RESUMEN
Novel research on the chemical compositions and biochemical activities of Camellia longii Orel and Luu leaf extracts revealed valuable resources with potential applications in Alzheimer's disease treatment. Qualitative phytochemicals detected various compound groups, including polyphenols, saponins, tannins, flavonoids, alkaloids, amino acids, coumarins, and polysaccharides. HPLC-MS identified 23 compounds in C. longii leaves with compounds found at significant levels, including epicatechin gallate (17.12%), tryptophan (13.73%), isovitexin (12.91%), gallic acid (3.06%), and quercetin (3.06%). Interestingly, the ethanol extract (CLL-Ew) exhibited the highest extraction yield (26.6%) and potent antioxidant and acetylcholinesterase (AChE) inhibitory effects in vitro. In the Drosophila melanogaster model, CLL-Ew improved longevity, movement, and memory by reducing malondialdehyde and increasing glutathione levels. Docking simulations suggested that the above compounds bind tightly to AChE's active site, potentially contributing to memory enhancement. Interestingly, observations of male and female mice after administration of a dose of 5000 mg/kg C. longii leaf extract were recorded normally throughout the 14 day experiment. These findings highlight the potential of C. longii leaf extracts in functional foods and therapeutic interventions for memory impairment prevention and treatment.
RESUMEN
BACKGROUND: Despite the high incidence of blunt trauma in older adults, there is a lack of evidence-based guidance for computed tomography (CT) imaging in this population. We aimed to identify an algorithm to guide use of a Pan-Scan (Head/C-spine/Torso) or a Selective Scan (Head/C-spine ± Torso). We hypothesized that a patient's initial history and exam could be used to guide imaging. METHODS: We prospectively studied blunt trauma patients aged 65+ at 18 Level I/II trauma centers. Patients presenting >24 h after injury or who died upon arrival were excluded. We collected history and physical elements and final injury diagnoses. Injury diagnoses were categorized into CT body regions of Head/C-spine or Torso (chest, abdomen/pelvis, and T/L spine). Using machine learning and regression modeling as well as a priori clinical algorithms based, we tested various decision rules against our dataset. Our priority was to identify a simple rule which could be applied at the bedside, maximizing sensitivity (Sens) and negative predictive value (NPV) to minimize missed injuries. RESULTS: We enrolled 5,498 patients with 3,082 injuries. Nearly half (47.1%, n = 2,587) had an injury within the defined CT body regions. No rule to guide a Pan-Scan could be identified with suitable Sens/NPV for clinical use. A clinical algorithm to identify patients for Pan-Scan, using a combination of physical exam findings and specific high-risk criteria, was identified and had a Sens of 0.94 and NPV of 0.86 This rule would have identified injuries in all but 90 patients (1.6%) and would theoretically spare 11.9% (655) of blunt trauma patients a torso CT. CONCLUSIONS: Our findings advocate for Head/Cspine CT in all geriatric patients with the addition of torso CT in the setting of positive clinical findings and high-risk criteria. Prospective validation of this rule could lead to streamlined diagnostic care of this growing trauma population. LEVEL OF EVIDENCE: Level 2, Diagnostic Tests or Criteria.