Platelet trans fatty acids in relation to angiographically assessed coronary artery disease

Epidemiological and metabolic studies indicate that a higher intake of trans fatty acids (TFA) may be associated with increased risk of coronary heart disease (CHD). In a cross-sectional study of patients who underwent coronary angiography, the relationships between TFAs, measured in platelets, and the degree of coronary artery disease (CAD) were examined in 191 non-diabetic patients (134 men and 57 women). The degree of CAD was quantified by using an angiographic scoring system developed to provide an estimate of the extent of coronary atherosclerosis: an ‘extent score’. The TFA composition of platelets, including palmitelaidic (16:1ω7t), elaidic (18:1ω9t), trans-10-octadecaenoic acid (18:1 ω8t), trans vaccenic (18:1ω7t), trans-12-octadecaenoic acid (18:1ω6t) and linoelaidic (18:2ω6tt) acids, was measured by using gas chromatography and quantified as a percentage of total fatty acids. After adjustment for established CHD risk indicators, including age, gender, cigarette smoking, hypertension and serum total cholesterol concentration, elaidic acid (P = 0.0300) and trans-10-octadecaenoic acid (P = 0.0434) were positively associated with the extent score of CAD. The adjusted associations between other individual TFAs, including palmitelaidic acid (P = 0.1189), vaccenic acid (P = 0.7651), trans-12-octadecaenoic acid (P = 0.0582) and linoelaidic acid (P = 0.8793), and the extent score were not significant. The results of this study, therefore, provide evidence for an association between particular platelet TFAs and the degree of CAD in the patient population studied.     

A Two-Stage Methodology Using K-NN and False-Positive Minimizing ELM for Nominal Data Classification

This paper focuses on the problem of making decisions in the context of nominal data under specific constraints. The underlying goal driving the methodology proposed here is to build a decision-making model capable of classifying as many samples as possible while avoiding false positives at all costs, all within the smallest possible computational time. Under such constraints, one of the best type of model is the cognitive-inspired extreme learning machine (ELM), for the final decision process. A two-stage decision methodology using two types of classifiers, a distance-based one, K-NN, and the cognitive-based one, ELM, provides a fast means of obtaining a classification decision on a sample, keeping false positives as low as possible while classifying as many samples as possible (high coverage). The methodology only has two parameters, which, respectively, set the precision of the distance approximation and the final trade-off between false-positive rate and coverage. Experimental results using a specific dataset provided by F-Secure Corporation show that this methodology provides a rapid decision on new samples, with a direct control over the false positives and thus on the decision capabilities of the model.     

Role of nitric oxide in modulating neurotransmitter release from rat striatum

The effect of the nitric oxide synthase inhibitor N-nitro- -arginine methyl ester (L-NAME) on the basal and stimulation-evoked release of dopamine (DA) and acetylcholine (ACh) was investigated in rat striatum. The experiments were carried out in isolated superfused striatal slices, loaded with either [³H]-dopamine or [³H]-choline.We have found that L-NAME reduced the elecrical field stimulation-evoked release of DA, while its enantiomer N-nitro-D-arginine methyl ester (D-NAME) was ineffective. In the presence of the nitric oxide (NO) precursor -arginine L-NAME failed to influence DA release. Furthermore, treatment with the N-methyl- -aspartate (NMDA) receptor antagonist MK-801 completely reversed the effect of L-NAME on striatal DA release. In contrast, L-NAME had no effect on either the basal or the stimulation-evoked ACh release in any experimental conditions studied.Our data indicate that endogenously produced NO is involved in the modulation of striatal DA, but not in ACh release. Furthermore, it seems likely that the modulatory effect of NO is linked to activation of presynaptic NMDA receptors located on the striatal dopaminergic nerve terminals.     

A pragmatic neurological screen for patients with suspected cord compressive myelopathy

Physical therapists commonly use screening tests to identify upper motoneuron lesions such as cord compressive myelopathy (CCM), the presence of which necessitates appropriate medical referral. Signs and symptoms of CCM include sensory and ataxic changes of the lower extremities, poorly coordinated gait, weakness, tetraspasticity, clumsiness, spasticity, hyperreflexia, and primitive reflexes. Clinical tests and measures such as Hoffmann sign, clonus, Lhermitte sign, the grip and release test, the finger escape sign, the Babinski test, and the inverted supinator sign have historically been used as screens for CCM. For effectiveness as a screen, a clinical test or measure should demonstrate high sensitivity. Diagnostic accuracy studies have shown that clinical tests and measures for CCM often display low sensitivity, indicating that a negative finding may falsely suggest the absence of a condition or disease that actually is present. To counter the low levels of sensitivity, screening should include a combination of a thorough patient history, recognition of and appropriate referral for cauda equina symptoms, and clusters of any pertinent contributory tests and measures.     

Multimodal Management of Mechanical Neck Pain Using a Treatment Based Classification System

The purpose of this case study was twofold: 1) to illustrate the use of a treatment-based classification (TBC) system to direct the early intervention of a patient with mechanical neck pain, and 2) to show the progression of this patient with multimodal-modal intervention. The patient exhibited axial neck pain with referral into her upper extremity. Her pain peripheralized with cervical range of motion and centralized with joint mobilization placing her primarily in the centralization category. Her poor posture and associated muscle weakness along with the chronicity of symptoms placed her secondarily into the exercise and conditioning group resulting in a multi-modal treatment as the patient progressed. Although the design of this case report prevents wide applicability, this study does illustrate the effective use of the TBC system for the cervical spine as captured by accepted outcomes measures.KEYWORDS: Multi-Modal Intervention, Neck Pain, Treatment-Based ClassificationMechanical neck pain commonly arises insidiously¹ and is generally multifactorial in origin, including one or more of the following: poor posture, anxiety, depression, neck strain, and sporting or occupational activities^2,3. In an estimated 50–80% of cases involving back or neck pain, an underlying pathology cannot be definitively determined⁴. Regardless of the primary source of pain, the prognosis for individuals experiencing chronic neck pain is poor, as many patients continue to suffer from persistent pain and disability following conservative physical therapy intervention^5,6. Chronic neck pain appears to be more persistent than low back pain⁷, and it is second only to lumbar pain as the causal factor for time missed from work.Despite the prevalence, less-than optimal prognosis, associated risk of disability, and economic consequences of individuals suffering from mechanical neck pain, there remains a significant gap in the literature, which fails to provide sufficient, high-quality evidence to effectively guide the conservative treatment of this patient population⁸. This lack of quality evidence largely stems from the poorly understood clinical course of neck pain in conjunction with the inconclusive results related to the efficacy of commonly used interventions^2,9,10. Left with poorer quality trials as a guide, Physical Therapists approach the management of this pathology with a plethora of interventions such as manual therapy (MT), therapeutic exercises, manual/mechanical traction, modalities, massage, and functional training^5,10–12.One reason the outcomes in the PT literature may be less than impressive is that many of the studies looking at conservative treatments for the management of neck pain use a heterogeneous subject population¹³. Many studies also combine some or all of the following clinical manifestations into the same case mix during clinical trials: acute whiplash, subacute and chronic mechanical disorders, and chronic cervical headache. The identification of a homogeneous patient population would likely enhance the potential to initiate targeted interventions and to specifically assess treatment responses¹⁴. One solution to acquiring more homogeneous patient populations is the use of treatment-based classification (TBC) systems.Classification systems are developed with the intent of both directing treatment and improving clinical outcomes by identifying detailed combinations of treatments that specifically benefit a subgroup of patients presenting with certain characteristics^5,15. The principle supporting classification systems centers around the following notion: a decrease in uncertainty concerning appropriate, effective treatments could be observed via the linkage of an impairment diagnosis to a treatment choice¹⁶. Classification systems can also serve to improve clinical research by identifying evidence-based practice patterns for specified subgroups of patients⁵. The goal of this model is to heighten decision-making abilities of clinicians in relation to intervention strategy and prognosis¹⁶.While the classification-based strategy has been shown to yield optimal outcomes for the lumbar spine^17–20, comparatively nominal research has been performed to investigate patient outcomes using a similar classification-based approach for the cervical spine^5,16. Despite this preliminary work, research has not served to confirm the validity of such a system⁵. One recent study reported a 98% between-raters percentage agreement with the use of a proposed treatment-based classification (TBC) system (Figure ​(Figure11)⁵. This indicates that the algorithm could be applied consistently by different examiners who are considering the same patient data. With intent to assist in the validation of the outcomes using the aforementioned strategy, the purpose of this case study is to describe the use of a TBC system approach in the management of a single patient with mechanical neck pain and referred pain into the arm.Open in a separate windowFIGURE 1Proposed classification decision-making algorithm.⁵ MVA= motor vehicle accident, NDI = Neck Disability Index. Used with permission.