Whole plant response of Pongamia pinnata to drought stress tolerance revealed by morpho-physiological,biochemical and transcriptome analysis

Molecular Biology Reports - Pongamia is considered an important biofuel species worldwide. Drought stress in the early growth stages of Pongamia influences negatively on the germination and...     

Predicting breast cancer using an expression values weighted clinical classifier

Background

Clinical data, such as patient history, laboratory analysis, ultrasound parameters-which are the basis of day-to-day clinical decision support-are often used to guide the clinical management of cancer in the presence of microarray data. Several data fusion techniques are available to integrate genomics or proteomics data, but only a few studies have created a single prediction model using both gene expression and clinical data. These studies often remain inconclusive regarding an obtained improvement in prediction performance. To improve clinical management, these data should be fully exploited. This requires efficient algorithms to integrate these data sets and design a final classifier.LS-SVM classifiers and generalized eigenvalue/singular value decompositions are successfully used in many bioinformatics applications for prediction tasks. While bringing up the benefits of these two techniques, we propose a machine learning approach, a weighted LS-SVM classifier to integrate two data sources: microarray and clinical parameters.

Results

We compared and evaluated the proposed methods on five breast cancer case studies. Compared to LS-SVM classifier on individual data sets, generalized eigenvalue decomposition (GEVD) and kernel GEVD, the proposed weighted LS-SVM classifier offers good prediction performance, in terms of test area under ROC Curve (AUC), on all breast cancer case studies.

Conclusions

Thus a clinical classifier weighted with microarray data set results in significantly improved diagnosis, prognosis and prediction responses to therapy. The proposed model has been shown as a promising mathematical framework in both data fusion and non-linear classification problems.     

A mass mortality of fishes caused by receding water levels in the vegetated littoral zone of the West Kleinemonde Estuary,South Africa

On 15 November 2017 the mouth of the West Kleinemonde Estuary breached following heavy catchment rains and increased river flow. The water level in the estuary following mouth opening decreased by 1.65 m within 24 h, resulting in an almost complete draining of the littoral zone where large beds of the aquatic macrophyte Ruppia cirrhosa and mats of the associated filamentous algae were present. As the water depth within the plant beds decreased, the macrophytes, together with the algal filaments, created an increasingly dense mat, trapping fish that were resident, foraging or passing through the littoral zone. By 16 November 2017 large numbers of fishes belonging to at least 20 species were trapped in pools and depressions within the littoral, as well as within the R. cirrhosa beds and filamentous algal mats in the lower reaches of this system. Other affected taxa included crustaceans, especially isopods, and large numbers of small bivalves attached to macrophyte vegetation. Beneficiaries of the fish kill, in terms of unexpected food availability, included a variety of piscivorous bird species and the Cape clawless otter Aonyx capensis. This is the first documented account of a diverse species fish kill associated with estuary mouth breaching.     

Trends in Malaria in Odisha,India—An Analysis of the 2003–2013 Time-Series Data from the National Vector Borne Disease Control Program

Background

Although Odisha is the largest contributor to the malaria burden in India, no systematic study has examined its malaria trends. Hence, the spatio-temporal trends in malaria in Odisha were assessed against the backdrop of the various anti-malaria strategies implemented in the state.

Methods

Using the district-wise malaria incidence and blood examination data (2003–2013) from the National Vector Borne Disease Control Program, blood examination-adjusted time-trends in malaria incidence were estimated and predicted for 2003–2013 and 2014–2016, respectively. An interrupted time series analysis using segmented regression was conducted to compare the disease trends between the pre (2003–2007) and post-intensification (2009–2013) periods. Key-informant interviews of state stakeholders were used to collect the information on the various anti-malaria strategies adopted in the state.

Results

The state annual malaria incidence declined from 10.82/1000 to 5.28/1000 during 2003–2013 (adjusted annual decline: -0.54/1000, 95% CI: -0.78 to -0.30). However, the annual blood examination rate remained almost unchanged from 11.25% to 11.77%. The keyinformants revealed that intensification of anti-malaria activities in 2008 led to a more rapid decline in malaria incidence during 2009–2013 as compared to that in 2003–2007 [adjusted decline: -0.83 (-1.30 to -0.37) and -0.27 (-0.41 to -0.13), respectively]. There was a significant difference in the two temporal slopes, i.e., -0.054 (-0.10 to -0.002, p = 0.04) per 1000 population per month, between these two periods, indicating almost a 200% greater decline in the post-intensification period. Although, the seven southern high-burden districts registered the highest decline, they continued to remain in that zone, thereby, making the achievement of malaria elimination (incidence <1/1000) unlikely by 2017.

Conclusion

The anti-malaria strategies in Odisha, especially their intensification since 2008, have helped improve its malaria situation in recent years. These successful measures need to be sustained and perhaps intensified further for eliminating malaria from Odisha.     

Multiple factors interact to produce responses resembling spectrum of human disease in Campylobacter jejuni infected C57BL/6 IL-10-/- mice

Background  

Campylobacter jejuni infection produces a spectrum of clinical presentations in humans - including asymptomatic carriage, watery diarrhea, and bloody diarrhea - and has been epidemiologically associated with subsequent autoimmune neuropathies. This microorganism is genetically variable and possesses genetic mechanisms that may contribute to variability in nature. However, relationships between genetic variation in the pathogen and variation in disease manifestation in the host are not understood. We took a comparative experimental approach to explore differences among different C. jejuni strains and studied the effect of diet on disease manifestation in an interleukin-10 deficient mouse model.     

The influence of water level on macrophyte growth and trophic interactions in eutrophic Mediterranean shallow lakes: a mesocosm experiment with and without fish

1. Water‐level fluctuations are typical of lakes located in the semi‐arid Mediterranean region, which is characterised by warm rainy winters and hot dry summers. Ongoing climate change may exacerbate fluctuations and lead to more severe episodes of drought, so information on the effects of water level on the functioning of lake ecosystems in such regions is crucial. 2. In eutrophic Lake Eymir, Turkey, we conducted a 4‐month (summer) field experiment using cylindrical 0.8‐m‐ (low‐water‐level) and 1.6‐m‐deep (high‐water‐level) mesocosms (kept open to the sediment and atmosphere). Fish (tench, Tinca tinca, and bleak, Alburnus escherichii) were added to half of the mesocosms, while the rest were kept fishless. Ten shoots of Potamogeton pectinatus were transplanted to each mesocosm. 3. Sampling for physicochemical variables, chlorophyll a (chl‐a), zooplankton and per cent plant volume inhabited (PVI%) by macrophytes was conducted weekly during the first 5 weeks, and subsequently biweekly. Macrophytes were harvested on the last sampling date. During the course of the experiment, the water level decreased by 0.41 ± 0.06 m. 4. Throughout the experiment, fish affected zooplankton abundance (?), nutrient concentrations (+), chl‐a (+) and water clarity (?) most strongly in the low‐water‐level mesocosms and the zooplankton community shifted towards dominance of small‐sized forms. The fishless mesocosms had a higher zooplankton/phytoplankton ratio, suggesting higher grazing. 5. Greatest macrophyte growth was observed in the low‐water‐level fishless mesocosms. However, despite high nutrient concentrations and low water clarity, macrophytes were also abundant in the fish mesocosms and particularly increased following a water‐level decrease from midsummer onwards. Macrophyte growth was poor in the high‐water‐level mesocosms, even in the fishless ones with high water clarity. This was ascribed to extensive periphyton development reducing light availability for the macrophytes. 6. Our results indicate that a reduction in water level during summer may help maintain the growth of macrophytes in Mediterranean eutrophic shallow lakes, despite a strong negative effect of fish predation on water clarity. It is therefore probable that an expected negative effect of global climate change on water clarity because of eutrophication and enhanced top‐down control of fish may be, at least partly, counteracted by reduced water level, provided that physical disturbance is not severe.     

NMR metabolomic analysis of dairy cows reveals milk glycerophosphocholine to phosphocholine ratio as prognostic biomarker for risk of ketosis

Ketosis is a common metabolic disease in dairy cows. Diagnostic markers for ketosis such as acetone and beta-hydroxybutyric acid (BHBA) are known, but disease prediction remains an unsolved challenge. Milk is a steadily available biofluid and routinely collected on a daily basis. This high availability makes milk superior to blood or urine samples for diagnostic purposes. In this contribution, we show that high milk glycerophosphocholine (GPC) levels and high ratios of GPC to phosphocholine (PC) allow for the reliable selection of healthy and metabolically stable cows for breeding purposes. Throughout lactation, high GPC values are connected with a low ketosis incidence. During the first month of lactation, molar GPC/PC ratios equal or greater than 2.5 indicate a very low risk for developing ketosis. This threshold was validated for different breeds (Holstein-Friesian, Brown Swiss, and Simmental Fleckvieh) and for animals in different lactations, with observed odds ratios between 1.5 and 2.38. In contrast to acetone and BHBA, these measures are independent of the acute disease status. A possible explanation for the predictive effect is that GPC and PC are measures for the ability to break down phospholipids as a fatty acid source to meet the enhanced energy requirements of early lactation.     

Nifedipine loaded chitosan microspheres prepared by emulsification phase-separation

A high yield of nifedipine-chitosan microspheres could be obtained using an emulsification phase-separation method. A high level of entrapment of nifedipine in the microspheres was achieved. The microspheres exhibited excellent swelling properties. Differential scanning calorimetry, X-ray diffractometry, and scanning electron microscopy confirmed that at 1.84% loading, nifedipine was dispersed molecularly. The microspheres exhibited faster release at low loadings compared to high loadings. Fitting the data to the coupled Fickian/case II equation, showed that at low loadings polymer relaxation coefficients (k₂) were high. As the polymer content increased in the microspheres, the value of n (diffusional exponent characteristic of the release mechanism) approached one, which is indicative of zero order.     

Real time in vitro studies of doxorubicin release from PHEMA nanoparticles

Background  

Many anticancer agents have poor water solubility and therefore the development of novel delivery systems for such molecules has received significant attention. Nanocarriers show great potential in delivering therapeutic agents into the targeted organs or cells and have recently emerged as a promising approach to cancer treatments. The aim of this study was to prepare and use poly-2-hydroxyethyl methacrylate (PHEMA) nanoparticles for the controlled release of the anticancer drug doxorubicin.