
Osteoporosis (OSP) decreases bone mass and affects millions of people; the diagnosis is often late. Considering the side effects of conventional treatments, search for natural therapies should be a constant. Among natural treatments, herbal medicines stand out with very promising results. One of the plants that has drawn a lot of attention to prevent OSP is Plinia cauliflora (PC) Kausel. The objective was to evaluate the effect of PC extract in the OSP prevention in ovariectomized rats. In total, 60 female Wistar rats were divided into six experimental groups: positive control, negative control, sham, and three groups to test different doses (37.5, 75, and 150 mg) of PC bark extract. Bone mineral density (BMD), bone mineral content (BMC), hormone dosage, and osteocalcin were evaluated. One of the regions evaluated was the legs, where prolonged treatment with extract of PC in 75 mg, had a gain of 1.4 times of BMC. The levels of osteocalcin were found to be high at the lowest dose (37.5 mg), increasing the BMC by 70%, and moderately increasing the levels of dehydroepiandrosterone, proving that the pathway that increases BMC is through osteocalcin. PC resulted in increased BMC related mainly to increased osteocalcin, at the lowest dose preserving the bone matrix.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
