Modulation of growth and angiogenic potential of oral squamous carcinoma cells in vitro using salvianolic acid B

<p>Abstract</p> <p>Background</p> <p>Our previous studies showed that Salvianolic acid B (Sal B) inhibited 7,12-dimethylbenz[a]anthracene (DMBA)-induced oral carcinogenesis in hamsters and such anti-cancer effects might be related to the inhibition of angiogenesis. This study was aimed to further investigate the anti-proliferative effect of Sal B on the most common type of oral cancer, oral squamous cell carcinoma (OSCC) and the possible mechanisms of action with respect to angiogenesis inhibition.</p> <p>Methods</p> <p>Two well-characterized oral squamous cell carcinoma cell lines, CAL27 and SCC4, and premalignant leukoplakia cells were treated with different concentrations of Sal B. Cytotoxicity was assessed by MTT assay. cDNA microarray was utilized to evaluate the expression of 96 genes known to be involved in modulating the biological processes of angiogenesis. Real-time reverse transcription-polymerase chain reaction analysis was conducted to confirm the cDNA microarray data.</p> <p>Results</p> <p>Sal B induced growth inhibition in OSCC cell lines but had limited effects on premalignant cells. A total of 17 genes showed a greater than 3-fold change when comparing Sal B treated OSCC cells to the control. Among these genes, HIF-1α, TNFα and MMP9 are specifically inhibited, expression of THBS2 was up-regulated.</p> <p>Conclusions</p> <p>Sal B has inhibitory effect on OSCC cell growth. The antitumor effect can be attributed to anti-angiogenic potential induced by a decreased expression of some key regulator genes of angiogenesis. Sal B may be a promising modality for treating oral squamous cell carcinoma.</p

The Immune Cell Composition in Barrett's Metaplastic Tissue Resembles That in Normal Duodenal Tissue

BACKGROUND AND OBJECTIVE: Barrett's esophagus (BE) is characterized by the transition of squamous epithelium into columnar epithelium with intestinal metaplasia. The increased number and types of immune cells in BE have been indicated to be due to a Th2-type inflammatory process. We tested the alternative hypothesis that the abundance of T-cells in BE is caused by a homing mechanism that is found in the duodenum. PATIENTS AND METHODS: Biopsies from BE and duodenal tissue from 30 BE patients and duodenal tissue from 18 controls were characterized by immmunohistochemistry for the presence of T-cells and eosinophils(eos). Ex vivo expanded T-cells were further phenotyped by multicolor analysis using flowcytometry. RESULTS: The high percentage of CD4(+)-T cells (69±3% (mean±SEM/n = 17, by flowcytometry)), measured by flowcytometry and immunohistochemistry, and the presence of non-activated eosinophils found in BE by immunohistochemical staining, were not different from that found in duodenal tissue. Expanded lymphocytes from these tissues had a similar phenotype, characterized by a comparable but low percentage of αE(CD103) positive CD4(+)cells (44±5% in BE, 43±4% in duodenum of BE and 34±7% in duodenum of controls) and a similar percentage of granzyme-B(+)CD8(+) cells(44±5% in BE, 33±6% in duodenum of BE and 36±7% in duodenum of controls). In addition, a similar percentage of α4β7(+) T-lymphocytes (63±5% in BE, 58±5% in duodenum of BE and 62±8% in duodenum of controls) was found. Finally, mRNA expression of the ligand for α4β7, MAdCAM-1, was also similar in BE and duodenal tissue. No evidence for a Th2-response was found as almost no IL-4(+)-T-cells were seen. CONCLUSION: The immune cell composition (lymphocytes and eosinophils) and expression of intestinal adhesion molecule MAdCAM-1 is similar in BE and duodenum. This supports the hypothesis that homing of lymphocytes to BE tissue is mainly caused by intestinal homing signals rather than to an active inflammatory response

Immediate surgery compared with short-course neoadjuvant gemcitabine plus capecitabine, FOLFIRINOX, or chemoradiotherapy in patients with borderline resectable pancreatic cancer (ESPAC5): a four-arm, multicentre, randomised, phase 2 trial.

BACKGROUND: Patients with borderline resectable pancreatic ductal adenocarcinoma have relatively low resection rates and poor survival despite the use of adjuvant chemotherapy. The aim of our study was to establish the feasibility and efficacy of three different types of short-course neoadjuvant therapy compared with immediate surgery. METHODS: ESPAC5 (formerly known as ESPAC-5f) was a multicentre, open label, randomised controlled trial done in 16 pancreatic centres in two countries (UK and Germany). Eligible patients were aged 18 years or older, with a WHO performance status of 0 or 1, biopsy proven pancreatic ductal adenocarcinoma in the pancreatic head, and were staged as having a borderline resectable tumour by contrast-enhanced CT criteria following central review. Participants were randomly assigned by means of minimisation to one of four groups: immediate surgery; neoadjuvant gemcitabine and capecitabine (gemcitabine 1000 mg/m2 on days 1, 8, and 15, and oral capecitabine 830 mg/m2 twice a day on days 1-21 of a 28-day cycle for two cycles); neoadjuvant FOLFIRINOX (oxaliplatin 85 mg/m2, irinotecan 180 mg/m2, folinic acid given according to local practice, and fluorouracil 400 mg/m2 bolus injection on days 1 and 15 followed by 2400 mg/m2 46 h intravenous infusion given on days 1 and 15, repeated every 2 weeks for four cycles); or neoadjuvant capecitabine-based chemoradiation (total dose 50·4 Gy in 28 daily fractions over 5·5 weeks [1·8 Gy per fraction, Monday to Friday] with capecitabine 830 mg/m2 twice daily [Monday to Friday] throughout radiotherapy). Patients underwent restaging contrast-enhanced CT at 4-6 weeks after neoadjuvant therapy and underwent surgical exploration if the tumour was still at least borderline resectable. All patients who had their tumour resected received adjuvant therapy at the oncologist's discretion. Primary endpoints were recruitment rate and resection rate. Analyses were done on an intention-to-treat basis. This trial is registered with ISRCTN, 89500674, and is complete. FINDINGS: Between Sept 3, 2014, and Dec 20, 2018, from 478 patients screened, 90 were randomly assigned to a group (33 to immediate surgery, 20 to gemcitabine plus capecitabine, 20 to FOLFIRINOX, and 17 to capecitabine-based chemoradiation); four patients were excluded from the intention-to-treat analysis (one in the capecitabine-based chemoradiotherapy withdrew consent before starting therapy and three [two in the immediate surgery group and one in the gemcitabine plus capecitabine group] were found to be ineligible after randomisation). 44 (80%) of 55 patients completed neoadjuvant therapy. The recruitment rate was 25·92 patients per year from 16 sites; 21 (68%) of 31 patients in the immediate surgery and 30 (55%) of 55 patients in the combined neoadjuvant therapy groups underwent resection (p=0·33). R0 resection was achieved in three (14%) of 21 patients in the immediate surgery group and seven (23%) of 30 in the neoadjuvant therapy groups combined (p=0·49). Surgical complications were observed in 29 (43%) of 68 patients who underwent surgery; no patients died within 30 days. 46 (84%) of 55 patients receiving neoadjuvant therapy were available for restaging. Six (13%) of 46 had a partial response. Median follow-up time was 12·2 months (95% CI 12·0-12·4). 1-year overall survival was 39% (95% CI 24-61) for immediate surgery, 78% (60-100) for gemcitabine plus capecitabine, 84% (70-100) for FOLFIRINOX, and 60% (37-97) for capecitabine-based chemoradiotherapy (p=0·0028). 1-year disease-free survival from surgery was 33% (95% CI 19-58) for immediate surgery and 59% (46-74) for the combined neoadjuvant therapies (hazard ratio 0·53 [95% CI 0·28-0·98], p=0·016). Three patients reported local disease recurrence (two in the immediate surgery group and one in the FOLFIRINOX group). 78 (91%) patients were included in the safety set and assessed for toxicity events. 19 (24%) of 78 patients reported a grade 3 or worse adverse event (two [7%] of 28 patients in the immediate surgery group and 17 [34%] of 50 patients in the neoadjuvant therapy groups combined), the most common of which were neutropenia, infection, and hyperglycaemia. INTERPRETATION: Recruitment was challenging. There was no significant difference in resection rates between patients who underwent immediate surgery and those who underwent neoadjuvant therapy. Short-course (8 week) neoadjuvant therapy had a significant survival benefit compared with immediate surgery. Neoadjuvant chemotherapy with either gemcitabine plus capecitabine or FOLFIRINOX had the best survival compared with immediate surgery. These findings support the use of short-course neoadjuvant chemotherapy in patients with borderline resectable pancreatic ductal adenocarcinoma. FUNDING: Cancer Research UK

A ROC analysis-based classification method for landslide susceptibility maps

[EN] A landslide susceptibility map is a crucial tool for landuse spatial planning and management in mountainous areas. An essential issue in such maps is the determination of susceptibility thresholds. To this end, the map is zoned into a limited number of classes. Adopting one classification system or another will not only affect the map's readability and final appearance, but most importantly, it may affect the decision-making tasks required for effective land management. The present study compares and evaluates the reliability of some of the most commonly used classification methods, applied to a susceptibility map produced for the area of La Marina (Alicante, Spain). A new classification method based on ROC analysis is proposed, which extracts all the useful information from the initial dataset (terrain characteristics and landslide inventory) and includes, for the first time, the concept of misclassification costs. This process yields a more objective differentiation of susceptibility levels that relies less on the intrinsic structure of the terrain characteristics. The results reveal a considerable difference between the classification methods used to define the most susceptible zones (in over 20% of the surface) and highlight the need to establish a standard method for producing classified susceptibility maps. The method proposed in the study is particularly notable for its consistency, stability and homogeneity, and may mark the starting point for consensus on a generalisable classification method.Cantarino-Martí, I.; Carrión Carmona, MÁ.; Goerlich-Gisbert, F.; Martínez Ibáñez, V. (2018). A ROC analysis-based classification method for landslide susceptibility maps. Landslides. 1-18. doi:10.1007/s10346-018-1063-4S118Armstrong MP, Xiao N, Bennett DA (2003) Using genetic algorithms to create multicriteria class intervals for choropleth maps. Ann Assoc Am Geogr 93(3):595–623. https://doi.org/10.1111/1467-8306.9303005Atkinson P, Massari R (1998) Generalised linear modelling of susceptibility to landsliding in the central Apennines, Italy. Comput Geosci 24(4):373–385. https://doi.org/10.1016/S0098-3004(97)00117-9Ayalew L, Yamagishi H (2005) The application of GIS-based logistic regression for landslide susceptibility mapping in the Kakuda-Yahiko Mountains, Central Japan. Geomorphology 65(1–2):15–31. https://doi.org/10.1016/j.geomorph.2004.06.010Baeza C, Lantada N, Amorim S (2016) Statistical and spatial analysis of landslide susceptibility maps with different classification systems. Environ Earth Science 75:1318. https://doi.org/10.1007/s12665-016-6124-1Basofi A, Fariza A, Ahsan AS, Kamal IM (2015) A comparison between natural and head/tail breaks in LSI (landslide susceptibility index) classification for landslide susceptibility mapping: a case study in Ponorogo, East Java, Indonesia. 2015 International Conference on Science in Information Technology, pp 337–342Cantarino I (2013) Elaboración y validación de un modelo jerárquico derivado de SIOSE. Revista de Teledetección 39:5–21Carrara A, Crosta GB, Frattini P (2008) Comparing models of debris-flow susceptibility in the alpine environment. Geomorphology 94(3–4):353–378. https://doi.org/10.1016/j.geomorph.2006.10.033Chacón J, Irigaray C, Fernández T, El Hamdouni R (2006) Engineering geology maps: landslides and geographical information systems. Bull Eng Geol Environ 65(4):341–411Chung CJF, Fabbri AG (2003) Validation of spatial prediction models for landslide hazard mapping. Nat Hazards 30:451–472COPUT (1998) Lithology, exploitation of industrial rocks and landslide risk in the Valencian Community. Thematic Mapping Series. Department of Public Works of the Valencian Regional GovernmentDrummond C, Holte RC (2006) Cost curves: an improved method for visualizing classifier performance. Mach Learn 65(1):95–130Duman TY, Can T, Gokceoglu C, Nefeslioglu HA, Sonmez H (2006) Application of logistic regression for landslide susceptibility zoning of Cekmece Area, Istanbul, Turkey. Environ Geol 51(2):241–256. https://doi.org/10.1007/s00254-006-0322-1Evans IS (1977) The selection of class intervals. Transactions of the Institute of British Geographers. Contemp Cartograph 2(1):98–124. https://doi.org/10.2307/622195Fleiss JL, Levin B, Paik MC (2003) Statistical methods for rates and proportions, Book Series: Wiley Series in Probability and Statistics. John Wiley & Sons. Print ISBN: 9780471526292. doi: https://doi.org/10.1002/0471445428Foody GM (2004) Thematic map comparison: evaluating the statistical significance of differences in classification accuracy. Photogramm Eng Remote Sens 70(5):627–633Fotheringham AS, Brunsdon C, Charlton M (2000) Quantitative geography: perspectives on spatial data analysis. SAGE Publications, Thousand Oaks 270 ppFrattini P, Crosta G, Carrara A (2010) Techniques for evaluating the performance of landslide susceptibility models. Eng Geol 111(1–4):62–72. https://doi.org/10.1016/j.enggeo.2009.12.004Geisser S (1998) Comparing two tests used for diagnostic or screening processes. Stat Probability Lett 40:113–119Greiner M, Pfeiffer D, Smith RD (2000) Principles and practical application of the receiver-operating characteristic analysis for diagnostic tests. Prev Vet Med 45:23–41Günther A, Reichenbach P, Malet JP, van den Eeckhaut M, Hervás J, Dashwood C, Guzzetti F (2013) Tier-based approaches for landslide susceptibility assessment in Europe. Landslides 10:529–546. https://doi.org/10.1007/s10346-012-0349-1Günther A, Van Den Eeckhaut M, Malet J-P, Reichenbach P, Hervás J (2014) Climate-physiographically differentiated Pan-European landslide susceptibility assessment using spatial multi-criteria evaluation and transnational landslide information. Geomorphology 224:69–85Gupta RP, Kanungo DP, Arora MK, Sarkar S (2008) Approaches for comparative evaluation of raster GIS-based landslide susceptibility zonation maps. Int J Appl Earth Obs Geoinf 10(3):330–341. https://doi.org/10.1016/j.jag.2008.01.003Guzzetti F, Reichenbach P, Ardizzone F, Cardinali M, Galli M (2006) Estimating the quality of landslide susceptibility models. Geomorphology 81(1–2):166–184. https://doi.org/10.1016/j.geomorph.2006.04.007Hervás J (2017) El inventario de movimientos de ladera de España ALISSA: Metodología y análisis preliminar. In: Alonso E, Corominas J, Hürlimann M (Eds.), Taludes 2017. Proc. IX Simposio Nacional sobre Taludes y Laderas Inestables, Santander, 27–30 June 2017. CIMNE, Barcelona, pp. 629–639Jaedicke C, Van Den Eeckhaut M, Nadim F et al (2014) Identification of landslide hazard and risk ‘hotspots’ in Europe. Bull Eng Geol Environ 73:325. https://doi.org/10.1007/s10064-013-0541-0Jenks GF (1967) The data model concept in statistical mapping. Int Yearbook Cartograph 7:186–190Jiang B (2013) Head/tail breaks: a new classification scheme for data with a heavy-tailed distribution. Prof Geogr 65(3):482–494. https://doi.org/10.1080/00330124.2012.700499Kiang MY (2003) A comparative assessment of classification methods. Decis Support Syst 35(4):441–454. https://doi.org/10.1016/S0167-9236(02)00110-0Landis JR, Koch GG (1977) The measurement of observer agreement for categorical data. Biometrics 33(1):159–174Langping L, Hengxing L, Changbao G, Yongshuang Z, Quanwen L, Yuming W (2017) A modified frequency ratio method for landslide susceptibility assessment. Landslides 14:727–741. https://doi.org/10.1007/s10346-016-0771-xLee S (2007) Comparison of landslide susceptibility maps generated through multiple logistic regression for three test areas in Korea. Earth Surf Process Landforms 32:2133–2148. https://doi.org/10.1002/esp.1517Liu C, Frazier P, Kumar L (2007) Comparative assessment of the measures of thematic classification accuracy. Remote Sens Environ 107(4):606–616. https://doi.org/10.1016/j.rse.2006.10.010López-Ratón M, Rodríguez-Álvarez MX, Cadarso-Suárez C, Gude-Sampedro F (2014) Optimal cutpoints: an R package for selecting optimal cutpoints in diagnostic tests. J Stat Softw 61(8):4Malet JP, Puissant A, Mathieu A, Van Den Eeckhaut M, Fressard M (2013) Integrating spatial multi-criteria evaluation and expert knowledge for country-scale landslide susceptibility analysis: application to France. In: Margottini C, Canuti P, Sassa K (eds) Landslide science and practice. Springer, Berlin. https://doi.org/10.1007/978-3-642-31325-7_40McGee S (2002) Simplifying likelihood ratios. J Gen Intern Med 17:647–650Metz C (1978) Basic principles of ROC analysis. Semin Nucl Med VIII(4):183–198Nadim F, Kjekstad O, Peduzzi P, Herold C, Jaedicke C (2006) Global landslide and avalanche hotspots. Landslides 3:159–173. https://doi.org/10.1007/s10346-006-0036-1Ohlmacher G, Davis J (2003) Using multiple logistic regression and GIS technology to predict landslide hazard in northeast Kansas, USA. Eng Geol 69(3–4):331–343. https://doi.org/10.1016/S0013-7952(03)00069-3Powell RL, Matzke N, de Souza C Jr, Clark M, Numata I, Hess LL, Roberts DA (2004) Sources of error accuracy assessment of thematic land-cover maps in the Brazilian Amazon. Remote Sens Environ 90(2):221–234. https://doi.org/10.1016/j.rse.2003.12.007Saaty T (1980) The analytic hierarchy process. McGraw Hill, New YorkSmits PC, Dellepiane SG, Schowengerdt RA (1999) Quality assessment of image classification algorithms for land-cover mapping: a review and proposal for a cost-based approach. Int J Remote Sens 20:1461–1486Stehman SV, Czaplewski RL (1998) Design and analysis of thematic map accuracy assessment: fundamental principles. Remote Sens Environ 64:331–344Swets JA (1988) Measuring the accuracy of diagnostic systems. Science 240(4857):1285–1293Van Den Eeckhaut M, Hervás J, Jaedicke C, Malet J-P, Montanarella L, Nadim F (2012) Statistical modelling of Europe-wide landslide susceptibility using limited landslide inventory data. Landslides 8:357–369Varnes DJ (1984) Landslide hazard zonation: a review of principles and practice. Natural hazards. UNESCO, ParisZhu X (2016) GIS for environmental applications. Routledge, Abingdon, p 490Zweig MH, Campbell G (1993) Receiver-operating characteristic (ROC) plots: a fundamental evaluation tool in clinical medicine. Clin Chem 39(4):561–57

Informatics Technology Mimics Ecology: Dense, Mutualistic Collaboration Networks Are Associated with Higher Publication Rates

Information technology (IT) adoption enables biomedical research. Publications are an accepted measure of research output, and network models can describe the collaborative nature of publication. In particular, ecological networks can serve as analogies for publication and technology adoption. We constructed network models of adoption of bioinformatics programming languages and health IT (HIT) from the literature

Infant Brain Atlases from Neonates to 1- and 2-Year-Olds

Background: Studies for infants are usually hindered by the insufficient image contrast, especially for neonates. Prior knowledge, in the form of atlas, can provide additional guidance for the data processing such as spatial normalization, label propagation, and tissue segmentation. Although it is highly desired, there is currently no such infant atlas which caters for all these applications. The reason may be largely due to the dramatic early brain development, image processing difficulties, and the need of a large sample size. Methodology: To this end, after several years of subject recruitment and data acquisition, we have collected a unique longitudinal dataset, involving 95 normal infants (56 males and 39 females) with MRI scanned at 3 ages, i.e., neonate, 1-yearold, and 2-year-old. State-of-the-art MR image segmentation and registration techniques were employed, to construct which include the templates (grayscale average images), tissue probability maps (TPMs), and brain parcellation maps (i.e., meaningful anatomical regions of interest) for each age group. In addition, the longitudinal correspondences between agespecific atlases were also obtained. Experiments of typical infant applications validated that the proposed atlas outperformed other atlases and is hence very useful for infant-related studies. Conclusions: We expect that the proposed infant 0–1–2 brain atlases would be significantly conducive to structural and functional studies of the infant brains. These atlases are publicly available in our website