Flexible Modeling of Epidemics with an Empirical Bayes Framework

Seasonal influenza epidemics cause consistent, considerable, widespread loss annually in terms of economic burden, morbidity, and mortality. With access to accurate and reliable forecasts of a current or upcoming influenza epidemic’s behavior, policy makers can design and implement more effective countermeasures. This past year, the Centers for Disease Control and Prevention hosted the “Predict the Influenza Season Challenge”, with the task of predicting key epidemiological measures for the 2013–2014 U.S. influenza season with the help of digital surveillance data. We developed a framework for in-season forecasts of epidemics using a semiparametric Empirical Bayes framework, and applied it to predict the weekly percentage of outpatient doctors visits for influenza-like illness, and the season onset, duration, peak time, and peak height, with and without using Google Flu Trends data. Previous work on epidemic modeling has focused on developing mechanistic models of disease behavior and applying time series tools to explain historical data. However, tailoring these models to certain types of surveillance data can be challenging, and overly complex models with many parameters can compromise forecasting ability. Our approach instead produces possibilities for the epidemic curve of the season of interest using modified versions of data from previous seasons, allowing for reasonable variations in the timing, pace, and intensity of the seasonal epidemics, as well as noise in observations. Since the framework does not make strict domain-specific assumptions, it can easily be applied to some other diseases with seasonal epidemics. This method produces a complete posterior distribution over epidemic curves, rather than, for example, solely point predictions of forecasting targets. We report prospective influenza-like-illness forecasts made for the 2013–2014 U.S. influenza season, and compare the framework’s cross-validated prediction error on historical data to that of a variety of simpler baseline predictors.     

A Higher Mutational Burden in Females Supports a “Female Protective Model” in Neurodevelopmental Disorders

Increased male prevalence has been repeatedly reported in several neurodevelopmental disorders (NDs), leading to the concept of a “female protective model.” We investigated the molecular basis of this sex-based difference in liability and demonstrated an excess of deleterious autosomal copy-number variants (CNVs) in females compared to males (odds ratio [OR] = 1.46, p = 8 × 10⁻¹⁰) in a cohort of 15,585 probands ascertained for NDs. In an independent autism spectrum disorder (ASD) cohort of 762 families, we found a 3-fold increase in deleterious autosomal CNVs (p = 7 × 10⁻⁴) and an excess of private deleterious single-nucleotide variants (SNVs) in female compared to male probands (OR = 1.34, p = 0.03). We also showed that the deleteriousness of autosomal SNVs was significantly higher in female probands (p = 0.0006). A similar bias was observed in parents of probands ascertained for NDs. Deleterious CNVs (>400 kb) were maternally inherited more often (up to 64%, p = 10⁻¹⁵) than small CNVs < 400 kb (OR = 1.45, p = 0.0003). In the ASD cohort, increased maternal transmission was also observed for deleterious CNVs and SNVs. Although ASD females showed higher mutational burden and lower cognition, the excess mutational burden remained, even after adjustment for those cognitive differences. These results strongly suggest that females have an increased etiological burden unlinked to rare deleterious variants on the X chromosome. Carefully phenotyped and genotyped cohorts will be required for identifying the symptoms, which show gender-specific liability to mutational burden.     

Cytokine profile of autologous conditioned serum for treatment of osteoarthritis, <Emphasis Type="Italic">in vitro</Emphasis>effects on cartilage metabolism and intra-articular levels after injection

Introduction  

Intraarticular administration of autologous conditioned serum (ACS) recently demonstrated some clinical effectiveness in treatment of osteoarthritis (OA). The current study aims to evaluate the in vitro effects of ACS on cartilage proteoglycan (PG) metabolism, its composition and the effects on synovial fluid (SF) cytokine levels following intraarticular ACS administration.     

Simultaneous occurrence of Hb C trait and polycythaemia vera

A slow abnormal haemoglobin was found in a 27 year-old Negro man who had polycythaemia vera. Chemical and structural analysis showed it to be Hb C. The oxygen affinity showed a normal P50 value. Clinical and haematological investigations are described and discussed.     

How myosin VI coordinates its heads during processive movement

A processive molecular motor must coordinate the enzymatic state of its two catalytic domains in order to prevent premature detachment from its track. For myosin V, internal strain produced when both heads of are attached to an actin track prevents completion of the lever arm swing of the lead head and blocks ADP release. However, this mechanism cannot work for myosin VI, since its lever arm positions are reversed. Here, we demonstrate that myosin VI gating is achieved instead by blocking ATP binding to the lead head once it has released its ADP. The structural basis for this unique gating mechanism involves an insert near the nucleotide binding pocket that is found only in class VI myosin. Reverse strain greatly favors binding of ADP to the lead head, which makes it possible for myosin VI to function as a processive transporter as well as an actin-based anchor. While this mechanism is unlike that of any other myosin superfamily member, it bears remarkable similarities to that of another processive motor from a different superfamily--kinesin I.