Clinical selection strategies to identify ischemic stroke patients with large anterior vessel occlusion: results from SITS-ISTR (Safe Implementation of Thrombolysis in Stroke International Stroke Thrombolysis Registry)

Background and Purpose—The National Institutes of Health Stroke Scale (NIHSS) correlates with presence of large anterior vessel occlusion (LAVO). However, the application of the full NIHSS in the prehospital setting to select patients eligible for treatment with thrombectomy is limited. Therefore, we aimed to evaluate the prognostic value of simple clinical selection strategies. Methods—Data from the Safe Implementation of Thrombolysis in Stroke International Stroke Thrombolysis Registry (January 2012–May 2014) were analyzed retrospectively. Patients with complete breakdown of NIHSS scores and documented vessel status were included. We assessed the association of prehospital stroke scales and NIHSS symptom profiles with LAVO (internal carotid artery, carotid-terminus or M1-segment of the middle cerebral artery). Results—Among 3505 patients, 23.6% (n=827) had LAVO. Pathological finding on the NIHSS item best gaze was strongly associated with LAVO (adjusted odds ratio 4.5, 95% confidence interval 3.8–5.3). All 3 face–arm–speech–time test (FAST) items identified LAVO with high sensitivity. Addition of the item gaze to the original FAST score (G-FAST) or high scores on other simplified stroke scales increased specificity. The NIHSS symptom profiles representing total anterior syndromes showed a 10-fold increased likelihood for LAVO compared with a nonspecific clinical profile. If compared with an NIHSS threshold of ≥6, the prehospital stroke scales performed similarly or even better without losing sensitivity. Conclusions—Simple modification of the face–arm–speech–time score or evaluating the NIHSS symptom profile may help to stratify patients’ risk of LAVO and to identify individuals who deserve rapid transfer to comprehensive stroke centers. Prospective validation in the prehospital setting is required

Early detection of doxorubicin-induced cardiotoxicity in rats by its cardiac metabolic signature assessed with hyperpolarized MRI.

Doxorubicin (DOX) is a widely used chemotherapeutic agent that can cause serious cardiotoxic side effects culminating in congestive heart failure (HF). There are currently no clinical imaging techniques or biomarkers available to detect DOX-cardiotoxicity before functional decline. Mitochondrial dysfunction is thought to be a key factor driving functional decline, though real-time metabolic fluxes have never been assessed in DOX-cardiotoxicity. Hyperpolarized magnetic resonance imaging (MRI) can assess real-time metabolic fluxes in vivo. Here we show that cardiac functional decline in a clinically relevant rat-model of DOX-HF is preceded by a change in oxidative mitochondrial carbohydrate metabolism, measured by hyperpolarized MRI. The decreased metabolic fluxes were predominantly due to mitochondrial loss and additional mitochondrial dysfunction, and not, as widely assumed hitherto, to oxidative stress. Since hyperpolarized MRI has been successfully translated into clinical trials this opens up the potential to test cancer patients receiving DOX for early signs of cardiotoxicity

Oligo-DNA Custom Macroarray for Monitoring Major Pathogenic and Non-Pathogenic Fungi and Bacteria in the Phyllosphere of Apple Trees

BACKGROUND: To monitor the richness in microbial inhabitants in the phyllosphere of apple trees cultivated under various cultural and environmental conditions, we developed an oligo-DNA macroarray for major pathogenic and non-pathogenic fungi and bacteria inhabiting the phyllosphere of apple trees. METHODS AND FINDINGS: First, we isolated culturable fungi and bacteria from apple orchards by an agar-plate culture method, and detected 32 fungal and 34 bacterial species. Alternaria, Aureobasidium, Cladosporium, Rhodotorula, Cystofilobasidium, and Epicoccum genera were predominant among the fungi, and Bacillus, Pseudomonas, Sphingomonas, Methylobacterium, and Pantoea genera were predominant among the bacteria. Based on the data, we selected 29 major non-pathogenic and 12 phytopathogenic fungi and bacteria as the targets of macroarray. Forty-one species-specific 40-base pair long oligo-DNA sequences were selected from the nucleotide sequences of rDNA-internal transcribed spacer region for fungi and 16S rDNA for bacteria. The oligo-DNAs were fixed on nylon membrane and hybridized with digoxigenin-labeled cRNA probes prepared for each species. All arrays except those for Alternaria, Bacillus, and their related species, were specifically hybridized. The array was sensitive enough to detect 10(3) CFU for Aureobasidium pullulans and Bacillus cereus. Nucleotide sequencing of 100 each of independent fungal rDNA-ITS and bacterial 16S-rDNA sequences from apple tree was in agreement with the macroarray data obtained using the same sample. Finally, we analyzed the richness in the microbial inhabitants in the samples collected from apple trees in four orchards. Major apple pathogens that cause scab, Alternaria blotch, and Marssonina blotch were detected along with several non-phytopathogenic fungal and bacterial inhabitants. CONCLUSIONS: The macroarray technique presented here is a strong tool to monitor the major microbial species and the community structures in the phyllosphere of apple trees and identify key species antagonistic, supportive or co-operative to specific pathogens in the orchard managed under different environmental conditions

Automatically Harnessing Sparse Acceleration

Sparse linear algebra is central to many scientific programs, yet compilers fail to optimize it well. High-performance libraries are available, but adoption costs are significant. Moreover, libraries tie programs into vendor-specific software and hardware ecosystems, creating non-portable code. In this paper, we develop a new approach based on our specification Language for implementers of Linear Algebra Computations (LiLAC). Rather than requiring the application developer to (re)write every program for a given library, the burden is shifted to a one-off description by the library implementer. The LiLAC-enabled compiler uses this to insert appropriate library routines without source code changes. LiLAC provides automatic data marshaling, maintaining state between calls and minimizing data transfers. Appropriate places for library insertion are detected in compiler intermediate representation, independent of source languages. We evaluated on large-scale scientific applications written in FORTRAN; standard C/C++ and FORTRAN benchmarks; and C++ graph analytics kernels. Across heterogeneous platforms, applications and data sets we show speedups of 1.1$\times$ to over 10$\times$ without user intervention.Comment: Accepted to CC 202

Incidence of Listeria species in seafood products of Mysore, India

Listeria monocytogenes is one of the most important foodborne pathogens causing illness in humans and animals. Thus, a study was undertaken to investigate the incidence of Listeria species in fresh and dry fish samples marketed in Mysore, India. A total of 164 fresh and dry fish samples collected from retail outlet shops of Mysore, South India, during the period August 2005 through August 2006 were examined for the presence of Listeria species by using ISO 11290 protocol. The incidence of Listeria species was positive in 62 samples (37.8%), and L. monocytogenes was isolated from only three (1.83%) fresh fish samples. Listeria species in seafood were predominant in the order of Listeria innocua (50) (30.49%), Listeria grayi (eight) (4.9%), L. monocytogenes (three) (1.83%) and Listeria seeligeri (one) (0.6%). All isolates of Listeria species were subjected to polymerase chain reaction (PCR) and confirmed with the genus-specific set of primers, and special emphasis was given for detection of L. monocytogenes using a species-specific set of primers. The specificity and sensitivity of PCR were in good correlation with the cultural methods. The results indicated a high incidence of Listeria species and L. monocytogenes in fresh fish samples. This warrants the need for appropriate control measures as this would pose a serious threat to human health

Pcr method for the detection of genus fusarium and fumonisin-producing isolates from freshly harvested sorghum grains grown in Karnataka, India

ABSTRACT Sixty-four isolates of Fusarium species isolated from 44 sorghum samples collected during 2004–2005 were subjected to polymerase chain reaction (PCR) analysis. PCR detection was performed on all Fusarium species using two different sets of primers, namely, internal transcribed spacer (ITS) and FUM1. The developed protocol is rapid for small-scale extraction of DNA from fungal mycelia for the detection of Fusarium species using diagnostic PCR. Sixty-four Fusarium isolates, namely, Fusarium verticillioides (45), Fusarium proliferatum (4), Fusarium anthophilum (4), Fusarium sporotrichioides (3), Fusarium pallidoroseum (6) and Fusarium oxysporum (2), were analyzed by PCR using the ITS and FUM1 set of primers. All Fusarium species scored positive with the ITS set of primers. Among the 64 isolates, 53 have scored positive with the FUM1 set of primers. These 53 isolates represent F. verticillioides (45), F. proliferatum (4) and F. anthophilum (4), respectively. The results of the study revealed that PCR-based technique could be used to identify a group of potential fumonisin-producing Fusarium species. PRACTICAL APPLICATIONS Polymerase chain reaction (PCR) method provides the basis for a simple, accurate, rapid and precise detection of potential fumonisin producing Fusarium species, which are of considerable risk to animal and human health. The detection of Fusarium species is therefore crucial for the prevention of toxins entering the food chain. The protocols developed in this study are helpful for a rapid and small-scale extraction of nucleic acid from fungal mycelia, occurring on contaminated sorghum samples. A large number of samples can be screened in relatively less time using this PCR protocol when compared with the conventional methods

Detection of phomopsis azadirachtae from dieback affected neem twigs, seeds, embryo by polymerase chain reaction

Twigs and seeds of Azadirachta indica (Neem) infected with dieback disease, collected from different regions of Karnataka, India were analysed to determine the pathogens. Phomopsis azadirachtae, the causal agent of dieback disease of neem was found to be seed borne. Phomopsis azadirachtae was isolated on PDA and MEA from dieback-infected neem twigs, seeds and embryo. Phomopsis genus-specific primers (5.8S r-DNA) were then used for the detection of Phomopsis azadirachtae, the causative agent of dieback of neem by polymerase chain reaction (PCR). Reactions were performed on DNA isolated from twigs, seeds and embryo of dieback-affected neem trees. Studies revealed the amplification of expected 141 bp DNA in Phomopsis azadirachtae isolated from various parts of diseased trees indicating the causal organism of dieback disease on neem. Isolation and identification by conventional technique takes around 15 – 21 days, whereas the present technique is capable of detecting very low propogules within 4 – 5 days