Structural Assessment of the 13th Century Great Mosque and Hospital of Divrigi: A World Heritage Listed Structure

The Great Mosque and Hospital of Divrigi is located in the central eastern part of Turkey, in Divrigi, Sivas. The historical facility consists of a monumental mosque and a two-story hospital, which are adjacent to each other. The structure dates back to 13th century Mengujekids period and has been listed by the UNESCO as a World Heritage since 1985. Great Mosque and Hospital of Divrigi is particularly notable for its monumental stone portals that are decorated with three-dimensional ornaments carved from stone. The structural system of the monument consists of multi-leaf stone masonry walls and stone piers that support the roof structure which consists of stone and brick arches and vaults. The structure is located about 90 km away from the North Anatolian Fault Line, that has been causing several destructive earthquakes. Consequently, the structure is prone to destructive seismic activities. In this study, after a brief introduction on the structural system and current condition of the structure, the structural performance of the Great Mosque and Hospital of Divrigi is investigated through site observations and structural analyses. For this purpose, linear and nonlinear 3D finite element models of the structure are developed and the structure is examined under the effects of vertical loads and seismic actions. In the light of the analyses results, recommendations for potential interventions are outlined for further preservation of the structure

Electrophysiological evaluation of phrenic nerve injury during cardiac surgery – a prospective, controlled, clinical study

BACKGROUND: According to some reports, left hemidiaphragmatic paralysis due to phrenic nerve injury may occur following cardiac surgery. The purpose of this study was to document the effects on phrenic nerve injury of whole body hypothermia, use of ice-slush around the heart and mammary artery harvesting. METHODS: Electrophysiology of phrenic nerves was studied bilaterally in 78 subjects before and three weeks after cardiac or peripheral vascular surgery. In 49 patients, coronary artery bypass grafting (CABG) and heart valve replacement with moderate hypothermic (mean 28°C) cardiopulmonary bypass (CPB) were performed. In the other 29, CABG with beating heart was performed, or, in several cases, peripheral vascular surgery with normothermia. RESULTS: In all patients, measurements of bilateral phrenic nerve function were within normal limits before surgery. Three weeks after surgery, left phrenic nerve function was absent in five patients in the CPB and hypothermia group (3 in CABG and 2 in valve replacement). No phrenic nerve dysfunction was observed after surgery in the CABG with beating heart (no CPB) or the peripheral vascular groups. Except in the five patients with left phrenic nerve paralysis, mean phrenic nerve conduction latency time (ms) and amplitude (mV) did not differ statistically before and after surgery in either group (p > 0.05). CONCLUSIONS: Our results indicate that CPB with hypothermia and local ice-slush application around the heart play a role in phrenic nerve injury following cardiac surgery. Furthermore, phrenic nerve injury during cardiac surgery occurred in 10.2 % of our patients (CABG with CPB plus valve surgery)

TLR 9 Activation in Dendritic Cells Enhances Salmonella Killing and Antigen Presentation via Involvement of the Reactive Oxygen Species

Synthetic CpG containing oligodeoxynucleotide Toll like receptor-9 agonist (CpG DNA) activates innate immunity and can stimulate antigen presentation against numerous intracellular pathogens. It was observed that Salmonella Typhimurium growth can be inhibited by the CpG DNA treatment in the murine dendritic cells. This inhibitory effect was mediated by an increased reactive oxygen species production. In addition, it was noted that CpG DNA treatment of dendritic cells during Salmonella infection leads to an increased antigen presentation. Further this increased antigen presentation was dependent on the enhanced reactive oxygen species production elicited by Toll like receptor-9 activation. With the help of an exogenous antigen it was shown that Salmonella antigen could also be cross-presented in a better way by CpG induction. These data collectively indicate that CpG DNA enhance the ability of murine dendritic cells to contain the growth of virulent Salmonella through reactive oxygen species dependent killing

Effects of typical and atypical antipsychotic drugs on gene expression profiles in the liver of schizophrenia subjects

<p>Abstract</p> <p>Background</p> <p>Although much progress has been made on antipsychotic drug development, precise mechanisms behind the action of typical and atypical antipsychotics are poorly understood.</p> <p>Methods</p> <p>We performed genome-wide expression profiling to study effects of typical antipsychotics and atypical antipsychotics in the postmortem liver of schizophrenia patients using microarrays (Affymetrix U133 plus2.0). We classified the subjects into typical antipsychotics (n = 24) or atypical antipsychotics (n = 26) based on their medication history, and compared gene expression profiles with unaffected controls (n = 34). We further analyzed individual antipsychotic effects on gene expression by sub-classifying the subjects into four major antipsychotic groups including haloperidol, phenothiazines, olanzapine and risperidone.</p> <p>Results</p> <p>Typical antipsychotics affected genes associated with nuclear protein, stress responses and phosphorylation, whereas atypical antipsychotics affected genes associated with golgi/endoplasmic reticulum and cytoplasm transport. Comparison between typical antipsychotics and atypical antipsychotics further identified genes associated with lipid metabolism and mitochondrial function. Analyses on individual antipsychotics revealed a set of genes (151 transcripts, FDR adjusted p < 0.05) that are differentially regulated by four antipsychotics, particularly by phenothiazines, in the liver of schizophrenia patients.</p> <p>Conclusion</p> <p>Typical antipsychotics and atypical antipsychotics affect different genes and biological function in the liver. Typical antipsychotic phenothiazines exert robust effects on gene expression in the liver that may lead to liver toxicity. The genes found in the current study may benefit antipsychotic drug development with better therapeutic and side effect profiles.</p

Diagnostic assessment of deep learning algorithms for detection of lymph node metastases in women with breast cancer

Importance Application of deep learning algorithms to whole-slide pathology images can potentially improve diagnostic accuracy and efficiency. Objective Assess the performance of automated deep learning algorithms at detecting metastases in hematoxylin and eosin–stained tissue sections of lymph nodes of women with breast cancer and compare it with pathologists’ diagnoses in a diagnostic setting. Design, Setting, and Participants Researcher challenge competition (CAMELYON16) to develop automated solutions for detecting lymph node metastases (November 2015-November 2016). A training data set of whole-slide images from 2 centers in the Netherlands with (n = 110) and without (n = 160) nodal metastases verified by immunohistochemical staining were provided to challenge participants to build algorithms. Algorithm performance was evaluated in an independent test set of 129 whole-slide images (49 with and 80 without metastases). The same test set of corresponding glass slides was also evaluated by a panel of 11 pathologists with time constraint (WTC) from the Netherlands to ascertain likelihood of nodal metastases for each slide in a flexible 2-hour session, simulating routine pathology workflow, and by 1 pathologist without time constraint (WOTC). Exposures Deep learning algorithms submitted as part of a challenge competition or pathologist interpretation. Main Outcomes and Measures The presence of specific metastatic foci and the absence vs presence of lymph node metastasis in a slide or image using receiver operating characteristic curve analysis. The 11 pathologists participating in the simulation exercise rated their diagnostic confidence as definitely normal, probably normal, equivocal, probably tumor, or definitely tumor. Results The area under the receiver operating characteristic curve (AUC) for the algorithms ranged from 0.556 to 0.994. The top-performing algorithm achieved a lesion-level, true-positive fraction comparable with that of the pathologist WOTC (72.4% [95% CI, 64.3%-80.4%]) at a mean of 0.0125 false-positives per normal whole-slide image. For the whole-slide image classification task, the best algorithm (AUC, 0.994 [95% CI, 0.983-0.999]) performed significantly better than the pathologists WTC in a diagnostic simulation (mean AUC, 0.810 [range, 0.738-0.884]; P < .001). The top 5 algorithms had a mean AUC that was comparable with the pathologist interpreting the slides in the absence of time constraints (mean AUC, 0.960 [range, 0.923-0.994] for the top 5 algorithms vs 0.966 [95% CI, 0.927-0.998] for the pathologist WOTC). Conclusions and Relevance In the setting of a challenge competition, some deep learning algorithms achieved better diagnostic performance than a panel of 11 pathologists participating in a simulation exercise designed to mimic routine pathology workflow; algorithm performance was comparable with an expert pathologist interpreting whole-slide images without time constraints. Whether this approach has clinical utility will require evaluation in a clinical setting