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"Background: Currently available molecular method to detect HER2I655V polymorphism such as PCR-RFLP ishampered by costly experimental method and post-PCR treatment requirment that make this technique is not meetingfor high-throughput analysis purpose. In this study we developed a accurate, simple, low cost and rapid test to detectpolymorphism at HER2 gene using SBR Green I based-melting curve method. Methods: Two forward allele-specificprimers and one common reverse primer were used then these primers were tested to discriminate known genotypes ofgenomic templates (GG type or AA type) and genomic samples retrieved from breast cancer patients. Results: Meltingcurve analysis derived from SYBR Green I-based allele-specific PCR with defined primers concentration and annelingtemperature at 54.3 °C showed good discrimination level of Tm peaks in which GG genotype melted at 89 °C slightlyhigher than AA genotype which melted at 86 °C, while AG genotype harbored both of homozygous Tm characteristics.Conclusions: This preliminary result will be as basic for further large-scale typing of HER2I655V polymorphism."

"Breast cancer can be detected using digital mammograms. In this research study, a system is designed to classify digital mammograms into two classes, namely normal and abnormal, using the k-Nearest Neighbor (kNN) method. Prior to classification, the region of interest (ROI) of a mammogram is cropped, and the feature is extracted using the wavelet transformation method. Energy, mean, and standard deviation from wavelet decomposition coefficients are used as input for the classification. Optimal accuracy is obtained when wavelet decomposition level 3 is used with the feature combination of mean and standard deviation. The highest accuracy, sensitivity, and specificity of this method are 96.8%, 100%, and 95%, respectively."

"Virus dengue (DENV) adalah penyebab penyakit infeksi yang endemik di 100 negara di dunia. DENV dapat menyebabkan infeksi primer dan sekunder. Infeksi sekunder diperkirakan lebih berat dan akan menyebabkan menjadi Demam Berdarah Dengue (DBD) dan Sindrom Renjatan Dengue (SRD). Penatalaksanaan yang lebih dini dan tepat akan membantu mengurangi terjadinya kasus berat seperti DBD dan SRD. Teknik diagnostik yang dikembangkan belum ada yang dapat mendeteksi secara cepat dan tepat pada awal infeksi terutama untuk virus dengue strain Indonesia. Tujuan penelitian ini untuk mendapatkan kondisi yang optimal untuk deteksi DENV dan analisis validasi tehnik in house multiplek realtime Reverse Transcriptase-Polimerase Chain Reaction (rRT-PCR) sehingga dapat digunakan untuk deteksi dini dan cepat infeksi DENV. Rancangan penelitian ini adalah penelitian eksperimental laboratorium. Strain standar DENV diisolasi dengan kit Roche® dan spesimen diekstraksi dengan kit Qiagen®. Strain standar DENV digunakan untuk optimasi suhu annealing dan konsentrasi primer masing-masing serotipe DENV dengan metode in house multiplek rRT-PCR berbasis SYBR green. Sebagai pembanding digunakan RT-PCR konvensional dengan menggunakan primer di daerah C-PrM. Primer in house multiplek rRT-PCR didesain di daerah envelope pada masing masing serotipe. Analisis limit of detection (LOD) dilakukan dengan pengenceran titer virus 105, 104, 103, 102, 10 dan 1 FFU/ml (in house multiplek rRT-PCR) pada keempat serotipe. Hasil in house multiplek rRT-PCR dibandingkan dengan hasil RT-PCR konvensional Lanciotti pada pasien dengue yang telah masuk dalam kriteria inklusi dan eksklusi. Suhu annealing optimal didapatkan pada suhu 58oC sedangkan konsentrasi optimal masing-masing primer untuk in house multiplek rRT-PCR adalah 4 pmol. LOD RNA pada DENV-1, DENV-2, DENV-3, DENV-4 adalah 1 FFU/ml, 10 FFU/ml, 104 FFU/ml dan 1 FFU/ml. In house multiplek rRT-PCR dibandingkan RT-PCR konvensional mempunyai sensitivitas sebesar 100%, spesifisitas 94,2 %, nilai prediksi positif 85,7% dan nilai prediksi negatif 100 %. In house multiplek rRT-PCR berbasis SYBR green merupakan metode yang dini, cepat dan tepat untuk deteksi DENV pada awal infeksi dengan sensitivitas dan spesifisitas yang baik sebagai metode diagnostik infeksi dengue dimasa mendatang.

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Dengue virus (DENV) is an infectious disease that is endemic in 100 countries in the World. Dengue virus infections can cause primary and secondary. Secondary infection is estimated to be more severe DHF and SDD. Developed diagnostic technique that no one has been able to quickly and accurately detect the infection early, especially for the Indonesian strain of dengue virus. The purpose of this study is to obtain optimal conditions for the detection of dengue infection and analysis techniques in-house validation of multiplex real-time Reverse Transcriptase-Polymerase Chain Reaction (rRT-PCR) for the Indonesian strain of dengue virus.

Design of this study is an experimental research laboratory. Standard strains of dengue virus was isolated with a kit Roche® and the specimen was extracted with Qiagen® kit. Standard strains of dengue virus is used for optimization primer annealing temperature and the concentration primers of each serotype dengue virus by multiplex rRT-PCR method based on SYBR green. Primers for RT-PCR conventional based lanciotii et al while rRT-PCR primer was designed in the envelope gen at each serotype. Limit of detection (LOD) by diluting the virus titer 105, 104, 103, 102 FFU /ml performed by rRTPCR in all four serotypes.

The results of multiplex rRT-PCR compared with results of conventional RT-PCR in patients with dengue lanciotti superbly into the criteria inclusion and exclusion. Optimal annealing temperature results obtained at a temperature of 58oC and optimal primer concentration of 4 pmol of each primer for 25 ul total reaction. LOD RNA in DENV-1, DENV-2, DENV-3 and DENV-4 at titer of 1 FFU / ml, 10 FFU/ml, 104 FFU/ml and 1 FFU/ml. .In house multiplex rRT-PCR compared with RT-PCR has a sensitivity of 100%, specificity 95,2%, positive predictive value 85,7% and negative predictive value of 100%. In-house multiplex rRT-PCR with SYBR green-based research is a method that is rapid and precise detection of dengue virus in early infection with good sensitivity and specificity compared to RT-PCR as a diagnostic method in the future dengue infection."

"Kanker payudara (KPD) merupakan salah satu penyakit yang masih banyak terjadi di negara berkembang seperti Indonesia. Di Indonesia sendiri, KPD menempati peringkat pertama terbanyak dari berbagai jenis kanker yang terjadi.  Pendeteksian kanker ini dapat dilakukan sejak dini dengan memeriksa manual apakah terdapat benjolan atau kelainan pada payudara. Jika terasa ada benjolan, maka disarankan untuk diperiksa ke dokter dengan berbagai metode, seperti mammogram, Magnetic Resonance Imaging (MRI), dan USG. Diagnosa citra ini sering terkendala karena tidak setiap rumah sakit memiliki tenaga spesialis radiologi. Maka dari itu, untuk mengatasinya diperlukan bantuan komputer untuk mendiagnosa citra tersebut yang sering disebut computer aided diagnostis (CAD). Algoritma Convolutional Neural Network didasari pada hasil pemeriksaan rutin citra x-ray payudara normal/abnormal yang cenderung menunjukkan perubahan, salah satunya tekstur (konten). Data yang digunakan pada penelitian ini diambil dari website Pilot European Image Processing Archive (PEIPA) yaitu dataset Mammographic Image Analysis Society (MIAS). Sistem dimulai dengan mengenal dan mempelajari data 3 jenis mamografi, yakni mamografi normal (sehat), mamografi benign, dan mamografi malignant. Setelah mempelajari data tersebut, sistem akan mencoba untuk mendeteksi jenis kanker payudara dari data baru yang dimasukkan. Nilai akurasi yang didapatkan adalah 100%, dengan rasio data pembelajaran sebanyak 1247 data (setelah diaugmentasi) dan data pengujian sebanyak 93 data, sehingga disimpulkan bahwa sistem ini baik. Namun nilai ini hanya untuk data MIAS, sehingga masih perlu pengembangan lebih lanjut supaya dapat diterapkan ke data-data yang lain juga.

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Breast Cancer (BC) is one of the diseases that still occur a lot in developing countries like Indonesia. In Indonesia alone, BC is the number one most occurrence cancer. This cancer detection can be done early by manual, checking if there is any lump or abnormality in breast. If there are any lump, it is recommended to go check in hospital. There are a lot of methods like Magnetic Resonance Imaging (MRI), and Ultrasonography (USG). This image diagnostics sometimes got constrained by the lack of radiology specialist in some hospital. Therefore, to counter this problem, Computer Aided Diagnostics (CAD) help is needed to detect those images. Convolutional Neural Network algorithm is based on the result of the routine x-ray's check of breast, both normal and abnormal which tend to show some changes, which one of them is texture (content). Data used in this research came from Pilot European Image Processing Archive (PEIPA) website, Mammographic Image Analysis Society (MIAS) database. The system start by recognizing and learning 3 types of mammograph data, normal (healthy), benign and malignant. Then, system will try to detect and classify breast cancer type from the new input data. The accuracy score is 100%, with a ratio of 1247 datas for learning (after augmented) and 93 datas for testing, so it can be concluded that this system is good. But this score is achieved only for MIAS data, it still need further improvement  so it can be applied to another data."

"Penyakit kanker payudara menjadi penyebab angka kematian tertinggi untuk perempuan. Teknologi pencitraan medis yang dapat mendiagnosis kanker payudara saat ini beberapa telah dikembangkan. Namun masih memiliki kekurangan dari segi keamanan dan tingkat akurasinya. Salah satu teknologi pencitraan yang dapat digunakan untuk mengatasi kekurangan teknologi yang ada yaitu dengan teknik pencitraan Terahertz. Pencitraan kanker payudara dengan Terahertz dapat menjadi lebih efektif untuk mendiagnosis kanker pada jaringan yang lunak, karena dapat memberikan informasi spatial dan spektral dari kanker yang dicitrakan secara bersamaan. Kualitas resolusi spatial bergantung pada beamwidth antena dan scan density. Oleh karena itu, dibutuhkan antena dengan beamwidth yang sempit dan gain yang lebih tinggi agar mendapatkan kualitas gambar yang diinginkan.Dalam penelitian ini dirancang antena mikrostrip array 2x2 dan 2x3 yang bekerja pada frekuensi 0,312 THz untuk mengetahui pengaruh beamwidth pada hasil pencitraan untuk deteksi kanker payudara. Antena array 2x2 memiliki beamwidth horizontal 46,4 derajat dan vertikal 33,0 derajat dengan gain 9,0 dB, bandwidth 53 GHz, pola radiasi directional, dan polarisasi linear. Antena array 2x3 memiliki beamwidth horizontal 39,0 derajat dan vertikal 22,8 derajat dengan gain 8,8 dB, bandwidth 11 GHz, pola radiasi directional, dan polarisasi linear. Objek yang dicitrakan yaitu phantom jaringan payudara yang berbentuk balok dengan dimensi panjang 2 mm, lebar 2 mm, dan ketebalan 1 mm. Model phantom terdiri dari jaringan fat (  = 2,41), fibrous ( = 2,80), dan tumor (  = 3,15). Pencitraan Terahertz dilakukan dengan metode pemindaian translasi dengan menggunakan perangkat lunak CST Microwave Studio. Terdapat dua skema pencitraan Terahertz, yaitu dengan variasi beamwidth dengan menggunakan kedua antena dan variasi jarak masing-masing antena. Pada hasil simulasi pencitraan Terahertz variasi beamwidth menghasilkan gambar yang lebih baik pada antena array 2x3 karena beamwidth antena tersebut lebih sempit. Pada hasil simulasi pencitraan Terahertz dengan variasi jarak memiliki hasil citra yang ideal pada jarak 7,5 mm untuk kedua antena secara kualitatif dan kuantitatif.

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Breast cancer is the leading cause of death for women. Medical imaging technologies that can diagnose breast cancer are currently being developed. But it still has disadvantages in terms of security and level of accuracy. One of imaging technology that can be used to overcome the shortage of existing technologies is Terahertz imaging techniques. Terahertz imaging of breast cancer can be more effective in diagnosing cancer for soft tissue, because it can provide spatial and spectral information from cancer simultaneously. The quality of resolution depends on beamwidth of antenna and scan density. Therefore, an antenna with a narrow beamwidth and higher gain is needed to get the desired image quality.

In this study, 2x2 and 2x3 microstrip array antenna was designed at a frequency of 0.312 THz to find out the affect of beamwidth to the imaging results for breast cancer detection. 2x2 array antenna has horizontal beamwidth of 46.4 degrees and vertical beamwidth of 33.0 degrees with gain of 9 dB, bandwidth of 53 GHz, directional radiation patterns, and linear polarization. 2x3 array antenna has horizontal beamwidth of 39.0 degrees and vertical beamwidth of 22.8 degrees with gain of 8.8 dB, bandwidth of 11 GHz, directional radiation patterns, and linear polarization. The object that is imaged is phantom breast tissue in the block shape with total dimensions of 2 mm in length, 2 mm in width, and 1 mm in thickness. The phantom model consists of tissue fat (  = 2.41), fibrous (  = 2.80), and tumor (  = 3.15).

Terahertz imaging is done by the translation scanning method using CST Microwave Studio software. There are two Terahertz imaging schemes, with variation of beamwidth using both antennas and variation in the distance of each antenna. In the imaging simulation results, the variation in beamwidth produces a better image on the 2x3 antenna because the antenna beamwidth is narrower. The results of Terahertz imaging simulation with distance variations have ideal image results at distance of 7.5 mm for both of antennas qualitatively and quantitatively."

"Deteksi dini kanker payudara sangat penting dilakukan bagi wanita berisiko, khususnya Pemeriksaan Payudara Sendiri (SADARI). Pemeriksaan ini secara rutin dilakukan untuk mendeteksi adanya kelainan atau benjolan sejak awal. Penelitian ini bertujuan menganalisis faktor-faktor yang mempengaruhi deteksi dini kanker payudara pada wanita berisiko kanker payudara. Desain yang digunakan Crossectional dengan 135 responden yang teknik concecutive sampling. Hasil penelitian menunjukan ada hubungan yang signifikan antara pengetahuan tanda dan gejala, pengetahuan deteksi dini, pendidikan, riwayat operasi, dimana faktor yang dominan yaitu variabel pengetahuan tanda dan gejala (p< 0,05;OR=0.095 C.I: 0.013-0,687). Faktor-faktor tersebut dapat dijadiakan salah satu eviden base dalam mengidentifikasi masalah dalam usaha mencegah terjadinya kanker payudara pada wanita berisiko kanker payudara.

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Early detection for breast cancer is very important for the high-risk women especially Self Breast Examination (BSE). This examination is done routinely detects the unusual changes or lumps. This research aims to identify the factors influencing early detection of breast cancer in women at risk for breast cancer. Cross sectional design to 135 respondents that were selected by consecutive sampling. The results show that there is significant correlation between the knowledge about signs and symptoms, knowledge about early detection, knowledge about surgery records by which the dominant factor is the knowledge about signs and symptoms (p< 0,05;OR=0.095 C.I: 0.013-0,687). These factors can be presented as an evidence base in identifying problems in an effort to prevent breast cancer in high-risk women for breast cancer."

"The book is the first one published exclusively on the field of nutritional epidemiology of breast cancer. It summarizes the currently existing knowledge, with an updated and comprehensive international bibliography (~ 1.000 references). The authors also performed a review on the epidemiological studies on nutrition and breast cancer carried out in Uruguay between 1994 and 2011, which allowed exploring and identifying the main risk and protective factors for the disease in this high-risk country. "

"This book is the one of the few textbooks that summarizes the latest information dated to inflammatory breast cancer. The uniqueness of this book is that it has summarized the latest molecular and mechanistic findings, which may lead to novel diagnostic tool or therapeutic approach to fight this deadly disease."

"Skrining kanker payudara merupakan salah satu strategi pencegahan yang dilakukan perawat sebagai peran dan tanggung jawab professional untuk menurunkan angka mortalitas dan morbiditas kanker payudara, namun saat ini penerapan praktiknya belum berjalan dengan optimal. Tujuan dari telaah sistematik ini adalah untuk mengidendifikasi, menilai, dan mensintesis gambaran penerapan kemampuan perawat dalam praktik deteksi dini kanker payudara. Pencarian data penelitian dilakukan dengan strategi PRISMA melalui lima basis data: Google Schoolar, PubMed Central, Science Direct, ProQuest, dan Oxford Journals pada bulan Mei-Juli 2020 dan dihasilkan 10 artikel untuk dianalisis. Pengetahuan dan sikap memengaruhi praktik perawat dalam deteksi dini kanker payudara. Pemahaman yang belum cukup baik memengaruhi praktik skrining kanker payudara yang rendah, walaupun sikap sudah positif. Penelitian menunjukkan pentingnya meningkatkan kemampuan perawat dalam praktik skrining kanker payudara melalui pendidikan berkelanjutan dan pelatihan yang adekuat serta dukungan dari penyusun kebijakan.

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Breast cancer screening is a preventive strategy carried out by nurses as a professional role and responsibility to reduce mortality and morbidity due to breast cancer, but currently the practice has not been optimal. The purpose of this systematic study was to identify, assess, and synthesize an overview of the application of nurses' abilities in the practice of early detection of breast cancer. Research data search was carried out using the PRISMA strategy through five databases:  Google Schoolar, PubMed Central, Science Direct, ProQuest, and Oxford Journals during May-July 2020 and produced 10 articles to be analyzed.  Knowledge and attitudes influence nurses' practices in early detection of breast cancer. Inadequate understanding caused inadequate breast cancer screening practices, even though their attitudes were already positive. This study showed the importance of promoting nurses' abilities of breast cancer screening practices through continuing education and adequate training as well as supports from policy markers."

"Latar Belakang: Stromal Cell-Derived Factor-1 SDF-1 mengkode protein SDF-1 yang berperan dalam angiogenesis dan metastasis sel kanker. Polimorfisme genetik SDF-1 G801A telah dilaporkan memiliki hubungan dengan kanker kepala leher KKL. Tujuan: Mendeteksi polimorfisme genetik SDF-1 G801A pada penderita KKL dan individu sehat populasi Indonesia. Metode: Sampel DNA tersimpan dari 50 penderita KKL dan 50 individu sehat dianalisis dengan metode PCR-RFLP dengan menggunakan enzim restriksi HpaII serta divisualisasi dengan elektroforesis. Hasil: Polimorfisme genetik SDF-1 G801A terdeteksi sebesar 54 pada kelompok penderita KKL dan 74 pada kelompok individu sehat. Simpulan: Polimorfisme genetik SDF-1 G801A terdeteksi pada penderita KKL dan individu sehat populasi Indonesia.

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Introduction: Stromal Cell Derived Factor 1 SDF 1 gene encodes SDF 1 protein which plays roles in angiogenesis and metastasis of cancer cell. SDF 1 G801A genetic polymorphism has been reported to have an association with head and neck cancer HNC.

Aims: To detect SDF 1 G801A genetic polymorphism in HNC patients and healthy subjects of Indonesian population.

Methods: Stored DNA samples extracted from blood of 50 HNC patients and 50 healthy subjects were analyzed with PCR RFLP method using HpaII restriction enzyme and visualized by electrophoresis.

Results: There were 54 and 74 SDF 1 G801A genetic polymorphisms detected in HNC samples and healthy subject samples.

Conclusion: SDF 1 G801A genetic polymorphism was detected in HNC patients and healthy subject of Indonesian population."