Citations

Hepatic stellate cells (HSC) and liver endothelial cells (LEC) migrate to sites of injury and perpetuate alcohol-induced liver injury. High-mobility group box 1 (HMGB1) is a protein released from the nucleus of injured cells that has been implicated as a proinflammatory mediator. We hypothesized that HMGB1 may be released from ethanol-stimulated liver parenchymal cells and contribute to HSC and LEC recruitment. Ethanol stimulation of rat hepatocytes and HepG2 cells resulted in translocation of HMGB1 from the nucleus as assessed by Western blot. HMGB1 protein levels were increased in the supernatant of ethanol-treated hepatocytes compared with vehicle-treated cells. Migration of both HSC and LEC was increased in response to conditioned medium for ethanol-stimulated hepatocytes (CMEtOH) compared with vehicle-stimulated hepatocytes (CMVEH) ( P < 0.05). However, the effect of CMEtOHon migration was almost entirely reversed by treatment with HMGB1-neutralizing antibody or when HepG2 cells were pretransfected with HMGB1-siRNA compared with control siRNA-transfected HepG2 cells ( P < 0.05). Recombinant HMGB1 (100 ng/ml) also stimulated migration of HSC and LEC compared with vehicle stimulation ( P < 0.05 for both HSC and LEC). HMGB1 stimulation of HSC increased the phosphorylation of Src and Erk and HMGB1-induced HSC migration was blocked by the Src inhibitor PP2 and the Erk inhibitor U0126. Hepatocytes release HMGB1 in response to ethanol with subsequent recruitment of HSC and LEC. This pathway has implications for HSC and LEC recruitment to sites of ethanol-induced liver injury.

AbstractBackgroundSurgical treatment and clinical management of foot pathology requires accurate, reliable assessment of foot deformities. Foot and ankle deformities are multi‐planar and therefore difficult to quantify by standard radiographs. Three‐dimensional (3D) imaging modalities have been used to define bone orientations using inertial axes based on bone shape, but these inertial axes can fail to mimic established bone angles used in orthopaedics and clinical biomechanics. To provide improved clinical relevance of 3D bone angles, we developed techniques to define bone axes using landmarks on quantitative computed tomography (QCT) bone surface meshes. We aimed to assess measurement precision of landmark‐based, 3D bone‐to‐bone orientations of hind foot and lesser tarsal bones for expert raters and a template‐based automated method.MethodsTwo raters completed two repetitions each for twenty feet (10 right, 10 left), placing anatomic landmarks on the surfaces of calcaneus, talus, cuboid, and navicular. Landmarks were also recorded using the automated, template‐based method. For each method, 3D bone axes were computed from landmark positions, and Cardan sequences produced sagittal, frontal, and transverse plane angles of bone‐to‐bone orientations. Angular reliability was assessed using intraclass correlation coefficients (ICCs) and the root mean square standard deviation (RMS‐SD) for intra‐rater and inter‐rater precision, and rater versus automated agreement.ResultsIntra‐ and inter‐rater ICCs were generally high (≥ 0.80), and the ICCs for each rater compared to the automated method were similarly high. RMS‐SD intra‐rater precision ranged from 1.4 to 3.6° and 2.4 to 6.1°, respectively, for the two raters, which compares favorably to uni‐planar radiographic precision. Greatest variability was in Navicular: Talus sagittal plane angle and Cuboid: Calcaneus frontal plane angle. Precision of the automated, atlas‐based template method versus the raters was comparable to each rater's internal precision.ConclusionsIntra‐ and inter‐rater precision suggest that the landmark‐based methods have adequate test‐retest reliability for 3D assessment of foot deformities. Agreement of the automated, atlas‐based method with the expert raters suggests that the automated method is a valid, time‐saving technique for foot deformity assessment. These methods have the potential to improve diagnosis of foot and ankle pathologies by allowing multi‐planar quantification of deformities.

Abstract Purpose: Patients with hormone receptor–negative breast cancer generally do not benefit from endocrine-targeted therapies. However, a subset with androgen receptor (AR) expression is predicted to respond to antiandrogen therapies. This phase II study explored bicalutamide in AR-positive, estrogen receptor (ER), and progesterone receptor (PgR)-negative metastatic breast cancer. Experimental Design: Tumors from patients with ER/PgR-negative advanced breast cancer were tested centrally for AR [immunohistochemistry (IHC) &gt; 10% nuclear staining considered positive]. If either the primary or a metastatic site was positive, patients were eligible to receive the AR antagonist bicalutamide at a dose of 150 mg daily. Clinical benefit rate (CBR), the primary endpoint, was defined as the total number of patients who show a complete response (CR), partial response (PR), or stable disease (SD) &gt; 6 months; secondary endpoints included progression-free survival (PFS) and toxicity. Correlative studies included measurement of circulating endocrine markers and IHC surrogates for basal-like breast cancer. Results: Of 424 patients with ER/PgR-negative breast cancer, 12% tested AR-positive. The 6-month CBR was 19% [95% confidence interval (CI), 7%–39%] for bicalutamide. The median PFS was 12 weeks (95% CI, 11–22 weeks). Bicalutamide was well-tolerated with no grade 4/5 treatment-related adverse events observed. Conclusion: AR was expressed in 12% of patients with ER/PgR-negative breast cancer screened for this trial. The CBR of 19% observed with bicalutamide shows proof of principle for the efficacy of minimally toxic androgen blockade in a select group of patients with ER/PgR-negative, AR-positive breast cancer. Clin Cancer Res; 19(19); 5505–12. ©2013 AACR.

Abstract Background: The etiology and natural history of Parkinson’s disease (PD) are not well understood. Some non-motor symptoms such as hyposmia, rapid eye movement sleep behavior disorder, and constipation may develop during the prodromal stage of PD and precede PD diagnosis by years. Objectives: We examined the promise and pitfalls of research on premotor symptoms of PD and developed priorities and strategies to understand their clinical and etiological implications. Methods: This review was based on a workshop, Parkinson’s Disease Premotor Symptom Symposium, held 7–8 June 2012 at the National Institute of Environmental Health Sciences in Research Triangle Park, North Carolina. Discussion: Research on premotor symptoms of PD may offer an excellent opportunity to characterize high-risk populations and to better understand PD etiology. Such research may lead to evaluation of novel etiological hypotheses such as the possibility that environmental toxicants or viruses may initiate PD pathogenesis in the gastrointestinal tract or olfactory bulb. At present, our understanding of premotor symptoms of PD is in its infancy and faces many obstacles. These symptoms are often not specific to PD and have low positive predictive value for early PD diagnosis. Further, the pathological bases and biological mechanisms of these premotor symptoms and their relevance to PD pathogenesis are poorly understood. Conclusion: This is an emerging research area with important data gaps to be filled. Future research is needed to understand the prevalence of multiple premotor symptoms and their etiological relevance to PD. Animal experiments and mechanistic studies will further understanding of the biology of these premotor symptoms and test novel etiological hypothesis. Citation: Chen H, Burton EA, Ross GW, Huang X, Savica R, Abbott RD, Ascherio A, Caviness JN, Gao X, Gray KA, Hong JS, Kamel F, Jennings D, Kirshner A, Lawler C, Liu R, Miller GW, Nussbaum R, Peddada SD, Comstock Rick A, Ritz B, Siderowf AD, Tanner CM, Tröster AI, Zhang J. 2013. Research on the premotor symptoms of Parkinson’s Disease: clinical and etiological implications. Environ Health Perspect 121:1245–1252; http://dx.doi.org/10.1289/ehp.1306967

AbstractThe Alzheimer's Disease Neuroimaging Initiative (ADNI) is an ongoing, longitudinal, multicenter study designed to develop clinical, imaging, genetic, and biochemical biomarkers for the early detection and tracking of Alzheimer's disease (AD). The study aimed to enroll 400 subjects with early mild cognitive impairment (MCI), 200 subjects with early AD, and 200 normal control subjects; $67 million funding was provided by both the public and private sectors, including the National Institute on Aging, 13 pharmaceutical companies, and 2 foundations that provided support through the Foundation for the National Institutes of Health. This article reviews all papers published since the inception of the initiative and summarizes the results as of February 2011. The major accomplishments of ADNI have been as follows: (1) the development of standardized methods for clinical tests, magnetic resonance imaging (MRI), positron emission tomography (PET), and cerebrospinal fluid (CSF) biomarkers in a multicenter setting; (2) elucidation of the patterns and rates of change of imaging and CSF biomarker measurements in control subjects, MCI patients, and AD patients. CSF biomarkers are consistent with disease trajectories predicted by β‐amyloid cascade (Hardy, J Alzheimers Dis 2006;9(Suppl 3):151–3) and tau‐mediated neurodegeneration hypotheses for AD, whereas brain atrophy and hypometabolism levels show predicted patterns but exhibit differing rates of change depending on region and disease severity; (3) the assessment of alternative methods of diagnostic categorization. Currently, the best classifiers combine optimum features from multiple modalities, including MRI, [18F]‐fluorodeoxyglucose‐PET, CSF biomarkers, and clinical tests; (4) the development of methods for the early detection of AD. CSF biomarkers, β‐amyloid 42 and tau, as well as amyloid PET may reflect the earliest steps in AD pathology in mildly symptomatic or even nonsymptomatic subjects, and are leading candidates for the detection of AD in its preclinical stages; (5) the improvement of clinical trial efficiency through the identification of subjects most likely to undergo imminent future clinical decline and the use of more sensitive outcome measures to reduce sample sizes. Baseline cognitive and/or MRI measures generally predicted future decline better than other modalities, whereas MRI measures of change were shown to be the most efficient outcome measures; (6) the confirmation of the AD risk loci CLU, CR1, and PICALM and the identification of novel candidate risk loci; (7) worldwide impact through the establishment of ADNI‐like programs in Europe, Asia, and Australia; (8) understanding the biology and pathobiology of normal aging, MCI, and AD through integration of ADNI biomarker data with clinical data from ADNI to stimulate research that will resolve controversies about competing hypotheses on the etiopathogenesis of AD, thereby advancing efforts to find disease‐modifying drugs for AD; and (9) the establishment of infrastructure to allow sharing of all raw and processed data without embargo to interested scientific investigators throughout the world. The ADNI study was extended by a 2‐year Grand Opportunities grant in 2009 and a renewal of ADNI (ADNI‐2) in October 2010 through to 2016, with enrollment of an additional 550 participants.

This study was to evaluate the efficacy and safety of acupuncture for chronic functional constipation. Randomized controlled trials were searched in several databases. The primary outcome was a change in the number of weekly spontaneous bowel movements. The secondary outcomes included colonic transit activity, effective rate, Cleveland Clinic Score, and health-related quality of life score. Meta-analysis was done by using RevMan 5.1. After strict screening, 15 RCTs were included, containing 1256 participants. All of them were conducted in China and published in Chinese journals. Meta-analysis indicated that acupuncture for chronic functional constipation was probably as effective as conventional medical therapy in the change of bowel movements. For the colonic transit activity, acupuncture might be the same as conventional medical therapy and could be better than sham acupuncture. For the Cleveland Clinic Score, acupuncture was unlikely inferior to conventional medical therapy and the deep acupuncture was better than normal depth acupuncture in abdominal region. No obvious adverse event was associated with acupuncture for constipation. In conclusion, acupuncture for chronic functional constipation is safe and may improve weekly spontaneous bowel movements, quality of life, and relevant symptoms. However, the evidence was limited by the small sample size and the methodological quality.

The cytochrome P450 2B6 (CYP2B6) is involved in the metabolism of testosterone. Functional changes in this enzyme may influence endogenous hormone exposure, which has been associated with risk of breast cancer. To assess potential associations between two functional polymorphisms CYP2B6_516_G>T (rs3745274) and CYP2B6_785_A>G (rs2279343) and breast cancer risk, we established a specific matrix‐assisted laser desorption/ionization time‐of‐flight mass spectrometry assay. The GENICA breast cancer case–control study showed associations between the variant genotypes CYP2B6_516_TT and CYP2B6_785_GG and breast cancer risk with odds ratios (ORs) of 1.34 (p = 0.001) and 1.31 (p = 0.002), respectively. A similar effect was observed for carriers of the CYP2B6_516_T allele in a validation study including four independent studies from Germany, Sweden and USA. In a pooled analysis of all five studies involving 4,638 breast cancer cases and 3,594 controls of European ancestry, carriers of the CYP2B6_516_G and the CYP2B6_785_G variant had an increased breast cancer risk with ORs of 1.10 (p = 0.027) and 1.10 (p = 0.031), respectively. We conclude that the genetic variants CYP2B6_516_G and CYP2B6_785_G (designated CYP2B6*6), which are known to decrease activity of the CYP2B6 enzyme, contribute to an increased breast cancer risk.

Because of privacy concerns and the expense involved in creating an annotated corpus, the existing small-annotated corpora might not have sufficient examples for learning to statistically extract all the named-entities precisely. In this work, we evaluate what value may lie in automatically generated features based on distributional semantics when using machine-learning named entity recognition (NER). The features we generated and experimented with include n-nearest words, support vector machine (SVM)-regions, and term clustering, all of which are considered distributional semantic features. The addition of the n-nearest words feature resulted in a greater increase in F-score than by using a manually constructed lexicon to a baseline system. Although the need for relatively small-annotated corpora for retraining is not obviated, lexicons empirically derived from unannotated text can not only supplement manually created lexicons, but also replace them. This phenomenon is observed in extracting concepts from both biomedical literature and clinical notes.

A large amount of medication information resides in the unstructured text found in electronic medical records, which requires advanced techniques to be properly mined. In clinical notes, medication information follows certain semantic patterns (eg, medication, dosage, frequency, and mode). Some medication descriptions contain additional word(s) between medication attributes. Therefore, it is essential to understand the semantic patterns as well as the patterns of the context interspersed among them (ie, context patterns) to effectively extract comprehensive medication information. In this paper we examined both semantic and context patterns, and compared those found in Mayo Clinic and i2b2 challenge data. We found that some variations exist between the institutions but the dominant patterns are common.