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Fibroblast growth factor 19 (FGF-19) is one of the founding members of the endocrine FGF subfamily. Recently, it has been the subject of much interest owing to its role in various physiological processes affecting glucose and lipid metabolism and the regulation of bile acid secretion as well as cell proliferation, differentiation, and motility. Additionally, FGF-19 secretion in an autocrine style has reportedly contributed to cancer progression in various types of malignancies including hepatocellular carcinoma (HCC).To estimate the serum FGF-19 concentrations in HCC cases and assess its diagnostic performance for the detection of HCC.We recruited 90 adult participants and divided them into three equal groups: Healthy controls, cirrhosis patients, and HCC patients. Serum FGF-19 concentrations were measured using the Human FGF-19 ELISA kit.We detected a high statistically significant difference in serum FGF-19 levels among the three groups. The highest level was observed in the HCC group, followed by the cirrhosis and control groups (236.44 ± 40.94FGF-19 represents a possible novel non-invasive marker for HCC. It may improve the prognosis of HCC patients due to its utility in several aspects of HCC detection and management.

BACKGROUND Biliary complications (BCs) after liver transplantation (LT) remain a considerable cause of morbidity, mortality, increased cost, and graft loss. AIM To investigate the impact of BCs on chronic graft rejection, graft failure and mortality. METHODS From 2011 to 2016, 215 adult recipients underwent right-lobe living-donor liver transplantation (RT-LDLT) at our centre. We excluded 46 recipients who met the exclusion criteria, and 169 recipients were included in the final analysis. Donors’ and recipients’ demographic data, clinical data, operative details and postoperative course information were collected. We also reviewed the management and outcomes of BCs. Recipients were followed for at least 12 mo post-LT until December 2017 or graft or patient loss. RESULTS The overall incidence rate of BCs including biliary leakage, biliary infection and biliary stricture was 57.4%. Twenty-seven (16%) patients experienced chronic graft rejection. Graft failure developed in 20 (11.8%) patients. A total of 28 (16.6%) deaths occurred during follow-up. BCs were a risk factor for the occurrence of chronic graft rejection and failure; however, mortality was determined by recurrent hepatitis C virus infection. CONCLUSION Biliary complications after RT-LDLT represent an independent risk factor for chronic graft rejection and graft failure; nonetheless, effective management of these complications can improve patient and graft survival.

The use of claims data in clinical research is gaining widespread acceptance by stakeholders, resulting in increased utilization by researchers in the real-world, late phase space. Coupled with technological advances and robust processes in data extraction, cleaning and integration with clinical data from electronic medical records, claims data hold the promise of potentially increasing the reliability of research results while simultaneously decreasing site and patient burden to participating in clinical trials. In this chapter, we explore diverse examples of how claims data can be used to design, implement and troubleshoot various issues in the pragmatic clinical trial space. Challenges and solutions are highlighted using examples from clinical trials in multiple therapeutic areas with the intent of continuing the discussion on how the use of claims data in clinical research can potentially be refined in the future.

The corrugated steel cladding used to cover most of steel buildings is considered as non-structural element. This research will reflect the effect of cladding as a shear diaphragm in increasing the normal elastic capacity of columns. This study is important because of the lack of information of the behavior of cladding and secondary members in various codes. Mathematical models for six different cases are carried by software. The results extracted from the program have been plotted showing the effects of different variables on the ultimate load of column. The variables considered in our research are the spacing between columns and the thickness of the corrugated sheet representing the sheet stiffness., {"references":["Minimum Design Loads for Buildings and Other Structures, ASCE\nSTANDARD ASCE/ ISEI, July, (2005).","AISC 325-05 Steel Construction Manual, Thirteenth Edition American\nInstitute of Steel Construction / 01, Feb, (2006).","Ansys, 2002. Engineering Analysis System. On line manuals.\nLundgren, K., Gustavson, R., & Magnusson, J., 2002. Finite element\nmodeling as a tool to understand the bond mechanisms. Proceedings,\nBond in concrete - from research to standards, 8 p., Budapest.","ANSYS Workbench 11, ANSYS, Inc. Canonsburg, PA, 2007.","Yu, W.W., \"Cold-Formed Steel Structures\" Structural Engineering\nHandbook, Ed. Chen Wai-Fah, Boca Raton: CRC Press LLC, 1999.","Egyptian code of practice for steel construction and bridges (allowable\nstress design), code No. ECP 205 - 2001, edition 2007.","Zhi-ming Ye, Roger J. Kettle, Long-Yuan Li, and W. Schafer, \"\nBuckling Behaviour of Cold formed Zed-Purlins Partially Restrained by\nSteel Sheeting\" Thin-Walled Structures 40 (2002) 853-864.","Zhi-ming Ye, Roger J. Kettle, and Long-Yuan Li, \" Analysis of Cold\nformed Zed-Purlins Partially Restrained by Steel Sheeting\" Computers\nand Structures 82 (2004) 731-739.","M. Lokman , F. Fayez and H. El Tobgey \" Effect of Corrugated Sheets\nas Shear Diaphragms on Stability of Steel Frames\" Degree of Master\nScience in Structural Engineering Cairo University (2008)."]}

The calculation of buckling length factor (K) for steel frames columns is a major and governing processes to determine the dimensions steel frame columns cross sections during design. The buckling length of steel frames columns has a direct effect on the cost (weight) of using cross section. A new formula is required to determine buckling length factor (K) by simplified way. In this research a new formula for buckling length factor (K) was established to determine by accurate method for a limited interval of columns ends rigidity (GA, GB). The new formula can be used ease to evaluate the buckling length factor without needing to complicated equations or difficult charts., {"references":["Pierre Dumonteil, (1992) , \"Simple Equations for Effective Length\nFactor\",Engineering journal, American Institute of steel Construction,\nThird quarter (1992), pp. 111-115.","Minimum Design Loads for Buildings and Other Structures, ASCE\nSTANDARD ASCE/ ISEI, July, (2005).","AISC 325-05 Steel Construction Manual, Thirteenth Edition American\nInstilled of Steel Construction / 01, Feb, (2006).","Egyptian Code of Practice for Steel Construction (ECP), first edition,\n(2008).","El - Sayed Bahaa Machaly, (2001), \"Behavior, Analysis and Design of\nStructural Steel Elements\", Professor of steel structures, faculty\nEngineering, Cairo University, Egypt.","Barakat, M., and Chen, W. F, \"Practical Analysis of Scmi-Rigid\nFramQS.\", AISC Engineering Journal, Vol. 27, No. 2 (2nd Quarter 1990),\npp. 54-68.","American Concrete Institute, Building Code Requirements for\nReinforced Concrete/Commentary, ACI 318R05, Paragraph RIO. 11.2.","McGuire, W., \"Computers and Steel Design\", Modern Steel\nConstruction, Vol. 32, No. 7, pp .39^2, July 1992.","Yura, J . A., \"The Effective Length of Columns in Untraced Frames\",\nAISC Engineering Journal, Vol. 8, 2 pp, 37 ^ 2, THIRD\nQUARTER/1992.\n[10] National Standard of Canada CAN/CSA-S16, 1-M89, Limit States\nDesign of Steel Structures, 1989."]}