Eggshell membrane and green seaweed (Ulva lactuca) micronized powders for in vivo diabetic wound healing in albino rats: a comparative study.

Background: Nonhealing diabetic wounds are a serious complication associated with extremely lethargic wound closure and a high risk of infection, leading to amputation or limb loss, as well as substantial health care costs and a poor quality of life for the patient. The effects of either eggshell membrane (ESM) and green seaweed (Ulva lactuca) extracts alone or in combination were evaluated for in vivo skin wound healing in a rat model of induced diabetes.

Methods: Micronized powders of waste hen ESM, Ulva lactuca, and their 1:1 mixture were prepared using regular procedures.

Hydrothermal extraction and physicochemical characterization of biogenic hydroxyapatite nanoparticles from buffalo waste bones for in vivo xenograft in experimental rats.

Hydroxyapatite (HA) can be used in odontology and orthopedic grafts to restore damaged bone due to its stable chemical characteristics, composition, and crystal structural affinity for human bone. A three-step hydrothermal method was used for the extraction of biogenic calcined HA from the buffalo waste bones at 700 °C (HA-700) and 1000 °C (HA-1000). Extracts were analyzed by thermogravimetric analysis, differential scanning calorimetry, X-ray fluorescence, X-ray diffraction, Fourier transform infrared spectroscopy, scanning electron microscopy, and in vivo examination of HA xenografts for femoral lesions in experimental rats.

A Novel Morphological Analysis of DXA-DICOM Images by Artificial Neural Networks for Estimating Bone Mineral Density in Health and Disease.

One of the best methods for diagnosing bone disease in humans is site-specific and total bone mineral density (BMD) measurements by Dual-energy X-ray Absorptiometry (DXA) machines. The basic disadvantage of this technology is inconsistent BMD measurements among different DXA machines from different manufacturers due to different image analysis algorithms. The objective of the present study was to apply artificial neural networks (ANNs) to estimate total BMD for diagnosing a population of Egyptians with and without pathology, using extracted features from DXA-DICOM images based on the Histogram and Binary algorithms as compared to reference BMD measurements by DXA machine.