Mechanical induction of osteoanabolic Wnt1 promotes osteoblast differentiation via Plat.

Physical activity-induced mechanical stimuli play a crucial role in preserving bone mass and structure by promoting bone formation. While the Wnt pathway is pivotal for mediating the osteoblast response to loading, the exact mechanisms are not fully understood. Here, we found that mechanical stimulation induces osteoblastic Wnt1 expression, resulting in an upregulation of key osteogenic marker genes, including Runx2 and Sp7, while Wnt1 knockdown using siRNA prevented these effects. RNAseq analysis identified Plat as a major target through which Wnt1 exerts its osteogenic influence. This was corroborated by Plat depletion using siRNA, confirming its positive role in osteogenic differentiation. Moreover, we demonstrated that mechanical stimulation enhances Plat expression, which, in turn leads to increased expression of osteogenic markers like Runx2 and Sp7. Notably, Plat depletion by siRNA prevented this effect. We have established that Wnt1 regulates Plat expression by activating ß-Catenin. Silencing Wnt1 impairs mechanically induced ß-Catenin activation, subsequently reducing Plat expression. Furthermore, our findings showed that Wnt1 is essential for osteoblasts to respond to mechanical stimulation and induce Runx2 and Sp7 expression, in part through the Wnt1/ß-Catenin/Plat signaling pathway. Additionally, we observed significantly reduced Wnt1 and Plat expression in bones from ovariectomy (OVX)-induced and age-related osteoporotic mouse models compared with non-OVX and young mice, respectively. Overall, our data suggested that Wnt1 and Plat play significant roles in mechanically induced osteogenesis. Their decreased expression in bones from OVX and aged mice highlights their potential involvement in post-menopausal and age-related osteoporosis, respectively.

Why Animal Experiments Are Still Indispensable in Bone Research: A Statement by the European Calcified Tissue Society.

Major achievements in bone research have always relied on animal models and in vitro systems derived from patient and animal material. However, the use of animals in research has drawn intense ethical debate and the complete abolition of animal experimentation is demanded by fractions of the population. This phenomenon is enhanced by the reproducibility crisis in science and the advance of in vitro and in silico techniques. 3D culture, organ-on-a-chip, and computer models have improved enormously over the last few years. Nevertheless, the overall complexity of bone tissue cross-talk and the systemic and local regulation of bone physiology can often only be addressed in entire vertebrates. Powerful genetic methods such as conditional mutagenesis, lineage tracing, and modeling of the diseases enhanced the understanding of the entire skeletal system. In this review endorsed by the European Calcified Tissue Society (ECTS), a working group of investigators from Europe and the US provides an overview of the strengths and limitations of experimental animal models, including rodents, fish, and large animals, as well the potential and shortcomings of in vitro and in silico technologies in skeletal research. We propose that the proper combination of the right animal model for a specific hypothesis and state-of-the-art in vitro and/or in silico technology is essential to solving remaining important questions in bone research. This is crucial for executing most efficiently the 3R principles to reduce, refine, and replace animal experimentation, for enhancing our knowledge of skeletal biology, and for the treatment of bone diseases that affect a large part of society. © 2023 The Authors. Journal of Bone and Mineral Research published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research (ASBMR).

Formulation and Optimization of Repaglinide Nanoparticles Using Microfluidics for Enhanced Bioavailability and Management of Diabetes.

The technologies for fabrication of nanocrystals have an immense potential to improve solubility of a variety of the poor water-soluble drugs with subsequent enhanced bioavailability. Repaglinide (Rp) is an antihyperglycemic drug having low bioavailability due to its extensive first-pass metabolism. Microfluidics is a cutting-edge technique that provides a new approach for producing nanoparticles (NPs) with controlled properties for a variety of applications. The current study's goal was to engineer repaglinide smart nanoparticles (Rp-Nc) utilizing microfluidic technology (Dolomite Y shape), and then to perform in-vitro, in-vivo, and toxicity evaluations of them. This method effectively generated nanocrystals with average particle sizes of 71.31 ± 11 nm and a polydispersity index (PDI) of 0.072 ± 12. The fabricated Rp's crystallinity was verified by Differential scanning calorimetry (DSC) and Powder X-ray diffraction (PXRD). In comparison to the raw and commercially available tablets, the fabricated Rp's nanoparticles resulted in a higher saturation solubility and dissolving rate (p < 0.05). Rp nanocrystals had a considerably lower (p < 0.05) IC50 value than that of the raw drug and commercial tablets. Moreover, Rp nanocrystals at the 0.5 and 1 mg/kg demonstrated a significant decrease in blood glucose level (mg/dL, p < 0.001, n = 8) compared to its counterparts. Rp nanocrystals at the 0.5 mg/kg demonstrated a significant decrease (p < 0.001, n = 8) in blood glucose compared to its counterparts at a dose of 1 mg/kg. The selected animal model's histological analyses and the effect of Rp nanocrystals on several internal organs were determined to be equivalent to those of the control animal group. The findings of the present study indicated that nanocrystals of Rp with improved anti-diabetic properties and safety profiles can be successfully produced using controlled microfluidic technology, an innovative drug delivery system (DDS) approach.

Facial expression recognition using lightweight deep learning modeling.

Facial expression is a type of communication and is useful in many areas of computer vision, including intelligent visual surveillance, human-robot interaction and human behavior analysis. A deep learning approach is presented to classify happy, sad, angry, fearful, contemptuous, surprised and disgusted expressions. Accurate detection and classification of human facial expression is a critical task in image processing due to the inconsistencies amid the complexity, including change in illumination, occlusion, noise and the over-fitting problem. A stacked sparse auto-encoder for facial expression recognition (SSAE-FER) is used for unsupervised pre-training and supervised fine-tuning. SSAE-FER automatically extracts features from input images, and the softmax classifier is used to classify the expressions. Our method achieved an accuracy of 92.50% on the JAFFE dataset and 99.30% on the CK+ dataset. SSAE-FER performs well compared to the other comparative methods in the same domain.

Frequency and Antibiotics Sensitivity Pattern of Culture-Positive Salmonella Typhi in Children.

OBJECTIVE: To calculate the frequency of positive blood culture in clinically diagnosed cases of enteric fever and antibiotic sensitivity patterns in culture-positive cases of S.typhi Study Design: Observational Study. Place and Duration of the Study: Department of Paediatrics Medicine, Services Hospital Lahore, from November 15th 2020 to May 15th 2021. METHODOLOGY: A total of 246 patients, fulfilling the definition of a suspected case of enteric fever were enrolled. Blood cultures were drawn on the spot. Antimicrobial sensitivity for 8 antimicrobial agents-Ampicillin, amoxicillin, chloramphenicol, cefixime, ceftriaxone, cefotaxime, ciprofloxacin, meropenem, and Azithromycin, were performed. A p-value of <0.05 was considered statistically significant. RESULTS: Blood cultures were positive in 62 (25.2%), patients out of which 34 (54.9%) were females and 28 (45.1%) were males, of which, 58 were S. typhi and 4 were S. Paratyphi A or B. Cefixime was sensitive in 27.4% of patients and intermediate sensitivity was found in 3.2% of cases and 69.4% of cases were resistant, ceftriaxone was sensitive in 38.7% of cases and Azithromycin was sensitive in 96.7% of cases, whereas meropenem showed 100% sensitivity. Chloramphenicol and Ciprofloxacin were resistant in 80.6% and 27.3% of the cases respectively. Among isolates, 32.3% (20) were categorised as sensitive enteric fever; 64.5% (40) as MDR, and 3.2% (2) as XDR enteric fever. CONCLUSION: MDR and XDR enteric fever are a major concern. For such cases, Azithromycin remains the best oral antibiotic with a sensitivity of up to 96.7%. Meropenem was sensitive in 100% of cases and was the only antibiotic with no documented resistance in this study. KEY WORDS: Enteric fever, Salmonella, Antibiotic sensitivity, Blood culture, MDR, XDR, Azithromycin, Meropenem.

Wnt1 Boosts Fracture Healing by Enhancing Bone Formation in the Fracture Callus.

Despite considerable improvement in fracture care, 5%-10% of all fractures still heal poorly or result in nonunion formation. Therefore, there is an urgent need to identify new molecules that can be used to improve bone fracture healing. One activator of the Wnt-signaling cascade, Wnt1, has recently gained attention for its intense osteoanabolic effect on the intact skeleton. The aim of the present study was to investigate whether Wnt1 might be a promising molecule to accelerate fracture healing both in skeletally healthy and osteoporotic mice that display a diminished healing capacity. Transgenic mice for a temporary induction of Wnt1 specifically in osteoblasts (Wnt1-tg) were subjected to femur osteotomy. Non-ovariectomized and ovariectomized Wnt1-tg mice displayed significantly accelerated fracture healing based on a strong increase in bone formation in the fracture callus. Transcriptome profiling revealed that Hippo/yes1-associated transcriptional regulator (YAP)-signaling and bone morphogenetic protein (BMP) signaling pathways were highly enriched in the fracture callus of Wnt1-tg animals. Immunohistochemical staining confirmed increased activation of YAP1 and expression of BMP2 in osteoblasts in the fracture callus. Therefore, our data indicate that Wnt1 boosts bone formation during fracture healing via YAP/BMP signaling both under healthy and osteoporotic conditions. To further test a potential translational application of Wnt1, we applied recombinant Wnt1 embedded into a collagen gel during critical-size bone-defect repair. Mice treated with Wnt1 displayed increased bone regeneration compared to control mice accompanied by increased YAP1/BMP2 expression in the defect area. These findings are of high clinical relevance because they indicate that Wnt1 could be used as a new therapeutic agent to treat orthopedic complications in the clinic. © 2023 The Authors. Journal of Bone and Mineral Research published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research (ASBMR).

Downregulation of the Autism Spectrum Disorder Gene Shank2 Decreases Bone Mass in Male Mice.

Mutations of the postsynaptic scaffold protein Shank2 lead to autism spectrum disorders (ASD). These patients frequently suffer from higher fracture risk. Here, we investigated whether Shank2 directly regulates bone mass. We show that Shank2 is expressed in bone and that Shank2 levels are increased during osteoblastogenesis. Knockdown of Shank2 by siRNA targeting the encoding regions for PDZ and SAM domain inhibits osteoblastogenesis of primary murine calvarial osteoblasts. Shank2 knockout mice (Shank2 -/-) have a decreased bone mass due to reduced osteoblastogenesis and bone formation, whereas bone resorption remains unaffected. Induced pluripotent stem cells (iPSCs)-derived osteoblasts from a loss-of-function Shank2 mutation in a patient showed a significantly reduced osteoblast differentiation potential. Moreover, silencing of known Shank2 interacting proteins revealed that a majority of them promote osteoblast differentiation. From this we conclude that Shank2 and interacting proteins known from the central nervous system are decisive regulators in osteoblast differentiation. © 2022 The Authors. JBMR Plus published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research.

Increased osteoclastogenesis contributes to bone loss in the Costello syndrome Hras G12V mouse model.

RAS GTPases are ubiquitous GDP/GTP-binding proteins that function as molecular switches in cellular signalling and control numerous signalling pathways and biological processes. Pathogenic mutations in RAS genes severely affect cellular homeostasis, leading to cancer when occurring in somatic cells and developmental disorders when the germline is affected. These disorders are generally termed as RASopathies and among them Costello syndrome (CS) is a distinctive entity that is caused by specific HRAS germline mutations. The majority of these mutations affect residues 12 and 13, the same sites as somatic oncogenic HRAS mutations. The hallmarks of the disease include congenital cardiac anomalies, impaired thriving and growth, neurocognitive impairments, distinctive craniofacial anomalies, and susceptibility to cancer. Adult patients often present signs of premature aging including reduced bone mineral density and osteoporosis. Using a CS mouse model harbouring a Hras G12V germline mutation, we aimed at determining whether this model recapitulates the patients' bone phenotype and which bone cells are driving the phenotype when mutated. Our data revealed that Hras G12V mutation induces bone loss in mice at certain ages. In addition, we identified that bone loss correlated with an increased number of osteoclasts in vivo and Hras G12V mutations increased osteoclastogenesis in vitro. Last, but not least, mutant osteoclast differentiation was reduced by treatment in vitro with MEK and PI3K inhibitors, respectively. These results indicate that Hras is a novel regulator of bone homeostasis and an increased osteoclastogenesis due to Hras G12V mutation contributes to bone loss in the Costello syndrome.

A Machine Vision Approach for Classification of Skin Cancer Using Hybrid Texture Features.

The main purpose of this study is to observe the importance of machine vision (MV) approach for the identification of five types of skin cancers, namely, actinic-keratosis, benign, solar-lentigo, malignant, and nevus. The 1000 (200 × 5) benchmark image datasets of skin cancers are collected from the International Skin Imaging Collaboration (ISIC). The acquired ISIC image datasets were transformed into texture feature dataset that was a combination of first-order histogram and gray level co-occurrence matrix (GLCM) features. For the skin cancer image, a total of 137,400 (229 × 3 x 200) texture features were acquired on three nonover-lapping regions of interest (ROIs). Principal component analysis (PCA) clustering approach was employed for reducing the dimension of feature dataset. Each image acquired twenty most discriminate features based on two different approaches of statistical features such as average correlation coefficient plus probability of error (ACC + POE) and Fisher (Fis). Furthermore, a correlation-based feature selection (CFS) approach was employed for feature reduction, and optimized 12 features were acquired. Furthermore, a classification algorithm naive bayes (NB), Bayes Net (BN), LMT Tree, and multilayer perception (MLP) using 10 K-fold cross-validation approach were employed on optimized feature datasets and the overall accuracy achieved by MLP is 97.1333%.

A Lightweight Convolutional Neural Network Model for Liver Segmentation in Medical Diagnosis.

Liver segmentation and recognition from computed tomography (CT) images is a warm topic in image processing which is helpful for doctors and practitioners. Currently, many deep learning methods are used for liver segmentation that takes a long time to train the model which makes this task challenging and limited to larger hardware resources. In this research, we proposed a very lightweight convolutional neural network (CNN) to extract the liver region from CT scan images. The suggested CNN algorithm consists of 3 convolutional and 2 fully connected layers, where softmax is used to discriminate the liver from background. Random Gaussian distribution is used for weight initialization which achieved a distance-preserving-embedding of the information. The proposed network is known as Ga-CNN (Gaussian-weight initialization of CNN). General experiments are performed on three benchmark datasets including MICCAI SLiver'07, 3Dircadb01, and LiTS17. Experimental results show that the proposed method performed well on each benchmark dataset.

Efficient Liver Segmentation from Computed Tomography Images Using Deep Learning.

Segmentation of a liver in computed tomography (CT) images is an important step toward quantitative biomarkers for a computer-aided decision support system and precise medical diagnosis. To overcome the difficulties that come across the liver segmentation that are affected by fuzzy boundaries, stacked autoencoder (SAE) is applied to learn the most discriminative features of the liver among other tissues in abdominal images. In this paper, we propose a patch-based deep learning method for the segmentation of a liver from CT images using SAE. Unlike the traditional machine learning methods, instead of anticipating pixel by pixel learning, our algorithm utilizes the patches to learn the representations and identify the liver area. We preprocessed the whole dataset to get the enhanced images and converted each image into many overlapping patches. These patches are given as input to SAE for unsupervised feature learning. Finally, the learned features with labels of the images are fine tuned, and the classification is performed to develop the probability map in a supervised way. Experimental results demonstrate that our proposed algorithm shows satisfactory results on test images. Our method achieved a 96.47% dice similarity coefficient (DSC), which is better than other methods in the same domain.

Inhibition of Cdk5 increases osteoblast differentiation and bone mass and improves fracture healing.

Identification of regulators of osteoblastogenesis that can be pharmacologically targeted is a major goal in combating osteoporosis, a common disease of the elderly population. Here, unbiased kinome RNAi screening in primary murine osteoblasts identified cyclin-dependent kinase 5 (Cdk5) as a suppressor of osteoblast differentiation in both murine and human preosteoblastic cells. Cdk5 knockdown by siRNA, genetic deletion using the Cre-loxP system, or inhibition with the small molecule roscovitine enhanced osteoblastogenesis in vitro. Roscovitine treatment significantly enhanced bone mass by increasing osteoblastogenesis and improved fracture healing in mice. Mechanistically, downregulation of Cdk5 expression increased Erk phosphorylation, resulting in enhanced osteoblast-specific gene expression. Notably, simultaneous Cdk5 and Erk depletion abrogated the osteoblastogenesis conferred by Cdk5 depletion alone, suggesting that Cdk5 regulates osteoblast differentiation through MAPK pathway modulation. We conclude that Cdk5 is a potential therapeutic target to treat osteoporosis and improve fracture healing.

Inhibition of Cdk5 Ameliorates Skeletal Bone Loss in Glucocorticoid-Treated Mice.

Glucocorticoids (GCs) are widely used to treat inflammatory diseases. However, their long-term use leads to glucocorticoid-induced osteoporosis, increasing morbidity and mortality. Both anabolic and anti-resorptive drugs are used to counteract GC-induced bone loss, however, they are expensive and/or have major side effects. Therefore, identifying new targets for cost-effective, small-molecule inhibitors is essential. We recently identified cyclin-dependent kinase 5 (Cdk5) as a suppressor of osteoblast differentiation and showed that its inhibition with roscovitine promoted osteoblastogenesis, thus improving the skeletal bone mass and fracture healing. Here, we assessed whether Cdk5 knockdown or inhibition could also reverse the GC-mediated suppression of osteoblast differentiation, bone loss, and fracture healing. We first demonstrated that Cdk5 silencing abolished the dexamethasone (Dex)-induced downregulation of alkaline phosphatase (Alp) activity, osteoblast-specific marker gene expression (Runx2, Sp7, Alpl, and Bglap), and mineralization. Similarly, Cdk5 inhibition rescued Dex-induced suppression of Alp activity. We further demonstrated that Cdk5 inhibition reversed prednisolone (Pred)-induced bone loss in mice, due to reduced osteoclastogenesis rather than improved osteoblastogenesis. Moreover, we revealed that Cdk5 inhibition failed to improve Pred-mediated impaired fracture healing. Taken together, we demonstrated that Cdk5 inhibition with roscovitine ameliorated GC-mediated bone loss but did not reverse GC-induced compromised fracture healing in mice.

Activity guided isolation and mechanistic approach towards analgesic potential of Chenopodium mediated through opioidergic pathway.

The current study is focused towards screening for its phytochemicals, phenolic and flavonoid contents of different species of Chenopodium. The plants were also screened for corroborating the traditional use of medicinal plants locally used for pain by determining the extract and their fractions for the in-vivo analgesic activity by using the modern scientific system. Among chloroform fractions, a high level of total phenolic contents was found in chloroform fraction of Chenopodium ambrosioides (ChAm-Chf) with 57.12±1.02 followed by Chenopodium botrys (ChBt-Chf) with 56.79±0.71. High content of flavonoids was found in chloroform fraction of Chenopodium botrys (ChBt-Chf) extract with 78.35±0.84 followed by Chenopodium ambrosioides (ChAm-Chf) with 75.20±0.81. The crude extract Chenopodium album, Chenopodium botrys and Chenopodium ambrosioides (ChAl-Crd, ChBt-Crd and ChAm-Crd) at 100 and 200 mg/kg, chloroform and ethylacetate fractions (ChAl-Chf, ChBt-Chf, ChAm-Chf, ChAl-Et, ChBt-Et and ChAm-Et) at 75 mg/kg caused significant inhibition (P<0.05, P<0.01, P<0.001, n=8) of the analgesic response induced by acetic acid, formalin and hotplate method. Mechanistically, the naloxone overturns completely the analgesic effects of beta-sitosterol (SN2) while partial reversal was observed by ursolic acid (SN1) indicating other possible mechanisms in association with opioid receptors.

Leukemia inhibitory factor treatment attenuates the detrimental effects of glucocorticoids on bone in mice.

Glucocorticoids (GCs) are widely used drugs for the treatment of inflammatory and autoimmune diseases. However, a severe side effect induced by long-term GC therapy is osteoporosis. Leukemia inhibitory factor (LIF) - a glycoprotein 130 (gp130) dependent cytokine and member of the interleukin-6 cytokine family - is an activator protein 1 (AP-1) target gene that may be involved in one of the mechanisms underlying GC-induced bone loss. Indeed, we previously reported that the mRNA expression level of LIF was enhanced upon osteogenic differentiation, but was significantly decreased in GC-treated osteoblasts. In this study, we show that in vitro LIF treatment rescues the decreased early osteogenic differentiation and mineralization of GC-treated osteoblasts. Furthermore, we also demonstrate that in vivo LIF treatment protects against GC-mediated trabecular bone loss by decreasing the loss of both trabecular bone formation and osteoblast numbers. This protection appears to be conferred by LIF rescuing GC decreased activity of Stat3, MAPK, and Akt signaling pathways. Thus, the specific targeting of LIF signaling may represent a new therapeutic strategy to prevent GC-induced trabecular bone loss.

RNF40 exerts stage-dependent functions in differentiating osteoblasts and is essential for bone cell crosstalk.

The role of histone ubiquitination in directing cell lineage specification is only poorly understood. Our previous work indicated a role of the histone 2B ubiquitin ligase RNF40 in controlling osteoblast differentiation in vitro. Here, we demonstrate that RNF40 has a stage-dependent function in controlling osteoblast differentiation in vivo. RNF40 expression is essential for early stages of lineage specification, but is dispensable in mature osteoblasts. Paradoxically, while osteoblast-specific RNF40 deletion led to impaired bone formation, it also resulted in increased bone mass due to impaired bone cell crosstalk. Loss of RNF40 resulted in decreased osteoclast number and function through modulation of RANKL expression in OBs. Mechanistically, we demonstrate that Tnfsf11 (encoding RANKL) is an important target gene of H2B monoubiquitination. These data reveal an important role of RNF40-mediated H2B monoubiquitination in bone formation and remodeling and provide a basis for exploring this pathway for the treatment of conditions such as osteoporosis or cancer-associated osteolysis.

Despite Genetic Iron Overload, Hfe-Hemochromatosis Mice Do Not Show Bone Loss.

One of the most prevalent genetic iron overload disorders in Caucasians is caused by mutations in the HFE gene. Both HFE patients and Hfe-mouse models develop a progressive accumulation of iron in the parenchymal cells of various tissues, eventually resulting in liver cirrhosis, hepatocellular carcinoma, cardiomyopathies, hypogonadism, and other pathologies. Clinical data and preclinical models have brought considerable attention to the correlation between iron overload and the development of osteoporosis in HFE/Hfe hemochromatosis. Our study critically challenges this concept. We show that systemic iron overload, at the degree present in Hfe -/- mice, does not associate with the microarchitecture impairment of long bones, thus excluding a negative effect of iron overload on bone integrity. We further reveal that Hfe actions in osteoblasts and osteoclasts are dispensable for the maintenance of bone and iron homeostasis in mice under steady-state conditions. We conclude that, despite systemic iron overload, Hfe -/- mice present normal physiological bone homeostasis. © 2019 The Authors. JBMR Plus in published by Wiley Periodicals, Inc. on behalf of the American Society for Bone and Mineral Research.

A Jack of All Trades: Impact of Glucocorticoids on Cellular Cross-Talk in Osteoimmunology.

Glucocorticoids (GCs) are known to have a strong impact on the immune system, metabolism, and bone homeostasis. While these functions have been long investigated separately in immunology, metabolism, or bone biology, the understanding of how GCs regulate the cellular cross-talk between innate immune cells, mesenchymal cells, and other stromal cells has been garnering attention rather recently. Here we review the recent findings of GC action in osteoporosis, inflammatory bone diseases (rheumatoid and osteoarthritis), and bone regeneration during fracture healing. We focus on studies of pre-clinical animal models that enable dissecting the role of GC actions in innate immune cells, stromal cells, and bone cells using conditional and function-selective mutant mice of the GC receptor (GR), or mice with impaired GC signaling. Importantly, GCs do not only directly affect cellular functions, but also influence the cross-talk between mesenchymal and immune cells, contributing to both beneficial and adverse effects of GCs. Given the importance of endogenous GCs as stress hormones and the wide prescription of pharmaceutical GCs, an improved understanding of GC action is decisive for tackling inflammatory bone diseases, osteoporosis, and aging.

Cell-based RNAi screening and high-content analysis in primary calvarian osteoblasts applied to identification of osteoblast differentiation regulators.

Osteoblasts are responsible for the maintenance of bone homeostasis. Deregulation of their differentiation is etiologically linked to several bone disorders, making this process an important target for therapeutic intervention. Systemic identification of osteoblast regulators has been hampered by the unavailability of physiologically relevant in vitro systems suitable for efficient RNAi and for differentiation read-outs compatible with fluorescent microscopy-based high-content analysis (HCA). Here, we report a new method for identification of osteoblast differentiation regulators by combining siRNA transfection in physiologically relevant cells with high-throughput screening (HTS). Primary mouse calvarial osteoblasts were seeded in 384-well format and reverse transfected with siRNAs and their cell number and differentiation was assayed by HCA. Automated image acquisition allowed high-throughput analyses and classification of single cell features. The physiological relevance, reproducibility, and sensitivity of the method were validated using known regulators of osteoblast differentiation. The application of HCA to siRNAs against expression of 320 genes led to the identification of five potential suppressors and 60 activators of early osteoblast differentiation. The described method and the associated analysis pipeline are not restricted to RNAi-based screening, but can be adapted to large-scale drug HTS or to small-scale targeted experiments, to identify new critical factors important for early osteoblastogenesis.