The Tree-Generative Capacity of Combinatory Categorial Grammars

The generative capacity of combinatory categorial grammars as acceptors of tree languages is investigated. It is demonstrated that the such obtained tree languages can also be generated by simple monadic context-free tree grammars. However, the subclass of pure combinatory categorial grammars cannot even accept all regular tree languages. Additionally, the tree languages accepted by combinatory categorial grammars with limited rule degrees are characterized: If only application rules are allowed, then they can accept only a proper subset of the regular tree languages, whereas they can accept exactly the regular tree languages once first degree composition rules are permitted

Prevalence and Correlates of Cognitive Impairment in Kidney Transplant Patients Using the DemTect—Results of a KTx360 Substudy

Cognitive impairment in kidney transplantation (KTx) patients is associated with allograft survival and mortality. However, the prevalence of cognitive impairment after KTx is still understudied. Thus, we aimed to assess the prevalence of cognitive impairment in KTx patients and to identify sociodemographic, medical, donation-specific, and psychological variables associated with cognitive impairment. In this cross-sectional two-center study, 583 KTx patients participated in a structured post-transplant care program. The DemTect was used to assess cognition, and cognitive impairment was defined as a score of 30 kg/m2). Using logistic regression analysis, all variables except age remained significant. Our results suggest that cognitive impairment affects a significant number of patients after KTx. Transplant centers may consider screening for cognitive impairment using objective tests, especially in patients with a high-risk profile. Furthermore, studies with longitudinal designs are required in order to assess moderators and mediators for cognitive trajectories

Rationale and design of the RIACT–study: a multi-center placebo controlled double blind study to test the efficacy of RItuximab in Acute Cellular tubulointerstitial rejection with B-cell infiltrates in renal Transplant patients: study protocol for a randomized controlled trial

BACKGROUND: Acute kidney allograft rejection is a major cause for declining graft function and has a negative impact on the long-term graft survival. The majority (90%) of acute rejections are T-cell mediated and, therefore, the anti-rejection therapy targets T-cell-mediated mechanisms of the rejection process. However, there is increasing evidence that intragraft B-cells are also important in the T-cell-mediated rejections. First, a significant proportion of patients with acute T-cell-mediated rejection have B-cells present in the infiltrates. Second, the outcome of these patients is inferior, which has been related to an inferior response to the conventional anti-rejection therapy. Third, treatment of these patients with an anti-CD20 antibody (rituximab) improves the allograft outcome as reported in single case observations and in one small study. Despite the promise of these observations, solid evidence is required before incorporating this treatment option into a general treatment recommendation. METHODS/DESIGN: The RIACT study is designed as a randomized, double-blind, placebo-controlled, parallel group multicenter Phase III study. The study examines whether rituximab, in addition to the standard treatment with steroid-boli, leads to an improved one-year kidney allograft function, compared to the standard treatment alone in patients with acute T-cell mediated tubulointerstitial rejection and significant B-cell infiltrates in their biopsies. A total of 180 patients will be recruited. DISCUSSION: It is important to clarify the relevance of anti-B cell targeting in T-cell mediated rejection and answer the question whether this novel concept should be incorporated in the conventional anti-rejection therapy. TRIAL REGISTRATION: Clinical trials gov. number: NCT0111766

Modelling human choices: MADeM and decision‑making

Research supported by FAPESP 2015/50122-0 and DFG-GRTK 1740/2. RP and AR are also part of the Research, Innovation and Dissemination Center for Neuromathematics FAPESP grant (2013/07699-0). RP is supported by a FAPESP scholarship (2013/25667-8). ACR is partially supported by a CNPq fellowship (grant 306251/2014-0)

Tractable Parsing for CCGs of Bounded Degree

Unlike other mildly context-sensitive formalisms, Combinatory Categorial Grammar (CCG) cannot be parsed in polynomial time when the size of the grammar is taken into account. Refining this result, we show that the parsing complexity of CCG is exponential only in the maximum degree of composition. When that degree is fixed, parsing can be carried out in polynomial time. Our finding is interesting from a linguistic perspective because a bounded degree of composition has been suggested as a universal constraint on natural language grammar. Moreover, ours is the first complexity result for a version of CCG that includes substitution rules, which are used in practical grammars but have been ignored in theoretical work

The tree-generative capacity of combinatory categorial grammars

The generative capacity of combinatory categorial grammars (CCGs) as generators of tree languages is investigated. It is demonstrated that the tree languages generated by CCGs can also be generated by simple monadic context-free tree grammars. However, the important subclass of pure combinatory categorial grammars cannot even generate all regular tree languages. Additionally, the tree languages generated by combinatory categorial grammars with limited rule degrees are characterized: If only application rules are allowed, then these grammars can generate only a proper subset of the regular tree languages, whereas they can generate exactly the regular tree languages once first-degree composition rules are permitted. (C) 2021 The Author(s). Published by Elsevier Inc.Funding Agencies|Centre for Industrial IT (CENIIT) [15.02]; German Research Foundation (DFG) Research Training Group GRK 1763 Quantitative Logics and AutomataGerman Research Foundation (DFG)</p

Obesity After Kidney Transplantation—Results of a KTx360°Substudy

Objective There is solid evidence that kidney transplant (KTx) patients are susceptible to weight gain after transplantation. Post-transplantation obesity [body mass index (BMI) ≥ 30 kg/m2] seems to be associated with higher risks of hypertension, dyslipidemia, diabetes mellitus, and cardiovascular events, while there are contradicting findings regarding the association between obesity and mortality, graft failure after transplantation as well as other variables. We aimed to evaluate the course of weight after KTx and to assess the prevalence of post-transplant obesity in a large sample of German KTx patients. Further, we focused on potential associations between weight gain, obesity, and BMI after transplantation with sociodemographic, medical, psychological [levels of anxiety and depression measured with the Hospital Anxiety and Depression Scale (HADS)], and donation-specific variables. Methods In a structured post-transplant care program 433 KTx patients were evaluated at Hannover Medical School. Information on the pre-transplant body weight/dry weight of dialysis patients was taken from the electronic patient charts. At post-transplant assessment body weight was measured in the transplant center. For statistical analyses, descriptive statistics, analyses of variance, tests for correlations, and regression analyses were used. Results Mean age was 51.3 years, 59% were male and 26.3% had ≥12 years of school attendance. Regarding somatic conditions 6.0% were suffering from type 2 diabetes mellitus, 6.9% were affected by new-onset diabetes after transplantation (NODAT), and the mean estimated glomerular filtration rate (eGFR) was 47.7 ml/min/1.73m2. The prevalence rates of obesity before and after kidney transplantation were 14.8 and 19.9%, respectively. This represents an increase of 34%. Obesity after transplantation was associated with higher rates of type 2 diabetes mellitus and of NODAT. Additionally, there was an association between increasing pre-transplant as well as post-transplant BMI and decreasing eGFR. Higher age and female sex were associated with higher rates of post-transplant obesity. Conclusions Our results suggest that obesity represents a serious problem in KTx patients, especially regarding the association between increasing BMI and decreasing graft functioning (eGFR). However, this aspect is often overlooked and information on effective treatment options for these patients are scarce making further research on this topic necessary

p38 MAPK activation and H3K4 trimethylation is decreased by lactate in vitro and high intensity resistance training in human skeletal muscle.

Exercise induces adaptation of skeletal muscle by acutely modulating intracellular signaling, gene expression, protein turnover and myogenic activation of skeletal muscle stem cells (Satellite cells, SCs). Lactate (La)-induced metabolic stimulation alone has been shown to modify SC proliferation and differentiation. Although the mechanistic basis remains elusive, it was demonstrated that La affects signaling via p38 mitogen activated protein kinase (p38 MAPK) which might contribute to trimethylation of histone 3 lysine 4 (H3K4me3) known to regulate satellite cell proliferation and differentiation. We investigated the effects of La on p38 MAPK and H3K4me3 in a model of activated SCs. Differentiating C2C12 myoblasts were treated with La (20 mM) and samples analysed using qRT-PCR, immunofluorescence, and western blotting. We determined a reduction of p38 MAPK phosphorylation, decreased H3K4me3 and reduced expression of Myf5, myogenin, and myosin heavy chain (MHC) leading to decreased differentiation of La-treated C2C12 cells after 5 days of repeated La treatment. We further investigated whether this regulatory pathway would be affected in human skeletal muscle by the application of two different resistance exercise regimes (RE) associated with distinct metabolic demands and blood La accumulation. Muscle biopsies were obtained 15, 30 min, 1, 4, and 24 h post exercise after moderate intensity RE (STD) vs. high intensity RE (HIT). Consistent with in vitro results, reduced p38 phosphorylation and blunted H3K4me3 were also observed upon metabolically demanding HIT RE in human skeletal muscle. Our data provide evidence that La-accumulation acutely affects p38 MAPK signaling, gene expression and thereby cell differentiation and adaptation in vitro, and likely in vivo

IO Challenges for Human Brain Atlasing Using Deep Learning Methods - An In-Depth Analysis

The use of Deep Learning methods have been identified as a key opportunity for enabling processing of extreme-scale scientific datasets. Feeding data into compute nodes equipped with several high-end GPUs at sufficiently high rate is a known challenge. Facilitating processing of these datasets thus requires the ability to store petabytes of data as well as to access the data with very high bandwidth. In this work, we look at two Deep Learning use cases for cytoarchitectonic brain mapping. These applications are very challenging for the underlying IO system. We present an in depth analysis of their IO requirements and performance. Both applications are limited by the IO performance, as the training processes often have to wait several seconds for new training data. Both applications read random patches from a collection of large HDF5 datasets or TIFF files, which result in many small non-consecutive accesses to the parallel file systems. By using a chunked data format or storing temporally copies of the required patches, the IO performance can be improved significantly. These leads to a decrease of the total runtime of up to 80%