Raman Spectroscopic Analysis to Detect Reduced Bone Quality after Sciatic Neurectomy in Mice

Bone mineral density (BMD) is a commonly used diagnostic indicator for bone fracture risk in osteoporosis. Along with low BMD, bone fragility accounts for reduced bone quality in addition to low BMD, but there is no diagnostic method to directly assess the bone quality. In this study, we investigated changes in bone quality using the Raman spectroscopic technique. Sciatic neurectomy (NX) was performed in male C57/BL6J mice (NX group) as a model of disuse osteoporosis, and sham surgery was used as an experimental control (Sham group). Eight months after surgery, we acquired Raman spectral data from the anterior cortical surface of the proximal tibia. We also performed a BMD measurement and micro-CT measurement to investigate the pathogenesis of osteoporosis. Quantitative analysis based on the Raman peak intensities showed that the carbonate/phosphate ratio and the mineral/matrix ratio were significantly higher in the NX group than in the Sham group. There was direct evidence of alterations in the mineral content associated with mechanical properties of bone. To fully understand the spectral changes, we performed principal component analysis of the spectral dataset, focusing on the matrix content. In conclusion, Raman spectroscopy provides reliable information on chemical changes in both mineral and matrix contents, and it also identifies possible mechanisms of disuse osteoporosis.

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DIAGNOSIS OF ENDOCRINE DISEASE: Evaluation of bone fragility in endocrine disorders

Acta Endocrinologica ◽

10.1530/eje-18-0991 ◽

2019 ◽

Vol 180 (6) ◽

pp. R213-R232 ◽

Cited By ~ 11

Author(s):

Cristina Eller-Vainicher ◽

Alberto Falchetti ◽

Luigi Gennari ◽

Elisa Cairoli ◽

Francesco Bertoldo ◽

...

Keyword(s):

Bone Density ◽

Fracture Risk ◽

Bone Quality ◽

Risk Estimation ◽

Underlying Disease ◽

Bone Fragility ◽

Endocrine Disorders ◽

Mineral Density ◽

Endocrine Diseases ◽

Density Evaluation

An underlying disease affecting bone health is present in up to 40 and 60% of osteoporotic postmenopausal women and men respectively. Among the disorders leading to a secondary form of osteoporosis, the endocrine diseases are highly represented. A frequent finding in patients affected with an endocrine-related forms of bone disease is that the skeletal fragility is partially independent of the bone density, since the fracture risk in these patients is related more to a reduction of bone quality than to a decrease of bone mass. As a consequence, bone mineral density evaluation by dual-X-ray absorptiometry may be inadequate for establishing the risk of fracture in the setting of the endocrine-related forms of osteoporosis. In the recent years, several attempts to non-invasively estimating bone quality have been done. Nowadays, some new tools are available in the clinical practice for optimising the fracture risk estimation in patients with endocrine disorders. The aim of this review is to summarise the evidence regarding the role of the different imaging tools for evaluating bone density and bone quality in the most frequent forms of endocrine-related osteoporosis, such as obesity, diabetes, acromegaly, thyrotoxicosis, primary hyperparathyroidism, hypercortisolism and hypogonadism. For each of these disorders, data regarding both the current available tools and the future possible new techniques for assessing bone fragility in patients with endocrine diseases are reported.

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Liraglutide Inhibits Osteoclastogenesis and Improves Bone Loss by Downregulating Trem2 in Female Type 1 Diabetic Mice: Findings From Transcriptomics

Frontiers in Endocrinology ◽

10.3389/fendo.2021.763646 ◽

2021 ◽

Vol 12 ◽

Author(s):

Jie Yu ◽

Yan-Chuan Shi ◽

Fan Ping ◽

Wei Li ◽

Hua-Bing Zhang ◽

...

Keyword(s):

Gene Expression ◽

Bone Loss ◽

Bone Quality ◽

Normal Glucose Tolerance ◽

Bone Fragility ◽

Protective Effects ◽

Mineral Density ◽

Normal Glucose ◽

Glucagon Like Peptide 1

BackgroundThe mechanisms of bone fragility in type 1 diabetes (T1D) are not fully understood. Whether glucagon-like peptide-1 receptor (GLP-1R) agonists could improve bone quality in T1D context also remains elusive.AimsWe aimed to explore the possible mechanisms of bone loss in T1D and clarify whether liraglutide has effects on bone quality of T1D mice using transcriptomics.MethodsFemale streptozotocin-induced diabetic C57BL/6J mice were randomly divided into four groups and received the following treatments daily for 8 weeks: saline as controls, insulin, liraglutide, and liraglutide combined with insulin. These groups were also compared with non-STZ-treated normal glucose tolerance (NGT) group. Trunk blood and bone tissues were collected for analysis. Three tibia from each of the NGT, saline-treated, and liraglutide-treated groups were randomly selected for transcriptomics.ResultsCompared with NGT mice, saline-treated T1D mice manifested markedly hyperglycemia and weight loss, and micro-CT revealed significantly lower bone mineral density (BMD) and deficient microarchitectures in tibias. Eight weeks of treatment with liraglutide alone or combined with insulin rescued the decreased BMD and partly corrected the compromised trabecular microarchitectures. Transcriptomics analysis showed there were 789 differentially expressed genes mainly mapped to osteoclastogenesis and inflammation pathways. The RT-qPCR verified that the gene expression of Trem2, Nfatc1, Trap, and Ctsk were significantly increased in the tibia of T1D compared with those in the NGT group. Liraglutide treatment alone or combined with insulin could effectively suppress osteoclastogenesis by downregulating the gene expression of Trem2, Nfatc1, Ctsk, and Trap.ConclusionsTaken together, increased osteoclastogenesis with upregulated expression of Trem2 played an important role in bone loss of T1D mice. Liraglutide provided protective effects on bone loss in T1D mice by suppressing osteoclastogenesis.

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Osseointegration of Dental Implants and Osteoporosis

10.5772/intechopen.100270 ◽

2021 ◽

Author(s):

Sara Gibreel ◽

Hasaan Gassim Mohamed ◽

Amartya Raj Suraj ◽

Sukumaran Anil

Keyword(s):

Dental Implants ◽

Dental Implant ◽

Bone Quality ◽

Bone Fragility ◽

Bisphosphonate Therapy ◽

Mineral Density ◽

Implant Placement ◽

Antiresorptive Agents ◽

Implant Therapy ◽

Maxilla And Mandible

Osteoporosis is a disease characterized by low bone mass and microarchitectural deterioration of bone tissue, leading to enhanced bone fragility and susceptibility to fractures. Osteoporosis also results in loss of bone mineral density throughout the body, including the maxilla and mandible. Successful osseointegration of dental implants is attributed to their ability to integrate well with bone. The influence of bone quality on dental implant osseointegration has been discussed in several studies, and higher rates of dental implant failure have been reported in patients with low bone quality and an inadequate bone volume. Osteoporosis represents a risk factor for osseointegration, and this relationship may be derived from the association of the disease with a deficiency in bone formation. This condition would compromise the healing capacity and the apposition of bone at the implant interface. Currently, there is no clear consensus regarding dental implant treatment in osteoporotic individuals. Studies have revealed contradictory reports regarding the success and failure of dental implants in patients with osteoporosis. Antiresorptive agents have been widely used to treat osteoporosis. Dental implant placement in patients on bisphosphonate therapy may trigger osteonecrosis of the bone. Hence, it is important to analyze factors that have to be taken into consideration prior to implant therapy in patients with osteoporosis and those undergoing treatment. This chapter outlines dental implant osseointegration under osteoporotic conditions. The possible effect of bisphosphonate therapy on dental implant survival will also be discussed based on the current literature.

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Development of diabetes-sensitive fracture resistance analysis using finite element method to predict diabetic bone fragility and bone quality

Bone Reports ◽

10.1016/j.bonr.2021.100883 ◽

2021 ◽

Vol 14 ◽

pp. 100883

Author(s):

Cemre Yavuz ◽

Eva Maria Wölfel ◽

Katharina Jähn-Rickert ◽

Herbert Mushumba ◽

Birgit Wulff ◽

...

Keyword(s):

Finite Element Method ◽

Finite Element ◽

Bone Quality ◽

Fracture Resistance ◽

Bone Fragility ◽

Resistance Analysis ◽

Element Method

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Raman Spectral Signatures of Serum-Derived Extracellular Vesicle-Enriched Isolates May Support the Diagnosis of CNS Tumors

Cancers ◽

10.3390/cancers13061407 ◽

2021 ◽

Vol 13 (6) ◽

pp. 1407

Author(s):

Matyas Bukva ◽

Gabriella Dobra ◽

Juan Gomez-Perez ◽

Krisztian Koos ◽

Maria Harmati ◽

...

Keyword(s):

Lumbar Disc ◽

Area Under The Curve ◽

Principal Component ◽

Extracellular Vesicle ◽

Classification Performance ◽

Cns Tumors ◽

Clinical Samples ◽

Support Vector ◽

Serum Samples ◽

Raman Spectroscopic

Investigating the molecular composition of small extracellular vesicles (sEVs) for tumor diagnostic purposes is becoming increasingly popular, especially for diseases for which diagnosis is challenging, such as central nervous system (CNS) malignancies. Thorough examination of the molecular content of sEVs by Raman spectroscopy is a promising but hitherto barely explored approach for these tumor types. We attempt to reveal the potential role of serum-derived sEVs in diagnosing CNS tumors through Raman spectroscopic analyses using a relevant number of clinical samples. A total of 138 serum samples were obtained from four patient groups (glioblastoma multiforme, non-small-cell lung cancer brain metastasis, meningioma and lumbar disc herniation as control). After isolation, characterization and Raman spectroscopic assessment of sEVs, the Principal Component Analysis–Support Vector Machine (PCA–SVM) algorithm was performed on the Raman spectra for pairwise classifications. Classification accuracy (CA), sensitivity, specificity and the Area Under the Curve (AUC) value derived from Receiver Operating Characteristic (ROC) analyses were used to evaluate the performance of classification. The groups compared were distinguishable with 82.9–92.5% CA, 80–95% sensitivity and 80–90% specificity. AUC scores in the range of 0.82–0.9 suggest excellent and outstanding classification performance. Our results support that Raman spectroscopic analysis of sEV-enriched isolates from serum is a promising method that could be further developed in order to be applicable in the diagnosis of CNS tumors.

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Effect of Age on Bone Structure Parameters in Laying Hens

Animals ◽

10.3390/ani11020570 ◽

2021 ◽

Vol 11 (2) ◽

pp. 570

Author(s):

Masayoshi Yamada ◽

Chongxiao Chen ◽

Toshie Sugiyama ◽

Woo Kyun Kim

Keyword(s):

Cortical Bone ◽

Bone Quality ◽

Bone Mineral ◽

Volume Fraction ◽

Bone Structure ◽

Bone Volume ◽

Egg Laying ◽

Medullary Bone ◽

Mineral Density ◽

Tibial Diaphysis

Changes in medullary and cortical bone structure with age remain unclear. Twenty Hy-Line W36 hens, 25 or 52 weeks of age, were euthanized, and both tibiae were collected when an egg was present in the magnum. Serial cross sections of the tibiae were stained with Alcian blue. The bones were scanned using micro-computed tomography. Trabecular width (Tb.Wi) was significantly higher (p < 0.05) in 25-week-old hens, whereas medullary bone tissue volume (TV) was significantly higher (p < 0.01) in 52-week-old hens. 25-week-old hens had significantly higher (p < 0.01) bone volume fraction (BVF = calcified tissue / TV). Moreover, the cortical bone parameters were significantly higher (TV and bone mineral content (BMC) at p < 0.05, and bone volume (BV) and BVF at p < 0.01) in younger hens. Open porosity and total porosity, which indicate less density, were significantly higher (p < 0.01) in older hens. Older hens showed significantly higher (p < 0.01) tibial diaphysis TV than younger hens. Younger hens had significantly higher (p < 0.01) BV, BVF and bone mineral density (BMD) of the tibial diaphysis. These findings reveal that reductions in medullary bone quality might be associated with age-related low estrogen levels and stimulation of osteoclastic bone resorption by parathyroid hormone. Cortical bone quality decreased with enlargement of the Haversian canals and loss of volume, with a longer egg-laying period leading to osteoporosis.

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MECHANISMS IN ENDOCRINOLOGY: Mechanisms and evaluation of bone fragility in type 1 diabetes mellitus

Acta Endocrinologica ◽

10.1530/eje-15-0820 ◽

2016 ◽

Vol 174 (4) ◽

pp. R127-R138 ◽

Cited By ~ 66

Author(s):

F S Hough ◽

D D Pierroz ◽

C Cooper ◽

S L Ferrari ◽

_ _

Keyword(s):

Diabetes Mellitus ◽

Type 1 Diabetes ◽

Type 1 Diabetes Mellitus ◽

Bone Fragility ◽

Mineral Density ◽

Good Glycaemic Control ◽

Marrow Adiposity ◽

Igf1 Deficiency

Subjects with type 1 diabetes mellitus (T1DM) have decreased bone mineral density and an up to sixfold increase in fracture risk. Yet bone fragility is not commonly regarded as another unique complication of diabetes. Both animals with experimentally induced insulin deficiency syndromes and patients with T1DM have impaired osteoblastic bone formation, with or without increased bone resorption. Insulin/IGF1 deficiency appears to be a major pathogenetic mechanism involved, along with glucose toxicity, marrow adiposity, inflammation, adipokine and other metabolic alterations that may all play a role on altering bone turnover. In turn, increasing physical activity in children with diabetes as well as good glycaemic control appears to provide some improvement of bone parameters, although robust clinical studies are still lacking. In this context, the role of osteoporosis drugs remains unknown.

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Variety Identification of Orchids Using Fourier Transform Infrared Spectroscopy Combined with Stacked Sparse Auto-Encoder

Molecules ◽

10.3390/molecules24132506 ◽

2019 ◽

Vol 24 (13) ◽

pp. 2506 ◽

Cited By ~ 1

Author(s):

Yunfeng Chen ◽

Yue Chen ◽

Xuping Feng ◽

Xufeng Yang ◽

Jinnuo Zhang ◽

...

Keyword(s):

Fourier Transform ◽

Principal Component ◽

Fourier Transform Infrared ◽

Spectroscopic Technique ◽

Variety Identification ◽

Support Vector ◽

K Nearest Neighbors ◽

Discriminant Models ◽

The Fourier Transform ◽

Better Than

The feasibility of using the fourier transform infrared (FTIR) spectroscopic technique with a stacked sparse auto-encoder (SSAE) to identify orchid varieties was studied. Spectral data of 13 orchids varieties covering the spectral range of 4000–550 cm−1 were acquired to establish discriminant models and to select optimal spectral variables. K nearest neighbors (KNN), support vector machine (SVM), and SSAE models were built using full spectra. The SSAE model performed better than the KNN and SVM models and obtained a classification accuracy 99.4% in the calibration set and 97.9% in the prediction set. Then, three algorithms, principal component analysis loading (PCA-loading), competitive adaptive reweighted sampling (CARS), and stacked sparse auto-encoder guided backward (SSAE-GB), were used to select 39, 300, and 38 optimal wavenumbers, respectively. The KNN and SVM models were built based on optimal wavenumbers. Most of the optimal wavenumbers-based models performed slightly better than the all wavenumbers-based models. The performance of the SSAE-GB was better than the other two from the perspective of the accuracy of the discriminant models and the number of optimal wavenumbers. The results of this study showed that the FTIR spectroscopic technique combined with the SSAE algorithm could be adopted in the identification of the orchid varieties.

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