Targeted genetic screening in mice through haploid embryonic stem cells identifies critical genes in bone development.

Mutagenic screening is powerful for identifying key genes involved in developmental processes. However, such screens are successful only in lower organisms. Here, we develop a targeted genetic screening approach in mice through combining androgenetic haploid embryonic stem cells (AG-haESCs) and clustered regularly interspaced palindromic repeats/CRISPR-associated protein 9 (CRISPR-Cas9) technology. We produced a mutant semi-cloned (SC) mice pool by oocyte injection of AG-haESCs carrying constitutively expressed Cas9 and an single guide RNA (sgRNA) library targeting 72 preselected genes in one step and screened for bone-development-related genes through skeletal analysis at birth. This yielded 4 genes: Zic1 and Clec11a, which are required for bone development, and Rln1 and Irx5, which had not been previously considered. Whereas Rln1-/- mice exhibited small skeletal size only at birth, Irx5-/- mice showed skeletal abnormalities both in postnatal and adult phases due to decreased bone mass and increased bone marrow adipogenesis. Mechanistically, iroquois homeobox 5 (IRX5) promotes osteoblastogenesis and inhibits adipogenesis by suppressing peroxisome proliferator activated receptor γ (PPARγ) activation. Thus, AG-haESC-mediated functional mutagenic screening opens new avenues for genetic interrogation of developmental processes in mice.

Portable Device Improves the Detection of Atrial Fibrillation After Ablation.

Asymptomatic recurrences of atrial fibrillation (AF) have been found to be common after ablation.A randomized controlled trial of AF screening using a handheld single-lead ECG monitor (BigThumb®) or a traditional follow-up strategy was conducted in patients with non-valvular AF after catheter ablation. Consecutive patients were randomized to either BigThumb Group (BT Group) or Traditional Follow-up Group (TF Group). The ECGs collected via BigThumb were compared using the automated AF detection algorithm, artificial intelligence (AI) algorithm, and cardiologists' manual review. Subsequent changes in adherence to oral anticoagulation of patients were also recorded. In this study, we examined 218 patients (109 in each group). After a follow-up of 345.4 ± 60.2 days, AF-free survival rate was 64.2% in BT Group and 78.9% in TF Group (P = 0.0163), with more adherence to oral anticoagulation in BT Group (P = 0.0052). The participants in the BT Group recorded 26133 ECGs, among which 3299 (12.6%) were diagnosed as AF by cardiologists' manual review. The sensitivity and specificity of the AI algorithm were 94.4% and 98.5% respectively, which are significantly higher than the automated AF detection algorithm (90.7% and 96.2%).As per our findings, it was determined that follow-up after AF ablation using BigThumb leads to a more frequent detection of AF recurrence and more adherence to oral anticoagulation. AI algorithm improves the accuracy of ECG diagnosis and has the potential to reduce the manual review.

A gene-phenotype relationship extraction pipeline from the biomedical literature using a representation learning approach.

Motivation: The fundamental challenge of modern genetic analysis is to establish gene-phenotype correlations that are often found in the large-scale publications. Because lexical features of gene are relatively regular in text, the main challenge of these relation extraction is phenotype recognition. Due to phenotypic descriptions are often study- or author-specific, few lexicon can be used to effectively identify the entire phenotypic expressions in text, especially for plants. Results: We have proposed a pipeline for extracting phenotype, gene and their relations from biomedical literature. Combined with abbreviation revision and sentence template extraction, we improved the unsupervised word-embedding-to-sentence-embedding cascaded approach as representation learning to recognize the various broad phenotypic information in literature. In addition, the dictionary- and rule-based method was applied for gene recognition. Finally, we integrated one of famous information extraction system OLLIE to identify gene-phenotype relations. To demonstrate the applicability of the pipeline, we established two types of comparison experiment using model organism Arabidopsis thaliana. In the comparison of state-of-the-art baselines, our approach obtained the best performance (F1-Measure of 66.83%). We also applied the pipeline to 481 full-articles from TAIR gene-phenotype manual relationship dataset to prove the validity. The results showed that our proposed pipeline can cover 70.94% of the original dataset and add 373 new relations to expand it. Availability and implementation: The source code is available at http://www.wutbiolab.cn: 82/Gene-Phenotype-Relation-Extraction-Pipeline.zip. Supplementary information: Supplementary data are available at Bioinformatics online.

The Effects of Petroleum Hydrocarbons on Algae Can Be Reversed in the Presence of a Primary Consumer.

The ecotoxicological effects of a mixture of petroleum hydrocarbons were tested on densities of two algae, Platymonas helgolandica var. tsingtaoensis and Isochrysis galbana, and of a rotifer, Brachionus plicatilis, by single-species and customized community experiments. Test concentrations ranged from 0 to 100 mg L(-1), while five to seven treatments were assessed in triplicate within 1 month. A significant decrease in densities during single-species toxicity tests were found when concentrations of petroleum hydrocarbons were above 1.0 mg L(-1). However, equilibrium densities of algae in the customized community showed a different pattern, which increased with concentration and reached a peak at 20.0 mg L(-1). The community-based no observed effect concentration (NOEC; 1.0 mg L(-1)) was different from the NOEC derived by single-species toxic tests (0.25 mg L(-1)). This demonstrates that ecotoxicological effects on plankton as part of a community is significantly different from single-species toxicity tests owing to ecological interactions.

The effect of fear-avoidance intervention on kinesiophobia and self-efficacy in patients after percutaneous coronary intervention: study protocol for a clinical randomized controlled trial.

BACKGROUND: Kinesiophobia after percutaneous coronary intervention (PCI) may lead to decreased compliance with rehabilitation exercises. Effective interventions are essential to overcome kinesiophobia after PCI. The aim of this trial is to investigate the clinical effects of an intervention based on the fear-avoidance model (FAM) on kinesiophobia in post-PCI patients. METHODS: Eighty participants will be recruited in the Department of Cardiology in Hebei Provincial People's Hospital. And they will be randomly allocated to the test group and undergo a 5-day step-to-step intervention. The primary outcome will be the scores of a scale on kinesiophobia. Secondary outcome measures included self-efficacy for exercise, psychogenic anxiety, and the occurrence of cardiovascular adverse events. Primary and secondary outcome data will be collected at baseline (t0), on the day of discharge (t1), and one month after discharge (t2). DISCUSSION: The effectiveness of an intervention based on the FAM to increase exercise self-efficacy and decrease kinesiophobia in post-PCI patients will be demonstrated. The findings of this study will facilitate post-PCI patients to participate in cardiac rehabilitation. TRIAL REGISTRATION: ChiCTR2200065649 Effect of an intervention based on the fear-avoidance model on exercise fear in patients after percutaneous coronary intervention. Registered on November 10, 2022.

Robust Artificial Intelligence Tool for Atrial Fibrillation Diagnosis: Novel Development Approach Incorporating Both Atrial Electrograms and Surface ECG and Evaluation by Head-to-Head Comparison With Hospital-Based Physician ECG Readers.

BACKGROUND: Atrial fibrillation (AF) increases risk of embolic stroke, and in postoperative patients, increases cost of care. Consequently, ECG screening for AF in high-risk patients is important but labor-intensive. Artificial intelligence (AI) may reduce AF detection workload, but AI development presents challenges. METHODS AND RESULTS: We used a novel approach to AI development for AF detection using both surface ECG recordings and atrial epicardial electrograms obtained in postoperative cardiac patients. Atrial electrograms were used only to facilitate establishing true AF for AI development; this permitted the establishment of an AI-based tool for subsequent AF detection using ECG records alone. A total of 5 million 30-second epochs from 329 patients were annotated as AF or non-AF by expert ECG readers for AI training and validation, while 5 million 30-second epochs from 330 different patients were used for AI testing. AI performance was assessed at the epoch level as well as AF burden at the patient level. AI achieved an area under the receiver operating characteristic curve of 0.932 on validation and 0.953 on testing. At the epoch level, testing results showed means of AF detection sensitivity, specificity, negative predictive value, positive predictive value, and F1 (harmonic mean of positive predictive value and sensitivity) as 0.970, 0.814, 0.976, 0.776, and 0.862, respectively, while the intraclass correlation coefficient for AF burden detection was 0.952. At the patient level, AF burden sensitivity and positive predictivity were 96.2% and 94.5%, respectively. CONCLUSIONS: Use of both atrial electrograms and surface ECG permitted development of a robust AI-based approach to postoperative AF recognition and AF burden assessment. This novel tool may enhance detection and management of AF, particularly in patients following operative cardiac surgery.

Composition diversity and nutrition conditions for accumulation of polyhydroxyalkanoate (PHA) in a bacterial community from activated sludge.

We investigated the effect of chemical oxygen demand (COD)/N ratio on polyhydroxybutyrate (PHB) accumulating ability in an anaerobic/aerobic cycle sequential batch reactor (SBR). Compared the COD/N ratio of 10, 20, 50, and 125, the COD/N of 125 was the most suitable nutritional proportion. When COD was 1,200 mg/L and COD/N/P was 1,200/9.6/30, activated sludge PHB synthesis reached a maximum of 64.2 % of the dry weight of the cells. The population of the activated sludge was detected periodically by denaturing gradient gel electrophoresis (DGGE). The predominant strains belonged to five genera: Bacteroidetes sp., Acinetobacter sp., Betaproteobacteria sp., Gammaproteobacteria sp., Arcobacter sp., and Bacillus sp. Pyrosequencing analysis of the 16S rRNA gene indicated that the PHB synthesis community was more diverse than that was detected by DGGE, specifically Acidobacteria (12.25 %), Alphaproteobacteria (10.78 %), Actinomycetales (9.68 %), Actinobacteria (5.15 %), Proteobacteria (4.04 %), and unclassified bacteria (24.14 %).

Effect of Fasted Live-Weight Gain during the Cashmere Non-Growing Period on Cashmere Production Performance and Secondary Hair Follicle Activity of Cashmere Goats.

The objective of this study was to investigate the effects of fasted live-weight gain during the cashmere non-growing period on cashmere production performance and secondary hair follicle activity, to provide a theoretical basis for appropriate supplementary feeding of cashmere goats. Fifty Inner Mongolian cashmere goats aged 2-4 years old were randomly selected and weighed in May and September 2019, respectively. Based on fasted live-weight gain between the two weights, the experimental ewe goats were divided into two groups: 0-5.0 kg group (n = 30) and 5.0-10.0 kg group (n = 20). Skin samples and cashmere samples were collected. Results of a Pearson correlation analysis showed that fasted live-weight gain during the cashmere non-growing period had a moderate and strong positive correlation with cashmere yield (p = 0.021) and cashmere staple length (p = 0.002), respectively, but did not correlate with cashmere diameter (p = 0.254). Compared with cashmere goats with a fasted live-weight gain of 0-5.0 kg, cashmere goats with a fasted live-weight gain of 5.0-10.0 kg had a 17.10% increase in cashmere yield (p = 0.037) and an 8.09% increase in cashmere staple length (p = 0.045), but had no significant difference in cashmere diameter (p = 0.324). Results of a Pearson correlation analysis showed that there was a strong positive correlation between fasted live-weight gain and the population of active secondary hair follicles in the skin of cashmere goats (p < 0.01). Compared with cashmere goats with a fasted live-weight gain of 0-5.0 kg, cashmere goats with a fasted live-weight gain of 5.0-10.0 kg had an increase in the population of active secondary hair follicles (p < 0.05). In conclusion, the fasted live-weight gain during the cashmere non-growing period had a significant effect on secondary hair follicle activity and cashmere production performance in cashmere goats. Since fasted live-weight gain reflects nutritional level to a certain extent, this study suggests that nutritional manipulations such as supplementary feeding during cashmere non-growing periods can increase cashmere production performance. However, specific nutritional manipulations during the cashmere non-growing period need further research to increase cashmere production performance.

Skeletal stem cells: origins, definitions, and functions in bone development and disease.

Skeletal stem cells (SSCs) are tissue-specific stem cells that can self-renew and sit at the apex of their differentiation hierarchy, giving rise to mature skeletal cell types required for bone growth, maintenance, and repair. Dysfunction in SSCs is caused by stress conditions like ageing and inflammation and is emerging as a contributor to skeletal pathology, such as the pathogenesis of fracture nonunion. Recent lineage tracing experiments have shown that SSCs exist in the bone marrow, periosteum, and resting zone of the growth plate. Unraveling their regulatory networks is crucial for understanding skeletal diseases and developing therapeutic strategies. In this review, we systematically introduce the definition, location, stem cell niches, regulatory signaling pathways, and clinical applications of SSCs.

Quantitative Analysis the Weak Non-Covalent Interactions of the Polymorphs of Donepezil.

Donepezil has polymorphism. Different crystalline forms can exhibit different physicochemical properties and biological activities. Exploration of intermolecular interactions is essential to reveal the formation mechanism and differences in properties of polymorphs. This study explores the weak non-covalent intermolecular interactions of donepezil polymorphs through fully ab initio quantum mechanical methods, semi-empirical methods, and Hirshfeld surface analysis. The results show that the Hirshfeld surface analysis method can clearly and intuitively reveal the intermolecular interactions. Theoretical calculations using the atom-atom Coulomb-London-Pauli (AA-CLP) method were also performed to understand the interaction energies toward the total lattice energy. The value of the lattice energy was in accordance with the melting points of the donepezil polymorphs and brought to light the nature of thermal stability. In the specific energy distribution, the contribution of the dispersion force is the most prominent. Further interaction energy analysis found that within a distance of 3.8 Å from the center of the donepezil molecule, different crystalline forms of donepezil molecules have different interaction energies with surrounding molecules. The different interaction energies between polymorphs may lead to polymorphs with different physical-chemical properties.

An Evolving Role of Aqueous Piperazine to Improve the Solubility of Non-Steroidal Anti-Inflammatory Drugs.

Piperazine (PIP) is a pharmaceutically acceptable molecule and a good co-conformer in crystallographic engineering. Most of the non-steroidal anti-inflammatory drugs (NSAIDs) have poor aqueous solubility, which hinders their clinical application. The reports show that the solubility of many insoluble drugs can be significantly improved through salt formation with the PIP. In this work, we obtained a series of NSAIDs-PIP salts, such as ibuprofen-piperazine (IBU-0.5PIP) salt, indomethacin-piperazine (IND-0.5PIP) salt, sulindac-piperazine (SUL-0.5PIP) salt, phenylbutazone-piperazine (PBZ-0.5PIP) salt, ketoprofen-piperazine (KPF-0.5PIP) salt and flurbiprofen-piperazine (FLB-0.5PIP) salt. The spatial structure, arrangement, interaction and associations were expatiated by single crystal X-ray diffraction. Powder X-ray diffraction, Fourier transform infrared, differential scanning calorimetry, and thermogravimetric analysis were used to characterize the novel salts. The six new salts had more than 10 folds of solubility and a faster dissolution rate improved corresponding to the bulk drugs in pure water, and the significant improvement of solubility is closely related to the structure of salts.

Discovery and Application of Postnatal Nucleus Pulposus Progenitors Essential for Intervertebral Disc Homeostasis and Degeneration.

Intervertebral disc degeneration (IDD) results from the dysfunction of nucleus pulposus (NP) cells and the exhaustion of NP progenitors (ProNPs). The cellular applications of NP cells during IDD are currently limited due to the lack of in vivo studies showing whether NP cells are heterogeneous and contain ProNPs throughout postnatal stages. In this study, single-cell RNA sequencing of purified NP cells is used to map four molecularly defined populations and urotensin II receptor (UTS2R)-expressing postnatal ProNPs is identified, which are markedly exhausted during IDD, in mouse and human specimens. The lineage tracing shows that UTS2R+ ProNPs preferentially resides in the NP periphery with its niche factor tenascin-C and give rise to functional NP cells. It is also demonstrated that transplanting UTS2R+ ProNPs with tenascin-C into injured intervertebral discs attenuate the progression of IDD. The study provides a novel NP cell atlas, identified resident ProNPs with regenerative potential, and revealed promising diagnostic and therapeutic targets for IDD.

Design, Preparation, Characterization and Evaluation of Five Cocrystal Hydrates of Fluconazole with Hydroxybenzoic Acids.

To modulate the physicochemical properties of fluconazole (FLZ), a multifunctional antifungal drug, the crystal engineering technique was employed. In this paper, five novel cocrystal hydrates of FLZ with a range of phenolic acids from the GRAS list, namely, 2,4-dihydroxybenzoic acid (24DHB), 3,4-dihydroxybenzoic acid (34DHB, form I and form II), 3,5-dihydroxybenzoic acid (35DHB), and 3,4,5-trihydroxybenzoic acid (345THB) were disclosed and reported for the first time. Crystals of these five hydrates were all obtained for single-crystal X-ray diffraction (SCXRD) analysis. Robust (hydroxyl/carboxyl) O-H. . . Narom hydrogen bonds between acids and FLZ triazolyl moiety were observed to be dominant in guiding these crystal forms. The water molecule plays the role of supramolecular "linkage" in the strengthening and stabilization of these hydrates by interacting with FLZ and acids through O-H. . . O hydrogen bonds. In particular, the formation of FLZ-34DHB-H2O (1:1:1) significantly reduces hygroscopicity and hence improves the stability of FLZ, the latter of which is unstable and easily transforms into its monohydrate form. Increased initial dissolution rates were observed in the obtained cocrystal forms, and an enhanced intrinsic dissolution rate was obtained in FLZ-35DHB-H2O (1:1:1) in comparison with commercialized FLZ form II.

Design of a dual-band terahertz metamaterial absorber using two identical square patches for sensing application.

A dual-band terahertz metamaterial absorber composed of two identical square metallic patches and an insulating medium layer on top of a continuous metallic ground is demonstrated. Two resonance peaks (labeled A and B) with near 100% absorbance are obtained, of which peak A derived from the localized resonance of the two square patches has a line-width of 0.2571 THz and quality factor of 6.9156, while peak B which resulted from the hybrid coupling of the localized resonance of the two square patches and surface lattice resonance of the device has a very narrow line-width of 0.0083 THz and large quality factor of 296.2771. Narrow line-width and large quality factor have important prospects in sensing application. Based on this, the sensing performance of the device is explored; it is revealed that peak B exhibits highly sensitive sensing ability (including a sensing sensitivity of 1.9010 THz per RIU and figure of merit of 229.04) in terms of the surrounding index. In addition, the influence of structural parameters on the absorption performance is discussed to further verify the formation mechanism of these two absorption peaks.

Histone demethylase LSD1 is critical for endochondral ossification during bone fracture healing.

Bone fracture is repaired predominantly through endochondral ossification. However, the regulation of endochondral ossification by key factors during fracture healing remains largely enigmatic. Here, we identify histone modification enzyme LSD1 as a critical factor regulating endochondral ossification during bone regeneration. Loss of LSD1 in Prx1 lineage cells severely impaired bone fracture healing. Mechanistically, LSD1 tightly controls retinoic acid signaling through regulation of Aldh1a2 expression level. The increased retinoic acid signaling in LSD1-deficient mice suppressed SOX9 expression and impeded the cartilaginous callus formation during fracture repair. The discovery that LSD1 can regulate endochondral ossification during fracture healing will benefit the understanding of bone regeneration and have implications for regenerative medicine.

Tendon-derived cathepsin K-expressing progenitor cells activate Hedgehog signaling to drive heterotopic ossification.

Heterotopic ossification (HO) is pathological bone formation characterized by ossification within muscle, tendons, or other soft tissues. However, the cells of origin and mechanisms involved in the pathogenesis of HO remain elusive. Here we show that deletion of suppressor of fused (Sufu) in cathepsin K-Cre-expressing (Ctsk-Cre-expressing) cells resulted in spontaneous and progressive ligament, tendon, and periarticular ossification. Lineage tracing studies and cell functional analysis demonstrated that Ctsk-Cre could label a subpopulation of tendon-derived progenitor cells (TDPCs) marked by the tendon marker Scleraxis (Scx). Ctsk+Scx+ TDPCs are enriched for tendon stem cell markers and show the highest self-renewal capacity and differentiation potential. Sufu deficiency caused enhanced chondrogenic and osteogenic differentiation of Ctsk-Cre-expressing tendon-derived cells via upregulation of Hedgehog (Hh) signaling. Furthermore, pharmacological intervention in Hh signaling using JQ1 suppressed the development of HO. Thus, our results show that Ctsk-Cre labels a subpopulation of TDPCs contributing to HO and that their cell-fate changes are driven by activation of Hh signaling.

A gene prioritization method based on a swine multi-omics knowledgebase and a deep learning model.

The analyses of multi-omics data have revealed candidate genes for objective traits. However, they are integrated poorly, especially in non-model organisms, and they pose a great challenge for prioritizing candidate genes for follow-up experimental verification. Here, we present a general convolutional neural network model that integrates multi-omics information to prioritize the candidate genes of objective traits. By applying this model to Sus scrofa, which is a non-model organism, but one of the most important livestock animals, the model precision was 72.9%, recall 73.5%, and F1-Measure 73.4%, demonstrating a good prediction performance compared with previous studies in Arabidopsis thaliana and Oryza sativa. Additionally, to facilitate the use of the model, we present ISwine ( http://iswine.iomics.pro/ ), which is an online comprehensive knowledgebase in which we incorporated almost all the published swine multi-omics data. Overall, the results suggest that the deep learning strategy will greatly facilitate analyses of multi-omics integration in the future.

Lkb1 deletion in periosteal mesenchymal progenitors induces osteogenic tumors through mTORC1 activation.

Bone osteogenic sarcoma has a poor prognosis as the exact cell of origin and the signaling pathways underling tumor formation remain undefined. Here, we report an osteogenic tumor mouse model based on the conditional knockout of liver kinase b1 (Lkb1; also known as Stk11) in Cathepsin K (Ctsk)-Cre expressing cells. Lineage tracing studies demonstrated that Ctsk-Cre could label a population of periosteal cells. The cells functioned as mesenchymal progenitors with regard to markers and functional properties. LKB1 deficiency increased proliferation and osteoblast differentiation of Ctsk+ periosteal cells, while downregulation of mTORC1 activity, using Raptor genetic mouse model or mTORC1 inhibitor treatment, ameliorated tumor progression of Ctsk-Cre Lkb1fllfl mice. Xenograft mouse models, using human osteosarcoma cell lines, also demonstrated that LKB1 deficiency promoted tumor formation, while mTOR inhibition suppressed xenograft tumor growth. In summary, we identified periosteum-derived Ctsk-Cre expressing cells as a cell of origin for osteogenic tumor and suggested the LKB1-mTORC1 pathway as a promising target for treatment of osteogenic tumor.

Phenotype Extraction Based on Word Embedding to Sentence Embedding Cascaded Approach.

As a significant determinant in the development of named entity recognition, phenotypic descriptions are normally presented differently in biomedical literature with the use of complicated semantics. In this paper, a novel approach has been proposed to identify plant phenotypes by adopting word embedding to sentence embedding cascaded approach. We make use of a word embedding method to find high-frequency phenotypes with original sentences used as input in a sentence embedding method. In doing so, a variety of complicated phenotypic expressions can be recognized accurately. Besides, the state-of-the-art word representation models have been compared and among them, skip-gram with negative sampling was selected with the best performance. To evaluate the performance of our approach, we applied it to the dataset composed of 56 748 PubMed abstracts of model organism Arabidopsis thaliana. The experiment results showed that our approach yielded the best performance, as it achieved a 2.588-fold increase in terms of the number of new phenotypic descriptions when compared to the original phenotype ontology.

Paracrine and endocrine actions of bone-the functions of secretory proteins from osteoblasts, osteocytes, and osteoclasts.

The skeleton is a dynamic organ that is constantly remodeled. Proteins secreted from bone cells, namely osteoblasts, osteocytes, and osteoclasts exert regulation on osteoblastogenesis, osteclastogenesis, and angiogenesis in a paracrine manner. Osteoblasts secrete a range of different molecules including RANKL/OPG, M-CSF, SEMA3A, WNT5A, and WNT16 that regulate osteoclastogenesis. Osteoblasts also produce VEGFA that stimulates osteoblastogenesis and angiogenesis. Osteocytes produce sclerostin (SOST) that inhibits osteoblast differentiation and promotes osteoclast differentiation. Osteoclasts secrete factors including BMP6, CTHRC1, EFNB2, S1P, WNT10B, SEMA4D, and CT-1 that act on osteoblasts and osteocytes, and thereby influenceaA osteogenesis. Osteoclast precursors produce the angiogenic factor PDGF-BB to promote the formation of Type H vessels, which then stimulate osteoblastogenesis. Besides, the evidences over the past decades show that at least three hormones or "osteokines" from bone cells have endocrine functions. FGF23 is produced by osteoblasts and osteocytes and can regulate phosphate metabolism. Osteocalcin (OCN) secreted by osteoblasts regulates systemic glucose and energy metabolism, reproduction, and cognition. Lipocalin-2 (LCN2) is secreted by osteoblasts and can influence energy metabolism by suppressing appetite in the brain. We review the recent progresses in the paracrine and endocrine functions of the secretory proteins of osteoblasts, osteocytes, and osteoclasts, revealing connections of the skeleton with other tissues and providing added insights into the pathogenesis of degenerative diseases affecting multiple organs and the drug discovery process.