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"Epigenetics in psychiatry covers all major areas of psychiatry in which extensive epigenetic research has been performed, fully encompassing a diverse and maturing field, including drug addiction, bipolar disorder, epidemiology, cognitive disorders, and the uses of putative epigenetic-based psychotropic drugs. Uniquely, each chapter correlates epigenetics with relevant advances across genomics, transcriptomics, and proteomics. The book acts as a catalyst for further research in this potentially very important and useful area of psychiatry.The elucidation of basic principles of epigenetic biology points to the creation of more optimal and effective therapies for major classes of psychiatric disease. In this regard, epigenetic therapy, the use of drugs to correct epigenetic defects, may help in the pharmacotherapy of patients with these disorders. With time, such advances may eventually point to replacements for psychotropic drugs presently of symptomatic value and low efficacy. Moreover, there is evidence to suggest that other forms of treatment commonly used in the management of psychiatric disorders, like psychotherapy and electroconvulsive therapy, may also act by epigenetic mechanisms."

"Insidensi kanker payudara terus meningkat secara global setiap tahun. Di negara berpendapatan menengah ke bawah, meningkatnya insidensi ini diikuti dengan meningkatnya angka kematian akibat kanker payudara yang disebabkan oleh keterlambatan diagnosis yang sering terjadi, sehingga pengobatan dan perawatan kanker payudara tidak lagi efektif dilakukan. Pada penelitian ini dilakukan analisis metode peningkatan deteksi dini terencana kanker payudara yang telah dilakukan di beberapa negara berpendapatan menengah ke bawah dengan menggunakan systematic review. Systematic review dilakukan dengan melakukan identifikasi literatur dari Google scholar, ProQuest, ScienceDirect, Scopus, dan Pubmed dengan menggunakan kata kunci improve, early detection, screening, breast cancer, low middle-income countries, dan LMIC, lalu dilakukan pencarian lanjutan dengan teknik snowball dari literatur yang sudah didapatkan. Kriteria inklusi pada pencarian literatur adalah artikel full text berbahasa Inggris yang diterbitkan pada tahun 2010 – Juni tahun 2020 dan memiliki lokasi studi di negara berpendapatan menengah ke bawah. Sebelas artikel didapatkan dari pencarian dan proses seleksi menggunakan diagram alir PRISMA. Ditemukan 5 jenis program dalam upaya peningkatan deteksi dini kanker payudara di negara berpendapatan menengah ke bawah, yaitu program skrining berbasis populasi, program skrining oportunistik, program peningkatan pengetahuan dan kesadaran, program pengalihan tugas, dan pelaksanaan program nasional deteksi dini kanker payudara. Program-program tersebut diketahui berhasil meningkatkan deteksi dini kanker payudara pada latar negara berpendapatan menengah ke bawah. Program peningkatan pengetahuan dan kesadaran, dan program pengalihan tugas dinilai sebagai program yang paling sesuai untuk dilaksanakan di negara berpendapatan menengah ke bawah. Meski begitu, perlu dilakukan pilot studi dan evaluasi biaya untuk melihat keefektifan program deteksi dini ini.

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Incidence of breast cancer keeps increasing globally every year, and in low-and middle-income countries it followed by increased mortality rate. This phenomenon could be associated with late-stage diagnosis that made treatments no longer effective. This study aimed to analyse methods to increase early detection for breast cancer that has been done in several low-and middle-income countries by using systematic review. Systematic review was carried out by identifying literatures from online databases such as Google scholar, ProQuest, ScienceDirect, Scopus, and Pubmed using “improve”, “early detection”, “screening”, “breast cancer”, “low middle-income countries", and “LMIC” as keywords, and followed by manually searching literatures using snowball technique from the literatures that had been identified earlier. Inclusion criterias in this study were English full text that were published between 2010 – June 2020 with low-and middle-income countries setting. Eleven articles were obtained using PRISMA flow diagram and 5 types of programs were found to increase early detection for breast cancer in low-and middle-income countries; population-based screening program, oportunistic screening program, program to improve knowledge and awareness about breast cancer and early detection, task shifting program, and implementation of national breast cancer early detection program. These programs were known to be able to improve early detection in their respective study location. Improving knowledge and awareness, and task shifting program were the most suitable program to be executed in low-and middle-income countries setting. These countries shall do some pilot studies and cost evaluation to identify and analyse the effectivity of these programs before implementing it widely."

"Metilasi DNA merupakan salah satu penyebab umum inaktivasi Mismatch Repair Gene (MMR). Gen MMR memperbaiki kesalahan penyisipan/penghapusan basa nukleotida pada proses sintesis DNA. Metilasi pada promoter gen MMR memiliki asosiasi dengan pembentukan kanker kolon, sehingga metilasi tersebut perlu diidentifikasi. Identifikasi gen MMR dapat dilakukan menggunakan teknik methylation-specific multiplex ligation-dependent probe amplification amplification (MS-MLPA). Prinsip dari teknik MS-MLPA yaitu amplifikasi probe yang menempel pada sekuens termetilasi. Tujuan dari penelitian ini yaitu untuk mengoptimasi teknik MS-MLPA dan mengidentifikasi metilasi gen MMR pada kanker kolon dengan teknik MS-MLPA. Penelitian ini menggunakan 27 sampel jaringan frozen kanker kolon yang telah tersedia di Biobank Rumah Sakit Kanker Dharmais (RSKD). Sampel tersebut dianalisis menggunakan probemix Mismatch Repair Gene [ME011-C1][C1-0518] yang telah didesain khusus untuk mendeteksi pada beberapa gen MMR yakni MLH1, PMS2, MSH6, dan MSH2. Hasil penelitian menunjukkan optimasi teknik MS-MLPA telah berhasil dilakukan, sehingga identifikasi metilasi pada gen MMR telah berhasil diperoleh pada 4 sampel pasien. Gen MMR tersebut yakni MLH1 dan MSH6, dengan persentase masing-masing 75% dan 25%.

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DNA methylation is one of the most common causes of mismatch repair gene (MMR) inactivation. The MMR gene corrects errors in the insertion/deletion of nucleotide bases in the DNA synthesis process. MMR gene promoter methylation has an association with the formation of colon cancer, so the methylation needs to be identified. Identification of the MMR gene can be done using the methylation-specific multiplex ligation-dependent probe amplification (MS-MLPA) technique. The principle of the MS-MLPA technique is the amplification of the probe attached to the methylated sequence. The purpose of this study was to optimize the MS-MLPA technique and identify MMR gene methylation in colon cancer using the MS-MLPA technique. This study used 27 samples of frozen colon cancer tissue that were available at the Dharmais Cancer Hospital Biobank (RSKD). The samples were analyzed using the Mismatch Repair Gene probemix [ME011-C1][C1-0518] which has been specially designed to detect several MMR genes, namely MLH1, PMS2, MSH6, and MSH2. The results show that the optimization of the MS-MLPA technique has been successfully carried out, so that the identification of methylation in the MMR gene has been successfully obtained in 4 patient samples. The MMR genes are MLH1 and MSH6, with a percentage of 75% and 25%, respectively. analyzed using probemix Mismatch Repair Gene [ME011-C1][C1-0518] which has been specifically designed to detect several MMR genes namely MLH1, PMS2,

MSH6, and MSH2. The results showed that the optimization of the MS-MLPA technique was successful, so that identification of the methylation in the MMR gene was successfully obtained in 4 patient samples. The MMR genes are MLH1 and MSH6, with percentages of 75% and 25% respectively."

"Metilasi DNA merupakan perubahan epigenetik yang umum terjadi sebagai penyebab inaktivasi gen pada tumor suppressor genes (TSGs). Metilasi pada promoter TSG memiliki asosiasi dengan pembentukan kanker tiroid. Metode methylation-specific multiplex ligation dependent-probe amplification (MS-MLPA) merupakan salah satu metode berbasis PCR yang dapat melakukan identifikasi metilasi pada beberapa gen dan analisis copy number variant secara simultan. Tujuan dari penelitian ini adalah untuk mengoptimasi metode MS-MLPA dan mengidentifikasi metilasi TSG pada kanker tiroid dengan metode MS-MLPA. Sebanyak 40 sampel fine needle aspiration biopsy (FNAB) dikumpulkan secara retrospektif di Rumah Sakit Kanker Dharmais. Sampel FNAB berasal dari pasien yang memiliki kelainan nodul tiroid. Metilasi TSG dianalisis dengan metode MS-MLPA menggunakan probemix Tumour Suppressor Mix 1 ME001-C2 (MRC-Holland). Sampel FNAB dibandingkan dengan reference sample berupa sampel darah yang berasal dari individu sehat. Penelitian ini berhasil mengoptimasi metode MS-MLPA dan mendeteksi metilasi pada 4 jenis tumor suppressor genes, yaitu gen RASSF1A, gen CASP8, gen FHIT, dan gen CHFR. Hasil identifikasi menunjukkan bahwa terdapat 20 sampel tumor ganas dan 2 sampel tumor jinak mengalami metilasi.

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DNA methylation is a common epigenetic change that causes gene inactivation in tumor suppressor genes (TSGs). TSGpromoter methylation has an association with the formation of thyroid cancer. Methylation-specific multiplex ligation-dependent probe amplification (MS-MLPA) is a PCR-based method that can identify methylation in several genes and copy number variant simultaneously. The aim of this study is to optimize methylation-specific multiplex ligation-dependent probe amplification (MS-MLPA) and to identify tumor suppressor genes methylation of thyroid cancer using MS-MLPA. Retrospectively 40 Fine Needle Aspiration Biopsy samples were collected in Dharmais Cancer Hospital. FNAB samples were collected from patients with thyroid nodules abnormalities. Tumor suppressor genes methylation were analyzed using Tumour Suppressor Mix 1 ME001-C2 probemix (MRC-Holland) as MS-MLPA reagents. FNAB samples were compared with reference sample from blood that were collected from healthy people. This study has successfully optimizing MS-MLPA method and detecting 4 methylated tumor suppressor genes, RASSF1A, CAPS8, FHIT and CHFR. Methylation identification shows 20 malignant histopathology samples and 2 benign histopathology samples were methylated.

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"In recent years, cancer stem cells have been recognized as important component in carcinogenesis and they seem to form the basis of many (if not all) tumor types. Cancer stem cells or "cancer cell like stem cells" have been isolated from various cancers of different origin (blood, breast, brain, skin, head and neck, thyroid, cervix, lung, retina, colon, pancreas and so on). Cancer stem cells - rare cells with indefinite proliferative potential that drive the formation and growth of tumours- seem to show intriguing relationships with physiological stem cells. Specifically, these cancer cells show significant similarities in the mechanisms that regulate self-renewal of normal stem cells. Moreover, tumour cells might directly arise from normal stem cells. Further, the cellular biology of cancer stem cells show a lot of similarities with normal stem cells."

"Kanker merupakan kelompok penyakit yang ditandai dengan pertumbuhan dan penyebaran sel-sel abnormal yang tidak terkendali. Jika penyebaran sel tersebut tidak terkendali, hal ini dapat menyebabkan kematian. Berdasarkan American Cancer Society, pendeteksian dini terhadap sel kanker dapat meningkatkan angka harapan hidup seorang pasien lebih dari 97 . Banyak penelitian yang telah meneliti mengenai klasifikasi kanker menggunakan microarray data. Microarray data terdiri dari ribuan fitur gen namun hanya memiliki puluhan atau ratusan sampel. Hal tersebut dapat menurunkan akurasi klasifikasi sehingga perlu dilakukannya pemilihan fitur sebelum proses klasifikasi.Pada penelitian ini dilakukan dua tahap pemilihan fitur. Pertama, support vector machine recursive feature elimination SVM-RFE digunakan untuk prefilter gen. Kedua, hasil pemilihan fitur SVM-RFE diseleksi kembali dengan menggunakan artificial bee colony ABC yang merupakan algoritma optimisasi berdasarkan perilaku lebah madu. Penelitian ini menggunakan dua dataset, yaitu data kanker paru-paru Michigan dan Ontario dari Kent Ridge Biomedical Dataset.Hasil percobaan dengan menggunakan SVM-RFE dan ABC menunjukkan nilai akurasi klasifikasi yang lebih tinggi daripada tanpa pemilihan fitur, SVM-RFE, dan ABC, yaitu 98 untuk data kanker paru-paru Michigan dengan menggunakan 100 fitur dan 97 untuk data kanker paru-paru Ontario dengan menggunakan 70 fitur.

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Cancer is a group of diseases characterized by the uncontrolled growth and spread of abnormal cells. If the spread is not controlled, it can result in death. Based on American Cancer Society, early detection of cancerous cells can increase survival rates for patients by more than 97 . Many study showed new aspect of cancer classification based microarray data. Microarray data are composed of many thousands of features genes and from tens to hundreds of instances. It can decrease classification accuracy so feature selection is needed before the classification process

In this paper, we propose two stages feature selection. First, support vector machine recursive feature elimination recursive feature elimination SVM RFE is used to prefilter the genes. Second, the SVM RFE features selection result is selected again using Artificial Bee Colony ABC which is an optimization algorithm based on a particular intelligent behavior of honeybee swarms. This research conducted experiments on Ontario and Michigan Lung Cancer Data from Kent Ridge Biomedical Dataset.

Experiment results demonstrate that this approach provides a higher classification accuracy rate than without feature selection, SVM RFE, and ABC, 98 for Michigan lung cancer dataset with using 100 features and 97 for Ontario lung cancer dataset with using 70 features."

"Latar Belakang: Methylenetetrahydrofolate reductase (MTHFR) merupakan enzim penting untuk membentuk folat dan metabolisme methionin, sehingga enzim ini sangat dibutuhkan untuk sintesis DNA dan metilasi. Varian dari MTHFR C677T dan A1298C dapat menurunkan folat dalam plasma dan meningkatkan suseptibilitas terhadap spermatogenic arrest. Penelitian ini bertujuan untuk menganalisis polimorfisme gen MTHFR SNP A1298C dan C677T dan hubungannya dengan infertilitas pria oligozoospermia dan azoospermia di Indonesia. Metode: Penelitian ini merupakan penelitian cross sectional dengan mengambil darah 3 mL pada pria oligozoospermia dan azoospermia sejumlah 150 orang. Gen MTHFR dianalisis menggunakan teknik polymerase chain reaction (PCR) dengan primer spesifik. Penelitian dilakukan dengan teknik PCR-RFLP menggunakan enzim restriksi MboII dan HinfI. Analisis PCR-RFLP gen MTHFR digunakan untuk mendeterminasi alotip gen MTHFR SNP A1298C dan SNP C677T pada kelompok pria oligozoospermia dan azoospermia dalam populasi Indonesia. Hasil: Hasil penelitian menunjukkan bahwa distribusi alotip gen MTHFR SNP A1298C tidak berbeda bermakna (p>0,05) antara kelompok oligozoospermia dan azoospermia. Selanjutnya, distribusi alotip gen MTHFR SNP A677T antara kelompok oligozoospermia dan azoospermia juga tidak berbeda bermakna (p > 0.05). Kesimpulan: Polimorfisme gen MTHFR pada SNP A1298C dan C677T tidak berhubungan dengan infertilitas pria oligozoospermia dan azoospermia di Indonesia.

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AbstractBackground: Methylenetetrahydrofolate reductase (MTHFR) is an important enzyme of folate and methionin metabolism, making it crucial for DNA synthesis and methylation. Variants of MTHFR C677T and A1298C gene result in reduced plasma folate levels and increase the susceptibility to spermatogenic arrest. This research aims to analyses MTHFR C677T and A1298C gene polymorphism in Indonesian infertile men with azoospermia and oligozoospermia. Methods: This cross sectional study takes 3 mL of blood from 150 infertile men with oligozoospermia and azoospermia. MTHFR gene is analyzed using polymerase chain reaction technique (PCR) with specific primers. PCR-RFLP analysis of the MTHFR gene using restriction enzymes MboII and HinfI determines allotypes, both of SNP A1298C and C677T in oligozoospermia and azoospermia in Indonesian population. Results: The results show that the distribution of allotypes of MTHFR gene SNP A1298C and A677T is not significantly different (p>0.05) between patient groups with oligozoospermia and azoospermia. Conclusion: MTHFR gene polymorphisms, both of SNP A1298C and C677T are not associated with male infertility in Indonesian men including patients with severe oligozoospermia and azoospermia."