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Black Garlic: Kandungan Senyawa Bioaktif, dan Bioaktivitasnya Fistara Lesti Rahmafitria; Nuniek Herdyastuti
Unesa Journal of Chemistry Vol. 15 No. 3 (2026): Vol 15 No 3 (2026): On progress
Publisher : Department of Chemistry, Faculty of Mathematics and Natural Sciences, Surabaya State University, located at Jl Ketintang, Surabaya, East Java, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26740/ujc.v15n3.p97-111

Abstract

Black garlic is a processed garlic product (Allium sativum L.) produced through controlled heating at high temperatures and humidity for a specific period. This process causes distinctive sensory changes, including a black color, a softer texture, a sweeter flavor, and a less pungent aroma compared to fresh garlic. These thermal changes lead to chemical changes, such as a decrease in allicin and an increase in more stable bioactive compounds such as S-allyl-L-cysteine ​​(SAC), polyphenols, flavonoids, and Maillard reaction products. These compositional changes are closely related to various bioactivities of black garlic, especially antioxidant activity, followed by anti-inflammatory, antidiabetic, anticancer, antimicrobial, and cardiovascular and metabolic effects. Research reports still show high data heterogeneity due to differences in processing conditions, raw material varieties, analytical methods, and biological models used. Furthermore, available scientific evidence is still limited to analytical, in vitro, and animal studies, while clinical evidence in humans is still very limited. This article reviews the manufacturing process, physicochemical and chemical changes, bioactive content, bioactivity, and research gaps in black garlic as a basis for developing garlic-based functional foods.
Open-Data Serum Metabolomics of Lung Adenocarcinoma for Equitable Early Detection under SDG Target 3.4 Muhammad Nurrohman Sidiq; Rudiana Agustini; Nuniek Herdyastuti; Prima Retno Wikandari; Mirwa Adiprahara Anggarani
Journal of Current Studies in SDGs Vol. 3 No. 4 (2027): December
Publisher : Sekolah Tinggi Agama Islam Sabilul Muttaqin Mojokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63230/jocsis.3.4.325

Abstract

Objective: Sustainable Development Goal (SDG) target 3.4 addresses premature non-communicable disease mortality, yet lung cancer leads cancer mortality among Indonesian men, and low-dose computed tomography screening presumes imaging capacity most low-income settings lack. This study asked which serum pathways are recoverable from open lung adenocarcinoma metabolomics and whether their enzymes are altered in tumor tissue. Method: Serum GC-TOF MS data from the ST000385 ADC2 cohort (43 cases, 43 controls, 152 compounds) were reanalysed in MetaboAnalyst 6.0 using PLS-DA with permutation testing, multivariate ROC, and KEGG enrichment. Enzymes were examined in TCGA-LUAD (483 tumor, 347 normal) with GEPIA2 and survival analysis, and the cohort ST000386 underwent metadata testing. Results: The one-component model separated the groups (R² = 0.492, Q² = 0.302, permutation p < 5 × 10⁻⁴) and reached an AUC of 0.882 on five metabolites, which a sensitivity analysis showed to rest on one correlated axis. Twenty metabolites passed a 5% FDR, and arginine biosynthesis was the most enriched pathway (FDR = 5.8 × 10⁻⁵), whereas the TCA cycle and taurine metabolism did not survive correction. LDHA, PKM and CDO1 predicted survival. ARG1, OTC and CPS1 medians fell in tumor while ASS1 and ARG2 rose modestly. ST000386 carried subject-level metadata that does not associate with its own metabolome. Novelty: The dominant pathway is arginine biosynthesis rather than the Warburg axis of earlier readings, and the enzyme layer shows a dysregulated rather than silenced urea cycle.
Open-Data Serum Metabolomics of Lung Adenocarcinoma for Equitable Early Detection under SDG Target 3.4 Muhammad Nurrohman Sidiq; Rudiana Agustini; Nuniek Herdyastuti; Prima Retno Wikandari; Mirwa Adiprahara Anggarani
Journal of Current Studies in SDGs Vol. 3 No. 4 (2027): December
Publisher : Sekolah Tinggi Agama Islam Sabilul Muttaqin Mojokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63230/jocsis.3.4.325

Abstract

Objective: Sustainable Development Goal (SDG) target 3.4 addresses premature non-communicable disease mortality, yet lung cancer leads cancer mortality among Indonesian men, and low-dose computed tomography screening presumes imaging capacity most low-income settings lack. This study asked which serum pathways are recoverable from open lung adenocarcinoma metabolomics and whether their enzymes are altered in tumor tissue. Method: Serum GC-TOF MS data from the ST000385 ADC2 cohort (43 cases, 43 controls, 152 compounds) were reanalysed in MetaboAnalyst 6.0 using PLS-DA with permutation testing, multivariate ROC, and KEGG enrichment. Enzymes were examined in TCGA-LUAD (483 tumor, 347 normal) with GEPIA2 and survival analysis, and the cohort ST000386 underwent metadata testing. Results: The one-component model separated the groups (R² = 0.492, Q² = 0.302, permutation p < 5 × 10⁻⁴) and reached an AUC of 0.882 on five metabolites, which a sensitivity analysis showed to rest on one correlated axis. Twenty metabolites passed a 5% FDR, and arginine biosynthesis was the most enriched pathway (FDR = 5.8 × 10⁻⁵), whereas the TCA cycle and taurine metabolism did not survive correction. LDHA, PKM and CDO1 predicted survival. ARG1, OTC and CPS1 medians fell in tumor while ASS1 and ARG2 rose modestly. ST000386 carried subject-level metadata that does not associate with its own metabolome. Novelty: The dominant pathway is arginine biosynthesis rather than the Warburg axis of earlier readings, and the enzyme layer shows a dysregulated rather than silenced urea cycle.