Parathyroid hormone venous sampling prior to reoperation for primary hyperparathyroidism

Background: The surgical cure rate for primary hyperparathyroidism is greater than 95%. For those who have recurrent or persistent disease, preoperative localization improves reoperation success rates. Selective parathyroid venous sampling (SPVS) for intact parathyroid hormone is particularly useful when non-invasive localization techniques are negative or inconclusive. Methods: We present all known cases (n = 13) between 1994 and 2002 who had venous sampling for localization at our institution prior to reoperation for recurrent or persistent primary hyperparathyroidism. Comparison was made with non-invasive localization procedures. Results of invasive and non-invasive localization were correlated with surgical findings. Results: Of the nine reoperated cases, eight had positive correlations between SPVS and operative findings and histopathology. SPVS did not reveal the parathyroid hormone source in one case with negative non-invasive localization procedures. Comparisons between SPVS, computerized tomography (CT), and parathyroid scintigraphy (MIBI) as expressed in terms of true positive (TP), false positive (FP) and false negative (FN) were: SPVS - TP 88.8%, FP 0%, FN 11.1%; CT - TP 22.2%, FP 22.2%, FN 55.5%; and MIBI - TP 33.3%, FP 0%, FN 66.6%. At least seven of the nine operated cases have been cured; another remained normocalcaemic 2 weeks after subtotal parathyroidectomy. Conclusion: In our institution SPVS has proven to be a valuable tool in cases with recurrent or persistent primary hyperparathyroidism and negative non-invasive localization procedures.

SPAnDX: a process-based population dynamics model to explore management and climate change impacts on an invasive alien plant, Acacia nilotica

This paper describes a process-based metapopulation dynamics and phenology model of prickly acacia, Acacia nilotica, an invasive alien species in Australia. The model, SPAnDX, describes the interactions between riparian and upland sub-populations of A. nilotica within livestock paddocks, including the effects of extrinsic factors such as temperature, soil moisture availability and atmospheric concentrations of carbon dioxide. The model includes the effects of management events such as changing the livestock species or stocking rate, applying fire, and herbicide application. The predicted population behaviour of A. nilotica was sensitive to climate. Using 35 years daily weather datasets for five representative sites spanning the range of conditions that A. nilotica is found in Australia, the model predicted biomass levels that closely accord with expected values at each site. SPAnDX can be used as a decision-support tool in integrated weed management, and to explore the sensitivity of cultural management practices to climate change throughout the range of A. nilotica. The cohort-based DYMEX modelling package used to build and run SPAnDX provided several advantages over more traditional population modelling approaches (e.g. an appropriate specific formalism (discrete time, cohort-based, process-oriented), user-friendly graphical environment, extensible library of reusable components, and useful and flexible input/output support framework). (C) 2003 Published by Elsevier Science B.V.

Photon-added detection

The production of conditional quantum states and quantum operations based on the result of measurement is now seen as a key tool in quantum information and metrology. We propose a different type of photon number detector. It functions nondeterministically, but when successful, it has high fidelity. The detector, which makes use of an n-photon auxiliary Fock state and high efficiency homodyne detection, allows a tunable trade-off between fidelity and probability. By sacrificing probability of operation, an excellent approximation to a photon-number detector is achieved.