Prodigy

The total phenolic content was determined by employing the methods given in the literature (Slinkard and Singleton, 1977 (link)) with some modification. Sample solution (1 mg/mL; 0.25 mL) was mixed with diluted Folin–Ciocalteu reagent (1 mL, 1:9, v/v) and shaken vigorously. After 3 min, Na₂CO₃ solution (0.75 mL, 1%) was added and the sample absorbance was read at 760 nm after a 2 h incubation at room temperature. The total phenolic content was expressed as milligrams of gallic acid equivalents (mg GAE/g extract) (Vlase et al., 2014 ).
The total flavonoids content was determined using AlCl₃ method (Zengin et al., 2014 (link)). Briefly, sample solution (1 mg/mL; 1 mL) was mixed with the same volume of aluminum trichloride (2%) in methanol. Similarly, a blank was prepared by adding sample solution (1 mL) to methanol (1 mL) without AlCl₃. The sample and blank absorbances were read at 415 nm after a 10 min incubation at room temperature. The absorbance of the blank was subtracted from that of the sample. Rutin was used as a reference standard and the total flavonoid content was expressed as milligrams of rutin equivalents (mg RE/g extract) (Mocan et al., 2015 (link)).
The total saponins content of the extract was determined by the vanillin-sulfuric acid method (Aktumsek et al., 2013 (link)). Sample solution (1 mg/mL; 0.25 mL) was mixed with vanillin (0.25 mL, 8%) and sulfuric acid (2 mL, 72%). The mixture was incubated for 10 min at 60°C. Then the mixture was cooled for another 15 min, followed by the sample absorbance measurement at 538 nm. The total saponin content was expressed as milligrams of quillaja equivalents (mg QAE/g extract).
The total triterpenoids content of the extracts was determined according to Zhang et al. (2010) (link) method with some modifications. Briefly, sample solution (1 mg/mL; 500 μL) was mixed with the vanillin–glacial acetic acid (5%, w/v, 0.5 mL) and 1 mL of perchloric acid. The mixture was incubated at 60°C for 10 min, cooled in an ice water bath for 15 min and then 5 mL glacial acetic acid was added and mixed well. After 6 min, the absorbance was read at 538 nm. Oleanolic acid was used as a reference standard and the content of total triterpenoids was expressed as oleanolic acid equivalents (mg OAE/g extract) through a calibration curve with oleanolic acid.
HPLC-PDA analyses were performed on a Waters liquid chromatograph equipped with a model 600 solvent pump and a 2996 photodiode array detector, and Empower v.2 Software (Waters Spa, Milford, MA, United States) was used for acquisition of data. A C18 reversed-phase packing column (Prodigy ODS (3), 4.6 × 150 mm, 5 μm; Phemomenex, Torrance, CA, United States) was used for the separation and the column was thermostated at 30 ± 1°C using a Jetstream2 Plus column oven. The injection volume was 20 μL. The mobile phase was directly on-line degassed by using Biotech DEGASi, mod. Compact (LabService, Anzola dell’Emilia, Italy). Gradient elution was performed using the mobile phase water-acetonitrile (93:7, v/v, 3% acetic acid) (Zengin et al., 2016 (link)). The UV/Vis acquisition wavelength was set in the range of 200–500 nm. The quantitative analyses were achieved at maximum wavelength for each compound.

All image analysis was performed in a custom-built Image Processing Language (IPL Version 5.06a-ucsf, Scanco Medical AG) that includes in-house-developed functionality. For reference, simulated areal bone mineral density (aBMD_sim) was calculated from the HR-pQCT images for the radius. This technique was established previously to approximate DXA aBMD measures with accuracy comparable with intermanufacturer differences (eg, Hologic versus Prodigy).(22 ) Additionally, the images were processed using the default clinical evaluation protocol provided by the manufacturer to derive standard cortical geometric and density measures.(10 (link)) This included cortical area (Ct.Ar), cortical thickness (Ct.Th), cortical volumetric bone mineral density (Ct.vBMD), and total volumetric bone mineral density (vBMD). Subsequent image processing and analysis were based on the binary image generated by the standard protocol.(10 (link)) This process segments the mineralized and background phases of fine structures using a simple fixed threshold following the application of a Laplace-Hamming edge-enhancement filter. Previously, this method was optimized for trabecular bone segmentation of images acquired with a lower-resolution pQCT device(23 (link)) and subsequently has been shown to provide good accuracy for HR-pQCT.(12 (link),13 ) Acceptable application of this technique for the segmentation of fine cortical structure was qualitatively verified by visual inspection in a series of data sets spanning a range of geometries. The periosteal and endosteal boundaries were defined using an automated contouring method similar to the technique described previously by Buie and colleagues.(24 (link)) The region between the two contours was considered the cortical compartment volume of interest (VOI) (Fig. 1A). Owing to the imprecise nature of the cortical compartment segmentation, this VOI typically includes void voxels from the background on the periosteal and endosteal margins as well as intracortical porosity (Fig. 1B). To exclusively segment the intracortical porosity volume, a novel algorithm based on 2D component labeling and a 3D region-growing process was applied: True intracortical porosity was estimated initially to be all void voxels unconnected to the background in each 2D axial slice. Next, a region-growing process additionally included void voxels connected along the z axis (SI direction) to the initial pore voxels (Fig. 1C, D). Based on this segmentation, cortical porosity (Ct.Po) was defined as a normalized volumetric index according to Eq. (1):

where Ct.PoV is the segmented pore volume, and Ct.BV is the mineralized cortical bone volume. In this way, variability related to cortical compartment segmentation and endosteal and periosteal surface irregularities did not bias the measure.

For each treatment, 30 healthy and mature leaves were selected, washed, and dried. Following a 30-min incubation at 105 °C, the leaves were dried at 75 °C, crushed, and screened. The ground leaves were collected in a self-sealing bag and stored in a dryer. Leaf samples were boiled in H₂SO₄–HClO₄ and HNO₃–HClO₄ solutions and then the nutrient element contents were determined using AutoAnalyzer 3 with XY-2 Sampler (SEAL Analytical, UK) and an inductively coupled plasma emission spectrometer (Prodigy Spec, Teledyne, USA).
On August 10, 10 randomly selected leaves (per treatment) were obtained from OY saplings to measure the catalase (CAT), peroxidase (POD), and superoxide dismutase (SOD) contents as previously described (Wang et al., 2018 (link)). CAT was determined by monitoring the decomposition of H₂O₂. SOD was assayed by monitoring the inhibition of the photochemical reduction of nitro blue tetrazolium. POD was determined by monitoring the oxidation reaction of guaiacol.

We performed a retrospective case-control study using data collected from medical records and radiographic reports between May 2012 and May 2019. The study protocol was reviewed and approved by the institutional review board. All participants provided informed consent before data collection.
Female patients over 50 years of age who underwent DEXA scans (Lunar Prodigy Advance, GE Healthcare, Madison, WI) at 3 different sites (lumbar spine, proximal femur, and distal forearm) in our hospital were initially classified into two groups. The experimental group consisted of patients with low energy-induced DRF (group 1), and the control group consisted of patients with other injuries excluding fragility fractures (group 2). A detailed list of inclusion and exclusion criteria is described in Fig. 1.Fig. 1

Flow diagram for inclusion and exclusion of the patients in each group

During the measurement of anthropometric characteristics and body composition, participants wore only light underwear and no shoes. Body mass (BM) was measured to the nearest 0.1 kg using a hand scale (Seca 709, Hamburg, Germany), and height was measured to the nearest 0.5 cm using a standardized wall-mounted height board. Body mass index (BMI) was calculated as the participant’s body mass in kilograms divided by the square of body height in meters.
Body composition (total mass, appendicular fat, skeletal muscle mass, and bone mass) was measured with a dual-x-ray absorptiometry (DXA) (Lunar Prodigy; GE Medicals, Madison WI). The DXA was calibrated daily with a standard phantom.