How value-glamour investors use financial information: UK evidence of investor's confirmation bias

The paper investigates investor’s behaviour in the context of value–glamour investing and fundamental analysis, and provides a direct test of the confirmation bias by bringing together the evidence from several strands of literature into a well-defined framework of investor behaviour. The empirical evidence presented is in line with a model of investor’s asymmetric reaction to good and bad news due to confirmation bias. Pessimistic value investors typically under-react to good financial information, but they process bad information rationally or over-confidently. On the contrary, glamour investors are often too optimistic to timely update prices following bad financial information, but they are likely to fairly price or even over-react when receiving good information

Probabilistic modeling of personalized drug combinations from integrated chemical screen and molecular data in sarcoma

BACKGROUND: Cancer patients with advanced disease routinely exhaust available clinical regimens and lack actionable genomic medicine results, leaving a large patient population without effective treatments options when their disease inevitably progresses. To address the unmet clinical need for evidence-based therapy assignment when standard clinical approaches have failed, we have developed a probabilistic computational modeling approach which integrates molecular sequencing data with functional assay data to develop patient-specific combination cancer treatments. METHODS: Tissue taken from a murine model of alveolar rhabdomyosarcoma was used to perform single agent drug screening and DNA/RNA sequencing experiments; results integrated via our computational modeling approach identified a synergistic personalized two-drug combination. Cells derived from the primary murine tumor were allografted into mouse models and used to validate the personalized two-drug combination. Computational modeling of single agent drug screening and RNA sequencing of multiple heterogenous sites from a single patient's epithelioid sarcoma identified a personalized two-drug combination effective across all tumor regions. The heterogeneity-consensus combination was validated in a xenograft model derived from the patient's primary tumor. Cell cultures derived from human and canine undifferentiated pleomorphic sarcoma were assayed by drug screen; computational modeling identified a resistance-abrogating two-drug combination common to both cell cultures. This combination was validated in vitro via a cell regrowth assay. RESULTS: Our computational modeling approach addresses three major challenges in personalized cancer therapy: synergistic drug combination predictions (validated in vitro and in vivo in a genetically engineered murine cancer model), identification of unifying therapeutic targets to overcome intra-tumor heterogeneity (validated in vivo in a human cancer xenograft), and mitigation of cancer cell resistance and rewiring mechanisms (validated in vitro in a human and canine cancer model). CONCLUSIONS: These proof-of-concept studies support the use of an integrative functional approach to personalized combination therapy prediction for the population of high-risk cancer patients lacking viable clinical options and without actionable DNA sequencing-based therapy

Labor And The Politics Of Structural Adjustment In Australia And Indonesia

The labour forces of Australia and Indonesia are compared for the period from the late 1960s to the 1990s. The position of labour in a global economy is also considered. It is determined that the outlook for organised labour is bleak, however its position is also contingent upon national circumstance

Evaluation of tuberculosis surveillance in Satun Province, Thailand, July 2011

Three main tuberculosis (TB) reporting systems were operating in Thailand: notifiable disease surveillance (R506), TB registration and control in Bureau of Tuberculosis (BTB) and TB report for reimbursement in National Health Security Office (NHSO). A cross-sectional study was conducted in Satun Province in July 2011 to determine whether the three systems responded well to the objectives of TB surveillance. Patients diagnosed with TB and received anti-TB drugs at least once in 2010 from three hospitals were compared with TB cases reported in three systems. In the hospitals, 170 TB cases, including 95 new smear positive pulmonary TB cases, were reviewed. Coverage and positive predictive value were 73% and 83% for R506, 87% and 100% for BTB, and 79% and 99% for NHSO respectively. Success rate (82%) of all cases was lower than that was reported in BTB (96%). Median duration from diagnosis to reporting in R506, BTB and NHSO were six, 61 and two days respectively. All systems had sufficient budget, human resources and regular training. In addition, all systems had good capacity to achieve the major objectives of TB surveillance and their specific objectives. However, the systems had total 295 variables which resulted in high workload for reporting. Integrating three systems as one national TB reporting system was recommended to improve coverage, timeliness and success rate