Formal groups arising from formal punctured ribbons

We investigate Picard functor of a formal punctured ribbon. We prove that under some conditions this functor is representable by a formal group scheme. Formal punctured ribbons were introduced in arXiv:0708.0985.Comment: 42 pages, minor change

Targeting undruggable carbohydrate recognition sites through focused fragment library design

Carbohydrate-protein interactions are key for cell-cell and host-pathogen recognition and thus, emerged as viable therapeutic targets. However, their hydrophilic nature poses major limitations to the conventional development of drug-like inhibitors. To address this shortcoming, four fragment libraries were screened to identify metal-binding pharmacophores (MBPs) as novel scaffolds for inhibition of Ca2+-dependent carbohydrate-protein interactions. Here, we show the effect of MBPs on the clinically relevant lectins DC-SIGN, Langerin, LecA and LecB. Detailed structural and biochemical investigations revealed the specificity of MBPs for different Ca2+-dependent lectins. Exploring the structure-activity relationships of several fragments uncovered the functional groups in the MBPs suitable for modification to further improve lectin binding and selectivity. Selected inhibitors bound efficiently to DCSIGN-expressing cells. Altogether, the discovery of MBPs as a promising class of Ca2+- dependent lectin inhibitors creates a foundation for fragment-based ligand design for future drug discovery campaigns

QSAR models of human data can enrich or replace LLNA testing for human skin sensitization

An example of structural transformation of human skin sensitizers into various non-sensitizers based on interpretation of QSAR models

Alarms about structural alerts

Integrative approach for safety assessment of new chemicals by combining structural alerts and QSAR models

CD169+ Monocyte and Regulatory T Cell Subsets Are Associated with Disease Activity in Rheumatoid Arthritis

Disease activity in rheumatoid arthritis (RA) is influenced by activation of circulating and synovial immune cells. Regulatory T cells (Tregs) and monocytes are key cells that drive inflammation in RA. This study investigated if a relationship exists between disease activity in RA and circulating Treg and monocyte numbers and phenotypes. A potential sialic acid (Sia) mediated link between Tregs and monocytes was also probed in vitro. Peripheral blood mononuclear cells (PBMCs) were isolated from RA patient (n = 62) and healthy control (n = 21) blood using density gradient separation. Flow cytometry was used to count and phenotype Treg and monocyte subsets, and to sort healthy control Tregs for Sia cell culture experiments. The effects of Sia on activated Treg FoxP3 and NFκB expression was assessed by flow cytometry and concentrations of secreted TNFα, IL-10 and IFNγ determined by ELISA. High disease activity RA patients who were unresponsive to disease modifying anti-rheumatic drugs (n = 31), have significantly lower relative numbers (percentages) of CD4(+)CD25(+)CD127(−) Tregs (p < 0.01) and memory CD45RA(−)FoxP3(+) Tregs (p < 0.01), compared to low disease activity responders (n = 24). Relative numbers of non-classical CD169(+) monocytes are associated with disease activity in RA (p = 0.012). Sia reduced Treg expression of FoxP3, NFκB and cytokines in vitro. A strong association has been identified between non-classical CD169(+) monocytes and post-treatment disease activity in RA. This study also indicates that Sia can reduce Treg activation and cytokine release. We postulate that such a reduction could be mediated by interaction with sialyted proteins captured by CD169(+) monocytes

Multiple myeloma with central nervous system relapse

Central nervous system involvement in multiple myeloma is a rare complication but carries a very poor prognosis. We provide a review of current literature, including presentation, treatment and survival data, and describe our experience in a regional hematologic malignancy diagnosis center where, over a 15-year period, ten cases were identified. Although the median age of onset, frequently between 50-60 years, is comparatively young, those diagnosed usually have a preceding diagnosis of multiple myeloma and often have had several lines of treatment. We discuss putative underlying factors such as prior treatment and associations including possible risk factors and features suggestive of a distinct biology. Central nervous system involvement may be challenging to diagnose in myeloma, displaying heterogeneous symptoms that can be confounded by neurological symptoms caused by the typical features of myeloma or treatment side-effects. We discuss the clinical features, imaging and laboratory methods used in diagnosis, and highlight the importance of considering this rare complication when neurological symptoms occur at presentation or, more commonly, during the disease pathway. In the absence of clinical trial data to inform an evidence-based approach to treatment, we discuss current and novel treatment options. Finally, we propose the establishment of an International Registry of such cases as the best way to collect and subsequently disseminate presentation, diagnostic and treatment outcome data on this rare complication of multiple myeloma

Age and Age-related Diseases: Role of Inflammation Triggers and Cytokines

Cytokine dysregulation is believed to play a key role in the remodeling of the immune system at older age, with evidence pointing to an inability to fine-control systemic inflammation, which seems to be a marker of unsuccessful aging. This reshaping of cytokine expression pattern, with a progressive tendency toward a pro-inflammatory phenotype has been called “inflamm-aging.” Despite research there is no clear understanding about the causes of “inflamm-aging” that underpin most major age-related diseases, including atherosclerosis, diabetes, Alzheimer’s disease, rheumatoid arthritis, cancer, and aging itself. While inflammation is part of the normal repair response for healing, and essential in keeping us safe from bacterial and viral infections and noxious environmental agents, not all inflammation is good. When inflammation becomes prolonged and persists, it can become damaging and destructive. Several common molecular pathways have been identified that are associated with both aging and low-grade inflammation. The age-related change in redox balance, the increase in age-related senescent cells, the senescence-associated secretory phenotype (SASP) and the decline in effective autophagy that can trigger the inflammasome, suggest that it may be possible to delay age-related diseases and aging itself by suppressing pro-inflammatory molecular mechanisms or improving the timely resolution of inflammation. Conversely there may be learning from molecular or genetic pathways from long-lived cohorts who exemplify good quality aging. Here, we will discuss some of the current ideas and highlight molecular pathways that appear to contribute to the immune imbalance and the cytokine dysregulation, which is associated with “inflammageing” or parainflammation. Evidence of these findings will be drawn from research in cardiovascular disease, cancer, neurological inflammation and rheumatoid arthritis

Predicting chemically-induced skin reactions. Part I: QSAR models of skin sensitization and their application to identify potentially hazardous compounds

Repetitive exposure to a chemical agent can induce an immune reaction in inherently susceptible individuals that leads to skin sensitization. Although many chemicals have been reported as skin sensitizers, there have been very few rigorously validated QSAR models with defined applicability domains (AD) that were developed using a large group of chemically diverse compounds. In this study, we have aimed to compile, curate, and integrate the largest publicly available dataset related to chemically-induced skin sensitization, use this data to generate rigorously validated and QSAR models for skin sensitization, and employ these models as a virtual screening tool for identifying putative sensitizers among environmental chemicals. We followed best practices for model building and validation implemented with our predictive QSAR workflow using random forest modeling technique in combination with SiRMS and Dragon descriptors. The Correct Classification Rate (CCR) for QSAR models discriminating sensitizers from non-sensitizers were 71–88% when evaluated on several external validation sets, within a broad AD, with positive (for sensitizers) and negative (for non-sensitizers) predicted rates of 85% and 79% respectively. When compared to the skin sensitization module included in the OECD QSAR toolbox as well as to the skin sensitization model in publicly available VEGA software, our models showed a significantly higher prediction accuracy for the same sets of external compounds as evaluated by Positive Predicted Rate, Negative Predicted Rate, and CCR. These models were applied to identify putative chemical hazards in the ScoreCard database of possible skin or sense organ toxicants as primary candidates for experimental validation