Diagnostic performance of line-immunoassay based algorithms for incident HIV-1 infection

Background Serologic testing algorithms for recent HIV seroconversion (STARHS) provide important information for HIV surveillance. We have previously demonstrated that a patient's antibody reaction pattern in a confirmatory line immunoassay (INNO-LIA™ HIV I/II Score) provides information on the duration of infection, which is unaffected by clinical, immunological and viral variables. In this report we have set out to determine the diagnostic performance of Inno-Lia algorithms for identifying incident infections in patients with known duration of infection and evaluated the algorithms in annual cohorts of HIV notifications. Methods Diagnostic sensitivity was determined in 527 treatment-naive patients infected for up to 12 months. Specificity was determined in 740 patients infected for longer than 12 months. Plasma was tested by Inno-Lia and classified as either incident (< = 12 m) or older infection by 26 different algorithms. Incident infection rates (IIR) were calculated based on diagnostic sensitivity and specificity of each algorithm and the rule that the total of incident results is the sum of true-incident and false-incident results, which can be calculated by means of the pre-determined sensitivity and specificity. Results The 10 best algorithms had a mean raw sensitivity of 59.4% and a mean specificity of 95.1%. Adjustment for overrepresentation of patients in the first quarter year of infection further reduced the sensitivity. In the preferred model, the mean adjusted sensitivity was 37.4%. Application of the 10 best algorithms to four annual cohorts of HIV-1 notifications totalling 2'595 patients yielded a mean IIR of 0.35 in 2005/6 (baseline) and of 0.45, 0.42 and 0.35 in 2008, 2009 and 2010, respectively. The increase between baseline and 2008 and the ensuing decreases were highly significant. Other adjustment models yielded different absolute IIR, although the relative changes between the cohorts were identical for all models. Conclusions The method can be used for comparing IIR in annual cohorts of HIV notifications. The use of several different algorithms in combination, each with its own sensitivity and specificity to detect incident infection, is advisable as this reduces the impact of individual imperfections stemming primarily from relatively low sensitivities and sampling bias.

Weak Senses as a Type of Semantic Information

'Weak senses' are a specific type of semantic information as opposed to assertions and presuppositions. The universal trait of weak senses is that they assume 'if' modality in negative contexts. In addition they exhibit several other diagnostic properties, e.g. they fill at least one of their valency places with a semantic element sensitive to negation (i.e. with an assertion or other weak sense), they normally do not fall within the scope of functors, do not play any role in causal relations, and resist intensification. As weak senses are widespread in lexical, grammatical and referential semantics, this notion holds the clue to phenomena as diverse as the oppositions little - a little, few - a few, edva ('hardly') - cut' ('slightly), where a little, a few, cut, convey 'weakly' approximately what little, few, and edva do in an assertive way, the semantics of the Russian perfect aspect, and the formation rules for conjunction strings. Zeldovich outlines a typology of weak senses, the main distinction being between weak senses unilaterally dependent upon the truthfulness of what they saturate their valency with, and weak senses exerting their own influence on the main situation. The latter, called, non-trivial, are instantiated by existential quantifiers involved in the semantics of indefinite pronouns, iterative verbs, etc.

High-resolution computer simulations of stacking of weak bases using a transient pH boundary in capillary electrophoresis. 1. Concept and impact of sample ionic strength

The dynamics of focusing weak bases using a transient pH boundary was examined via high-resolution computer simulation software. Emphasis was placed on the mechanism and impact that the presence of salt, namely, NaCl, has on the ability to focus weak bases. A series of weak bases with mobilities ranging from 5 x 10(-9) to 30 x 10(-9) m2/V x s and pKa values between 3.0 and 7.5 were examined using a combination of 65.6 mM formic acid, pH 2.85, for the separation electrolyte, and 65.6 mM formic acid, pH 8.60, for the sample matrix. Simulation data show that it is possible to focus weak bases with a pKa value similar to that of the separation electrolyte, but it is restricted to weak bases having an electrophoretic mobility of 20 x 10(-9) m2/V x s or quicker. This mobility range can be extended by the addition of NaCl, with 50 mM NaCl allowing stacking of weak bases down to a mobility of 15 x 10(-9) m2/V x s and 100 mM extending the range to 10 x 10(-9) m2/V x s. The addition of NaCl does not adversely influence focusing of more mobile bases, but does prolong the existence of the transient pH boundary. This allows analytes to migrate extensively through the capillary as a single focused band around the transient pH boundary until the boundary is dissipated. This reduces the length of capillary that is available for separation and, in extreme cases, causes multiple analytes to be detected as a single highly efficient peak.

Application and comparison of classification algorithms for recognition of Alzheimer's disease in electrical brain activity (EEG)

The early detection of subjects with probable Alzheimer's disease (AD) is crucial for effective appliance of treatment strategies. Here we explored the ability of a multitude of linear and non-linear classification algorithms to discriminate between the electroencephalograms (EEGs) of patients with varying degree of AD and their age-matched control subjects. Absolute and relative spectral power, distribution of spectral power, and measures of spatial synchronization were calculated from recordings of resting eyes-closed continuous EEGs of 45 healthy controls, 116 patients with mild AD and 81 patients with moderate AD, recruited in two different centers (Stockholm, New York). The applied classification algorithms were: principal component linear discriminant analysis (PC LDA), partial least squares LDA (PLS LDA), principal component logistic regression (PC LR), partial least squares logistic regression (PLS LR), bagging, random forest, support vector machines (SVM) and feed-forward neural network. Based on 10-fold cross-validation runs it could be demonstrated that even tough modern computer-intensive classification algorithms such as random forests, SVM and neural networks show a slight superiority, more classical classification algorithms performed nearly equally well. Using random forests classification a considerable sensitivity of up to 85% and a specificity of 78%, respectively for the test of even only mild AD patients has been reached, whereas for the comparison of moderate AD vs. controls, using SVM and neural networks, values of 89% and 88% for sensitivity and specificity were achieved. Such a remarkable performance proves the value of these classification algorithms for clinical diagnostics.

Minimal assumption derivation of a weak Clauser-Horne inequality

According to Bell's theorem a large class of hidden-variable models obeying Bell's notion of local causality (LC) conflict with the predictions of quantum mechanics. Recently, a Bell-type theorem has been proven using a weaker notion of LC, yet assuming the existence of perfectly correlated event types. Here we present a similar Bell-type theorem without this latter assumption. The derived inequality differs from the Clauser-Horne inequality by some small correction terms, which render it less constraining.

Algorithms for autonomous tandem operation of a dual M113 system

In mid-July 2003, the U.S. Army Tank-Automotive & Armaments Command (TACOM) performed a series of experiments at Keweenaw Research Center (KRC), with a remote operated mine roller system. This system, named Panther Lite, consists of two M113 Armored Personnel Carriers (APC’s) connected by a Tandem Vehicle Linkage Assembly (TVLA). The system has three sets of mine rollers, two of which are connected to the front of the lead vehicle with one set trailing from the trail vehicle. Currently, the system requires two joystick controllers. One regulates the braking of the tracks, throttle, and transmission of the lead vehicle and the other controls the braking and throttle of the rear vehicle. One operator controls both joysticks, attempting to maneuver the lead vehicle along a desired path. At the same time, this operator makes compensation maneuvers to reduce lateral loads in the TVLA and to guide the rear mine rollers along the desired path. The purpose of this project is to create algorithms that would allow the slave (trail) vehicle to operate using inputs that maneuver the control (lead) vehicle. The project will be completed by first reconstructing the experimental data. Kinematic models will be generated and simulations created. The models will then be correlated with the reconstructions of the experimental data. The successful completion of this project will be a first step to eliminating the need for the second joystick.

Control algorithms for large scale adaptive optics

In this dissertation, the problem of creating effective large scale Adaptive Optics (AO) systems control algorithms for the new generation of giant optical telescopes is addressed. The effectiveness of AO control algorithms is evaluated in several respects, such as computational complexity, compensation error rejection and robustness, i.e. reasonable insensitivity to the system imperfections. The results of this research are summarized as follows: 1. Robustness study of Sparse Minimum Variance Pseudo Open Loop Controller (POLC) for multi-conjugate adaptive optics (MCAO). The AO system model that accounts for various system errors has been developed and applied to check the stability and performance of the POLC algorithm, which is one of the most promising approaches for the future AO systems control. It has been shown through numerous simulations that, despite the initial assumption that the exact system knowledge is necessary for the POLC algorithm to work, it is highly robust against various system errors. 2. Predictive Kalman Filter (KF) and Minimum Variance (MV) control algorithms for MCAO. The limiting performance of the non-dynamic Minimum Variance and dynamic KF-based phase estimation algorithms for MCAO has been evaluated by doing Monte-Carlo simulations. The validity of simple near-Markov autoregressive phase dynamics model has been tested and its adequate ability to predict the turbulence phase has been demonstrated both for single- and multiconjugate AO. It has also been shown that there is no performance improvement gained from the use of the more complicated KF approach in comparison to the much simpler MV algorithm in the case of MCAO. 3. Sparse predictive Minimum Variance control algorithm for MCAO. The temporal prediction stage has been added to the non-dynamic MV control algorithm in such a way that no additional computational burden is introduced. It has been confirmed through simulations that the use of phase prediction makes it possible to significantly reduce the system sampling rate and thus overall computational complexity while both maintaining the system stable and effectively compensating for the measurement and control latencies.

Pelvic radiography in ATLS algorithms: A diminishing role?

ABSTRACT: BACKGROUND: Pelvic x-ray is a routine part of the primary survey of polytraumatized patients according to Advanced Trauma Life Support (ATLS) guidelines. However, pelvic CT is the gold standard imaging technique in the diagnosis of pelvic fractures. This study was conducted to confirm the safety of a modified ATLS algorithm omitting pelvic x-ray in hemodynamically stable polytraumatized patients with clinically stable pelvis in favour of later pelvic examination by CT scan. METHODS: We conducted a retrospective analysis of all polytraumatized patients in our emergency room between 01.07.2004 and 31.01.2006. Inclusion criteria were blunt abdominal trauma, initial hemodynamic stability and a stable pelvis on clinical examination. We excluded patients requiring immediate intervention because of hemodynamic instability. RESULTS: We reviewed the records of n = 452 polytraumatized patients, of which n = 91 fulfilled inclusion criteria (56% male, mean age = 45 years). The mechanism of trauma included 43% road traffic accidents, 47% falls. In 68/91 (75%) patients, both a pelvic x-ray and a CT examination were performed; the remainder had only pelvic CT. In 6/68 (9%) patients, pelvic fracture was diagnosed by pelvic x-ray. None of these 6 patients was found having a false positive pelvic x-ray, i.e. there was no fracture on pelvic CT scan. In 3/68 (4%) cases a fracture was missed in the pelvic x-ray, but confirmed on CT (false negative on x-ray). None of the diagnosed fractures needed an immediate therapeutic intervention. 5 (56%) were classified type A fractures, and another 4 (44%) B 2.1 in computed tomography (AO classification). One A 2.1 fracture was found in a clinically stable patient who only received CT scan (1/23). CONCLUSION: While pelvic x-ray is an integral part of ATLS assessment, this retrospective study suggests that in hemodynamically stable patients with clinically stable pevis, its sensitivity is only 67% and it may safely be omitted in favor of a pelvic CT examination if such is planned in adjunct assessment and available. The results support the safety and utility of our modified ATLS algorithm. A randomized controlled trial using the algorithm can safely be conducted to confirm the results.