Innovative molecular diagnosis of Trichinella species based on β-carbonic anhydrase genomic sequence

Trichinellosis is a helminthic infection where different species of Trichinella nematodes are the causative agents. Several molecular assays have been designed to aid diagnostics of trichinellosis. These assays are mostly complex and expensive. The genomes of Trichinella species contain certain parasite-specific genes, which can be detected by polymerase chain reaction (PCR) methods. We selected -carbonic anhydrase (-CA) gene as a target, because it is present in many parasites genomes but absent in vertebrates. We developed a novel -CA gene-based method for detection of Trichinella larvae in biological samples. We first identified a -CA protein sequence from Trichinella spiralis by bioinformatic tools using -CAs from Caenorhabditis elegans and Drosophila melanogaster. Thereafter, 16 sets of designed primers were tested to detect -CA genomic sequences from three species of Trichinella, including T.spiralis, Trichinellapseudospiralis and Trichinellanativa. Among all 16 sets of designed primers, the primer set No. 2 efficiently amplified -CA genomic sequences from T.spiralis, T.pseudospiralis and T.nativa without any false-positive amplicons from other parasite samples including Toxoplasma gondii, Toxocara cati and Parascaris equorum. This robust and straightforward method could be useful for meat inspection in slaughterhouses, quality control by food authorities and medical laboratories.Peer reviewe

Serum protein binding of 25 antiepileptic drugs in a routine clinical setting: A comparison of free non-protein-bound concentrations

Objective Given that only the free non–protein-bound concentration of an antiepileptic drug (AED) crosses the blood–brain barrier, entering the brain and producing an antiepileptic effect, knowledge and measurement of the free drug fraction is important. Such data are sparse, particularly for newer AEDs, and have arisen from the use of disparate methodologies and settings over the past six decades. We report on the protein binding of 25 AEDs that are available for clinical use, along with two pharmacologically active metabolites (carbamazepine-epoxide and N-desmethyl clobazam), using standardized methodology and under set conditions. Methods The protein binding of the various AEDs was undertaken in sera of 278 patients with epilepsy. Separation of the free non–protein-bound component was achieved by using ultracentrifugation (Amicon Centrifree Micropartition System) under set conditions: 500 μl serum volume; centrifugation at 1,000 g for 15 min, and at 25°C. Free and total AED concentrations were measured by use of fully validated liquid chromatography/mass spectroscopy (LC/MS) techniques. Results Gabapentin and pregabalin are non–protein-bound, whereas highly bound AEDs (≥88%) include clobazam, clonazepam, perampanel, retigabine, stiripentol, tiagabine, and valproic acid as well as the N-desmethyl-clobazam (89%) metabolite. The minimally bound drugs (<22%) include ethosuximide (21.8%), lacosamide (14.0%), levetiracetam (3.4%), topiramate, (19.5%) and vigabatrin (17.1%). Ten of the 25 AEDs exhibit moderate protein binding (mean range 27.7–74.8%). Significance These data provide a comprehensive comparison of serum protein binding of all available AEDs including the metabolites, carbamazepine-epoxide and N-desmethyl-clobazam. Knowledge of the free fraction of these AEDs can be used to optimize epilepsy treatment

Practical Defenses Against Storage Jamming

detection objects satisfy two properties 1. Indistinguishability: To any jamming process, a detection object is indistinguishable from a storage object. 2. Sensitivity: The only authentic process that modifies the detection object is the detection process. The implementation problem for a detection object defense is to preserve both indistinguishability (avoid counter-detection) and sensitivity (avoid false detections). In our example external jammer, we could model this by declaring a variable a to hold the subject of the security administrator. We could add the counter-detection by modifying line 23 to append a check 1 for ownership of the target. 38 || t, d[t] := rand(t), g(u.val) if count ³ JAM Ù u ¹ null Ùwrite Î P[s0, d[t]] 39 Ù own ÏP[a,d[t]] This kind of counterdetection may not even require inside knowledge of a particular system. If a proposed defense is known to always operate in this mode, a jamming program may be able to obtain a list of user names that correspond to ..