Thromboembolism prophylaxis during L-asparaginase therapy in acute lymphoblastic leukemia - time to reconsider current approaches?

Acute Lymphoblastic Leukemia (ALL) is the commonest malignancy in childhood with a second incidence peak in adulthood. Improvements in pediatric therapy including the addition of L-asparaginase (L-ASP) have enabled cure rates in excess of 90% to be achieved in children. More recently L-ASP-containing pediatric protocols are being used to treat younger adults with ALL and have improved survival by approximately 2-fold. However, a toxicity associated with L-ASP-containing therapy in ALL is venous thromboembolism (VTE) which is associated with significant morbidity in this patient population and results in interruptions in L-ASP therapy that can impact on survival outcomes. The incidence of VTE among adult patients with ALL receiving L-ASP containing therapy has been reported to be as high as 43%. Despite this, there is a lack of evidence-based recommendations for VTE prophylaxis in this clinical context; low-molecular weight heparin (LMWH) and/or AT replacement have mostly been used. The low-quality data and inconveniences associated with these VTE prophylaxis regimens highlight the need to evaluate alternatives such as direct oral anticoagulants for the prevention of L-ASP-associated VTE in ALL. This narrative will review the body of evidence on primary thromboprophylaxis in adult patients with ALL receiving L-ASP containing therapy.

Combined effects of HIV and obesity on the gastrointestinal microbiome of young men who have sex with men.

OBJECTIVES: The prevalence of obesity is rising among people living with HIV, which may synergistically increase inflammation and the risk of associated diseases. Disruption of gut bacterial communities may be one of the key drivers of this inflammation; however, the combined effects of HIV and obesity on the microbiome have not been explored. METHODS: This study included 381 men who have sex with men. Thirty-nine were HIV-positive and obese (H+O+), 143 were HIV-positive and nonobese, 64 were HIV-negative and obese, and 135 were HIV-negative and nonobese. Microbiome composition was assessed by targeted sequencing of the V4 region of the 16S ribosomal RNA (rRNA) gene using rectal swab samples. Inverse probability of treatment-weighted marginal structural models were used to investigate differences in microbial composition between groups while controlling for numerous clinical and behavioural confounders. RESULTS: Significant variability in microbial composition was explained by the combination of HIV and obesity, over and above each condition alone (R2 for the marginal contribution of the H+/O+ group = 0.008; P = 0.001). H+O+ participants had the highest ratios of Prevotella to Bacteroides, a pro-inflammatory enterotype that has been described in HIV infection and obesity independently. H+O+ participants had lower levels of Bacteroides and Veillonella than all other groups, suggesting a synergistic effect of HIV and obesity on these genera. CONCLUSIONS: Our findings support the hypothesis that HIV and obesity act together to disrupt gut microbial communities, which may help explain higher levels of generalized inflammation among people living with both HIV and obesity.

Study of inelastic nuclear interactions of 400 GeV/c protons in bent silicon crystals for beam steering purposes.

Inelastic nuclear interaction probability of 400 GeV/c protons interacting with bent silicon crystals was investigated, in particular for both types of crystals installed at the CERN Large Hadron Collider for beam collimation purposes. In comparison to amorphous scattering interaction, in planar channeling this probability is ∼ 36 % for the quasi-mosaic type (planes (111)), and ∼ 27 % for the strip type (planes (110)). Moreover, the absolute inelastic nuclear interaction probability in the axial channeling orientation, along the ⟨ 110 ⟩ axis, was estimated for the first time, finding a value of 0.6 % for a crystal 2 mm long along the beam direction, with a bending angle of 55 µ rad. This value is more than two times lower with respect to the planar channeling orientation of the same crystal, and increases with the vertical angular misalignment. Finally, the correlation between the inelastic nuclear interaction probability in the planar channeling and the silicon crystal curvature is reported.

Inappropriate sinus tachycardia: focus on ivabradine.

Inappropriate sinus tachycardia (IST) is an incompletely understood condition, characterised by an elevation in heart rate (HR) accompanied by wide ranging symptoms in the absence of an underlying physiological stimulus. The condition often takes a chronic course with significant adverse effects on quality of life. Currently, there is no effective treatment for IST. Beta-blockers, generally considered the cornerstone of treatment, are often ineffective and poorly tolerated. Ivabradine is a novel sinus node If 'funny current' inhibitor, which reduces the HR. It has been approved for the treatment of beta-blocker refractory chronic systolic heart failure and chronic stable angina but more recently has shown promise in the treatment of IST. This review provides an overview of IST prevalence and mechanisms followed by an examination of the evidence for the role and efficacy of ivabradine in the treatment of IST.

Beta-blocker, angiotensin-converting enzyme inhibitor/angiotensin receptor blocker, nitrate-hydralazine, diuretics, aldosterone antagonist, ivabradine, devices and digoxin (BANDAID(2) ): an evidence-based mnemonic for the treatment of systolic heart failure.

Heart failure causes significant morbidity and mortality, with recognised underutilisation rates of guideline-based therapies. Our aim was to review current evidence for heart failure treatments and derive a mnemonic summarising best practice, which might assist physicians in patient care. Treatments were identified for review from multinational society guidelines and recent randomised trials, with a primary aim of examining their effects in systolic heart failure patients on mortality, hospitalisation rates and symptoms. Secondary aims were to consider other clinical benefits. MEDLINE and EMBASE were searched using a structured keyword strategy and the retrieved articles were evaluated methodically to produce an optimised reference list for each treatment. We devised the mnemonic BANDAID (2) , standing for beta-blocker, angiotensin-converting enzyme inhibitor/angiotensin receptor blocker, nitrate-hydralazine (or potentially neprilysin inhibitor), diuretics, aldosterone antagonist, ivabradine, devices (automatic implantable cardioverter defibrillator, cardiac resynchronisation therapy or both) and digoxin as a representation of treatments with strong evidence for their use in systolic heart failure. Treatment with omega-3 fatty acids, statins or anti-thrombotic therapies has limited benefits in a general heart failure population. Adoption of this mnemonic for current evidence-based treatments for heart failure may help improve prescribing rates and patient outcomes in this debilitating, high mortality condition.

Neuron-adaptive higher order neural-network models for automated financial data modeling.

Real-world financial data is often nonlinear, comprises high-frequency multipolynomial components, and is discontinuous (piecewise continuous). Not surprisingly, it is hard to model such data. Classical neural networks are unable to automatically determine the optimum model and appropriate order for financial data approximation. We address this problem by developing neuron-adaptive higher order neural-network (NAHONN) models. After introducing one-dimensional (1-D), two-dimensional (2-D), and n-dimensional NAHONN models, we present an appropriate learning algorithm. Network convergence and the universal approximation capability of NAHONNs are also established. NAHONN Group models (NAHONGs) are also introduced. Both NAHONNs and NAHONGs are shown to be "open box" and as such are more acceptable to financial experts than classical (closed box) neural networks. These models are further shown to be capable of automatically finding not only the optimum model, but also the appropriate order for specific financial data.

Higherorder neural network group models for financial simulation.

Real world financial data is often discontinuous and non-smooth. If we attempt to use neural networks to simulate such functions, then accuracy will be a problem. Neural network group models perform this function much better. Both Polynomial Higher Order Neural network Group (PHONG) and Trigonometric polynomial Higher Order Neural network Group (THONG) models are developed. These HONG models are open box, convergent models capable of approximating any kind of piecewise continuous function, to any degree of accuracy. Moreover they are capable of handling higher frequency, higher order non-linear and discontinuous data. Results obtained using a Higher Order Neural network Group financial simulator are presented, which confirm that HONG group models converge without difficulty, and are considerably more accurate than neural network models (more specifically, around twice as good for prediction, and a factor of four improvement in the case of simulation).

Multicentre evaluation of a commercial test for the rapid diagnosis of Clostridium difficile-mediated antibiotic-associated diarrhoea.

An immunoassay for the detection of Clostridium difficile toxin A in stool samples (Clearview C. DIFF A; Unipath, UK) was evaluated against the cell cytotoxicity assay using 407 stool samples from patients suspected to have, or considered at risk of, antibiotic-associated diarrhoea. Of the samples tested, 98 were positive and 280 were negative by both tests (sensitivity 83.1%, specificity 96.9%). Following resolution of the 29 discrepant results, the sensitivity and specificity of the immunoassay were 91% and 98%, respectively, and the sensitivity for the cell cytotoxicity assay was calculated as 91.5%, with a specificity of 99%. The Clearview C. DIFF A test proved to be a rapid simple assay for the detection of Clostridium difficile toxin A in stool samples. The test was equally suited to single or batch testing, required minimal sample handling, and provided results within 30 min of applying the sample to the test unit.

Classification of user expertise level by neural networks.

A neural network approach to low-level user modeling is described, in the context of text editing tasks using the Jove editor. Knowledge of a user's expertise is extracted automatically, based on their interaction with Jove over a two week period. A MLP classifier which uses rprop learning and incorporates output data fuzzification is developed to classify users into one of five expertise levels. Classification into the correct level is achieved in around 80% of the cases, with misclassification being restricted to adjacent classes. The neurofuzzy system is seen to outperform not only the binary classifier of Beale [1989], but also production rule and inductive expert systems developed especially for comparison purposes in this study.

Did British society change character in the 1920s or the 1980s.

This is a response to Runciman's reply to my critique of his 1993 article. I argue that although the First World War brought about many changes in British society, it did not initiate a new stage in its development, for these changes were largely an acceleration of existing tendencies. Runciman's argument that the similarities between the 1930s and the 1980s show that British capitalism was essentially the same in both periods does not allow for the different directions in which British society was moving in the 1930s and in the 1980s. His treatment of the 1980s changes as another phase in the political cycle fails to grasp what was new about the 1980s or locate these changes in their wider economic and global context.

Face recognition using artificial neural network group-based adaptive tolerance (GAT) trees.

Recent artificial neural network research has focused on simple models, but such models have not been very successful in describing complex systems (such as face recognition). This paper introduces the artificial neural network group-based adaptive tolerance (GAT) tree model for translation-invariant face recognition, suitable for use in an airport security system. GAT trees use a two-stage divide-and-conquer tree-type approach. The first stage determines general properties of the input, such as whether the facial image contains glasses or a beard. The second stage identifies the individual. Face perception classification, detection of front faces with glasses and/or beards, and face recognition results using GAT trees under laboratory conditions are presented. We conclude that the neural network group-based model offers significant improvement over conventional neural network trees for this task.

An application of Hamiltonian neurodynamics using Pontryagin's Maximum (Minimum) Principle.

Classical optimal control methods, notably Pontryagin's Maximum (Minimum) Principle (PMP) can be employed, together with Hamiltonians, to determine optimal system weights in Artificial Neural dynamical systems. A new learning rule based on weight equations derived using PMP is shown to be suitable for both discrete- and continuous-time systems, and moreover, can also be applied to feedback networks. Preliminary testing shows that this PMP learning rule compares favorably with Standard BackPropagations (SBP) on the XOR problem.

Analysis of cyclopentafused isomers of benz(a)anthracene in wood smoke.

A previously-unidentified peak occurring in chromatograms of the polycyclic aromatic hydrocarbon fraction from wood smoke particulate extracts analysed by capillary gas chromatography on a DB-5 column was found to correspond in retention index and molecular mass either to benzo(a)fluoranthene or to benzo(1)aceanthrylene, one of a series of four novel and highly mutagenic cyclopentafused isomers of benz(a)anthracene. Detailed subfractionation, and re-analysis on a liquid crystal capillary column, indicated that the identity of this peak was most likely to be benzo(a)fluoranthene, a compound not previously reported in woodsmoke.

Hospital-health care plan affiliations: considerations for strategy design.

Hospital-health care plan affiliations are designed to use idle hospital service capacity while minimizing the resulting financial risks.