Objective To investigate the structure and biomechanical property differences in different regions of the femoral head for elderly patients with femoral neck fractures, and to study its influence on internal fixation for fracture. Methods Twenty femoral head specimens were collected from elderly patients with femoral neck fracture after joint replacement. The femoral head was divided into 3 parts (lateral, inferior and medial region) with reference to anatomical markers on surface of the femoral head. After the position and drilling direction of the ring drill were determined, a circular drill was used to obtain the cylindrical cancellous bone columns with 10 mm in diameter and 10 mm in height. The data of cancellous bone columns in different regions were analyzed by Micro-CT scanning system, including bone volume fraction (BVF), trabecular space (Tb.Sp), trabecular thickness (Tb.Th), the number of trabecular number (Tb.N), the bone surface volume ratio (bone surface/bone volume, BS/BV), structural model index (SMI). Mechanical property differences of bone tissues in different regions were calculated by micro-finite element analysis. ResultsBone mass in the elderly osteoporotic femoral head decreased, and there were significant differences in bone microstructure and mechanical properties in different regions of the femoral head. Bone microstructure and mechanical properties in medial region were obviously superior to those in lateral and interior region. Conclusions The bone structure and mechanical strength in medial region of the femoral head are obvious superior to those in lateral and inferior regions. The position for internal fixation should be fully considered during treatment of osteoporotic femoral neck fracture in clinic.

To address the increasing need for detecting and validating protein biomarkers in clinical specimens, mass spectrometry (MS)-based targeted proteomic techniques, including the selected reaction monitoring (SRM), parallel reaction monitoring (PRM), and massively parallel data-independent acquisition (DIA), have been developed. For optimal performance, they require the fragment ion spectra of targeted peptides as prior knowledge. In this report, we describe a MS pipe-line and spectral resource to support targeted proteomics studies for human tissue samples. To build the spectral resource, we integrated common open-source MS computational tools to assemble a freely accessible computational workflow based on Docker. We then applied the workflow to gen-erate DPHL, a comprehensive DIA pan-human library, from 1096 data-dependent acquisition (DDA) MS raw files for 16 types of cancer samples. This extensive spectral resource was then applied to a proteomic study of 17 prostate cancer (PCa) patients. Thereafter, PRM validation was applied to a larger study of 57 PCa patients and the differential expression of three proteins in prostate tumor was validated. As a second application, the DPHL spectral resource was applied to a study consisting of plasma samples from 19 diffuse large B cell lymphoma (DLBCL) patients and 18 healthy control subjects. Differentially expressed proteins between DLBCL patients and healthy control subjects were detected by DIA-MS and confirmed by PRM. These data demonstrate that the DPHL supports DIA and PRM MS pipelines for robust protein biomarker discovery. DPHL is freely accessible at https://www.iprox.org/page/project.html?id=IPX0001400000.