional association between AVT and neurosteroidogenesis in the early brain of teleosts remains elusive. We thus studied the developmental expression patterns of the avt gene and their V1 type receptor (avt-rv1 ) at various stages of development [90-150 days after hatching (dah)] in relation to neurosteroidogenesis and oestrogen signalling in the early brain of the orange-spotted grouper (Epinephelus coioides). avt and avt-rv1 mRNAs displayed a significantly increase in expression at 110 dah in the telencephalon and diencephalon. Further, avt mRNAs were localised in three magnocellular neuronal populations of the preoptic area, such as parvocellular, magnocellular and gigantocellular preoptic neurones. Intriguingly, the avt transcripts in those neurones were more abundant in 110 dah compared to other ages. Subsequently, dual fluorescence in situ hybridisation analysis showed that the avt and avt-rv1 genes were highly coexpressed with cyp11a1, hsd3b1, cyp17a1, erα, erβ and gpr30, which indicates their potential for functional association. Cyp19a1b-immunoreactive positive fibres were found in close proximity to avt-expressing neurones. Moreover, our results showed that exogenous Avt caused a significant increase in the cellular and gene levels of steroidogenic enzymes and oestrogen receptors (ers), whereas the administration of an Avt-rv1 antagonist caused a decrease in the expression of both steroidogenic enzymes and ers genes in the brain. Furthermore, exogenous oestradiol (E2 ) strongly up-regulated avt mRNAs in the grouper brain. Taken together, the present studies suggest that avt and steroidogenesis may positively work together to increase both E2 biosynthesis and early brain development.

Characterization of GM-CSF-inhibitory factor and Uracil DNA glycosylase encoding genes from camel pseudocowpoxvirus

The present study describes the PCR amplification of GM-CSF-inhibitory factor (GIF) and Uracil DNA glycosylase (UDG) encoding genes of pseudocowpoxvirus (PCPV) from the Indian Dromedaries (Camelus dromedarius) infected with contagious ecthyma using the primers based on the corresponding gene sequences of human PCPV and reindeer PCPV, respectively. The length of GIF gene of PCPV obtained from camel is 795 bp and due to the addition of one cytosine residue at position 374 and one adenine residue at position 516, the open reading frame (ORF) got altered, resulting in the production of truncated polypeptide. The ORF of UDG encoding gene of camel PCPV is 696 bp encoding a polypeptide of 26.0 kDa. Comparison of amino acid sequence homologies of GIF and UDG of camel PCPV revealed that the camel PCPV is closer to ORFV and PCPV (reference stains of both human and reindeer), respectively.

Comparative sequence analysis of double stranded RNA binding protein encoding gene of parapoxviruses from Indian camels

The dsRNA binding protein (RBP) encoding gene of parapoxviruses (PPVs) from the Dromedary camels, inhabitating different geographical region of Rajasthan, India were amplified by polymerase chain reaction using the primers of pseudocowpoxvirus (PCPV) from Finnish reindeer and cloned into pGEM-T for sequence analysis. Analysis of RBP encoding gene revealed that PPV DNA from Bikaner shared 98.3% and 76.6% sequence identity at the amino acid level, with Pali and Udaipur PPV DNA, respectively. Reference strains of Bovine papular stomatitis virus (BPSV) and PCPV (reindeer PCPV and human PCPV) shared 52.8% and 86.9% amino acid identity with RBP gene of camel PPVs from Bikaner, respectively. But different strains of orf virus (ORFV) from different geographical areas of the world shared 69.5-71.7% amino acid identity with RBP gene of camel PPVs from Bikaner. These findings indicate that the camel PPVs described are closely related to bovine PPV (PCPV) in comparison to caprine and ovine PPV (ORFV).

Beziehungen zwischen Phosphor-Halogen- und Phosphor-Sauerstoff-Bindungsgraden und der chemischen Verschiebung von 31P in Phosphorylhalogeniden OPF3, OPF2Cl, OPFCl2 und OPCl3

Der Gang der chemischen Verschiebung von 31P in der Reihe OPF3, OPF2Cl, OPFCl2 und OPCl3 wird mit Hilfe der möglichen dπ—pπ-Bindungen zwischen Phosphor und den Liganden erklärt.

Mittlere Schwingungsamplituden von tetraedrischen Oxoanionen und Thioanionen des Typs XO4 n⊖ bzw. XS4 2⊖

Mit Hilfe der Methode von CYVIN unter Benutzung von Symmetrie-Koordinaten werden mittlerequadratische Amplituden-Werte (mean-square amplitude quantities) und mittlere Schwingungsamplituden von tetraedrischen Oxo- und Thioanionen für gebundene und nichtgebundene Atome für 298 und 500 °K berechnet. Die Ergebnisse werden im Zusammenhang mit Bindungsverhältnissen und Kraftkonstanten diskutiert.

Mittlere Schwingungsamplituden des Trithiocarbonat- und Triselenocarbonations

Mean-square amplitude quantities and mean amplitudes of vibration for CS3 2⊖ and CSe3 2⊖ at 298 °K and 500 °K are computed. The method of Cyvin utilizing symmetry coordinates has been employed. A brief discussion of the results is given.

Experimental investigation of homogeneous charge compression ignition combustion of biodiesel fuel with external mixture formation in a CI engine

In parallel to the interest in renewable fuels, there has also been increased interest in homogeneous charge compression ignition (HCCI) combustion. HCCI engines are being actively developed because they have the potential to be highly efficient and to produce low emissions. Even though HCCI has been researched extensively, few challenges still exist. These include controlling the combustion at higher loads and the formation of a homogeneous mixture. To obtain better homogeneity, in the present investigation external mixture formation method was adopted, in which the fuel vaporiser was used to achieve excellent HCCI combustion in a single cylinder air-cooled direct injection diesel engine. In continuation of our previous works, in the current study a vaporised jatropha methyl ester (JME) was mixed with air to form a homogeneous mixture and inducted into the cylinder during the intake stroke to analyze the combustion, emission and performance characteristics. To control the early ignition of JME vapor-air mixture, cooled (30 °C) Exhaust gas recirculation (EGR) technique was adopted. The experimental result shows 81% reduction in NOx and 72% reduction in smoke emission.

Sindbis virus replicase-based DNA vaccine construct encoding FMDV-specific multivalent epitope gene: studies on its immune responses in guinea pigs

Foot-and-mouth disease (FMD) is still a perennial global menace affecting livestock health and production. It is imperative to figure out new ways to curb this disease. In this study, a sindbis virus replicase-based DNA vaccine, pSinCMV-Vac-MEG990, encoding a multivalent epitope gene (representing tandemly linked VP1 C-terminal halves of three foot-and-mouth disease virus (FMDV) serotypes) was constructed. In vitro transfection studies in BHK-21 cells revealed that the construct was able to express FMDV-specific antigen but does not overproduce the antigen. Immunization of guinea pigs with the construct at dose rate of 10, 5, 2 and 1 μg per animal through intramuscular route showed significant neutralizing antibody induction at all doses against all serotype tested as compared to non-immunized controls. On viral challenge of guinea pigs 4 week post-immunization with 1000 GPID(50) of FMDV serotype A, it was observed that the immunization not only delayed the appearance and reduced the severity of FMD lesions significantly (P < 0.05) but also provided complete protection in several guinea pigs. In fact, two of six and one of six guinea pigs were completely protected in 10 and 5 μg immunized groups, respectively. These results suggest that the development of the replicase-based DNA vaccine may provide a promising approach as an alternative vaccine strategy for controlling FMD.

Involvement of corticotrophin-releasing hormone and corticosteroid receptors in the brain-pituitary-gill of tilapia during the course of seawater acclimation

The mRNA expression of genes for corticotrophin-releasing hormone (CRH) and the hormone receptors CRH-receptor/CRH-R, glucocorticoid receptor 1/2 (GR1/2) and mineralocorticoid receptor (MR) was studied in the brain, pituitary and gill of tilapia (Oreochromis mossambibus) during salinity and handling stress by real-time quantitative-polymerase chain reaction analysis. The results indicated that the transcripts of CRH and CRH-R were increased in the forebrain, midbrain and gill, whereas elevated hypothalamic CRH mRNA suppressed the CRH-R mRNA in the pituitary in seawater (SW) fish. The levels of plasma osmolality and cortisol were significantly increased in SW compared to freshwater fish. The up-regulation of GR1, GR2, MR and α-NKA (Na(+) /K(+) -ATPase) transcripts in SW fish provided evidence that cortisol responds to stress and involves ion-base regulation via the GR1, GR2 and MR receptors in the gill. These data suggest that GR1, GR2 and MR have a pivotal role in the brain and gill. GR1, GR2 and MR expression may be dependent on CRH and cortisol expression in the brain and gill. In addition, we performed in situ hybridisation analysis to localise and differentiate the CRH, CRH-R, GR1, GR2 and MR transcripts in the brain of FW- and SW-acute acclimated tilapia during salinity stress. In almost all transcripts, the hybridisation signal was significantly abundant in the SW-acute acclimated tilapia brain, especially in the dorsal ventral cephalon, dorsal nucleus preopticus pars magnocellularis and dorsal nucleus preopticus pars parvocellularis. Salinity stress induced differential and specific responses in the gill and brain compared to handling stress.

Self Replicating Gene Vaccine Carrying P1-2A Gene of FMDV Serotype O and its Effects on the Immune Responses of Cattle

DNA vaccines are considered as alternatives to live attenuated ones for those diseases like foot-and-mouth disease (FMD) where the production and application of live vaccines have been found unsuccessful. However, stability of DNA and the quantity of antigen expressed are the major limitation with naked DNA vaccines. To address these issues self replicating gene vaccine construct was made for foot-and-mouth disease virus (FMDV) type 'O' and studied. The vector for vaccine construct, designated as pSinCMVVac carried CMV promoter and Poly(A) signal sequences at 5' and 3' end of Sindbis replicase gene respectively. Gene for structural protein precursor (P1-2A) of FMDV serotype 'O' was inserted into pSinCMVVac under subgenomic promoter. 5'UTR (untranslated region) of FMDV was introduced upstream of P1-2A to enhance the level of expression of cloned gene. Functionality of the vaccine construct was confirmed in vitro and in vivo. The self-replicating gene vaccine construct was tested in cattle in comparison with naked DNA vaccine carrying P1-2A and 3CD (pUP3CD). Humoral immune response by ELISA and SNT and cellular response by lymphoproliferation assay using MTT were studied. The default approach of using self replicating gene vaccine in high dose and multiple injection in cattle as followed in our studies might result in immunosuppression as this was observed in our subsequent experiments in guinea pigs. Hence based on dose response studies, vaccine strategy needs to be decided. However, the approach of using Sindbis polymerase gene and UTR in FMDV vaccine is the first report and shows future scope of developing such vaccines.

Cloning and sequence analysis of IL-2, IL-4 and IFN-γ from Indian Dromedary camels (Camelus dromedarius)

The cDNAs of three cytokines, viz., IL-2, IL-4 and IFN-γ from Dromedary camels were amplified by PCR using Bactrian camel sequences and subsequently cloned for sequence analysis. Relationship based on amino acid sequences revealed that Dromedary camel IL-2 shared 99.5% and 99.3% identity at the nucleotide and amino acid levels with Bactrian camel IL-2. In the case of IL-4, the identity of Dromedary camel was 99.7% and 99.2% at the nucleotide and amino acid levels, respectively with that of Bactrian camel. The Dromedary camel IFN-γ shared 100% identity both at nucleotide and amino acid levels with Bactrian camel IFN-γ. Phylogenetic analysis based on amino acid sequences indicated the close relationship in these cytokine genes between the Dromedary camel and other camelids.

Sequence analysis of topoisomerase gene of pseudocowpox virus isolates from camels (Camelus dromedarius)

Topoisomerase gene of pseudocowposvirus from Indian dromedarian camel was amplified by PCR using the primers of PCPV from Finnish reindeer and cloned into pGEM-T for sequence analysis. Analysis of amino acid identity revealed that Indian PCPV of camel shared 95.9-96.8 with PCPV of reindeer, 96.2-96.5 with ORFV and 87.5 with BPSV.

Cloning and phylogenetic analysis of Interleukin-6 (IL-6) and tumor necrosis factor-α (TNF-α) from Indian dromedaries (Camelus dromedarius)

The cDNAs of two proinflammatory cytokines viz., IL-6 and TNF-α from dromedarian camels were amplified by PCR using bactrian camel sequences and subsequently cloned for sequence analysis. Relationship based on amino acid revealed that dromedarian camel IL-6 shared 99.5% identity both at nucleotide and amino acid level with bactrian camel IL-6 and in case of TNF-α, the identity of dromedarian camel was 99.4% and 99.1% at nucleotide and amino acid level, respectively with that of bactrian camel. Phylogenetic analysis based on their amino acid sequences indicated the close relationship in these cytokine genes between dromedarian camel and other members of camelids.