Academic literature on the topic 'Ca 4 B C -65 A D Medea'

One form of early mathematical recognition is to introduce the concept of geometric shapes. Geometry is an important scientific discipline for present and future life by developing various ways that fit 21st century skills. This study aims to overcome the problem of early mathematical recognition of early childhood on geometry, especially how to recognize geometric forms based on computer learning. A total of 24 children aged 4-5 years in kindergarten has to carrying out 2 research cycles with a total of 5 meetings. Treatment activities in each learning cycle include mentioning, grouping and imitating geometric shapes. There were only 7 children who were able to recognize the geometric shapes in the pre-research cycle (29.2%). An increase in the number of children who are able to do activities well in each research cycle includes: 1) The activities mentioned in the first cycle and 75% in the second cycle; 2) Classifying activities in the first cycle were 37.5% and 75% in the second cycle; 3) Imitation activities in the first cycle 54.2% and 79.2% in the second cycle. The results of data acquisition show that computer learning application can improve the ability to recognize geometric shapes, this is because computer learning provides software that has activities to recognize geometric shapes with the animation and visuals displayed. Keywords: Early Childhood Computer Learning, Geometry Forms, Early Math Skills Reference Alia, T., & Irwansyah. (2018). Pendampingan Orang Tua pada Anak Usia Dini dalam Penggunaan Teknologi Digital. A Journal of Language, Literature, Culture and Education, 14(1), 65– 78. https://doi.org/10.19166/pji.v14i1.639 Ameliola, S., & Nugraha, H. D. (2013). Perkembangan Media Informasi dan Teknologi Terhadap Anak di Era Globalisasi. International Conferences in Indonesian Studies : “Etnicity and Globalization.” Anderson, L. W., Krathwohl, D. R., & Bloom, B. S. (2001). A taxonomy for learning, teaching, and assessing: a revision of Bloom’s taxonomy of educational objectives. New York: Longman. Arikunto, S. (2010). Prosedur Penelitian Suatu Pendekatan Praktik. Jakarta: Asdi Mahasatya. Arsyad, N., Rahman, A., & Ahmar, A. S. (2017). Developing a self-learning model based on open-ended questions to increase the students’ creativity in calculus. Global Journal of Engineering Education, 19(2), 143–147. https://doi.org/10.26858/gjeev19i2y2017p143147 Asiye, I., Ahmet, E., & Abdullah, A. (2018). Developing a Test for Geometry and Spatial Perceptions of 5-6 Year-Old. Kastamonu Education Journal, 26(1). Aslan, D., & Yasare, A. (2007). Three to Six Years OldChildren’s Recognition of Geometric Shapes. International Journal of Early Years Education, 15 :1, 83–104. Ben-Yehoshua, D., Yaski, O., & Eilam, D. (2011). Spatial behavior: the impact of global and local geometry. Animal Cognition Journal, 13(3), 341–350. https://doi.org/10.1007/s10071- 010-0368-z Charlesworth, R., & Lind, K. K. (2010). Math and Sciend for Young Children. Canada: Wadsworth/Cengage Learning. Chen, J.-Q., & Chang, C. (2006). using computers in early childhood classrooms teachers’ attitudes,skills and practices. Early Childhood Research. Clements, D. H., & Samara. (2003). Strip mining for gold: Research and policy in educational technology—a response to “Fool’s Gold.” Association for the Advancement of Computing in Education (AACE) Journal, 11(1), 7–69. Cohen, L., & Manion, L. (1994). Research Methods in Education (fourth edi). London: Routledge. Conorldi, C., Mammarela, I. C., & Fine, G. G. (2016). Nonverbal Learning Disability (J. P. Guilford, Ed.). New York. Corey, S. M. (1953). Action Research to Improve School Practice. New York: Teachers College, Columbia University. Couse, L. J., & Chen, D. W. (2010). A tablet computer for young children? Exploring its viability for early childhood education. Journal of Research on Technology in Education, 43(1), 75– 98. https://doi.org/10.1080/15391523.2010.10782562 Delima, R., Arianti, N. K., & Pramudyawardani, B. (2015). Identifikasi Kebutuhan Pengguna Untuk Aplikasi Permainan Edukasi Bagi Anak Usia 4 sampai 6 Tahun. Jurnal Teknik Informatika Dan Sistem Informasi, 1(1). Depdiknas. (2007). Permainan Berhitung Permulaan Di Taman Kanak-kanak. In Pedoman Pembelajaran. Jakarta: Depdiknas. Djadir, Minggi, I., Ja’faruddin., Zaki, A., & Sidjara, S. (2017). Sumber Belajar PLPG 2017: Bangun Datar. In Modul PLPG. Jakarta: Kementrian Pendidikan dan Kebudayaan Direktorat Jenderal Guru dan Tenaga Kependidikan.Dooley, T., Dunphy, E., & Shiel, G. (2014). Mathematics in Early Childhood and Primary Education (3-8 years). Duncan, G. J., Dowsett, C. J., Claessens, A., Magnuson, K., Huston, A. C., Klebanov, P., ... Japel, C. (2007). School Readiness and Later Achievement. Developmental Psychology, 43(6), 1428–1446. https://doi.org/10.1037/0012-1649.43.6.1428 Duncan, G. J., & Magnuson, K. (2011). The nature and impact of early achievement skills, attention skills, and behavior problems. Whither Opportunity?: Rising Inequality, Schools, and Children’s Life Chances, (0322356), 47–69. Edwards, S. (2009). Early Childhood Education and Care: a sociocultural Approach. New South Wales: Pademelon Press. Feliyanah, Norman, S., & Yulidesni. (2014). Meningkatkan Kemampuan Matematika dengan Menggunakan Teknik Mengurutkan dan Membandingkan. Universitas Bengkulu. Gardner, H. (2011). Frame of Mind ; The theory of Multiple Intelegences. New York: Basic Book. Gimbert, B., & Cristol, D. (2004). Teaching Curriculum with Technology: Enhancing Children’s Technological Competence During Early Childhood. Early Childhood Education Journal, 31(1). Gulay, H. (2011a). The evaluation of the relationship between the computer using habits and proso_cial and aggressive behaviours of 5–6 years old children. International Journal of Academic Research, 3(2), 252. Gulay, H. (2011b). The evaluation of the relationship between the computer using habits and proso_cial and aggressive behaviours of 5–6 years old children. International Journal of Academic Research, 3(2), 252–257. Gunawan, I., & Palupi, A. R. (2012). Taksonomi Bloom-Revisi Ranah Kognitif; Kerangka Landasan untuk Pembelajaran, Pengajaran, dan Penilaian. Jurnal Pendidikan Dasar Dan Pembelajaran, 2 No.2, 100–108. Inan, H. Z., & Dogan-Temur, O. (2010). Understanding kindergarten teachers’ perspectives of teaching basic geometric shapes: A phenomenographic research. ZDM - International Journal on Mathematics Education, 42(5), 457–468. https://doi.org/10.1007/s11858-010- 0241-1 Jackman, H. I., Beaver, N. H., & Wyatt, S. S. (2014). Early Childhood Curriculum: A child’s connection to the world. (sixth edit). Canada: Cengage Learning. Kennedy, L. M., Tipps, S., & Johnson, A. (2008). Guiding Children’s Learning of Mathematic (Eleventh E; Belmot, Ed.). CA: Thomson Wadsworth. Mackintosh, B. B., & McCoy, D. C. (2019). Exploring Social Competence as a Mediator of Head Start’s Impact on Children’s Early Math Skills: Evidence from the Head Start Impact Study. Early Education and Development, 30(5), 655–677. https://doi.org/10.1080/10409289.2019.1576156 Martin, M. O., Mullis, I. V. S., Foy, P., & Stanco, G. M. (2011). Results in Science. Mirawati. (2017). Matematika Kreatif; Pembelajaran Matematika bagi Anak Usia Dini Melalui Kegiatan yang Menyenangkan dan Bermakna. Jurnal Anak Usia Dini Dan Pendidikan Anak Usia Dini, 3. Mohammad, M., & Mohammad, H. (2012). Computer integration into the early childhood curriculum. Education, 133(1), 97–116. National Research Council. (2009). Mathematics Learning in Early Chidhood Paths Toward Excellence and Equity (C. T. Cross, T. Woods, & H. Schweingruber, Eds.). Washinton D.C: The National Academies Press. Norton, A., & Nurnberger-Haag, J. (2018). Bridging frameworks for understanding numerical cognition. Journal of Numerical Cognition, 4(1), 1–8. https://doi.org/10.5964/jnc.v4i1.160 Novitasari, D. R. (2010). Pembangunan Media Pembelajaran Bahasa Inggris Untuk Siswa Kelas 1 Pada Sekolah Dasar Negeri 15 Sragen. Sentra Penelitian Engineering Dan Edukas, Volume 2 N. Papadakis, S., Kalogiannakis, M., & Zaranis, N. (2017). Improving Mathematics Teaching in Kindergarten with Realistic Mathematical Education. Early Childhood Education Journal, 45(3), 369–378. https://doi.org/10.1007/s10643-015-0768-4 Papalia, Old, & Feldman. (2009). Human Development (Psikologi Perkembangan (Kesembilan). Jakarta: Kencana. Paquette, K. R., Fello, S. E., & Jalongo, M. R. (2007). The talking drawings strategy: Using primary children’s Illustrations and oral language to improve comprehension of expository text. Early Childhood Education Journal, 35(1), 65–73. https://doi.org/10.1007/s10643- 007-0184-5 Putra, L. D., & Ishartiwi. (2015). Pengembangan Multimedia Pembelajaram Interaktif Mengenal Angka dan Huruf untuk Anak Usia Dini. Jurnal Inovasi Teknologi Pendidikan, 2(2). Rich, B., & Thomas, C. (2009). Geometry: Includes Plane, Analytic, and Transformational Geometries. . (4th Editio). New York: McGraw-Hill. Rochanah, L. (2016). Pemanfaatan Media Berbasis Komputer Untuk Meningkatkan Kemampuan Huruf pada Anak Usia Dini (Urgensi Media Berbasis Komputer pada Peningkatan Kemampuan Mengenal Huruf ). Jurnal Program Studi PGRA, Volume 2 N, 1–8. Runtukahu, T., & Kandou, S. (2014). Pembelajaran matematika dasar bagi anak berkesulitan belajar. Yogyakarta: Ar-ruzz Media. Santrock, J. W. (2016). Children (Thirteenth). New York: McGraw-Hill Education. Sarama, J., & Clements, D. H. (2006). Mathematics, Young Students, and Computers: Software, Teaching Strategies and Professional Development. The Mathematics Educato, 9(2), 112– 134. Schoenfeld, A. H., & Stipek, D. (2011). Math Matters. Barkeley, California.Shilpa, S., & Sunita, M. (2013). A Study About Role of Multimedia in Early Childhood Education. International Journal of Humanities and Social Science Invention, 2(6). Siswono, T. Y. E. (2012). Belajar dan Mengajar Matematika Anak Usia Dini. Universitas Negeri Surabaya.Smaldino, S. E., Russel, J. D., & Lowther, D. L. (2014). Instructional Technology & Media for Learning (9th ed.). Jakarta: Kencana Prenada Media Group. Sudaryanti. (2006). Pengenalan Matematika Anak Usia Dini. Yogyakarta: FIP UNY. Sufa, F. F., & Setiawan, H. Y. (2017). Analisis Kebutuhan Anak Usia 4-6 Tahun Pada Pembelajaran Berbasis Komputer Pada Anak Usia Dini. Research Fair Unisri, 1(1). Suharjana, A. (2008). Pengenalan Bangun Ruang dan Sifat-sifatnya di SD. Yogyakarta: Pusat Pengembangan dan Pemberdayaan Pendidik dan Tenaga Kependidikan Matematika. Sujiono, Y . N. (2014). Batasan dan Dasar T eori Pengembangan Kognitif. In Hakikat Pengembangan Kognitif (p. 12). Suryana, D. (2013). Pendidikan Anak Usia Dini (teori dan praktik pembelajaran). Padang: UNP Press. Susperreguy, M. I., & Davis-Kean, P. E. (2016). Maternal Math Talk in the Home and Math Skills in Preschool Children. Early Education and Development, 27(6), 841–857. https://doi.org/10.1080/10409289.2016.1148480 Suwarna. (2010). Pengembangan Multimedia Pembelajaran untuk Pembinaan Kreativitas Melukis di Taman Kanak-kanak. Jurnal Universitas Negeri Yogyakarta. Suziedelyte, A. (2012). Can video games affect children’s cognitive and non-cognitive skills? UNSW Australian School of Business Research Paper. https://doi.org/10.2139/ssrn.2140983 Tarigan, D. (2006). Pembelajaran Matematika Realistik. Jakarta: Departeman Pendidikan Nasional, Direktorat Jendral Pendidikan Tunggi, Direktorat Pembinaan Pendidikan Tenaga Kependidikan dan Ketenaga Perguruan Tinggi. Tatang, S. (2012). Ilmu Pendidikan. Bandung: Pustaka Setia.Trawick, M. (2007). Enemy Line ; Warfare, Childhood, and Play in Batticaloa. London: University of California Press. Trifunović, A., Čičević, S., Lazarević, D., Mitrović1, S., & Dragovi, M. (2018). Comparing Tablets (Touchscreen Devices and PCs in Preschool Children Education: Testing Spatial Relationship Using Geometric Syimbols Traffic Signs. IETI Transections on Economics and Safety, 2(1), 35–41. https://doi.org/10.6722/TES.201808_2(1).0004 Vitianingsih, A. V. (2016). Game Edukasi Sebagai Media Pembelajaran Pendidikan Anak Usia Dini. Jurnal INFORM, 1 No. 1. Wang, F., & Kinzie, M. B. (2010). Applying Technology to Inquiry- Based Learning in Early Childhood Education. Early Childhood Education Journal. Weil, M., Calhoun, E., & Joyce, B. (2011). Models of Teaching. New York.: New York. Zack, N. (2014). Philosophy of Science and Race. New York: Routledge. Zare, Sarikhani, Salarii, & Mansouri. (2016). The Impact Of E-learning on University Student’s Academic Achievement and Creativity. Journal of Technical Education and Training (JTET), 8(11).

Penelitian ini bertujuan untuk mengetahui level penambahan kembang telang ditinjau dari bahan organik dan mineral. Penelitian ini dilaksanakan di Farm Sesetan Fakultas Peternakan Universitas Udayana, Jl. Raya Sesetan, Gang Markisa, Denpasar. Pengujian bahan organik dilaksanakan di Laboratorium Nutrisi dan Makanan Ternak Fakultas Peternakan Universitas Udayana dan pengujian mineral dilakukan di laboratorium Analitik Universitas Udayana. Rancangan penelitian yang digunakan adalah Rancangan Acak Lengkap (RAL) dengan 4 perlakuan dan 4 ulangan. Perlakuan A (65% batang pisang + 30% pollar + 5% (molasis + EM4)), B (55% batang pisang + 10% C. ternatea + 30% pollar + 5% (molasis + EM4)), C (45% batang pisang + 20% C. ternatea + 30% pollar + 5% (molasis + EM4)), D (35% batang pisang + 30% C. ternatea + 30% pollar + 5% (molasis + EM4)). Variabel yang diamati adalah bahan organik dan mineral (Ca, P, dan Zn). Hasil penelitian menunjukkan bahwa persentase bahan organik mengalami peningkatan secara nyata ( P<0,05). Mineral Ca, P, dan Zn mengalami peningkatan dan tertinggi pada perlakuan C masing – masing 32,58 ml/L, 0,75% dan 19,26 mg/kg. Dari hasil penelitian ini dapat disimpulkan bahwa penambahan kembang telang pada silase batang pisang dapat meningkatkan kandungan bahan organik dan mineral (Ca, P, dan Zn). Penambahan 30% kembang telang menghasilkan bahan organik tertinggi, sedangkan penambahan 20% kembang telang menghasilkan mineral (Ca, P, dan Zn) tertinggi pada silase batang pisang. Kata kunci: batang pisang, bahan organik, kembang telang , mineral Ca, P, Zn

Abstract An experimental investigation on the interference effect of lee-side balance housing bodies on the longitudinal aerodynamic characteristics of thin slab delta wings has been made using a special and novel thin three-component balance. This study has been conducted using wings with a t/c of 0.053 and sweep of 76°, 70° and 65° for three different lee-side bodies viz:Body (A), Body (B) and Body (C) of which Body (C) is the smallest. The testing was carried out at Mach number of 8·2, Reynolds number of 2·13 ˘ 106 and incidence of –4° to 12°. For the smallest body (Body (C)) tested, at the incidence at which this body first goes into the aerodynamic shadow of the wing (α = 6·5°), the difference in CN, CA, CM and L/D between the wing-body and the plain wing is around by 22%, 12%, 75% and 35% respectively. This difference decreases with increase in incidence and at the highest angle-of-attack up to which testing was done (α = 12°), the. corresponding values of CN, CA, CM and L/D are around 9%, 12%, 15% and 4% respectively. Contrary to the assumption in the literature pertinent to force measurements on thin slab delta wings, the interference of the lee-side bodies are found to be appreciable even after they come into the aerodynamic shadow of the wing.

e16054 Background: TGCT are the most frequent cancers in men aged 15-45. This population is increasingly exposed to CA that is illegal in France. Its consequences on treatment and prognosis remain unknown. Methods: The use and the quantity of CA were evaluated for all pts treated by C for a TGCT in the CLB from 01/2016 to 06/2018. Tobacco (T) and alcohol (A) co-addictions were also analyzed. All pts had before starting C pulmonary test with diffusing capacity of the lung for carbon monoxyde (DLCO) evaluation. We searched a link between the use of toxics, contraindication to Bleomycin (B) due to decreased DLCO and tumor characteristics: stage and IGCCCG prognostic groups. Results: One hundred and thirty two pts with a median age of 33.5 years (interval: 17-65) received C for TGCT mainly for NSGCT (n = 97, 73%). Nine pts (7%) were treated in the adjuvant setting (1: 6 or 2 BEP: 3). In metastatic pts, 79 (60%), 30 (23%) and 14 (10%) were considered as good, intermediate and poor prognosis (PG) according to IGCCCG respectively. BEP was given for 3 cycles to 63 pts and 4 to29 and 6 pts received a dose dense regimen according to GETUG13. Eleven pts didn’t received B (5: 4EP, 6: 4VIP) because of DLCO alteration before the beginning of C. Eleven pts treated with B switched to a regimen without B due to a decrease of the DLCO during treatment. CA use was frequent (n = 20, 15%) with 8 pts (6%) having a regular CA consumption (median 5 joints/d). Seventy eight pts (59%) were regular T smokers. Co-addictions for CA consumers were frequent (90% for T and 50% for A). T and CA smokers had more DLCO alteration leading to B contraindication (p = 0.01 and p = 0.04). A quarter (n = 5) of pts using CA didn’t received B, and only 1 pt who didn’t receive B was not a smoker (T and CA). The use of CA was associated with PG, OR 5.46 (CI 95%: 1.35-21.2; p = 008). We could not observe a relationship between relapse and the use of CA (p = 0.34) because of the small number of relapses (n = 8). Half (n = 10) of CA consumers were single men and 25% (n = 5) were unemployed. Conclusions: The use of CA is significantly associated with PG and with a reduction of B use due to adecreased DLCO. The impact of CA intoxication is negative on the quality of treatment (because of more contraindications to B). The association with PG remains unclear, but may be related to social isolation.

Abstract To optimize the use of dietary P by pigs, 5 feeding strategies were studied in a 3-phase feeding trial on 240 pigs (initial bodyweight (BW) of 31 kg): 1) C-C-C providing 100% of digestible phosphorus (Pdig, 4.3 g/kg STTD) and calcium (Ca, 9.7 g/kg) requirement to maximize bone mineralization, 2) L-L-L 60% of the Pdig and Ca requirements of C-C-C, 3) Phyt-Phyt-Phyt (phosphate-free, with phytase, 750, 686, 390 FTU/kg), providing 60% of Pdig and Ca requirements in phase 1, then 100%, 4) and 5) C in phases 1 and 3, and 60% of the need for Pdig in phase 2, associated with 65% of the requirements for Ca (N) or 80% (H), namely C-N-C and C-H-C. The BW and bone mineral content (BMC) were measured at the beginning and end of each phase. The BMC gain (gBMC), average daily gain (ADG) and average daily feed intake (ADFI) were calculated by phase. In phase 1, ADG was lower in the Phyt group than the C group (1.05 vs 1.10 kg/d, P &lt; 0.01) and the BMC of group C and gBMC were higher than those of the Phyt and B groups (P &lt; 0.05). In phase 2, C-C and Phyt-Phyt groups had similar BMC due to higher gBMC in the Phyt-Phyt (27.1 vs 18.4 g/d, P &lt; 0.01). At the end of phases 2 and 3, C-C-C, C-N-C and C-H-C groups had similar BMC. The Phyt and B groups showed an increased phosphorus-use efficiency during phases 1 and 2 (+20% vs C). Phosphorus retention was also higher in the C-N-C and C-H-C groups, during the depletion in phase 2 (+24% vs C, P&lt; 0.05). These results showed the potential of a depletion-repletion strategy including free phosphate diet to reduce phosphorus intake and excretion without affecting final growth performance and bone mineralization because of increased minerals utilization efficacies.

AbstractA new mineral majzlanite, ideally K2Na(ZnNa)Ca(SO4)4, was found in high-temperature exhalative mineral assemblages in the Yadovitaya fumarole, Second scoria cone of the Great Tolbachik Fissure Eruption (1975–1976), Tolbachik volcano, Kamchatka Peninsula, Russia. Majzlanite is associated closely with langbeinite and K-bearing thénardite. Majzlanite is grey with a bluish tint, has a white streak and vitreous lustre. The mineral is soluble in warm water. Majzlanite is monoclinic, C2/c, a = 16.007(2), b = 9.5239(11), c = 9.1182(10) Å, β = 94.828(7)°, V = 1385.2(3) Å3 and Z = 16. The eight strongest lines of the X-ray powder diffraction pattern are [d, Å (I, %)(hkl)]: 3.3721(40)($\bar{3}$12), 3.1473(56)($\bar{4}$02), 3.1062(65)($\bar{2}$22), 2.9495(50)($\bar{1}$31), 2.8736(100)($\bar{1}$13), 2.8350(70)(421), 2.8031(45)(511) and 2.6162(41)($\bar{5}$12). The following structural formula was obtained: K2Na(Zn0.88Na0.60Cu0.36Mg0.16)(Ca0.76Na0.24)(S0.98Al0.015Si0.005O4)4. The chemical composition determined by electron-microprobe analysis is (wt.%): Na2O 9.73, K2O 15.27, ZnO 11.20, CaO 7.03, CuO 4.26, MgO 1.07, Al2O3 0.47, SO3 51.34, SiO2 0.12, total 100.49. The empirical formula calculated on the basis of 16 O apfu is K1.99Na1.93Zn0.84Ca0.77Cu0.33Mg0.16(S3.94Al0.06Si0.01)O16 and the simplified formula is K2Na(Zn,Na,Cu,Mg)Σ2(Ca,Na)(SO4)4. No natural or synthetic compounds directly chemically and/or structurally related to majzlanite are known to date. The topology of the heteropolyhedral framework in majzlanite is complex. An interesting feature of the structure of majzlanite is an edge-sharing of ZnO6 octahedra with SO4 tetrahedra.

Background: Recent attempts have focused on identifying fewer magnitude of minimal residual disease (MRD) rather than exploring the biological and genetic features of the residual plasma cells (PCs). Interphase fluorescence in situ hybridization (iFISH) analyses in sequential samples provide a simple and reliable method to longitudinal track the dynamic changes in clonal architecture and speculate the possible evolutionary pattern. Here, we report for the first time the incidence and prognostic significance of cytogenetic abnormalities (CA) existed in the PCs of patients achieving at least partial remission. Methods: A cohort of 193 patients with at least one CA at diagnosis were analyzed using data from the prospective, non-randomized clinical trial (BDH 2008/02), and iFISH analyses were performed in patient-paired diagnostic and post-therapy samples. Results: Persistent CA in residual tumor cells were observed for the majority of patients (63%), even detectable in 28/63 (44%) patients with MRD negativity (<10-4). The absence of CA in residual PCs was associated with prolonged survival regardless of MRD status. It was noted that MRD-positive but FISH-negative patients experienced similar survival to MRD-negative patients (m-TTP 4.5 vs. 5.1 years, P=0.983). According to the change of the clonal size of specific CA, patients were clustered into five groups, reflecting five patterns of clone selection under therapy pressure. 1) Pattern A were observed in 36 (19%) patients where a minor subpopulation or undetectable subclone in the pre-treatment sample became dominant after therapy. 2) Pattern B was identified in 29 (15%) patients whose fractions of PCs harboring different CA were decreased with inconsistent extent. 3) Identical CA fraction in residual PCs were found in 22 (11%) patients as Pattern C. 4) Pattern D. The fractions of PCs harboring specific CA in 35 patients (18%) were uniformly declined. 5) 71 patients lost their abnormal cytogenetic clone after therapy (less than cut-off level) were classified as Pattern E. The cytogenetic dynamics of pattern A and B can be interpreted as a therapy-induced selection process with comparable inferior survival (m-TTP 1.2 vs. 1.6 years, respectively). Patients with pattern E experienced the most favorable outcome (m-TTP 5.0 years), following those with pattern D and C (m-TTP 3.5 and 2.5 years). Among the 65 patients with clonal selection, 24 underwent upfront auto-transplantation that experienced significantly improved survival. However, upfront transplant failed to completely reverse the inferior outcome caused by therapy-induced clonal selection. Longitudinal cytogenetic studies at relapse were available in 43 patients. The results suggested that sequential cytogenetic dynamics were observed in most patients, and the cytogenetic architecture of residual cells could to some extent predict the evolutional pattern at relapse. Conclusions: The repeat cytogenetic evaluation in residual cells could not only serves as a good complementary tool for MRD detection, but also provides a better understanding of clinical response and clonal evolution. Therapy-induced clonal selection was associated with inferior outcome regardless of the baseline cytogenetic profiles. The early identification of resistant clone may contribute to guide better tailored therapy strategies based on the feature of the residual tumor cells. Figure Disclosures Munshi: Celgene: Consultancy; Adaptive: Consultancy; Oncopep: Consultancy; Amgen: Consultancy; Janssen: Consultancy; Takeda: Consultancy; Abbvie: Consultancy.

Abstract Abstract 3421 Poster Board III-309 Introduction While the prognosis of patients with MM has been drastically improved with the introduction of novel agents into the treatment armamentarium, relapse management remains a difficult task, especially in the post-transplant and high-risk MM setting, as defined by the presence of cytogenetic abnormalities (CA) and gene expression profiling (GEP). Patients and Methods We have explored the efficacy and safety of SB in 95 patients with MM. The regimen comprised BCNU at 300mg/m2 on day 1, etoposide 200mg/m2 on days 1-4; cytarabine 400mg/m2 on days 1-5; melphalan 140mg/m2 on day 5 plus: bortezomib 1.0-1.3mg/m2 on days 1+4, thalidomide 100-200mg on days 1-5, dexamethasone 20-40mg days 1-5, cisplatin 10-12.5mg/m2/d by continuous infusion on days 1-5, rapamycin 3mg on day 1 and 1mg on days 2-5; followed by autotransplant (AT) on day 6. Results Patient characteristics included age >=65, 19%; LDH>ULN, 43%; CA, 67%; GEP high-risk, 44%; GEP MF, 15%; GEP delTP53, 22%; prior AT, 75% including 46% with 2AT and 12% with 3 AT. CR and near-CR status was documented in 50%; TRM occurred within 100 days in 6%. Three-year estimates of overall survival (OS) and event-free survival (EFS) were 34% and 18%; OS/EFS were superior: (a) without CA – 60%/50% versus 15%/5% with CA (p=0.003/0.0005); (b) with GEP low-risk – 55%/20% versus 10%/15% with high-risk MM (p=0.009/0.01); (c) with GEP Hyperdiploidy and Low Bone disease molecular subgroups – 70%/35% versus 20%/10% in the remainder (p=0,001/0.002); and (d) absence of progression prior to SB – 52%/35% versus 16%/5% for the remainder (p=0.002/0.0006). Univariately significant adverse variables for OS and EFS included low albumin, B2M>=3.5mg/L, CA, GEP high-risk and relapse just prior to SB, of which B2M, CA and pre-SB survived on multivariate analysis for the 78 patients with all variables; among the 57 with GEP data, OS was inferior with GEP high-risk MM (HR=3.55, p=0.007) whereas EFS was inferior with high LDH (HR=3.44, p=0.004), CA (HR=2.79, p=0.02) and pre-SB relapse (HR=2.94, p=0.035). Conclusions We conclude that SB is a safe salvage regimen that was well-tolerated for the majority in the outpatient setting. Although beneficial to patients lacking CA and GEP high-risk status, the poor outcome also with SB in the presence of these adverse features emphasize the urgent need to discover agents/strategies effective in this setting. Disclosures van Rhee: Genzyme Corporation: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding.

AbstractThe new mineral pansnerite, ideally K3Na3Fe3+6(AsO4)8, was found in the Arsenatnaya fumarole at the Second scoria cone of the Northern Breakthrough of the Great Tolbachik Fissure Eruption, Tolbachik volcano, Kamchatka, Russia. It is associated with aphthitalite, hematite, sanidine, badalovite, khrenovite, achyrophanite, arsenatrotitanite, ozerovaite, tilasite, calciojohillerite, johillerite, nickenichite, svabite, katiarsite, yurmarinite, anhydrite, rutile, cassiterite and pseudobrookite. Pansnerite forms tabular to lamellar (flattened on {010}), usually pseudo-hexagonal crystals up to 0.2 mm × 0.7 mm × 1 mm and crystal clusters up to 2 mm across. It is transparent to translucent, light green, pale greenish, yellowish–greenish or yellowish, with vitreous lustre. The mineral is brittle, with perfect {010} cleavage. The Mohs’ hardness is ca 3. Dcalc is 3.596 g cm–3. Pansnerite is optically biaxial (–), α = 1.702(4), β = 1.713(4), γ = 1.717(4), 2Vmeas = 45(10)° and 2Vcalc = 62°. Chemical composition (holotype, wt.%, electron microprobe data) is: Na2O 6.39, K2O 8.52, CaO 0.08, MgO 0.08, MnO 0.02, NiO 0.02, CuO 1.35, ZnO 0.34, Al2O3 7.35, Cr2O3 0.04, Fe2O3 16.72, SiO2 0.16, P2O5 0.22, V2O5 0.09, As2O5 57.76, SO3 0.04, total 99.20. The empirical formula based on 32 O apfu is K2.86Na3.26Ca0.02(Fe3+3.31Al2.28Cu0.27Zn0.07Mg0.03Cr0.01)Σ5.97(As7.95P0.05Si0.04V0.02S0.01)Σ8.06O32. Pansnerite is orthorhombic, Cmce, a = 10.7372(3), b = 20.8367(8), c = 6.47335(15) Å, V = 1448.27(7) Å3 and Z = 2. The strongest reflections of the X-ray powder diffraction pattern [d,Å(I)(hkl)] are: 10.49(100)(020), 5.380(88)(111), 4.793(65)(220), 3.105(46)(311, 002), 3.079(32)(112, 061), 2.932(35)(260), 2.783(65)(202) and 2.694(52)(400, 222). The crystal structure was solved from single-crystal X-ray diffraction data, R1 = 2.82%. The structure is based on heteropolyhedral layers formed by MO6 octahedra (M = Fe3+ and Al) sharing common vertices and connected by AsO4 tetrahedra. Na+ and K+ cations are located in the interlayer space. The mineral is named in honour of the German–Russian mineralogist and geographer Lavrentiy Ivanovich Pansner (1777–1851). Pansnerite forms a solid-solution series with the isotypic mineral ozerovaite, ideally KNa2Al3(AsO4)4.

AbstractWhiteite-(CaMnMn), CaMnMn2Al2[PO4]4(OH)2·8H2O, is a new hydrous phosphate of Ca, Mn and Al, which is closely related to both jahnsite-(CaMnMn) and the minerals of the whiteite group. It is monoclinic, P2/a, with a = 15.02(2), b = 6.95(1), c =10.13(3) Å, β = 111.6(1)°, V = 983.3(6) Å3, Z = 2 (from powder diffraction data) or a = 15.020(5), b = 6.959(2), c = 10.237(3) Å, β = 111.740(4)°, V = 984.3(5) Å3, Z = 2 (from single-crystal diffraction data). The mineral was found in the Hagendorf Süd granitic pegmatite (Germany) as small (up to 0.5 mm in size) crystals elongated on a and tabular on {010}. The crystals are either simply or polysynthetically twinned on {001}. They crystallize on the walls of voids within altered zwieselite crystals or form coronas (up to 1 mm in diameter) around cubic crystals of uraninite. The mineral is transparent, colourless to pale yellow (depending on Al–Fe3+ substitution), with a vitreous lustre and a white streak. The cleavage is perfect on {001}, the fracture is stepped and the Mohs hardness is 3½. In transmitted light, the mineral is colourless; dispersion was not observed. Whiteite-(CaMnMn) is biaxial (+), α = 1.589(2), β = 1.592(2), γ = 1.601(2) (589 nm), 2Vmeas = 60(10)°, 2Vcalc = 60.3°. The optical orientation is X = b, Z^a = 5°. The calculated and measured densities are Dcalc = 2.768 and Dmeas = 2.70(3) g cm–3, respectively. The mean chemical composition determined by electron microprobe is Na2O 0.53, MgO 0.88, Al2O3 11.66, P2O5 34.58, CaO 4.29, MnO 17.32, FeO 8.32, ZnO 2.60 wt.%, with H2O 19.50 wt.% (determined by the Penfield method), giving a total of 99.68 wt.%. The empirical formula calculated on the basis of four phosphorus atoms per formula unit, with ferric iron calculated to maintain charge balance, is (Ca0.63Zn0.26Na0.14)Σ1.03(Mn0.60Fe0.402+)Σ1.00(Mn1.40Fe0.372+Mg0.18Fe0.063+)Σ2.01(Al1.88Fe0.123+)Σ2.00[PO4]4(OH)2·7.89H2O. The simplified formula is CaMnMn2Al2[PO4]4(OH)2·8H2O. The mineral is easily soluble in 10% HCl at room temperature. The strongest X-ray powder-diffraction lines [listed as d in Å (I) (hkl)] are as follows: 9.443(65)(001), 5.596(25)(011), 4.929(80)(210), 4.719(47)(002), 3.494(46)(400), 2.7958(100)(022). The crystal structure of whiteite-(CaMnMn) was refined for a single crystal twinned on (001) to R1 = 0.068 on the basis of 5702 unique observed reflections. It is similar to the structures of other members of the whiteite group. The mineral is named for the chemical composition, in accordance with whiteite-group nomenclature.