Chemical Components of Essential Oils From the Leaves of Seven Species Belonging to Rutaceae Family from Binh Chau-Phuoc Buu Nature Reserve, Vietnam

Several plant species of the Rutaceae family are medicinal plants, oil bearing and food crops. To provide more information for utilization of some species of this family in Binh Chau-Phuoc Buu Nature Reserve, we extracted essential oils from the leaves of seven species of the Rutaceae family: Acronychia pedunculata (L.) Miq., Atalantia citroides Pierre ex Guillaumin, Clausena excavata Burm.f., Glycosmis pentaphylla (Retz.) DC., Luvunga scandens (Roxb.) Buch.-Ham. ex Wight & Arn, Melicope pteleifolia (Champ. ex Benth.) T.G. Hartley, and Micromelum sp., via hydrodistillation, and identified their components using GC/MS analysis. A total of 60 compounds were identified from essential oils of seven species. The main components of the essential oils isolated from five species, including A. pedunculata, C. excavata, M. pteleifolia, G. pentaphylla, and Micromelum sp., were caryophyllene (57.63% and 55.41% in A. pedunculata and C. excavata, respectively), 1,9-decadiyne (32.59%, M. pteleifolia), β-ocimene (23.10%, G. pentaphylla), and 3-carene (58.03%, Micromelum sp.). Additionally, this study revealed the chemical composition of essential oils of L. scandens and A. citroides for the first time. The main constituent of A. citroides was 7-oxabicyclo[4.1.0] heptane, 3-oxiranyl- (53.91%) and that of L. scandens was caryophyllene (34.66%). These findings provide the basis for further application of these species in medicine

Multimodal analysis of methylomics and fragmentomics in plasma cell-free DNA for multi-cancer early detection and localization

Despite their promise, circulating tumor DNA (ctDNA)-based assays for multi-cancer early detection face challenges in test performance, due mostly to the limited abundance of ctDNA and its inherent variability. To address these challenges, published assays to date demanded a very high-depth sequencing, resulting in an elevated price of test. Herein, we developed a multimodal assay called SPOT-MAS (screening for the presence of tumor by methylation and size) to simultaneously profile methylomics, fragmentomics, copy number, and end motifs in a single workflow using targeted and shallow genome-wide sequencing (~0.55×) of cell-free DNA. We applied SPOT-MAS to 738 non-metastatic patients with breast, colorectal, gastric, lung, and liver cancer, and 1550 healthy controls. We then employed machine learning to extract multiple cancer and tissue-specific signatures for detecting and locating cancer. SPOT-MAS successfully detected the five cancer types with a sensitivity of 72.4% at 97.0% specificity. The sensitivities for detecting early-stage cancers were 73.9% and 62.3% for stages I and II, respectively, increasing to 88.3% for non-metastatic stage IIIA. For tumor-of-origin, our assay achieved an accuracy of 0.7. Our study demonstrates comparable performance to other ctDNA-based assays while requiring significantly lower sequencing depth, making it economically feasible for population-wide screening