Differential expression of collectins in human placenta and role in inflammation during spontaneous Labor.

© 2014 Yadav et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.Collectins, collagen-containing Ca2+ dependent C-type lectins and a class of secretory proteins including SP-A, SP-D and MBL, are integral to immunomodulation and innate immune defense. In the present study, we aimed to investigate their placental transcript synthesis, labor associated differential expression and localization at feto-maternal interface, and their functional implication in spontaneous labor. The study involved using feto-maternal interface (placental/decidual tissues) from two groups of healthy pregnant women at term (≥37 weeks of gestation), undergoing either elective C-section with no labor ('NLc' group, n = 5), or normal vaginal delivery with spontaneous labor ('SLv' group, n = 5). The immune function of SP-D, on term placental explants, was analyzed for cytokine profile using multiplexed cytokine array. SP-A, SP-D and MBL transcripts were observed in the term placenta. The 'SLv' group showed significant up-regulation of SP-D (p = 0.001), and down-regulation of SP-A (p = 0.005), transcripts and protein compared to the 'NLc' group. Significant increase in 43 kDa and 50 kDa SP-D forms in placental and decidual tissues was associated with the spontaneous labor (p<0.05). In addition, the MMP-9-cleaved form of SP-D (25 kDa) was significantly higher in the placentae of 'SLv' group compared to the 'NLc' group (p = 0.002). Labor associated cytokines IL-1α, IL-1β, IL-6, IL-8, IL-10, TNF-α and MCP-1 showed significant increase (p<0.05) in a dose dependent manner in the placental explants treated with nSP-D and rhSP-D. In conclusion, the study emphasizes that SP-A and SP-D proteins associate with the spontaneous labor and SP-D plausibly contributes to the pro-inflammatory immune milieu of feto-maternal tissues.Funding provided by BT/PR15227/BRB/10/906/2011) Department of Biotechnology (DBT), Government of India http://dbtindia.nic.in/index.asp (TM) and Indian Council of Medical Research (ICMR) Junior Research Fellowship (JRF)/Senior Research Fellowship (SRF), Government of India, www.icmr.nic.in (AKY)

Management of chronic obstructive pulmonary disease in India: a systematic review.

OBJECTIVES: Chronic diseases are fast becoming the largest health burden in India. Despite this, their management in India has not been well studied. We aimed to systematically review the nature and efficacy of current management strategies for chronic obstructive pulmonary disease (COPD) in India. METHODS: We used database searches (MEDLINE, EMBASE, IndMED, CENTRAL and CINAHL), journal hand-searches, scanning of reference lists and contact with experts to identify studies for systematic review. We did not review management strategies aimed at chronic diseases more generally, nor management of acute exacerbations. Due to the heterogeneity of reviewed studies, meta-analysis was not appropriate. Thus, narrative methods were used. SETTING: India. PARTICIPANTS: All adult populations resident in India. MAIN OUTCOME MEASURES: 1. Trialled interventions and outcomes 2. Extent and efficacy of current management strategies 3. Above outcomes by subgroup. RESULTS: We found information regarding current management - particularly regarding the implementation of national guidelines and primary prevention - to be minimal. This led to difficulty in interpreting studies of management strategies, which were varied and generally of positive effect. Data regarding current management outcomes were very few. CONCLUSIONS: The current understanding of management strategies for COPD in India is limited due to a lack of published data. Determination of the extent of current use of management guidelines, availability and use of treatment, and current primary prevention strategies would be useful. This would also provide evidence on which to interpret existing and future studies of management outcomes and novel interventions

Diagnosis and management of tropomyosin receptor kinase (TRK) fusion sarcomas : expert recommendations from the World Sarcoma Network

Sarcomas are a heterogeneous group of malignancies with mesenchymal lineage differentiation. The discovery of neurotrophic tyrosine receptor kinase (NTRK) gene fusions as tissue-agnostic oncogenic drivers has led to new personalized therapies for a subset of patients with sarcoma in the form of tropomyosin receptor kinase (TRK) inhibitors. NTRK gene rearrangements and fusion transcripts can be detected with different molecular pathology techniques, while TRK protein expression can be demonstrated with immunohistochemistry. The rarity and diagnostic complexity of NTRK gene fusions raise a number of questions and challenges for clinicians. To address these challenges, the World Sarcoma Network convened two meetings of expert adult oncologists and pathologists and subsequently developed this article to provide practical guidance on the management of patients with sarcoma harboring NTRK gene fusions. We propose a diagnostic strategy that considers disease stage and histologic and molecular subtypes to facilitate routine testing for TRK expression and subsequent testing for NTRK gene fusions.Peer reviewe

Recombinant Baculovirus Associated with Bilosomes as an Oral Vaccine Candidate against HEV71 Infection in Mice

10.1371/journal.pone.0055536PLoS ONE82

Hydrological Investigations in Red Soils of a Micro Catchment Area for Dugout Farm Pond at UAS Raichur Campus

Aims: To measure and characterize storm wise runoff for the catchment area of the farm pond and to correlate rainfall intensity and runoff relationship for the catchment area will help to design the appropriate size of the farm pond and waste weirs of the bunding system. Place and Duration of Study: The study was conducted in a micro catchment (field sized area) of a dugout farm pond, having an area of 6 ha located in the new area of UAS campus Raichur, which comes under Zone II in Region-I of Karnataka state. Geographically it is located at 16° 12′ N latitude and 77° 20′ E longitude and at an elevation of 389 m above the mean sea level (MSL). The study was conducted for a period of one year during 2019. Methodology: The existing farm pond constructed was used for conducting hydrological studies. The detailed soil and rainfall characterization of the study area has been made through appropriate methods. The rainfall intensity for each storm has been measured using self-recording rain gauge. The runoff has been measured at the out let of the field sized micro catchment area of farm pond using hydraulic structures coupled with automatic runoff recorder. The event wise rainfall, rainfall intensity and runoff have been measured and analysed to see the relationship between rainfall intensity and runoff with prevailing soil and topographical characteristics of the study area. Results: The percent runoff varied from 6.79 to 50.42 and highest was 50.42 per cent occurred on 25-10-2019 followed by 44.03, 39.36 and 37.46 per cent. The data shows that the individual storm wise percent runoff was quite high as compared to annual percent runoff of 15.99 per cent. The storm wise high runoff percent was due to the fact that high intensity of rainfall followed by high AMC in the soil. Further the minimum runoff yield of 142.66 m3 was observed on 18-07-2019 against the rainfall of 35.00 mm and maximum of 2985.48 m3 was yielded on 25-09-2109 against rainfall of 113.00 mm and followed by 1086.64 m3, 944.24 m3, 665.61 m3 and 431.25 m3 against rainfall of 46.00 mm, 42.00 mm, 22.00 mm and 48.00 mm respectively. The total annual runoff yield was found to be 6255.90 m3 against the rainfall of 651.50 mm. Therefore, there is a scope for harvesting excess quantity of runoff which is going as a waste. The existing pond capacity of 547.77 m3 is insufficient to store prevailing runoff generated in the catchment area and hence, pond capacity may be enhanced. The maximum intensity of rainfall and runoff during six events were showed statistically insignificant relationship with R2 value of 0.370. There is no correlation between intensity of rainfall and runoff

Characterization of an Isotype-Dependent monoclonal antibody against linear neutralizing epitope effective for prophylaxis of enterovirus 71 infection

10.1371/journal.pone.0029751PLoS ONE71e2975

Variations in Soil Texture Using Machine Learning Models Based on the Spectral Response of Soil Samples in the Visible-Near-Infrared (Vis-NIR) Region

In this study, we systematically assessed the predictive performance of two machine learning models; Random Forest (RF) and Partial Least Squares Regression (PLSR), utilizing various pre-processing techniques for the determination of soil properties, including sand, silt and clay fractions. The evaluation was conducted based on key performance metrics, with the following values recorded: RF exhibited outstanding results with high R2 values (0.88 for calibration and 0.55 for validation) and low RMSE (0.48 for calibration and 1.81 for validation), especially excelling in predicting clay content (R2: 0.92 in calibration and 0.78 in validation). Moreover, the RF model demonstrated impressive RPD (12.5 in calibration and 4.55 in validation) and RPIQ (4.87 in calibration and 4.13 in validation) values for clay. PLSR demonstrated moderate performance, achieving acceptable R2 values for sand, silt and clay fractions, with the highest R2 value of 0.79 achieved in sand content prediction using MSC pre-processing. The RPD and RPIQ scores supported the model's reliability. These findings offer valuable guidance for selecting suitable models and pre-processing techniques for soil property prediction, with Random Forest emerging as the top choice for accurate and reliable results

Induction of protective immune responses against EV71 in mice by baculovirus encoding a novel expression cassette for capsid protein VP1

10.1016/j.antiviral.2012.05.017Antiviral Research953311-315ARSR

Not Available

Not AvailableThe Patapur micro-watershed situated in semi-arid region needs effective management of resources for sustainable agriculture. The Soil and Water Assessment Tool (SWAT), a semi distributed physically based model, was chosen and set up in the Patapur micro-watershed for hydrologic modeling. SWAT-CUP (SWAT-Calibration and Uncertainty Programs) was used for model calibration, sensitivity and uncertainty analysis, following the Sequential Uncertainty Fitting (SUFI2) technique. The model calibration was performed for the period (2009–2014), with initial 3 years of warm up (2009–2012), then, the model was validated for the subsequent 2 years of data (2014– 2006). To assess the competence of model calibration and uncertainty, two indices, the p-factor (observations bracketed by the prediction uncertainty) and the r-factor (achievement of small uncertainty band), were taken into account. The results had shown that p-factor for daily, monthly and annual time step were 0.07 (7%), 0.11(11%), 1.0 (100%), respectively while r-factor for daily, monthly and annual were 0.07 (7%), 0.33 (33%) and 0.0 (0%), respectively, while during the validation p factor and r-factor for daily, monthly and annual were 0.85, 0.17 and 1, respectively. Whereas r-factor for daily, monthly and annual time step were 0.05 (5%), 0.24(24%) and 0, respectively. After a rigorous calibration and validation, the goodness of fit was further assessed through the use of the coefficient of determination (R2 ) and the Nash–Sutcliffe efficiency (NS) between the observed and the final simulated values. The results indicated that R2 and NS were 0.88 and 0.87, respectively, during the daily calibration. The validation also indicated a satisfactory performance with R2 of 0.63 and NS of 0.64. The results would be useful to the hydrological community, water resources managers involved in agricultural water management and soil conservation, as well as to those involved in mitigating natural hazards such as droughts and floods.Not Availabl