Respiratory viral infections in exacerbation of chronic airway inflammatory diseases: novel mechanisms and insights from the upper airway epithelium.

Respiratory virus infection is one of the major sources of exacerbation of chronic airway inflammatory diseases. These exacerbations are associated with high morbidity and even mortality worldwide. The current understanding on viral-induced exacerbations is that viral infection increases airway inflammation which aggravates disease symptoms. Recent advances in in vitro air-liquid interface 3D cultures, organoid cultures and the use of novel human and animal challenge models have evoked new understandings as to the mechanisms of viral exacerbations. In this review, we will focus on recent novel findings that elucidate how respiratory viral infections alter the epithelial barrier in the airways, the upper airway microbial environment, epigenetic modifications including miRNA modulation, and other changes in immune responses throughout the upper and lower airways. First, we reviewed the prevalence of different respiratory viral infections in causing exacerbations in chronic airway inflammatory diseases. Subsequently we also summarized how recent models have expanded our appreciation of the mechanisms of viral-induced exacerbations. Further we highlighted the importance of the virome within the airway microbiome environment and its impact on subsequent bacterial infection. This review consolidates the understanding of viral induced exacerbation in chronic airway inflammatory diseases and indicates pathways that may be targeted for more effective management of chronic inflammatory diseases

Learning automata with side-effects

Automata learning has been successfully applied in the verification of hardware and software. The size of the automaton model learned is a bottleneck for scalability, and hence optimizations that enable learning of compact representations are important. This paper exploits monads, both as a mathematical structure and a programming construct, to design and prove correct a wide class of such optimizations. Monads enable the development of a new learning algorithm and correctness proofs, building upon a general framework for automata learning based on category theory. The new algorithm is parametric on a monad, which provides a rich algebraic structure to capture non-determinism and other side-effects. We show that this allows us to uniformly capture existing algorithms, develop new ones, and add optimizations

Secondary Prevention of Colorectal Cancer: Is There an Optimal Follow-up for Patients with Colorectal Cancer?

Secondary prevention of colorectal cancer, as opposed to primary prevention, indicates that a person has already had the disease and there are steps being taken to prevent cancer recurrence, usually as metachronous tumors. This generally involves annual surveillance with colonoscopy after surgical removal of the initial cancer if some aspect of the colon remains. However, some familial cases may involve other modalities, such as cyclooxygenase inhibitors, as an adjunct after the initial operation. Genetic testing in suspected familial cases may identify candidates for secondary prevention. The timing for secondary prevention is critical to prevent recurrent advanced disease, which is detrimental to patient survival. Recommendations are often empiric, but some cases are based on the biological behavior of the tumor. Close follow-up with a competent health care provider, such as a gastroenterologist, is necessary to help prevent recurrence

Combined In Silico, In Vivo, and In Vitro Studies Shed Insights into the Acute Inflammatory Response in Middle-Aged Mice

We combined in silico, in vivo, and in vitro studies to gain insights into age-dependent changes in acute inflammation in response to bacterial endotoxin (LPS). Time-course cytokine, chemokine, and NO2-/NO3- data from "middle-aged" (6-8 months old) C57BL/6 mice were used to re-parameterize a mechanistic mathematical model of acute inflammation originally calibrated for "young" (2-3 months old) mice. These studies suggested that macrophages from middle-aged mice are more susceptible to cell death, as well as producing higher levels of pro-inflammatory cytokines, vs. macrophages from young mice. In support of the in silico-derived hypotheses, resident peritoneal cells from endotoxemic middle-aged mice exhibited reduced viability and produced elevated levels of TNF-α, IL-6, IL-10, and KC/CXCL1 as compared to cells from young mice. Our studies demonstrate the utility of a combined in silico, in vivo, and in vitro approach to the study of acute inflammation in shock states, and suggest hypotheses with regard to the changes in the cytokine milieu that accompany aging. © 2013 Namas et al

Pain outcomes in patients with bone metastases from advanced cancer: assessment and management with bone-targeting agents

Bone metastases in advanced cancer frequently cause painful complications that impair patient physical activity and negatively affect quality of life. Pain is often underreported and poorly managed in these patients. The most commonly used pain assessment instruments are visual analogue scales, a single-item measure, and the Brief Pain Inventory Questionnaire-Short Form. The World Health Organization analgesic ladder and the Analgesic Quantification Algorithm are used to evaluate analgesic use. Bone-targeting agents, such as denosumab or bisphosphonates, prevent skeletal complications (i.e., radiation to bone, pathologic fractures, surgery to bone, and spinal cord compression) and can also improve pain outcomes in patients with metastatic bone disease. We have reviewed pain outcomes and analgesic use and reported pain data from an integrated analysis of randomized controlled studies of denosumab versus the bisphosphonate zoledronic acid (ZA) in patients with bone metastases from advanced solid tumors. Intravenous bisphosphonates improved pain outcomes in patients with bone metastases from solid tumors. Compared with ZA, denosumab further prevented pain worsening and delayed the need for treatment with strong opioids. In patients with no or mild pain at baseline, denosumab reduced the risk of increasing pain severity and delayed pain worsening along with the time to increased pain interference compared with ZA, suggesting that use of denosumab (with appropriate calcium and vitamin D supplementation) before patients develop bone pain may improve outcomes. These data also support the use of validated pain assessments to optimize treatment and reduce the burden of pain associated with metastatic bone disease

Evaluation of Force-Field Calculations of Lattice Energies on a Large Public Dataset, Assessment of Pharmaceutical Relevance, and Comparison to Density Functional Theory

Crystal lattice energy is a key property affecting the ease of processing pharmaceutical materials during manufacturing, as well as product performance. We present an extensive comparison of 324 force-field protocols for calculating the lattice energies of single component, organic molecular crystals (further restricted to Z′ less than or equal to one), corresponding to a wide variety of force-fields (DREIDING, Universal, CVFF, PCFF, COMPASS, COMPASSII), optimization routines, and other variations, which could be implemented as part of an automated workflow using the industry standard Materials Studio software. All calculations were validated using a large new dataset (SUB-BIG), which we make publicly available. This dataset comprises public domain sublimation data, from which estimated experimental lattice energies were derived, linked to 235 molecular crystals. Analysis of pharmaceutical relevance was performed according to two distinct methods based upon (A) public and (B) proprietary data. These identified overlapping subsets of SUB-BIG comprising (A) 172 and (B) 63 crystals, of putative pharmaceutical relevance, respectively. We recommend a protocol based on the COMPASSII force field for lattice energy calculations of general organic or pharmaceutically relevant molecular crystals. This protocol was the most highly ranked prior to subsetting and was either the top ranking or amongst the top 15 protocols (top 5%) following subsetting of the dataset according to putative pharmaceutical relevance. Further analysis identified scenarios where the lattice energies calculated using the recommended force-field protocol should either be disregarded (values greater than or equal to zero and/or the messages generated by the automated workflow indicate extraneous atoms were added to the unit cell) or treated cautiously (values less than or equal to −249 kJ/mol), as they are likely to be inaccurate. Application of the recommended force-field protocol, coupled with these heuristic filtering criteria, achieved an root mean-squared error (RMSE) around 17 kJ/mol (mean absolute deviation (MAD) around 11 kJ/mol, Spearman’s rank correlation coefficient of 0.88) across all 226 SUB-BIG structures retained after removing calculation failures and applying the filtering criteria. Across these 226 structures, the estimated experimental lattice energies ranged from −60 to −269 kJ/mol, with a standard deviation around 29 kJ/mol. The performance of the recommended protocol on pharmaceutically relevant crystals could be somewhat reduced, with an RMSE around 20 kJ/mol (MAD around 13 kJ/mol, Spearman’s rank correlation coefficient of 0.76) obtained on 62 structures retained following filtering according to pharmaceutical relevance method B, for which the distribution of experimental values was similar. For a diverse set of 17 SUB-BIG entries, deemed pharmaceutically relevant according to method B, this recommended force-field protocol was compared to dispersion corrected density functional theory (DFT) calculations (PBE + TS). These calculations suggest that the recommended force-field protocol (RMSE around 15 kJ/mol) outperforms PBE + TS (RMSE around 37 kJ/mol), although it may not outperform more sophisticated DFT protocols and future studies should investigate this. Finally, further work is required to compare our recommended protocol to other lattice energy calculation protocols reported in the literature, as comparisons based upon previously reported smaller datasets indicated this protocol was outperformed by a number of other methods. The SUB-BIG dataset provides a basis for these future studies and could support protocol refinement

The Reform of Employee Compensation in China’s Industrial Enterprises

Although employee compensation reform in Chinese industrial sector has been discussed in the literature, the real changes in compensation system and pay practices have received insufficient attention and warrant further examination. This paper briefly reviews the pre- and post-reform compensation system, and reports the results of a survey of pay practices in the four major types of industrial enterprises in China. The research findings indicate that the type of enterprise ownership has little influence on general compensation practices, adoption of profit-sharing plans, and subsidy and allowance packages. In general, pay is linked more to individual performance and has become an important incentive to Chinese employees. However, differences are found across the enterprise types with regard to performance-related pay. Current pay practices are positively correlated to overall effectiveness of the enterprise

Stronger Security and Constructions of Multi-Designated Verifier Signatures

Off-the-Record (OTR) messaging is a two-party message authentication protocol that also provides plausible deniability: there is no record that can later convince a third party what messages were actually sent. To extend OTR to group messaging we need to consider issues that are not present in the 2-party case. In group OTR (as in two-party OTR), the sender should be able to authenticate (or sign) his messages so that group members can verify who sent a message (that is, signatures should be unforgeable, even by group members). Also as in the two-party case, we want the off-the-record property: even if some verifiers are corrupt and collude, they should not be able to prove the authenticity of a message to any outsider. Finally, we need consistency, meaning that a corrupt sender cannot create confusion in the group as to what he said: if any group member accepts a signature, then all of them do. To achieve these properties it is natural to consider Multi-Designated Verifier Signatures (MDVS), which intuitively seem to target exactly the properties we require. However, existing literature defines and builds only limited notions of MDVS, where (a) the off-the-record property (referred to as source hiding) only holds when all verifiers could conceivably collude, and (b) the consistency property is not considered. The contributions of this paper are two-fold: stronger definitions for MDVS, and new constructions meeting those definitions. We strengthen source-hiding to support any subset of corrupt verifiers, and give the first formal definition of consistency. We give several constructions of our stronger notion of MDVS: one from generic standard primitives such as pseudorandom functions, pseudorandom generators, key agreement and NIZKs; one from specific instances of these primitives (for concrete efficiency); and one from functional encryption. The third construction requires an involved trusted setup step — including verification keys derived from a master secret — but this trusted setup buys us verifier-identity-based signing, for which such trusted setup is unavoidable. Additionally, in the third construction, the signature size can be made smaller by assuming a bound on colluding verifiers