Sphingolipid metabolism products: potential new players in the pathogenesis of bortezomib-induced neuropathic pain

Chemotherapy-induced peripheral neurotoxicity (CIPN) is one of the major dose-limiting adverse events of widely used drugs in both the oncologic and hematologic setting (1). Among its cardinal symptoms, neuropathic pain is frequently present (2). In particular, the incidence of bortezomib-induced peripheral neurotoxicity (BIPN) and neuropathic pain ranges from 14–45% and 5–39%, respectively, in myeloma multiple patients. BIPN is more frequently developed in pretreated patients, compared to those being chemotherapy-naïve (3,4), and this difference mostly accounts for the wide variability in the observed incidence rates. Bortezomib is the first proteasome inhibitor introduced in clinical practice. The mechanisms underlying the pathogenesis of peripheral neurotoxicity in bortezomib- treated patients are, yet, not fully elucidated (3,4)

Inconclusive evidence to support the use of minimally-invasive radiofrequency denervation against chronic low back pain

Low back pain (LBP), defined as the localized pain or discomfort between the costal margins and superior gluteal line, with or without associated lower limb pain, is one of the most commonly encountered pain syndromes in adults. It is considered chronic LBP (CLBP), when pain persists for more than three months (1). CLBP might be disabling with increased missing hours of productive work or of personal activities and it can also be associated with significant excess of healthcare costs (2). Commonly, CLBP also gives rise to the genesis or exacerbation of various psychiatric disorders, such as depression and/or anxiety (3)

On Sparsity Inducing Regularization Methods for Machine Learning

During the past years there has been an explosion of interest in learning methods based on sparsity regularization. In this paper, we discuss a general class of such methods, in which the regularizer can be expressed as the composition of a convex function $\omega$ with a linear function. This setting includes several methods such the group Lasso, the Fused Lasso, multi-task learning and many more. We present a general approach for solving regularization problems of this kind, under the assumption that the proximity operator of the function $\omega$ is available. Furthermore, we comment on the application of this approach to support vector machines, a technique pioneered by the groundbreaking work of Vladimir Vapnik.Comment: 12 pages. arXiv admin note: text overlap with arXiv:1104.143

Predictive Biomarkers of Oxaliplatin-Induced Peripheral Neurotoxicity

Oxaliplatin (OXA) is a platinum compound primarily used in the treatment of gastrointestinal cancer. OXA-induced peripheral neurotoxicity (OXAIPN) is the major non-hematological dose-limiting toxicity of OXA-based chemotherapy and includes acute transient neurotoxic effects that appear soon after OXA infusion, and chronic non-length dependent sensory neuronopathy symmetrically affecting both upper and lower limbs in a stocking-and-glove distribution. No effective strategy has been established to reverse or treat OXAIPN. Thus, it is necessary to early predict the occurrence of OXAIPN during treatment and possibly modify the OXA-based regimen in patients at high risk as an early diagnosis and intervention may slow down neuropathy progression. However, identifying which patients are more likely to develop OXAIPN is clinically challenging. Several objective and measurable early biomarkers for OXAIPN prediction have been described in recent years, becoming useful for informing clinical decisions about treatment. The purpose of this review is to critically review data on currently available or promising predictors of OXAIPN. Neurological monitoring, according to predictive factors for increased risk of OXAIPN, would allow clinicians to personalize treatment, by monitoring at-risk patients more closely and guide clinicians towards better counseling of patients about neurotoxicity effects of OXA

Efficient First Order Methods for Linear Composite Regularizers

A wide class of regularization problems in machine learning and statistics employ a regularization term which is obtained by composing a simple convex function omega with a linear transformation. This setting includes Group Lasso methods, the Fused Lasso and other total variation methods, multi-task learning methods and many more. In this paper, we present a general approach for computing the proximity operator of this class of regularizers, under the assumption that the proximity operator of the function \omega is known in advance. Our approach builds on a recent line of research on optimal first order optimization methods and uses fixed point iterations for numerically computing the proximity operator. It is more general than current approaches and, as we show with numerical simulations, computationally more efficient than available first order methods which do not achieve the optimal rate. In particular, our method outperforms state of the art O(1/T) methods for overlapping Group Lasso and matches optimal O(1/T2) methods for the Fused Lasso and tree structured Group Lasso

The effect of stimulation technique on sympathetic skin responses in healthy subjects

The aim of this study was to collect normative data for sympathetic skin responses (SSR) elicited by electrical stimulus of the ipsilateral and contralateral peripheral nerves, and by magnetic stimulus of cervical cord. SSRs were measured at the mid-palm of both hands following electrical stimulation of the left median nerve at the wrist and magnetic stimulation at the neck in 40 healthy adult volunteers (mean age 52.2 ± 12.2 years, 19 males). The onset latency, peak latency, amplitude and area were estimated in “P” type responses (i.e., waveforms with a larger positive, compared to negative, component). SSR onset and peak latency were prolonged when the electrical stimulus was applied at the contralateral side (i.e., the SSR recorded in the right palm P < 0.001). The onset latency was similar on both sides during cervical magnetic stimulation. However, peak latency was faster on the left side (P < 0.03). Comparison of electrical and magnetic stimulation revealed that both the onset and peak latency were shorter with magnetic stimulation (P < 0.001). The latency of a SSR varies depending on what type of stimulation is used and where the stimulus is applied. Electrically generated SSRs have a longer delay and the delay is prolonged at the contralateral side. These factors should be taken into account when interpreting SSR data

Considerations for establishing and maintaining international research collaboration: the example of chemotherapy-induced peripheral neurotoxicity (CIPN)—a white paper

PurposeThis white paper provides guidance regarding the process for establishing and maintaining international collaborations to conduct oncology/neurology-focused chemotherapy-induced peripheral neurotoxicity (CIPN) research.MethodsAn international multidisciplinary group of CIPN scientists, clinicians, research administrators, and legal experts have pooled their collective knowledge regarding recommendations for establishing and maintaining international collaboration to foster advancement of CIPN science.ResultsExperts provide recommendations in 10 categories: (1) preclinical and (2) clinical research collaboration; (3) collaborators and consortiums; (4) communication; (5) funding; (6) international regulatory standards; (7) staff training; (8) data management, quality control, and data sharing; (9) dissemination across disciplines and countries; and (10) additional recommendations about feasibility, policy, and mentorship.ConclusionRecommendations to establish and maintain international CIPN research collaboration will promote the inclusion of more diverse research participants, increasing consideration of cultural and genetic factors that are essential to inform innovative precision medicine interventions and propel scientific discovery to benefit cancer survivors worldwide.Relevance to inform research policyOur suggested guidelines for establishing and maintaining international collaborations to conduct oncology/neurology-focused chemotherapy-induced peripheral neurotoxicity (CIPN) research set forth a challenge to multinational science, clinical, and policy leaders to (1) develop simple, streamlined research designs; (2) address logistical barriers; (3) simplify and standardize regulatory requirements across countries; (4) increase funding to support international collaboration; and (5) foster faculty mentorship

Similarities between structural distortions under pressure and chemical doping in superconducting BaFe2As2

The discovery of a new family of high Tc materials, the iron arsenides (FeAs), has led to a resurgence of interest in superconductivity. Several important traits of these materials are now apparent, for example, layers of iron tetrahedrally coordinated by arsenic are crucial structural ingredients. It is also now well established that the parent non-superconducting phases are itinerant magnets, and that superconductivity can be induced by either chemical substitution or application of pressure, in sharp contrast to the cuprate family of materials. The structure and properties of chemically substituted samples are known to be intimately linked, however, remarkably little is known about this relationship when high pressure is used to induce superconductivity in undoped compounds. Here we show that the key structural features in BaFe2As2, namely suppression of the tetragonal to orthorhombic phase transition and reduction in the As-Fe-As bond angle and Fe-Fe distance, show the same behavior under pressure as found in chemically substituted samples. Using experimentally derived structural data, we show that the electronic structure evolves similarly in both cases. These results suggest that modification of the Fermi surface by structural distortions is more important than charge doping for inducing superconductivity in BaFe2As2

Pressure-induced magnetic transition and volume collapse in FeAs superconductors: An orbital-selective Mott scenario

Motivated by pressure experiments on FeAs-122 superconductors, we propose a scenario based on local-moment physics to explain the simultaneous disappearance of magnetism, reduction of the unit cell volume, and decrease in resistivity. In this scenario, the low-pressure magnetic phase derives from Fe moments, which become screened in the paramagnetic high-pressure phase. The quantum phase transition can be described as an orbital-selective Mott transition, which is rendered first order by coupling to the lattice, in analogy to a Kondo volume collapse. Spin-fluctuation driven superconductivity competes with antiferromagnetism and may be stabilized at low temperatures in the high-pressure phase. The ideas are illustrated by a suitable mean-field analysis of an Anderson lattice model.Comment: 9 pages, 3 figs; (v2) robustness of OS Mott transition vs. fragility of superconductivity discussed, final version to be publishe