Comparision and Optimisation of Wang Landau's Algorithm and Novel Chain Growth Method for HP-Proteins

Ett viktigt område inom forskning är att förstå hur proteiner viker sig till sitt grundtillstånd. Även med grova förenklingar är detta känt för att vara ett beräkningsmässigt svårt problem. I detta arbete har vi implementerat Wang-Landaus algoritm och en egenutvecklad metod för att hitta grundtillståndet för HP-proteiner (en enkel proteinmodell). Målet har varit att optimera dessa för körtid och jämföra dem för olika testproteiner. Vi har lyckats dra slutsatser om optimala parametervärden för båda metoderna och jämfört resultaten med tidigare studiers, och även låtit metoderna behandla ett manuellt designat protein. Vi har till exempel konstaterat att det ofta är gynnsamt att köra flera, kortare repetitioner av Wang-Landaus algoritm än en lång. Dessutom har vi hittat scenarier där vår egen metod presterar bättre än Wang Landau.A main research area in medicine is the simulation of proteins, as efficient simulation techniques for finding proteins' ground states would enable partial automation of drug development and greatly decrease development time. Even with rough simplifications finding the ground state is task well known for being difficult. In this project we have implemented and studied two methods for folding HP lattice proteins (a simple protein model), the Wang-Landau Monte Carlo method and a self-developed chain growth method. We have made an attempt to make general optimizations for these two methods, as well as comparing our Wang-Landau implementation with previously known results, and test the methods' ability to find the ground state of a manually designed HP-protein. We have been able to propose optimal parameter values for both methods with regards to the computational time needed to find the ground state. For example, it turns out to be advantageous to run multiple smaller Wang-Landau simulations rather than one large. We have also proved that our method is able to find ground states, and in certain scenarios is faster and more reliable than the Wang-Landau method

Mandibular Metastases of Papillary Thyroid Carcinoma Treated by Hemimandibulectomy and Costochondral Rib Graft

Summary: Papillary thyroid carcinoma (PTC) is the most common and well-differentiated cancer of the thyroid. Unlike most cancers, spread to local lymph node does not worsen the survival rate of PTC, and complete resection of the metastases seems to be important and may have favorable effects on the prognosis. A 33-year-old woman was referred to our clinic with a mass involving the right angulus mandible. Incisional biopsy of the mass diagnosed follicular variant of papillary thyroid carcinoma. Right hemimandibulectomy was performed and reconstructed with costochondral rib graft. The patient survived for 5 years after the hemimandibulectomy. Metastases to the oral cavity indicate a grave prognosis, but PTC has relatively indolent biological behavior; long-term survival is usually possible even in patients with metastatic disease

RNA sequencing-based single sample predictors of molecular subtype and risk of recurrence for clinical assessment of early-stage breast cancer

Multigene assays for molecular subtypes and biomarkers can aid management of early invasive breast cancer. Using RNA-sequencing we aimed to develop single-sample predictor (SSP) models for clinical markers, subtypes, and risk of recurrence (ROR). A cohort of 7743 patients was divided into training and test set. We trained SSPs for subtypes and ROR assigned by nearest-centroid (NC) methods and SSPs for biomarkers from histopathology. Classifications were compared with Prosigna in two external cohorts (ABiM, n = 100 and OSLO2-EMIT0, n = 103). Prognostic value was assessed using distant recurrence-free interval. Agreement between SSP and NC for PAM50 {five subtypes) was high (85%, Kappa = 0.78) for Subtype (four subtypes) very high {90%, Kappa = 0.84) and for ROR risk category high (84%, Kappa = 0.75, weighted Kappa = 0.90). Prognostic value was assessed as equivalent and clinically relevant. Agreement with histopathology was very high or high for receptor status, while moderate for Ki67 status and poor for Nottingham histological grade. SSP and Prosigna concordance was high for subtype (OSLO-EMIT0 83%, Kappa = 0.73 and ABiM 80%, Kappa = 0.72) and moderate and high for ROR risk category (68 and 84%, Kappa = 0.50 and 0.70, weighted Kappa = 0.70 and 0.78). Pooled concordance for emulated treatment recommendation dichotomized for chemotherapy was high (85%, Kappa = 0.66). Retrospective evaluation suggested that SSP application could change chemotherapy recommendations for up to 17% of postmenopausal ER+/HER2-/N0 patients with balanced escalation and de-escalation. Results suggest that NC and SSP models are interchangeable on a group-level and nearly so on a patient level and that SSP models can be derived to closely match clinical tests

Running title: Improved survival for women with stage I breast cancer

Improved survival for women with stage I breast cancer in south-east Sweden: A comparison between two time periods before and after increased use of adjuvant systemic therap