Osmoregulators proline and glycine betaine counteract salinity stress in canola

Salt inundation leads to increased salinization of arable land in many arid and semi-arid regions. Until genetic solutions are found farmers and growers must either abandon salt-affected fields or use agronomic treatments that alleviate salt stress symptoms. Here, field experiments were carried out to study the effect of the osmoregulators proline at 200 mg L-1 and glycine betaine at 400 mg L-1 in counteracting the harmful effect of soil salinity stress on canola plants grown in Egypt. We assessed growth characteristics, yield and biochemical constituents. Results show first that all growth characters decreased with increasing salinity stress but applied osmoregulators alleviated these negative effects. Second, salinity stress decreased photosynthetic pigments, K and P contents, whilst increasing proline, soluble sugars, ascorbic acid, Na and Cl contents. Third, application of osmoregulators without salt stress increased photosynthetic pigments, proline, soluble sugars, N, K and P contents whilst decreasing Na and Cl contents. It is concluded that the exogenously applied osmoregulators glycine betaine and proline can fully or partially counteract the harmful effect of salinity stress on growth and yield of canola.© INRA and Springer-Verlag, France 2012

Real-time PCR assay and rapid diagnostic tests for the diagnosis of clinically suspected malaria patients in Bangladesh

<p>Abstract</p> <p>Background</p> <p>More than 95% of total malaria cases in Bangladesh are reported from the 13 high endemic districts. <it>Plasmodium falciparum </it>and <it>Plasmodium vivax </it>are the two most abundant malaria parasites in the country. To improve the detection and management of malaria patients, the National Malaria Control Programme (NMCP) has been using rapid diagnostic test (RDT) in the endemic areas. A study was conducted to establish a SYBR Green-based modified real-time PCR assay as a gold standard to evaluate the performance of four commercially-available malaria RDTs, along with the classical gold standard- microscopy.</p> <p>Methods</p> <p>Blood samples were collected from 338 febrile patients referred for the diagnosis of malaria by the attending physician at Matiranga</p> <p>Upazila Health Complex (UHC) from May 2009 to August 2010. Paracheck RDT and microscopy were performed at the UHC. The blood samples were preserved in EDTA tubes. A SYBR Green-based real-time PCR assay was performed and evaluated. The performances of the remaining three RDTs (Falcivax, Onsite Pf and Onsite Pf/Pv) were also evaluated against microscopy and real-time PCR using the stored blood samples.</p> <p>Result</p> <p>In total, 338 febrile patients were enrolled in the study. Malaria parasites were detected in 189 (55.9%) and 188 (55.6%) patients by microscopy and real-time PCR respectively. Among the RDTs, the highest sensitivity for the detection of <it>P. falciparum </it>(including mixed infection) was obtained by Paracheck [98.8%, 95% confidence interval (CI) 95.8-99.9] and Falcivax (97.6%, 95% CI 94.1-99.4) compared to microscopy and real-time PCR respectively. Paracheck and Onsite Pf/Pv gave the highest specificity (98.8%, 95% CI 95.7-99.9) compared to microscopy and Onsite Pf/Pv (98.8, 95% CI 95.8-99.9) compared to real-time PCR respectively for the detection of <it>P. falciparum</it>. On the other hand Falcivax and Onsite Pf/Pv had equal sensitivity (90.5%, 95% CI 69.6-98.8) and almost 100% specificity compared to microscopy for the detection of <it>P. vivax</it>. However, compared to real-time PCR assay RDTs and microscopy gave low sensitivity (76.9%, 95% CI 56.4-91) in detecting of <it>P. vivax </it>although a very high specificity was obtained (99- 100%).</p> <p>Conclusion</p> <p>The results of this study suggest that the SYBR Green-based real-time PCR assay could be used as an alternative gold standard method in a reference setting. Commercially-available RDTs used in the study are quite sensitive and specific in detecting <it>P. falciparum</it>, although their sensitivity in detecting <it>P. vivax </it>was not satisfactory compared to the real-time PCR assay.</p

Non-contrast cardiac computed tomography can accurately detect chronic myocardial infarction: Validation study

BackgroundThis study evaluates whether non-contrast cardiac computed tomography (CCT) can detect chronic myocardial infarction (MI) in patients with irreversible perfusion defects on nuclear myocardial perfusion imaging (MPI).MethodsOne hundred twenty-two symptomatic patients with irreversible perfusion defect (N = 62) or normal MPI (N = 60) underwent coronary artery calcium (CAC) scanning. MI on these non-contrast CCTs was visually detected based on the hypo-attenuation areas (dark) in the myocardium and corresponding Hounsfield units (HU) were measured.ResultsNon-contrast CCT accurately detected MI in 57 patients with irreversible perfusion defect on MPI, yielding a sensitivity of 92%, specificity of 72%, negative predictive value (NPV) of 90%, and a positive predictive value (PPV) of 77%. On a per myocardial region analysis, non-contrast CT showed a sensitivity of 70%, specificity of 85%, NPV of 91%, and a PPV of 57%. The ROC curve showed that the optimal cutoff value of LV myocardium HU to predict MI on non-contrast CCT was 21.7 with a sensitivity of 97.4% and specificity of 99.7%.ConclusionNon-contrast CCT has an excellent agreement with MPI in detecting chronic MI. This study highlights a novel clinical utility of non-contrast CCT in addition to assessment of overall burden of atherosclerosis measured by CAC

Diversity of lactic acid bacteria of the bioethanol process

<p>Abstract</p> <p>Background</p> <p>Bacteria may compete with yeast for nutrients during bioethanol production process, potentially causing economic losses. This is the first study aiming at the quantification and identification of Lactic Acid Bacteria (LAB) present in the bioethanol industrial processes in different distilleries of Brazil.</p> <p>Results</p> <p>A total of 489 LAB isolates were obtained from four distilleries in 2007 and 2008. The abundance of LAB in the fermentation tanks varied between 6.0 × 10⁵and 8.9 × 10⁸CFUs/mL. Crude sugar cane juice contained 7.4 × 10⁷to 6.0 × 10⁸LAB CFUs. Most of the LAB isolates belonged to the genus <it>Lactobacillus </it>according to rRNA operon enzyme restriction profiles. A variety of <it>Lactobacillus </it>species occurred throughout the bioethanol process, but the most frequently found species towards the end of the harvest season were <it>L. fermentum </it>and <it>L. vini</it>. The different rep-PCR patterns indicate the co-occurrence of distinct populations of the species <it>L. fermentum </it>and <it>L. vini</it>, suggesting a great intraspecific diversity. Representative isolates of both species had the ability to grow in medium containing up to 10% ethanol, suggesting selection of ethanol tolerant bacteria throughout the process.</p> <p>Conclusions</p> <p>This study served as a first survey of the LAB diversity in the bioethanol process in Brazil. The abundance and diversity of LAB suggest that they have a significant impact in the bioethanol process.</p

Why is the Winner the Best?

International benchmarking competitions have become fundamental for the comparative performance assessment of image analysis methods. However, little attention has been given to investigating what can be learnt from these competitions. Do they really generate scientific progress? What are common and successful participation strategies? What makes a solution superior to a competing method? To address this gap in the literature, we performed a multicenter study with all 80 competitions that were conducted in the scope of IEEE ISBI 2021 and MICCAI 2021. Statistical analyses performed based on comprehensive descriptions of the submitted algorithms linked to their rank as well as the underlying participation strategies revealed common characteristics of winning solutions. These typically include the use of multi-task learning (63%) and/or multi-stage pipelines (61%), and a focus on augmentation (100%), image preprocessing (97%), data curation (79%), and post-processing (66%). The “typical” lead of a winning team is a computer scientist with a doctoral degree, five years of experience in biomedical image analysis, and four years of experience in deep learning. Two core general development strategies stood out for highly-ranked teams: the reflection of the metrics in the method design and the focus on analyzing and handling failure cases. According to the organizers, 43% of the winning algorithms exceeded the state of the art but only 11% completely solved the respective domain problem. The insights of our study could help researchers (1) improve algorithm development strategies when approaching new problems, and (2) focus on open research questions revealed by this work