Uji Aktivitas Antikanker (Preventif dan Kuratif) Ekstrak Etanol Temu Mangga (Curcuma Mangga Val.) Pada Mencit yang Diinduksi Siklofosfamid

Prevalensi kanker di Indonesia cukup tinggi, menurut data Riset Kesehatan Dasar (Riskesdas) tahun 2007 terdapat  4,3 per 1000 penduduk menderita kanker. Sementara itu umumnya antineoplastik yang digunakan untuk pengobatan kanker menyebabkan toksisitas karena kerjanya yang kurang selektif. Oleh karena itu diperlukan penemuan obat baru dari tanaman sebagai alternatif pengobatan yang efektif dan aman.  Penelitian ini dimaksudkan untuk membuktikan adanya aktivitas antikanker ekstrak etanol rimpang temu mangga baik sebagai agen preventif maupun kuratif. Penelitian dilakukan dengan metode eksperimental menggunakan mencit jantan sehat, dengan berat badan 20 – 30 g sebagai hewan percobaan. Ekstrak etanol rimpang temu mangga  diberikan kepada hewan uji dengan dosis 200, 400, dan 800 mg/kg BB. Pada uji antikanker sebagai agen preventif diberikan sediaan uji tersebut selama 7 hari, pada hari ke-8 diinduksi siklofosfamid secara parenteral. Tigapuluh jam kemudian hewan dibunuh dan dibedah. Darah  diambil  untuk penentuan nilai hematokrit dan sumsum tulang femur untuk pemeriksaan mikronukleusambil. Sedangkan pada uji antikanker sebagai agen kuratif hewan dinduksi siklofosfamid terlebih dahulu, 30 jam kemudian diberi sediaan uji selama 7 hari. Pada hari ke-8  hewan dibunuh dan dibedah, lalu diambil darah untuk penentuan nilai hematokrit dan sumsum tulang femur pemeriksaan mikronukleusambil. Berdasarkan hasil penelitian diketahui rimpang temu mangga menghambat pembentukan mikronukleus dan meningkatkan nilai hematokrit baik pada uji preventif maupun kuratif yang bermakna secara statistik (P0,05). Aktivitas terbaik tampak pada dosis 800 mg/kg BB dengan jumlah mikronukleus dan nilai hematokrit yang mendekati nilai pada kelompok yang diberi suspensi CMC 1%. Hasil penelitian disimpulkan bahwa ekstrak etanol rimpang temu mangga memiliki aktivitas antikanker baik sebagai agen preventif maupun kuratif

Transcriptomics-driven drug repositioning for the treatment of diabetic foot ulcer

Diabetic foot ulcers (DFUs) are a common complication of diabetes and can lead to severe disability and even amputation. Despite advances in treatment, there is currently no cure for DFUs and available drugs for treatment are limited. This study aimed to identify new candidate drugs and repurpose existing drugs to treat DFUs based on transcriptomics analysis. A total of 31 differentially expressed genes (DEGs) were identified and used to prioritize the biological risk genes for DFUs. Further investigation using the database DGIdb revealed 12 druggable target genes among 50 biological DFU risk genes, corresponding to 31 drugs. Interestingly, we highlighted that two drugs (urokinase and lidocaine) are under clinical investigation for DFU and 29 drugs are potential candidates to be repurposed for DFU therapy. The top 5 potential biomarkers for DFU from our findings are IL6ST, CXCL9, IL1R1, CXCR2, and IL10. This study highlights IL1R1 as a highly promising biomarker for DFU due to its high systemic score in functional annotations, that can be targeted with an existing drug, Anakinra. Our study proposed that the integration of transcriptomic and bioinformatic-based approaches has the potential to drive drug repurposing for DFUs. Further research will further examine the mechanisms by which targeting IL1R1 can be used to treat DFU

Mapping rheumatoid arthritis susceptibility through integrative bioinformatics and genomics

Rheumatoid arthritis (RA) is an autoimmune disease that influences several organs and tissues, especially the synovial joints, and is associated with multiple genetic and environmental factors. Numerous databases provide information on the relationship between a specific gene and the disease pathogenesis. However, it is important to further prioritize biological risk genes for downstream development and validation.  This study aims to map RA-association genetic variation using genome-wide association study (GWAS) databases and prioritize influential genes in RA pathogenesis based on functional annotations. These functional annotations include missense/nonsense mutations, cis-expression quantitative trait locus (cis-eQTL), overlap knockout mouse phenotype (KMP), protein-protein interaction (PPI), molecular pathway analysis (MPA), and primary immunodeficiency (PID). 119 genetic variants mapped had a potential high risk for RA based on functional scoring. The top eight risk genes of RA are TYK2 and IFNGR2, followed by TNFRSF1A, IL12RB1 and CD40, C5, NCF2, and IL6R. These candidate genes are potential biomarkers for RA that can aid drug discovery and disease diagnosis

Identifikasi Variasi Gen dan Ekspresi Gen Yang Berhubungan Dengan Anemia Aplastik Menggunakan Pendekatan Genomik dan Bioinformatika

Anemia aplastik merupakan anemia yang disertai oleh pansitopenia pada tepi darah yang disebabkan oleh kelainan primer pada sumsum tulang dalam bentuk aplasia atau hipoplasia tanpa adanya infiltrasi, supresi atau pendesakan sumsum tulang. Pada anemia aplastik terjadi penurunan produksi sel darah dari sumsum tulang sehingga menyebabkan retikulositopenia, anemia, granulositopenia, monositopenia dan trombositopenia. Anemia aplastika termasuk dalam penyakit yang rentan disebabkan oleh faktor genetik. Salah satu faktor genetik yang banyak diidentifikasi adalah variasi gen atau single nucleotide polymorphism ( SNP). Hingga hari inimetodologi untuk bantuan variasi gen tersebut sudah tersedia dengan bentuk berbagai macam database dan bioinformatika. Tujuan penelitian ini untuk mengidentifikasi variasi gen yang berhubungan dengan Anemia aplastik dan memprioritaskan variasi gen tersebut berdasarkan tingkat kerentanannya melalui pemanfaatan katalog GWAS dan integrasi beberapa database bioinformatika. Hasil penelitian ini kami menemukan ada dua SNP rs1042151 dan rs28367832 yang rentan terhadap anemia aplastik berdasarkan ekpresi gen di jaringan darah . Variasi gen tesebut juga mengkode gen  HLA- DPB1 dan HLA-B dan menunjukkan ekspresi yang tinggi pada jaringan darah ( whole blood ) .Penelitian ini menunjukkan bahwa integrasi variasi gen dan bioinformatika potensial untuk memberikan informasi kepada si terkait kerentanan suatu variasi gen pada suatu penyakit termasuk pada anemia aplastik

Publication trend of TMPRSS2 as SARS-CoV-2 receptor during the COVID-19 pandemic

The Coronavirus Disease 2019 (COVID-19) pandemic has not yet been fully under public health control, which is still currently impacting a large number of people worldwide in 2023. Since the pandemic emerged, the growing number of publications related to TMPRSS2 as a SARS-CoV-2 receptor worldwide has increased rapidly with various findings and qualities. It is important to determine the trend of TMPRSS2 publication as no such studies currently exist that represent the publication trend related to this critical field of study. Here, we employed a bibliometric-based approach to evaluate the research trends of TMPRSS2 mechanistically as the SARS-CoV-2 receptor. We identified 1012 research documents published between 2020 and 2022 for this study. The most common document category was "Research Article" (646 articles, 63.84%) followed by "Review Article" (261 articles, 25.79%), and letters to editors (57 articles, 5.63%). Germany was the most cited country with a total of citations (9400 citations), followed by the USA (6409 citations) and China (1788 citations), respectively. In conclusion, given the impact of COVID-19, this study indicated TMPRSS2 as a SARS-CoV-2 receptor as a timely and highly relevant research topic

Mapping rheumatoid arthritis susceptibility through integrative bioinformatics and genomics

Rheumatoid arthritis (RA) is an autoimmune disease that influences several organs and tissues, especially the synovial joints, and is associated with multiple genetic and environmental factors. Numerous databases provide information on the relationship between a specific gene and the disease pathogenesis. However, it is important to further prioritize biological risk genes for downstream development and validation. This study aims to map RA-association genetic variation using genome-wide association study (GWAS) databases and prioritize influential genes in RA pathogenesis based on functional annotations. These functional annotations include missense/nonsense mutations, cis-expression quantitative trait locus (cis-eQTL), overlap knockout mouse phenotype (KMP), protein-protein interaction (PPI), molecular pathway analysis (MPA), and primary immunodeficiency (PID). 119 genetic variants mapped had a potential high risk for RA based on functional scoring. The top eight risk genes of RA are TYK2 and IFNGR2, followed by TNFRSF1A, IL12RB1 and CD40, C5, NCF2, and IL6R. These candidate genes are potential biomarkers for RA that can aid drug discovery and disease diagnosis

Mapping Rheumatoid Arthritis Susceptibility through Integrative Bioinformatics and Genomics

Rheumatoid arthritis (RA) is an autoimmune disease that influences several organs and tissues, especially the synovial joints, and is associated with multiple genetic and environmental factors. Numerous databases provide information on the relationship between a specific gene and the disease pathogenesis. However, it is important to further prioritize biological risk genes for downstream development and validation. This study aims to map RA-association genetic variation using genome-wide association study (GWAS) databases and prioritize influential genes in RA pathogenesis based on functional annotations. These functional annotations include missense/nonsense mutations, cis-expression quantitative trait locus (cis-eQTL), overlap knockout mouse phenotype (KMP), protein-protein interaction (PPI), molecular pathway analysis (MPA), and primary immunodeficiency (PID). 119 genetic variants mapped had a potential high risk for RA based on functional scoring. The top eight risk genes of RA are TYK2 and IFNGR2, followed by TNFRSF1A, IL12RB1 and CD40, C5, NCF2, and IL6R. These candidate genes are potential biomarkers for RA that can aid drug discovery and disease diagnosis