Role of Advanced Glycation End-Products and Oxidative Stress in Type-2-Diabetes-Induced Bone Fragility and Implications on Fracture Risk Stratification

Type 2 diabetes (T2D) and osteoporosis (OP) are major causes of morbidity and mortality that have arelevant health and economic burden. Recent epidemiological evidence suggests that both of these disorders are often associated with each other and that T2D patients have an increased risk of fracture, making bone an additional target of diabetes. As occurs for other diabetic complications, the increased accumulation of advanced glycation end-products (AGEs) and oxidative stress represent the major mechanisms explaining bone fragility in T2D. Both of these conditions directly and indirectly (through the promotion of microvascular complications) impair the structural ductility of bone and negatively affect bone turnover, leading to impaired bone quality, rather than decreased bone density. This makes diabetes-induced bone fragility remarkably different from other forms of OP and represents a major challenge for fracture risk stratification, since either the measurement of BMD or the use of common diagnostic algorithms for OP have a poor predictive value. We review and discuss the role of AGEs and oxidative stress on the pathophysiology of bone fragility in T2D, providing some indications on how to improve fracture risk prediction in T2D patients

Energy metabolism and ketogenic diets: What about the skeletal health? a narrative review and a prospective vision for planning clinical trials on this issue

The existence of a common mesenchymal cell progenitor shared by bone, skeletal muscle, and adipocytes cell progenitors, makes the role of the skeleton in energy metabolism no longer surprising. Thus, bone fragility could also be seen as a consequence of a “poor” quality in nutrition. Ketogenic diet was originally proven to be effective in epilepsy, and long-term follow-up studies on epileptic children undergoing a ketogenic diet reported an increased incidence of bone fractures and decreased bone mineral density. However, the causes of such negative impacts on bone health have to be better defined. In these subjects, the concomitant use of antiepileptic drugs and the reduced mobilization may partly explain the negative effects on bone health, but little is known about the effects of diet itself, and/or generic alterations in vitamin D and/or impaired growth factor production. Despite these remarks, clinical studies were adequately designed to investigate bone health are scarce and bone health related aspects are not included among the various metabolic pathologies positively influenced by ketogenic diets. Here, we provide not only a narrative review on this issue, but also practical advice to design and implement clinical studies on ketogenic nutritional regimens and bone health outcomes. Perspectives on ketogenic regimens, microbiota, microRNAs, and bone health are also included

Source Attribution of Human Campylobacteriosis Using Whole-Genome Sequencing Data and Network Analysis

Campylobacter spp. are a leading and increasing cause of gastrointestinal infections world-wide. Source attribution, which apportions human infection cases to different animal species and food reservoirs, has been instrumental in control-and evidence-based intervention efforts. The rapid increase in whole-genome sequencing data provides an opportunity for higher-resolution source attribution models. Important challenges, including the high dimension and complex structure of WGS data, have inspired concerted research efforts to develop new models. We propose network analysis models as an accurate, high-resolution source attribution approach for the sources of human campylobacteriosis. A weighted network analysis approach was used in this study for source attribution comparing different WGS data inputs. The compared model inputs consisted of cgMLST and wgMLST distance matrices from 717 human and 717 animal isolates from cattle, chickens, dogs, ducks, pigs and turkeys. SNP distance matrices from 720 human and 720 animal isolates were also used. The data were collected from 2015 to 2017 in Denmark, with the animal sources consisting of domestic and imports from 7 European countries. Clusters consisted of network nodes representing respective genomes and links representing distances between genomes. Based on the results, animal sources were the main driving factor for cluster formation, followed by type of species and sampling year. The coherence source clustering (CSC) values based on animal sources were 78%, 81% and 78% for cgMLST, wgMLST and SNP, respectively. The CSC values based on Campylobacter species were 78%, 79% and 69% for cgMLST, wgMLST and SNP, respectively. Including human isolates in the network resulted in 88%, 77% and 88% of the total human isolates being clustered with the different animal sources for cgMLST, wgMLST and SNP, respectively. Between 12% and 23% of human isolates were not attributed to any animal source. Most of the human genomes were attributed to chickens from Denmark, with an average attribution percentage of 52.8%, 52.2% and 51.2% for cgMLST, wgMLST and SNP distance matrices respectively, while ducks from Denmark showed the least attribution of 0% for all three distance matrices. The best-performing model was the one using wgMLST distance matrix as input data, which had a CSC value of 81%. Results from our study show that the weighted network-based approach for source attribution is reliable and can be used as an alternative method for source attribution considering the high performance of the model. The model is also robust across the different Campylobacter species, animal sources and WGS data types used as input

The effects of vegetarian diets on bone health: a literature review

In these recent years many people are adopting a vegetarian type diet due to the numerous positive health effects of this regimen such as the reduction of the incidence of many chronic disorders like diabetes, hypertension, obesity and cancer. However this diet is quite restrictive and so it could be possible to have a deficiency in some specific nutrients, increasing the risk of osteoporosis and fractures. Although there are conflicting results on the effects of the vegetarian diet on bone health and fracture incidence, it is always recommendable in vegetarian people to have an adequate intake of calcium and vitamin D, through an increased intake of supplements, natural and fortified foods, an adequate intake of protein, fruit, vegetables, as well as vitamin B12. The aim of this literature review is to revise the actual knowledge of the effect of some nutrients and vegetarian diets on bone health. Copyright © 2022 Falchetti, Cavati, Valenti, Mingiano, Cosso, Gennari, Chiodini and Merlotti

Bone fragility in gastrointestinal disorders

Osteoporosis is a common systemic disease of the skeleton, characterized by compromised bone mass and strength, consequently leading to an increased risk of fragility fractures. In women, the disease mainly occurs due to the menopausal fall in estrogen levels, leading to an imbalance between bone resorption and bone formation and, consequently, to bone loss and bone fragility. Moreover, osteoporosis may affect men and may occur as a sequela to different diseases or even to their treatments. Despite their wide prevalence in the general population, the skeletal implications of many gastrointestinal diseases have been poorly investigated and their potential contribution to bone fragility is often underestimated in clinical practice. However, proper functioning of the gastrointestinal system appears essential for the skeleton, allowing correct absorption of calcium, vitamins, or other nutrients relevant to bone, preserving the gastrointestinal barrier function, and maintaining an optimal endocrine-metabolic balance, so that it is very likely that most chronic diseases of the gastrointestinal tract, and even gastrointestinal dysbiosis, may have profound implications for bone health. In this manuscript, we provide an updated and critical revision of the role of major gastrointestinal disorders in the pathogenesis of osteoporosis and fragility fractures. © 2022 by the authors. Licensee MDPI, Basel, Switzerland

Prediction of Overall Survival in Cervical Cancer Patients Using PET/CT Radiomic Features

Background: Radiomics is a field of research medicine and data science in which quantitative imaging features are extracted from medical images and successively analyzed to develop models for providing diagnostic, prognostic, and predictive information. The purpose of this work was to develop a machine learning model to predict the survival probability of 85 cervical cancer patients using PET and CT radiomic features as predictors. Methods: Initially, the patients were divided into two mutually exclusive sets: a training set containing 80% of the data and a testing set containing the remaining 20%. The entire analysis was separately conducted for CT and PET features. Genetic algorithms and LASSO regression were used to perform feature selection on the initial PET and CT feature sets. Two different survival models were employed: the Cox proportional hazard model and random survival forest. The Cox model was built using the subset of features obtained with the feature selection process, while all the available features were used for the random survival forest model. The models were trained on the training set; cross-validation was used to fine-tune the models and to obtain a preliminary measurement of the performance. The models were then validated on the test set, using the concordance index as the metric. In addition, alternative versions of the models were developed using tumor recurrence as an adjunct feature to evaluate its impact on predictive performance. Finally, the selected CT and PET features were combined to build a further Cox model. Results: The genetic algorithm was superior to the LASSO regression for feature selection. The best performing model was the Cox model, which was built using the selected CT features; it achieved a concordance index score of 0.707. With the addition of tumor recurrence as a predictive feature, the Cox CT model reached a concordance index score of 0.776. PET features, however, proved to be inadequate for survival prediction. The CT model performed better than the model with combined PET and CT features. Conclusions: The results showed that radiomic features can be used to successfully predict survival probability in cervical cancer patients. In particular, CT radiomic features proved to be better predictors than PET radiomic features in this specific case

Pathophysiology and Management of Type 2 Diabetes Mellitus Bone Fragility

Individuals with type 2 diabetes mellitus (T2DM) have an increased risk of bone fragility fractures compared to nondiabetic subjects. This increased fracture risk may occur despite normal or even increased values of bone mineral density (BMD), and poor bone quality is suggested to contribute to skeletal fragility in this population. These concepts explain why the only evaluation of BMD could not be considered an adequate tool for evaluating the risk of fracture in the individual T2DM patient. Unfortunately, nowadays, the bone quality could not be reliably evaluated in the routine clinical practice. On the other hand, getting further insight on the pathogenesis of T2DM-related bone fragility could consent to ameliorate both the detection of the patients at risk for fracture and their appropriate treatment. The pathophysiological mechanisms underlying the increased risk of fragility fractures in a T2DM population are complex. Indeed, in T2DM, bone health is negatively affected by several factors, such as inflammatory cytokines, muscle-derived hormones, incretins, hydrogen sulfide (H2S) production and cortisol secretion, peripheral activation, and sensitivity. All these factors may alter bone formation and resorption, collagen formation, and bone marrow adiposity, ultimately leading to reduced bone strength. Additional factors such as hypoglycemia and the consequent increased propensity for falls and the direct effects on bone and mineral metabolism of certain antidiabetic medications may contribute to the increased fracture risk in this population. The purpose of this review is to summarize the literature evidence that faces the pathophysiological mechanisms underlying bone fragility in T2DM patients