Monitoring and evaluation of childhood stunting reduction program based on fish supplement product in North Sumatera, Indonesia.

The government of Serdang Bedagai Regency initiated a supplementation program to reduce the high prevalence of stunting in the area by delivering extra supplementation, which were nutritious biscuits from national government and fish-based supplement produced from local resources. A 6-month study from April 2022 to September 2022 was conducted to monitor and evaluate the government program that involved 219 under-5-year-old children with height-for-age Z-score (HAZ-score) below - 2. We observed the stunting prevalence reduction by 37.00%, where 81 children recovered from stunting (HAZ-score ≥ - 2). Furthermore, the mean HAZ-score and WHZ-score (Weight-for-Height Z-score) were monitored to significantly improve by 0.97 ± 1.45 (P-value = 1.74e-14) and 1.00 ± 2.18 (P-value = and 2.40e-8), subsequently. The most significant improvement in HAZ-score was monitored among children receiving fish-based supplements with 1.04 ± 1.44 improvement (P-value = 6.59e-17). Then, a significant WHZ-score improvement was reported from children consuming fish-based supplements and a combination of fish-based supplements with nutritious biscuits (P-value = 2.32e-8 and 5.48e-5) by 1.04 ± 2.29 and 0.83 ± 1.84, respectively. The results of the observation become evidence that the program could effectively reduce the prevalence of stunting in children below five years old, especially among children who received locally produced fish-based supplements.

Changing Colorectal Cancer Trends in Asians: Epidemiology and Risk Factors.

Once an infrequent disease in parts of Asia, the rate of colorectal cancer in recent decades appears to be steadily increasing. Colorectal cancer represents one of the most important causes of cancer mortality worldwide, including in many regions in Asia. Rapid changes in socioeconomic and lifestyle habits have been attributed to the notable increase in the incidence of colorectal cancers in many Asian countries. Through published data from the International Agency for Cancer Research (IARC), we utilized available continuous data to determine which Asian nations had a rise in colorectal cancer rates. We found that East and South East Asian countries had a significant rise in colorectal cancer rates. Subsequently, we summarized here the known genetics and environmental risk factors for colorectal cancer among populations in this region as well as approaches to screening and early detection that have been considered across various countries in the region.

Intronic Variant of MUTYH Gene Exhibits A Strong Association with Early Onset of Breast Cancer Susceptibility in Indonesian Women Population.

OBJECTIVE: Several studies have recently indicated a huge shifting pattern toward early age onset cases in breast cancer (BC) patients. However, the studies exerted relatively limited to the Caucasian population. This preliminary study is aimed to investigate the genetic risk factors for young BC patients specifically in Indonesia population. METHODS: DNA samples were extracted from 79 BC patients aged younger than 40 years old and 90 healthy samples. These DNA samples were sequenced using Illumina NextSeq 500 platform and preprocessed to extract the single-nucleotide polymorphisms (SNPs) data. Firstly, multiple univariate logistic regressions were performed to test the association between each SNP and BC incidence in young patients. Furthermore, to analyze the polygenic effects derived from multiple SNPs, we employed a multivariate logistics regression. RESULTS: There were only 15 SNPs passed our 95% call rate threshold thus subsequently were used in the association test. One of these variants, rs3219493, emerged to be significantly associated with early-onset BC (p-value = 0.025, OR = 3.750, 95% CI = 1.178-11.938). This result is consistent with the multivariate logistic regression model, where the pertinent variant was found statistically significant (p-value = 0.008, OR = 8.398, 95% CI = 1.720-40.920). This variant was identified as an intronic variant within MUTYH gene which has been reported in several published studies to exhibit an association with the incidence of breast cancer in China, Italy and Sephardi Jews population. However, there is no evident this gene impacting the risk of developing early onset of BC in Indonesia population. CONCLUSION: Despite our limitation in terms of sample size analyzed in this preliminary study, our finding on significant association of intronic MUTHY with the early onset of BC in Indonesia led to a broadened insight of population-based unique aspect to being taken into an in-depth account for and advancement of chemotherapy.

SSMFN: a fused spatial and sequential deep learning model for methylation site prediction.

BACKGROUND: Conventional in vivo methods for post-translational modification site prediction such as spectrophotometry, Western blotting, and chromatin immune precipitation can be very expensive and time-consuming. Neural networks (NN) are one of the computational approaches that can predict effectively the post-translational modification site. We developed a neural network model, namely the Sequential and Spatial Methylation Fusion Network (SSMFN), to predict possible methylation sites on protein sequences. METHOD: We designed our model to be able to extract spatial and sequential information from amino acid sequences. Convolutional neural networks (CNN) is applied to harness spatial information, while long short-term memory (LSTM) is applied for sequential data. The latent representation of the CNN and LSTM branch are then fused. Afterwards, we compared the performance of our proposed model to the state-of-the-art methylation site prediction models on the balanced and imbalanced dataset. RESULTS: Our model appeared to be better in almost all measurement when trained on the balanced training dataset. On the imbalanced training dataset, all of the models gave better performance since they are trained on more data. In several metrics, our model also surpasses the PRMePred model, which requires a laborious effort for feature extraction and selection. CONCLUSION: Our models achieved the best performance across different environments in almost all measurements. Also, our result suggests that the NN model trained on a balanced training dataset and tested on an imbalanced dataset will offer high specificity and low sensitivity. Thus, the NN model for methylation site prediction should be trained on an imbalanced dataset. Since in the actual application, there are far more negative samples than positive samples.

Comparative study of predicted miRNA between Indonesia and China (Wuhan) SARS-CoV-2: a bioinformatics analysis.

BACKGROUND: Several reports on the discovery of SARS-CoV-2 mutations and variations in Indonesia COVID-19 cases led to genomic dysregulation with the first pandemic cases in Wuhan, China. MicroRNA (miRNA) plays an important role in this genetic regulation and contributes to the enhancement of viral RNA binding through the host mRNA. OBJECTIVE: This research is aimed to detect miRNA targets of SARS-CoV-2 and examines their role in Indonesia cases against Wuhan cases. METHODS: SARS-CoV-2 sequences were obtained from GISAID ( https://www.gisaid.org/ ), NCBI ( https://ncbi.nlm.nih.gov ), and National Genomics Data Center ( https://bigd.big.ac.cn/gwh/ ) databases. MiRDB ( https://github.com/gbnegrini/mirdb-custom-target-search ) was used to annotate and predict target human mature miRNAs. For statistical analysis, we utilized a series chi-square test to obtain significant miRNA. DIANA-miRPath v3.0 ( http://www.microrna.gr/miRPathv3 ) analyzed the Gene Ontology of mature miRNAs. RESULT: The statistical results detected five significant miRNAs. Two miRNAs: hsa-miR-4778-5p and hsa-miR-4531 were consistently found in the majority of Wuhan samples, while they were only found in less than half of the Indonesia samples. The other three miRNA, hsa-miR-6844, hsa-miR-627-5p, and hsa-miR-3674, were discovered in most samples in both groups but with a significant difference ratio. Among these five significant miRNA targets, hsa-miR-6844 is the only miRNA that has an association with the ORF1ab gene of SARS-CoV-2. CONCLUSION: The Gene Ontology analysis of five significant miRNA targets indicates a significant role in inflammation and the immune system. The specific detection of host miRNAs in this study shows that there are differences in the characteristics of SARS-CoV-2 between Indonesia and Wuhan.

Transcriptome Profile of Next-Generation Sequencing Data Relate to Proliferation Aberration of Nasopharyngeal Carcinoma Patients in Indonesia.

OBJECTIVE: Nasopharyngeal carcinoma (NPC) is the most common cancer arising from epithelial cells of the nasopharynx in  Indonesia. This study aims to determine the differential level of gene expression in NPC patients when compared with normal individuals. Transcriptome profiling analysis was performed using RNA-Seq technology to determine the differential gene expression relate to proliferation aberration that occurs in NPC patients compared with normal individuals. So we get the transcriptomic profile of Indonesia NPC patients. METHODS: In this study, we used 9 samples, 7 NPC samples and 2 normal samples as control.  Fresh tissue of tumor samples was collected from biopsy, and normal samples were collected brushing technique. The total RNA was isolated from fresh tissue samples and brushing samples using the Rneasy® RNA Extraction Mini Kit. The cDNA library was generated using TruSeq® RNA Library Preparation Kit V2, and its concentration was determined using qPCR. The library was sequenced using the Next-Generation Sequencing (NGS) Illumina Next Seq 550 platform. The raw sequence data quality was analyzed using FastQC and interpreted using HISAT2, HTSeq, edgeR, and PANTHER. RESULTS: From the analysis, 25493 gene transcripts were expressed, with 1956 genes were significantly upregulated, 90 genes were significantly downregulated in NPC samples, and 23897 genes didn't change the expression level significantly (p <0.05), 10 of which genes were associated with cell proliferation. These genes are involved in the regulation of cancer cell proliferation through several signaling pathways, which are the apoptosis signaling pathway, IGF signaling pathway, Notch signaling pathway, and P13K signaling pathway. CONCLUSION: There were significant differences in gene expression levels between NPC patients and normal individuals. Each gene that has changed the expression level plays a role in regulating various pathways that lead to cell proliferation aberration in NPC cases.

Transcriptome Related to Avoiding Immune Destruction in Nasopharyngeal Cancer in Indonesian Patients Using Next-Generation Sequencing.

OBJECTIVE: This study aims to obtain the transcriptomes profile associated with avoiding immune destruction from nasopharyngeal cancer patients in Indonesia using next-generation sequencing. METHODS: The samples are divided into two types of samples; 1) biopsy of nasopharyngeal cancer tissue samples, 2) brushing tissue of people without nasopharyngeal cancer as control samples. The sequencing results were mapped (HISAT2) and quantified (HTSeq) for differential expression analysis using edgeR software. Transcripts data analyzed with Pantherdb and DAVID software to find genes related to the immune system and pathways related to immune destruction by cancer. RESULTS: The differential expression results show that 2,046 genes that have a significant differential expression. The 90 genes expression has down-regulated and 1,956 genes expression up-regulated, there are 20 genes related to the immune system. The 20 genes related to the immune system by analyzing lionproject.net that directly related to hallmark avoiding immune destruction that genes are CXCL9/10/11. The gene expression of CXCL9/10/11 regulates PD-L1 expressions via the Jak/STAT signaling pathway. The interaction between the extracellular domain PD-1 and PD-L1 in cancer cells have avoiding immune destruction. CONCLUSION: The results of this study suggest that the gene expression of CXCL9/10/11 have up-regulated is related to avoiding immune destruction that can use as an early detection biomarker of nasopharyngeal cancer in Indonesian patients.

Transcriptome Profile of Next Generation Sequence Data Related to Inflammation on Nasopharyngeal Carcinoma Cases in Indonesia.

OBJECTIVE: Transcriptomic Profile Analysis Related to Inflammation in Nasopharyngeal Carcinoma Cases. METHODS: This study used 2 control samples taken using the brushing technique and 7 cancer samples with tissue biopsy. Isolate total RNA using Rneasy® RNA Extraction Mini Kit. Measurement of total RNA concentration and purity using a fluorometer and nanodrop Qubit. Synthesis of cDNA library uses TruSeq® RNA Library Preparation Kit V2 and concentration is measured using qPCR. Sequencing samples using NGS Illumina NextSeq 550 platform engine. Quality control results of sequencing using FASTQC, and raw data processing using HISAT2. Differential analysis of gene expression (DEGs) using edgeR and pathway analysis using DAVID and PANTHER. RESULTS: From the 25,493 genes that experienced a significant change in expression level (P <0.05) from DEG analysis there were 13 genes that play a role in the inflammatory process. Based on DAVID pathway analysis software, there are 8 genes detected based on the KEGG pathway database found in 2 pathways, namely Inflammatory Mediator Regulation of TRP Channels pathway with genes that play HTR2A, NGF, TRPA1, PRKCG, and ADCY8. CXCL9, CXCL10, and CXCL11 genes are found in the Toll-Like Receptor Signaling pathway. Based on PANTHER pathway analysis software, 6 genes were found, namely CXCL10, MYLK2, COL20A1, MYH2, ACTC1, and ALOX15 in the Inflammation Mediated by Chemokine and Cytokine Signaling pathways. Almost all genes found from DEGs are upregulated, except the ALOX15 gene that is downregulated. CONCLUSION: There are 13 genes that play a role in the inflammatory process in Nasopharyngeal Carcinomafrom a sample of the Indonesian population. Genes CXCL9, CXCL10, CXCL11, MYLK2, COL20A1, MYH2, ACTC1, HTR2A, NGF, TRPA1, PRKCG, and ADCY8 have been upregulated and ALOX15 has been downregulated. These genes play a role in the Inflammation Mediated by Chemokine and Cytokine Signaling pathways, Inflammatory Mediator Regulation of TRP Channels, and Toll-Like Receptor Signaling.