Quality Control of 11 Cannabinoids by Ultraperformance Liquid Chromatography Coupled with Mass Spectrometry (UPLC-MS/MS).

Objective: Cannabinoid extraction from Cannabis sativa L. (hemp) for nonmedical purposes has become popular in the United States. Concerns, however, have been raised regarding the accuracy of the labels for cannabinoid levels in the commercial products. Methods: In this study, we developed rapid, sensitive, selective, accurate, and validated liquid chromatography-tandem mass spectrometry for the quantification of cannabinoids. The methods are for determining 11 cannabinoids in cannabis (hemp) extracted in oil form, and we investigated the accuracy of the labeling and thermal stability regarding the cannabinoids on 17 oil cannabis samples. Results: In the UPLC chromatogram, we see a good resolution and there is no matrix effect and the accuracy were 98.2% to 102.6%, and the precision was 0.52%-8.18%. The linearity of the calibration curves in methanol was with a regression r2 ≥ 0.99. The lowest of detection (LOD) was 5-25 ng/mL, and the limit of quantification (LOQ) was 10-50 ng/mL. The study showed that only 30% of the commercial samples were within the acceptable range of +/-10% compared to the labeled ingredient concentrations. The thermal stability test profile showed a change in the concentration of cannabinoids in each sample at 37°C for one week, with an average loss of cannabinoids up to 15%. Conclusion: The validated method proved to be selective, accurate, and precise, with acceptable linearity within the calibration range with no matrix effect. The stability profile data indicated that high temperatures could change the quality of commercial samples.

Endocannabinoids are potential inhibitors of glioblastoma multiforme proliferation.

Globally, it is evident that glioblastoma multiforme (GBM) is an aggressive malignant cancer with a high mortality rate and no effective treatment options. Glioblastoma is classified as the stage-four progression of a glioma tumor, and its diagnosis results in a shortened life expectancy. Treatment options for GBM include chemotherapy, immunotherapy, surgical intervention, and conventional pharmacotherapy; however, at best, they extend the patient's life by a maximum of 5 years. GBMs are considered incurable due to their high recurrence rate, despite various aggressive therapeutic approaches which can have many serious adverse effects. Ceramides, classified as endocannabinoids, offer a promising novel therapeutic approach for GBM. Endocannabinoids may enhance the apoptosis of GBM cells but have no effect on normal healthy neural cells. Cannabinoids promote atypical protein kinase C, deactivate fatty acid amide hydrolase enzymes, and activate transient receptor potential vanilloid 1 (TRPV1) and TRPV2 to induce pro-apoptotic signaling pathways without increasing endogenous cannabinoids. In previous in vivo studies, endocannabinoids, chemically classified as amide formations of oleic and palmitic acids, have been shown to increase the pro-apoptotic activity of human cancer cells and inhibit cell migration and angiogenesis. This review focuses on the biological synthesis and pharmacology of endogenous cannabinoids for the enhancement of cancer cell apoptosis, which have potential as a novel therapy for GBM. Please cite this article as: Duzan A, Reinken D, McGomery TL, Ferencz N, Plummer JM, Basti MM. Endocannabinoids are potential inhibitors of glioblastoma multiforme proliferation. J Integr Med. 2023; 21(2): 120-128.

Mishel's uncertainty in illness theory: Informing nursing diagnoses and care planning.

PURPOSE: Patients with glioblastoma multiforme (GBM) face uncertainty during the illness trajectory that decreases their quality of life. Uncertainty manifests as an altered state of mind in patients with GBM and increases the burden of managing their diagnosis. The uncertainty in illness theory (UIT) can be used to guide nursing practice and create care plans to decrease this uncertainty. DATA SOURCES: The UIT and conceptual model were used to pair diagnoses from NANDA-I Nursing Diagnoses to form care plans for patients with GBM. METHODS: In a stepwise approach, concepts from the UIT were organized and cross-walked into an integrated theory-driven practice framework to enhance care planning. CONCLUSIONS: The UIT helps define and identify circumstances of uncertainty in patients experiencing illness, and Nursing Diagnoses provide engagement and outcomes for those uncertainty-based diagnoses. Some examples of the UIT guiding Nursing Diagnoses includes a patient's cognitive level guiding a Nursing Diagnosis care plan of Risk for Acute Confusion. Social Support can guide the care plan of Risk for Loneliness, and appraisal of uncertainty can guide a care plan for Ineffective Individual Coping. Using the UIT to guide theory-driven practice links interventions and outcomes in patients with GBM. IMPLICATIONS FOR PRACTICE: The UIT can guide NANDA-I Nursing Diagnoses to assist nurses in creating a nursing care plan for nursing engagement to decrease uncertainty and increase the quality of life in patients with GBM. Theory-driven research defines the application of the UIT in GBM and provides foundational knowledge for theory-driven practice to occur.