Michael and the Whiz Kids

Imagine a boy, five feet tall and one hundred pounds, who wants to play high school basketball. Now imagine that he was blind until the age of six and that he’s the first black student to attend his suburban school. And there you have Michael Thompson in 1965 in San Bruno, California. He played at the school where a young English teacher was coaching “lightweight basketball,” a competition for smaller players that has since disappeared. The team that Coach John Christgau put together came to be called the Whiz Kids for the way they rocketed up and down the court, led by Michael and invariably winning. Michael and the Whiz Kids tells the story of the team’s 1968 championship season. It is a tale of cliffhanger games and players as outsized in character as they are short in stature, from the wild-haired, bespectacled “Professor” to the well-traveled Latvian dubbed “Suitcase” to the quiet and tenacious “Salt,” as in “of the earth.” But it is also a tale of the time—of counterculture, suburbia, integration, and racial brawls erupting on the court. In Christgau’s deft telling, it is an absorbing, often comic story of coming of age, for coach and Whiz Kids alike

Efficient adjustment for complex covariates: Gaining efficiency with DOPE

Covariate adjustment is a ubiquitous method used to estimate the average treatment effect (ATE) from observational data. Assuming a known graphical structure of the data generating model, recent results give graphical criteria for optimal adjustment, which enables efficient estimation of the ATE. However, graphical approaches are challenging for high-dimensional and complex data, and it is not straightforward to specify a meaningful graphical model of non-Euclidean data such as texts. We propose an general framework that accommodates adjustment for any subset of information expressed by the covariates. We generalize prior works and leverage these results to identify the optimal covariate information for efficient adjustment. This information is minimally sufficient for prediction of the outcome conditionally on treatment. Based on our theoretical results, we propose the Debiased Outcome-adapted Propensity Estimator (DOPE) for efficient estimation of the ATE, and we provide asymptotic results for the DOPE under general conditions. Compared to the augmented inverse propensity weighted (AIPW) estimator, the DOPE can retain its efficiency even when the covariates are highly predictive of treatment. We illustrate this with a single-index model, and with an implementation of the DOPE based on neural networks, we demonstrate its performance on simulated and real data. Our results show that the DOPE provides an efficient and robust methodology for ATE estimation in various observational settings.Comment: 45 pages, 9 Figures. Comments are welcom

Bisimulationen und Äquivalenzbegriffe für Transitionssysteme und Ereignisstrukturen

In dieser Arbeit werden in zwei Teilen die wichtigsten Äquivalenzrelationen für Transitionssysteme und Ereignisstrukturen aus der Literatur zusammengestellt, in eine einheitliche Notation gebracht und wechselseitig miteinander verglichen. Weiterhin werden einige zusätzliche Varianten definiert

On Generators and Relations of the Rational Cohomology of Hilbert Schemes

We consider for $d\geq 1$ the graded commutative $\mathbb{Q}$-algebra $\mathcal{A}(d):=H^*(\operatorname{Hilb}^d(\mathbb{C}^2);\mathbb{Q})$, which is also connected to the study of generalised Hurwitz spaces by work of the first author. These Hurwitz spaces are in turn related to the moduli spaces of Riemann surfaces with boundary. We determine two distinct, minimal sets of $\lfloor d/2\rfloor$ multiplicative generators of $\mathcal{A}(d)$. Additionally, we prove when the lowest degree generating relations occur. For small values of $d$ we also determine a minimal set of generating relations, which leads to several conjectures about the necessary generating relations for $\mathcal{A}(d)$.Comment: 25 pages; v2. Minor revisions based on referee's comments. Published versio

Nonparametric Conditional Local Independence Testing

Conditional local independence is an asymmetric independence relation among continuous time stochastic processes. It describes whether the evolution of one process is directly influenced by another process given the histories of additional processes, and it is important for the description and learning of causal relations among processes. We develop a model-free framework for testing the hypothesis that a counting process is conditionally locally independent of another process. To this end, we introduce a new functional parameter called the Local Covariance Measure (LCM), which quantifies deviations from the hypothesis. Following the principles of double machine learning, we propose an estimator of the LCM and a test of the hypothesis using nonparametric estimators and sample splitting or cross-fitting. We call this test the (cross-fitted) Local Covariance Test ((X)-LCT), and we show that its level and power can be controlled uniformly, provided that the nonparametric estimators are consistent with modest rates. We illustrate the theory by an example based on a marginalized Cox model with time-dependent covariates, and we show in simulations that when double machine learning is used in combination with cross-fitting, then the test works well without restrictive parametric assumptions.Comment: 62 pages, 10 figures. Comments are welcom

Digital subtraction radiographic analysis of the combination of bioabsorbable membrane and bovine morphogenetic protein pool in human periodontal infrabony defects

Objectives: This study assessed the bone density gain and its relationship with the periodontal clinical parameters in a case series of a regenerative therapy procedure. Material and Methods: Using a split-mouth study design, 10 pairs of infrabony defects from 15 patients were treated with a pool of bovine bone morphogenetic proteins associated with collagen membrane (test sites) or collagen membrane only (control sites). The periodontal healing was clinically and radiographically monitored for six months. Standardized presurgical and 6-month postoperative radiographs were digitized for digital subtraction analysis, which showed relative bone density gain in both groups of 0.034 ± 0.423 and 0.105 ± 0.423 in the test and control group, respectively (p>0.05). Results: As regards the area size of bone density change, the influence of the therapy was detected in 2.5 mm2 in the test group and 2 mm2 in the control group (p>0.05). Additionally, no correlation was observed between the favorable clinical results and the bone density gain measured by digital subtraction radiography (p>0.05). Conclusions: The findings of this study suggest that the clinical benefit of the regenerative therapy observed did not come with significant bone density gains. Long-term evaluation may lead to a different conclusions

The Effect of Partially Exposed Connective Tissue Graft on Root‐Coverage Outcomes: A Systematic Review and Meta‐Analysis

The aim of this systematic review was to compare the root‐coverage outcomes of using a partially exposed connective tissue graft (CTG) technique with a fully covered CTG technique for root coverage. An electronic search up to February 28th, 2017, was performed to identify human clinical studies with data comparing outcomes of root coverage using CTG, with and without a partially exposed graft. Five clinical studies were selected for inclusion in this review. For each study, the gain of keratinized gingiva, reduction of recession depth, number of surgical sites achieving complete root coverage, percentage of root coverage, gain of tissue thickness, and changes of probing depth and clinical attachment level were recorded. Meta‐analysis for the comparison of complete root coverage between the two techniques presented no statistically significant differences. A statistically significant gain of keratinized tissue in favor of the sites with an exposed CTG and a tendency of greater reduction in recession depth were seen at the sites with a fully covered CTG. Based on the results, the use of a partially exposed CTG in root‐coverage procedures could achieve greater gain in keratinized gingiva, while a fully covered CTG might be indicated for procedures aiming to reduce recession depth

Ovariectomized rats as a model of postmenopausal osteoarthritis: validation and application

We aimed to assess the effect of ovariectomy on cartilage turnover and degradation, to evaluate whether ovariectomized (OVX) rats could form an experimental model of postmenopausal osteoarthritis. The effect of ovariectomy on cartilage was studied using two cohorts of female Sprague–Dawley rats, aged 5 and 7 months. In a third cohort, the effect of exogenous estrogen and a selective estrogen receptor modulator was analyzed. Knee joints were assessed by histological analysis of the articular cartilage after 9 weeks. Cartilage turnover was measured in urine by an immunoassay specific for collagen type II degradation products (CTX-II), and bone resorption was quantified in serum using an assay for bone collagen type I fragments (CTX-I). Surface erosion in the cartilage of the knee was more severe in OVX rats than in sham-operated animals, particularly in the 7-month-old cohort (P = 0.008). Ovariectomy also significant increased CTX-I and CTX-II. Both the absolute levels of CTX-II and the relative changes from baseline seen at week 4 correlated strongly with the severity of cartilage surface erosion at termination (r = 0.74, P < 0.01). Both estrogen and the selective estrogen receptor modulator inhibited the ovariectomy-induced acceleration of cartilage and bone turnover and significantly suppressed cartilage degradation and erosion seen in vehicle-treated OVX rats. The study indicates that estrogen deficiency accelerates cartilage turnover and increases cartilage surface erosion. OVX rats provide a useful experimental model for the evaluation of the chondroprotective effects of estrogens and estrogen-like substances and the model may be an in vivo representation of osteoarthritis in postmenopausal women

Gad65 is recognized by t-cells, but not by antibodies from nod-mice

Since the 64kDa-protein glutamic acid decarboxylase (GAD) is one of the major autoantigens in T-cell mediated Type 1 diabetes, its relevance as a T-cell antigen needs to be clarified. After isolation of splenic T-cells from non-obese diabetic (NOD) mice, a useful model for human Type 1 diabetes, we found that these T-cells proliferate spontaneously when incubated with human GAD65, but only marginally after incubation with GAD67, both recombinated in the baculovirus system. No effect was observed with non-diabetic NOD mice or with T-cells from H-2 identical NON-NOD-H-2g7 control mice. It has been published previously that NOD mice develop autoantibodies against a 64kDa protein detected with mouse beta cells. In immunoprecipitation experiments with sera from the same NOD mice and 33S-methionine-labelled GAD, no autoantibody binding could be detected. We conclude firstly that GAD65 is an important T-cell antigen which is relevant early in the development of Type 1 diabetes and secondly that there is an antigenic epitope in the human GAD65 molecule recognized by NOD T-cells, but not by NOD autoantibodies precipitating conformational epitopes. Our results therefore provide further evidence that GAD65 is a T-cell antigen in NOD mice, being possibly also involved in very early processes leading to the development of human Type 1 diabetes