26 research outputs found

    Peningkatan Prestasi Belajar CAD Mahasiswa Teknik Otomotif Non-Reguler FT UNY melalui Pembuatan “Pohon Kata” Perintah dalam Program AutoCAD

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    Penelitian ini bertujuan meningkatkan prestasi belajar mata kuliah Computer Aided Design (CAD) mahasiswa prodi Teknik Otomotif Non-Reguler yang dinyatakan dalam bentuk rerata nilai akhir semester yang berasal dari komponen nilai tugas harian, nilai ujian tengah semester dan nilai ujian akhir semester. Penelitian quasi-eksperimen ini terdiri dari tahapan penelitian diawali dengan penyusunan materi pembelajaran sejumlah pokok bahasan tertentu dalam satu job sheet (lembar kerja), dilanjutkan dengan pembuatan bantuan “Pohon Kata” perintah dalam Auto CAD kepada kelas eksperimen yang ditentukan secara random dari dua kelas peserta kuliah Auto CAD pada Semester Genap 2008/2009. Kedua kelas diamati prestasinya, baik kecepatan penyelesaiannya maupun kualitas kebenaran gambarnya. Prestasi belajar kedua kelas juga diukur melalui pemberian ujian tengah semester dan ujian akhir semester. Setelah data prestasi kedua kelas terkumpul dilanjutkan dengan analisis statistik melalui uji beda (t-test) setelah sebelumnya dilakukan uji persyaratan analisis yang ternyata dapat dipenuhi. Hasil penelitian ini disimpulkan bahwa: prestasi belajar CAD mahasiswa pada kelas yang diberi perlakuan strategi pembelajaran menggunakan “Pohon Kata” perintah dalam Program Auto CAD lebih baik dibanding prestasi belajar CAD mahasiswa pada kelas yang tidak diberi perlakuan (75,41>70,89), dengan demikian pembelajaran CAD menggunakan media “Pohon Kata” perintah dalam Program Auto CAD dapat meningkatkan prestasi belajar mahasiswa Teknik Otomotif Program Non-Reguler

    Modeling of Patient-Derived Xenografts in Colorectal Cancer.

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    Developing realistic preclinical models using clinical samples that mirror complex tumor biology and behavior are vital to advancing cancer research. While cell line cultures have been helpful in generating preclinical data, the genetic divergence between these and corresponding primary tumors has limited clinical translation. Conversely, patient-derived xenografts (PDX) in colorectal cancer are highly representative of the genetic and phenotypic heterogeneity in the original tumor. Coupled with high-throughput analyses and bioinformatics, these PDXs represent robust preclinical tools for biomarkers, therapeutic target, and drug discovery. Successful PDX engraftment is hypothesized to be related to a series of anecdotal variables namely, tissue source, cancer stage, tumor grade, acquisition strategy, time to implantation, exposure to prior systemic therapy, and genomic heterogeneity of tumors. Although these factors at large can influence practices and patterns related to xenotransplantation, their relative significance in determining the success of establishing PDXs is uncertain. Accordingly, we systematically examined the predictive ability of these factors in establishing PDXs using 90 colorectal cancer patient specimens that were subcutaneously implanted into immunodeficient mice. Fifty (56%) PDXs were successfully established. Multivariate analyses showed tissue acquisition strategy [surgery 72.0% (95% confidence interval (CI): 58.2-82.6) vs. biopsy 35% (95% CI: 22.1%-50.6%)] to be the key determinant for successful PDX engraftment. These findings contrast with current empiricism in generating PDXs and can serve to simplify or liberalize PDX modeling protocols. Better understanding the relative impact of these factors on efficiency of PDX formation will allow for pervasive integration of these models in care of colorectal cancer patients. Mol Cancer Ther; 16(7); 1435-42. ©2017 AACR

    Clinical utility of circulating cell-free DNA in advanced colorectal cancer

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    <div><p>Background</p><p>Circulating cell-free DNA (cfDNA) isolated from the plasma of cancer patients (pts) has been shown to reflect the genomic mutation profile of the tumor. However, physician and patient assessment of clinical utility of these assays in patients with metastatic colorectal cancer (mCRC) has not been previously described.</p><p>Methods</p><p>Patients were prospectively consented to a prospective genomic matching protocol (Assessment of Targeted Therapies Against Colorectal Cancer [ATTACC]), with collection of blood for cfDNA extraction and sequencing of a 54-gene panel in a CLIA-certified lab. Formalin-fixed, paraffin-embedded (FFPE) tissue from prior resections or biopsies underwent 50-gene sequencing. Results from both assays were returned to the treating physicians for patient care and clinical trial selection. Follow-up surveys of treating physicians and chart reviews assessed clinical utility.</p><p>Results</p><p>128 mCRC pts were enrolled between 6/2014 and 1/2015. Results were returned in median of 13 and 26 days for cfDNA and FFPE sequencing, respectively. With cfDNA sequencing, 78% (100/128) of samples had a detectable somatic genomic alteration. 50% of cfDNA cases had potentially actionable alterations, and 60% of these could be genomically matched to at least one clinical trial in our institution. 50% (15/30) of these pts enrolled onto an identified matched trial. Physicians reported that the cfDNA testing improved the quality of care they could provide in 73% of the cases, and that 89% of pts reported greater satisfaction with the efforts to personalize experimental therapeutic agents.</p><p>Conclusions</p><p>cfDNA sequencing can provide timely information on potentially actionable mutations and amplifications, thereby facilitating clinical trial enrollment and improving the perceived quality of care.</p></div

    Clinical utility of cfDNA sequencing results.

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    <p><b>(A)</b> Detectable mutations and/or amplification were present in 78% of patients. <b>(B)</b> 50% of these patients (N = 50) had “potentially actionable” mutations and/or amplifications. <b>(C)</b> Among these, 60% (N = 30) patients had a clinical trial identified based on the matched biomarker detected from the cfDNA (D) 15 patients ultimately enrolled on a biomarker-based clinical trial. Pt = patient; MDACC = MD Anderson Cancer Center.</p
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