Women have lower areal BMD (g/cm2) than men; however, the women have smaller-size bones. Our study showed that women ≤ 59 years have a hip volumetric BMD by DXA 3D similar to that of men of the same age. This makes us think about the importance of taking into account bone size at the time of analyzing the sex-related differences in bone mass. Women have lower areal BMD (g/cm ) than men; however, these studies do not take into account that women have smaller-size bones. Recently, three-dimensional (3D) modeling methods were proposed to analyze volumetric BMD (vBMD). We want to determine the values of vBMD at the hip by DXA-based 3D modeling in a cohort of people in order to know the age- and sex-related differences. A total of 2647 people of both sexes (65% women) were recruited from a large cohort (Camargo cohort, Santander, Spain). 3D-SHAPER® software (version 2.8, Galgo Medical, Barcelona, Spain) was used to derive 3D analysis from the hip DXA scans at baseline RESULTS The differences were less pronounced for vBMD (cortical sBMD 9.3%, trabecular vBMD 6.4%, integral vBMD 2.2%) compared to aBMD (FN aBMD 11.4% and TH aBMD 13.3%). After stratifying by age (≤ 59 years, 60-69 years, 70-79 years, and ≥ 80 years), we observed in ≤ 59 years that aBMD was lower in women compared to men, at FN (0.758 [0.114] g/cm vs. 0.833 [0.117] g/cm ; p = 1.4 × 10 ) and TH (0.878 [0.117] g/cm vs. 0.990 [0.119] g/cm ; p = 4.1 × 10 ). Nevertheless, no statistically significant difference was observed for integral vBMD (331 [58] mg/cm in women and 326 [51] mg/cm in men; p = 0.19) and trabecular vBMD (190 [41] mg/cm in women and 195 [39] mg/cm in men; p = 0.20). Our results make us think about the importance of taking into account bone size at the time of analyzing the sex-related differences in bone mass.Our results make us think about the importance of taking into account bone size at the time of analyzing the sex-related differences in bone mass.Metabolic reprogramming is a hallmark of cancer metastasis in which cancer cells manipulate their metabolic profile to meet the dynamic energetic requirements of the tumor microenvironment. Though cancer cell proliferation and migration through the extracellular matrix are key steps of cancer progression, they are not necessarily fueled by the same metabolites and energy production pathways. The two main metabolic pathways cancer cells use to derive energy from glucose, glycolysis and oxidative phosphorylation, are preferentially and plastically utilized by cancer cells depending on both their intrinsic metabolic properties and their surrounding environment. Mechanical factors in the microenvironment, such as collagen density, pore size, and alignment, and biochemical factors, such as oxygen and glucose availability, have been shown to influence both cell migration and glucose metabolism. As cancer cells have been identified as preferentially utilizing glycolysis or oxidative phosphorylation based on heterogeneous intrinsic or extrinsic factors, the relationship between cancer cell metabolism and metastatic potential is of recent interest. Here, we review current in vitro and in vivo findings in the context of cancer cell metabolism during migration and metastasis and extrapolate potential clinical applications of this work that could aid in diagnosing and tracking cancer progression in vivo by monitoring metabolism. We also review current progress in the development of a variety of metabolically targeted anti-metastatic drugs, both in clinical trials and approved for distribution, and highlight potential routes for incorporating our recent understanding of metabolic plasticity into therapeutic directions. Subasumstat in vitro By further understanding cancer cell energy production pathways and metabolic plasticity, more effective and successful clinical imaging and therapeutics can be developed to diagnose, target, and inhibit metastasis. Eradication of Helicobacter pylori (H. pylori) could not completely prevent the progression of gastric cancer (GC), suggesting that non-H. pylori bacteria may participate in the carcinogenesis of GC. The dysbiosis of microbiota in the stomach of GC has gradually been investigated, while the detailed mechanism that promotes GC in this process has not been elucidated. We aimed to identify a non-H. pylori bacteria that contribute to GC. GC tissues and adjacent normal tissues were collected to identify bacteria that significantly increased in GC tissues by 16S rRNA gene sequencing and fluorescence in situ hybridization (FISH) analysis. CCK8, wound healing assay, and trans-well assay were performed to analyze the tumor-promoting effect of this bacteria. Next, we detailed the mechanism for tumor-promoting effect of the bacteria by immunofluorescence, RT-qPCR, and western-blotting analysis. Comparing the microbial community from GC tissues and adjacent normal tissues, we found that Propionibacterium acnes (P. acnes) significantly increased in GC tissues, especially in H. pylori-negative tissues. We further found that the abundance of P. acnes correlated with TNM stages of GC patients. Interestingly, condition medium (CM) from P. acnes-primed macrophages promoted migration of GC cells, while P. acnes only could not. We next proved that P. acnes triggers M2 polarization of macrophages via TLR4/PI3K/Akt signaling. Together, our finding identified that P. acnes could be a possible agent for the progression of GC besides H. pylori. M2 polarization of macrophages could be promoted by P. acnes via TLR4/PI3K/Akt signaling, thus triggers the progression of GC.Together, our finding identified that P. acnes could be a possible agent for the progression of GC besides H. pylori. M2 polarization of macrophages could be promoted by P. acnes via TLR4/PI3K/Akt signaling, thus triggers the progression of GC.The optimal neuromuscular control (muscle activation strategy that minimises the consumption of metabolic energy) during level walking is very close to that which minimises the force transmitted through the joints of the lower limbs. Thus, any suboptimal control involves an overloading of the joints. Some total knee replacement patients adopt suboptimal control strategies during level walking; this is particularly true for patients with co-morbidities that cause neuromotor control degeneration, such as Parkinson's Disease (PD). The increase of joint loading increases the risk of implant failure, as reported in one study in PD patients (5.44% of failures at 9 years follow-up). One failure mode that is directly affected by joint loading is massive wear of the prosthetic articular surface. In this study we used a validated patient-specific biomechanical model to estimate how a severely suboptimal control could increase the wear rate of total knee replacements. Whereas autopsy-retrieved implants from non-PD patients typically show average polyethylene wear of 17 mm3 per year, our simulations suggested that a severely suboptimal control could cause a wear rate as high as of 69 mm3 per year.