Alpha(α)-thalassemia is a blood disorder caused by many types of inheritable α-globin gene mutations which causes no-to-severe clinical symptoms, such as Hb Bart’s hydrops fetalis that leads to early foetal death. Therefore, the aim of this meta-analysis was to provide an update from year 2010 to 2020 on the prevalence of α-thalassemia in Southeast Asia. A systematic literature search was performed using PubMed and SCOPUS databases for related studies published from 2010 to 2020, based on specified inclusion and exclusion criteria. Heterogeneity of included studies was examined with the I2 index and Q-test. Funnel plots and Egger’s tests were performed in order to determine publication bias in this meta-analysis. Twenty-nine studies with 83,674 subjects were included and pooled prevalence rates in this meta-analysis were calculated using random effect models based on high observed heterogeneity (I2 > 99.5, p-value < 0.1). Overall, the prevalence of α-thalassemia is 22.6%. The highest α-thalassemia prevalence was observed in Vietnam (51.5%) followed by Cambodia (39.5%), Laos (26.8%), Thailand (20.1%), and Malaysia (17.3%). No publication bias was detected. Conclusions: This meta-analysis suggested that a high prevalence of α-thalassemia occurred in selected Southeast Asia countries. This meta-analysis data are useful for designing thalassemia screening programs and improve the disease management.
Machine learning (ML) can enhance a dermatologist’s work, from diagnosis to customized care. The development of ML algorithms in dermatology has been supported lately regarding links to digital data processing (e.g., electronic medical records, Image Archives, omics), quicker computing and cheaper data storage. This article describes the fundamentals of ML-based implementations, as well as future limits and concerns for the production of skin cancer detection and classification systems. We also explored five fields of dermatology using deep learning applications: (1) the classification of diseases by clinical photos, (2) der moto pathology visual classification of cancer, and (3) the measurement of skin diseases by smartphone applications and personal tracking systems. This analysis aims to provide dermatologists with a guide that helps demystify the basics of ML and its different applications to identify their possible challenges correctly. This paper surveyed studies on skin cancer detection using deep learning to assess the features and advantages of other techniques. Moreover, this paper also defined the basic requirements for creating a skin cancer detection application, which revolves around two main issues: the full segmentation image and the tracking of the lesion on the skin using deep learning. Most of the techniques found in this survey address these two problems. Some of the methods also categorize the type of cancer too.
Background: Breast cancer is the most common type of cancer affecting Malaysian women. Recent statistics revealed that the cumulative probability of breast cancer and related deaths in Malaysia is higher than in most of the countries of Southeast Asia. Single nucleotide polymorphisms (SNPs) in CYP2E1 (rs6413432 and rs3813867), STK15 (rs2273535 and rs1047972) and XRCC1 (rs1799782 and rs25487) have been associated with breast cancer risk in a meta-analysis but any link in Southeast Asia, including Malaysia, remained to be determined. Hence, we investigated the relationship between these SNPs and breast cancer risk among Malaysian women in the present case-control study. Materials and Methods: Genomic DNA was isolated from peripheral blood of 71 breast cancer patients and 260 healthy controls and subjected to polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) analysis. Results: Our study showed that the c1/c2 genotype or subjects with at least one c2 allele in CYP2E1 rs3813867 SNP had significantly increased almost 1.8-fold higher breast cancer risk in Malaysian women overall. In addition, the variant Phe allele in STK15 rs2273535 SNP appeared to protect against breast cancer in Malaysian Chinese. No significance association was found between XRCC1 SNPs and breast cancer risk in the population. Conclusions: This study provides additional knowledge on CYP2E1, STK15 and XRCC1 SNP impact of risk of breast cancer, particularly in the Malaysian population. From our findings, we also recommend Malaysian women to perform breast cancer screening before 50 years of age.Keywords: Breast cancer -CYP2E1 -Malaysian women -single nucleotide polymorphisms -STK15 -XRCC1
Taraxerol is a pentacyclic triterpenoid that is actively produced by some higher plants as part of a defense mechanism. The biosynthesis of taraxerol in plants occurs through the mevalonate pathway in the cytosol, in which dimethylallyl diphosphate (DMAPP) and isopentyl pyrophosphate (IPP) are first produced, followed by squalene. Squalene is the primary precursor for the synthesis of triterpenoids, including taraxerol, β-amyrin, and lupeol, which are catalyzed by taraxerol synthase. Taraxerol has been extensively investigated for its medicinal and pharmacological properties, and various biotechnological approaches have been established to produce this compound using in vitro techniques. This review provides an in-depth summary of the hypothesized taraxerol biosynthetic pathway, the medicinal properties of taraxerol, and recent developments on tissue culture for the in vitro production of taraxerol.
Background: The XRCC1 protein facilitates various DNA repair pathways; single-nucleotide polymorphisms (SNPs) in this gene are associated with a risk of gastrointestinal cancer (GIC) with inconsistent results, but no data have been previously reported for the Sabah, North Borneo, population. We accordingly investigated the XRCC1 Arg194Trp and Arg399Gln SNPs in terms of GIC risk in Sabah. Materials and Methods: We performed genotyping for both SNPs for 250 GIC patients and 572 healthy volunteers using a polymerase chain reactionrestriction fragment length polymorphism approach. We validated heterozygosity and homozygosity for both SNPs using direct sequencing. Results: The presence of a variant 194Trp allele in the Arg194Trp SNP was significantly associated with a higher risk of GIC, especially with gastric and colorectal cancers. We additionally found that the variant 399Gln allele in Arg399Gln SNP was associated with a greater risk of developing gastric cancer. Our combined analysis revealed that inheritance of variant alleles in both SNPs increased the GIC risk in Sabah population. Based on our etiological analysis, we found that subjects ≥50 years and males who carrying the variant 194Trp allele, and Bajau subjects carrying the 399Gln allele had a significantly increased risk of GIC. Conclusions: Our findings suggest that inheritance of variant alleles in XRCC1 Arg194Trp and Arg399Gln SNPs may act as biomarkers for the early detection of GIC, especially for gastric and colorectal cancers in the Sabah population.
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