Predicting Successful Tapering of Biologic Therapy for Patients with Rheumatoid Arthritis in Remission – Why are we still using clinical remission criteria to inform decisions?

Remission is the optimum treatment target for patients with rheumatoid arthritis. With the advent of biologic therapies, and the use of treat to target strategies, many more patients are achieving remission. Once a patient has achieved a period of sustained remission, there is little to guide subsequent management and patients usually continue treatment long-term. This may be inappropriate. Recent evidence suggests that some patients may be able to reduce or even stop therapy however, the ideal patient profile is yet to be determined. Potential predictors have been identified, however have not entered routine clinical practice. There is a need for robust biomarkers to facilitate the prediction of successful tapering

The Combinatorial World (of Auctions) According to GARP

Revealed preference techniques are used to test whether a data set is compatible with rational behaviour. They are also incorporated as constraints in mechanism design to encourage truthful behaviour in applications such as combinatorial auctions. In the auction setting, we present an efficient combinatorial algorithm to find a virtual valuation function with the optimal (additive) rationality guarantee. Moreover, we show that there exists such a valuation function that both is individually rational and is minimum (that is, it is component-wise dominated by any other individually rational, virtual valuation function that approximately fits the data). Similarly, given upper bound constraints on the valuation function, we show how to fit the maximum virtual valuation function with the optimal additive rationality guarantee. In practice, revealed preference bidding constraints are very demanding. We explain how approximate rationality can be used to create relaxed revealed preference constraints in an auction. We then show how combinatorial methods can be used to implement these relaxed constraints. Worst/best-case welfare guarantees that result from the use of such mechanisms can be quantified via the minimum/maximum virtual valuation function

Welfare and Revenue Guarantees for Competitive Bundling Equilibrium

We study equilibria of markets with $m$ heterogeneous indivisible goods and $n$ consumers with combinatorial preferences. It is well known that a competitive equilibrium is not guaranteed to exist when valuations are not gross substitutes. Given the widespread use of bundling in real-life markets, we study its role as a stabilizing and coordinating device by considering the notion of \emph{competitive bundling equilibrium}: a competitive equilibrium over the market induced by partitioning the goods for sale into fixed bundles. Compared to other equilibrium concepts involving bundles, this notion has the advantage of simulatneous succinctness ($O(m)$ prices) and market clearance. Our first set of results concern welfare guarantees. We show that in markets where consumers care only about the number of goods they receive (known as multi-unit or homogeneous markets), even in the presence of complementarities, there always exists a competitive bundling equilibrium that guarantees a logarithmic fraction of the optimal welfare, and this guarantee is tight. We also establish non-trivial welfare guarantees for general markets, two-consumer markets, and markets where the consumer valuations are additive up to a fixed budget (budget-additive). Our second set of results concern revenue guarantees. Motivated by the fact that the revenue extracted in a standard competitive equilibrium may be zero (even with simple unit-demand consumers), we show that for natural subclasses of gross substitutes valuations, there always exists a competitive bundling equilibrium that extracts a logarithmic fraction of the optimal welfare, and this guarantee is tight. The notion of competitive bundling equilibrium can thus be useful even in markets which possess a standard competitive equilibrium

Dynamic multilateral markets

We study dynamic multilateral markets, in which players' payoffs result from intra-coalitional bargaining. The latter is modeled as the ultimatum game with exogenous (time-invariant) recognition probabilities and unanimity acceptance rule. Players in agreeing coalitions leave the market and are replaced by their replicas, which keeps the pool of market participants constant over time. In this infinite game, we establish payoff uniqueness of stationary equilibria and the emergence of endogenous cooperation structures when traders experience some degree of (heterogeneous) bargaining frictions. When we focus on market games with different player types, we derive, under mild conditions, an explicit formula for each type's equilibrium payoff as the market frictions vanish

High rate, fast timing Glass RPC for the high {\eta} CMS muon detectors

The HL-LHC phase is designed to increase by an order of magnitude the amount of data to be collected by the LHC experiments. To achieve this goal in a reasonable time scale the instantaneous luminosity would also increase by an order of magnitude up to $6.10^{34} cm^{-2} s^{-1}$ . The region of the forward muon spectrometer ($|{\eta}| > 1.6$) is not equipped with RPC stations. The increase of the expected particles rate up to $2 kHz/cm^{2}$ (including a safety factor 3) motivates the installation of RPC chambers to guarantee redundancy with the CSC chambers already present. The actual RPC technology of CMS cannot sustain the expected background level. The new technology that will be chosen should have a high rate capability and provides a good spatial and timing resolution. A new generation of Glass-RPC (GRPC) using low-resistivity (LR) glass is proposed to equip at least the two most far away of the four high ${\eta}$ muon stations of CMS. First the design of small size prototypes and studies of their performance in high-rate particles flux is presented. Then the proposed designs for large size chambers and their fast-timing electronic readout are examined and preliminary results are provided.Comment: 14 pages, 11 figures, Conference proceeding for the 2016 Resistive Plate Chambers and Related Detector

Unusual case of dorsal vertebral metastases from a male breast cancer

Introduction: Breast cancer is a malignant neoplasm arising from mammary glands and is a rare entity in the male patient. Spine is a common site for skeletal metastases. Case presentation: A 53-years-old male was admitted to our Neurosurgical unit because of an untreatable dorsal pain. He had been treated 3 years before for breast cancer. A dorsal Magnetic Resonance Imaging (MRI) evidenced pathological masses at T8 level. A total body Computed Tomography (CT) scan revealed lungs and liver metastases. After a multidisciplinary consult, a posterior T8 decompression, a radiofrequency thermoablation in T8 vertebral body followed by screws and rods fixation (T7-T9) was performed. Post-operative course was uneventful and the patient experienced a significant improvement of dorsal pain. Cycles of adjuvant chemo-radiotherapy followed. After 8 months, patient is still alive and in good general conditions but a spine MRI revealed a rapid and widespread diffusion of ostelytic metastases. Conclusion: Despite the high incidence of breast cancer metastases to the spine, very few clinical reports (just eight, whose only one treated surgically) in the literature deal specifically with metastases from male breast cancer, which is rarer and with a worst prognosis than female counterpart. In spite of the poor course, surgery still plays a role in treating these kind of malignancies and in improving quality of life