Internal Control Weakness and Stock Price Crash Risk

Considering that stock price crashes are positively associated with opaque financial reporting and that effective internal control over financial reporting is essential for reliable and transparent financial reporting, it is thus vital to establish and maintain effective internal control over financial reporting. In this paper, we investigate the impact of internal control weakness on stock price crash risk, using the disclosures under Section 404 of the 2002 Sarbanes­–Oxley Act. We find that material weakness in internal control over financial reporting increases information asymmetry by producing unreliable and/or opaque financial reporting, subsequently resulting in a stock price crash. Our study provides evidence that ineffective internal control over financial reporting is an indicator of future stock price crashes

Protein side-chain placement: probabilistic inference and integer programming methods

The prediction of energetically favorable side-chain conformations is a fundamental element in homology modeling of proteins and the design of novel protein sequences. The space of side-chain conformations can be approximated by a discrete space of probabilistically representative side-chain conformations (called rotamers). The problem is, then, to find a rotamer selection for each amino acid that minimizes a potential energy function. This is called the Global Minimum Energy Conformation (GMEC) problem. This problem is an NP-hard optimization problem. The Dead-End Elimination theorem together with the A* algorithm (DEE/A*) has been successfully applied to this problem. However, DEE fails to converge for some complex instances. In this paper, we explore two alternatives to DEE/A* in solving the GMEC problem. We use a probabilistic inference method, the max-product (MP) belief-propagation algorithm, to estimate (often exactly) the GMEC. We also investigate integer programming formulations to obtain the exact solution. There are known ILP formulations that can be directly applied to the GMEC problem. We review these formulations and compare their effectiveness using CPLEX optimizers. We also present preliminary work towards applying the branch-and-price approach to the GMEC problem. The preliminary results suggest that the max-product algorithm is very effective for the GMEC problem. Though the max-product algorithm is an approximate method, its speed and accuracy are comparable to those of DEE/A* in large side-chain placement problems and may be superior in sequence design.Singapore-MIT Alliance (SMA

Exact rotamer optimization for computational protein design

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2008.Includes bibliographical references (leaves 235-244).The search for the global minimum energy conformation (GMEC) of protein side chains is an important computational challenge in protein structure prediction and design. Using rotamer models, the problem is formulated as a NP-hard optimization problem. Dead-end elimination (DEE) methods combined with systematic A* search (DEE/A*) have proven useful, but may not be strong enough as we attempt to solve protein design problems where a large number of similar rotamers is eligible and the network of interactions between residues is dense. In this thesis, we present an exact solution method, named BroMAP (branch-and-bound rotamer optimization using MAP estimation), for such protein design problems. The design goal of BroMAP is to be able to expand smaller search trees than conventional branch-and-bound methods while performing only a moderate amount of computation in each node, thereby reducing the total running time. To achieve that, BroMAP attempts reduction of the problem size within each node through DEE and elimination by energy lower bounds from approximate maximurn-a-posteriori (MAP) estimation. The lower bounds are also exploited in branching and subproblem selection for fast discovery of strong upper bounds. Our computational results show that BroMAP tends to be faster than DEE/A* for large protein design cases. BroMAP also solved cases that were not solvable by DEE/A* within the maximum allowed time, and did not incur significant disadvantage for cases where DEE/A* performed well. In the second part of the thesis, we explore several ways of improving the energy lower bounds by using Lagrangian relaxation. Through computational experiments, solving the dual problem derived from cyclic subgraphs, such as triplets, is shown to produce stronger lower bounds than using the tree-reweighted max-product algorithm.(cont.) In the second approach, the Lagrangian relaxation is tightened through addition of violated valid inequalities. Finally, we suggest a way of computing individual lower bounds using the dual method. The preliminary results from evaluating BroMAP employing the dual bounds suggest that the use of the strengthened bounds does not in general improve the running time of BroMAP due to the longer running time of the dual method.by Eun-Jong Hong.Ph.D

Agmatine protects retinal ganglion cells from hypoxia-induced apoptosis in transformed rat retinal ganglion cell line

<p>Abstract</p> <p>Background</p> <p>Agmatine is an endogenous polyamine formed by the decarboxylation of L-arginine. We investigated the protective effects of agmatine against hypoxia-induced apoptosis of immortalized rat retinal ganglion cells (RGC-5). RGC-5 cells were cultured in a closed hypoxic chamber (5% O₂) with or without agmatine. Cell viability was determined by lactate dehydrogenase (LDH) assay and apoptosis was examined by annexin V and caspase-3 assays. Expression and phosphorylation of mitogen-activated protein kinases (MAPKs; JNK, ERK p44/42, and p38) and nuclear factor-kappa B (NF-κB) were investigated by Western immunoblot analysis. The effects of agmatine were compared to those of brain-derived neurotrophic factor (BDNF), a well-known protective neurotrophin for retinal ganglion cells.</p> <p>Results</p> <p>After 48 hours of hypoxic culture, the LDH assay showed 52.3% cell loss, which was reduced to 25.6% and 30.1% when agmatine and BDNF were administered, respectively. This observed cell loss was due to apoptotic cell death, as established by annexin V and caspase-3 assays. Although total expression of MAPKs and NF-κB was not influenced by hypoxic injury, phosphorylation of these two proteins was increased. Agmatine reduced phosphorylation of JNK and NF-κB, while BDNF suppressed phosphorylation of ERK and p38.</p> <p>Conclusion</p> <p>Our results show that agmatine has neuroprotective effects against hypoxia-induced retinal ganglion cell damage in RGC-5 cells and that its effects may act through the JNK and NF-κB signaling pathways. Our data suggest that agmatine may lead to a novel therapeutic strategy to reduce retinal ganglion cell injury related to hypoxia.</p