Optimizing Lane Departure Warning System towards AI-Centered Autonomous Vehicles.

The operational efficacy of lane departure warning systems (LDWS) in autonomous vehicles is critically influenced by the retro-reflectivity of road markings, which varies with environmental wear and weather conditions. This study investigated how changes in road marking retro-reflectivity, due to factors such as weather and physical wear, impact the performance of LDWS. The study was conducted at the Yeoncheon SOC Demonstration Research Center, where various weather scenarios, including rainfall and transitions between day and night lighting, were simulated. We applied controlled wear to white, yellow, and blue road markings and measured their retro-reflectivity at multiple stages of degradation. Our methods included rigorous testing of the LDWS's recognition rates under these diverse environmental conditions. Our results showed that higher retro-reflectivity levels significantly improve the detection capability of LDWS, particularly in adverse weather conditions. Additionally, the study led to the development of a simulation framework for analyzing the cost-effectiveness of road marking maintenance strategies. This framework aims to align maintenance costs with the safety requirements of autonomous vehicles. The findings highlight the need for revising current road marking guidelines to accommodate the advanced sensor-based needs of autonomous driving systems. By enhancing retro-reflectivity standards, the study suggests a path towards optimizing road safety in the age of autonomous vehicles.

AM-18002, a derivative of natural anmindenol A, enhances radiosensitivity in mouse breast cancer cells.

Natural anmindenol A isolated from the marine-derived bacteria Streptomyces sp. caused potent inhibition of inducible nitric oxide synthase without any significant cytotoxicity. This compound consists of a structurally unique 3,10-dialkylbenzofulvene skeleton. We previously synthesized and screened the novel derivatives of anmindenol A and identified AM-18002, an anmindenol A derivative, as a promising anticancer agent. The combination of AM-18002 and ionizing radiation (IR) improved anticancer effects, which were exerted by promoting apoptosis and inhibiting the proliferation of FM3A mouse breast cancer cells. AM-18002 increased the production of reactive oxygen species (ROS) and was more effective in inducing DNA damage. AM-18002 treatment was found to inhibit the expansion of myeloid-derived suppressor cells (MDSC), cancer cell migration and invasion, and STAT3 phosphorylation. The AM-18002 and IR combination synergistically induced cancer cell death, and AM-18002 acted as a potent anticancer agent by increasing ROS generation and blocking MDSC-mediated STAT3 activation in breast cancer cells.

Breast cancer malignancy is governed by regulation of the macroH2A2/TM4SF1 axis, the AKT/NF-κB pathway, and elevated MMP13 expression.

The histone variant, macroH2A (mH2A) influences gene expression through epigenetic regulation. Tumor suppressive function of mH2A isoforms has been reported in various cancer types, but few studies have investigated the functional role of mH2A2 in breast cancer pathophysiology. This study aimed to determine the significance of mH2A2 in breast cancer development and progression by exploring its downstream regulatory mechanisms. Knockdown of mH2A2 facilitated the migration and invasion of breast cancer cells, whereas its overexpression exhibited the opposite effect. In vivo experiments revealed that augmenting mH2A2 expression reduced tumor growth and lung metastasis. Microarray analysis showed that TM4SF1 emerged as a likely target linked to mH2A2 owing to its significant suppression in breast cancer cell lines where mH2A2 was overexpressed among the genes that exhibited over twofold upregulation upon mH2A2 knockdown. Suppressing TM4SF1 reduced the migration, invasion, tumor growth, and metastasis of breast cancer cells in vitro and in vivo. TM4SF1 depletion reversed the increased aggressiveness triggered by mH2A2 knockdown, suggesting a close interplay between mH2A2 and TM4SF1. Our findings also highlight the role of the mH2A2/TM4SF1 axis in activating the AKT/NF-κB pathway. Consequently, activated NF-κB signaling leads to increased expression and secretion of MMP13, a potent promoter of metastasis. In summary, we propose that the orchestrated regulation of the mH2A2/TM4SF1 axis in conjunction with the AKT/NF-κB pathway and the subsequent elevation in MMP13 expression constitute pivotal factors governing the malignancy of breast cancer.

Understanding cross-data dynamics of individual and social/environmental factors through a public health lens: explainable machine learning approaches.

Introduction: The rising prevalence of obesity has become a public health concern, requiring efficient and comprehensive prevention strategies. Methods: This study innovatively investigated the combined influence of individual and social/environmental factors on obesity within the urban landscape of Seoul, by employing advanced machine learning approaches. We collected 'Community Health Surveys' and credit card usage data to represent individual factors. In parallel, we utilized 'Seoul Open Data' to encapsulate social/environmental factors contributing to obesity. A Random Forest model was used to predict obesity based on individual factors. The model was further subjected to Shapley Additive Explanations (SHAP) algorithms to determine each factor's relative importance in obesity prediction. For social/environmental factors, we used the Geographically Weighted Least Absolute Shrinkage and Selection Operator (GWLASSO) to calculate the regression coefficients. Results: The Random Forest model predicted obesity with an accuracy of >90%. The SHAP revealed diverse influential individual obesity-related factors in each Gu district, although 'self-awareness of obesity', 'weight control experience', and 'high blood pressure experience' were among the top five influential factors across all Gu districts. The GWLASSO indicated variations in regression coefficients between social/environmental factors across different districts. Conclusion: Our findings provide valuable insights for designing targeted obesity prevention programs that integrate different individual and social/environmental factors within the context of urban design, even within the same city. This study enhances the efficient development and application of explainable machine learning in devising urban health strategies. We recommend that each autonomous district consider these differential influential factors in designing their budget plans to tackle obesity effectively.

Downregulation of complement factor H attenuates the stemness of MDA­MB­231 breast cancer cells via modulation of the ERK and p38 signaling pathways.

The complement system is a powerful innate immune system deployed in the immediate response to pathogens and cancer cells. Complement factor H (CFH), one of the regulators involved in the complement cascade, can interrupt the death of target cells. Certain types of cancer, such as breast cancer, can adopt an aggressive phenotype, such as breast cancer stem cells (BCSCs), through enhancement of the defense system against complement attack by amplifying various complement regulators. However, little is known about the association between CFH and BCSCs. In the present study, the roles of CFH in the CSC characteristics and radioresistance of MDA-MB-231 human breast cancer cells were investigated. CFH knockdown in MDA-MB-231 cells decreased the viability of the cells upon complement cascade activation. Notably, CFH knockdown also decreased cell survival and suppressed mammosphere formation, cell migration and cell invasion by attenuating radioresistance. Additionally, CFH knockdown further enhanced irradiation-induced apoptosis through G2/M cell cycle arrest. It was also discovered that CFH knockdown attenuated the aggressive phenotypes of cancer cells by regulating CSC-associated gene expression. Finally, by microarray analysis, it was found that the expression of erythrocyte membrane protein band 4.1-like 3 (EPB41L3) was markedly increased following CFH knockdown. EPB41L3 inhibited ERK and activated the p38 MAPK signaling pathway. Taken together, these results indicated that CFH knockdown attenuated CSC properties and radioresistance in human breast cancer cells via controlling MAPK signaling and through upregulation of the tumor suppressor, EPB41L3.

Reptiles as Promising Sources of Medicinal Natural Products for Cancer Therapeutic Drugs.

Natural products have historically played an important role as a source of therapeutic drugs for various diseases, and the development of medicinal natural products is still a field with high potential. Although diverse drugs have been developed for incurable diseases for several decades, discovering safe and efficient anticancer drugs remains a formidable challenge. Reptiles, as one source of Asian traditional medicines, are known to possess anticancer properties and have been used for a long time without a clarified scientific background. Recently, it has been reported that extracts, crude peptides, sera, and venom isolated from reptiles could effectively inhibit the survival and proliferation of various cancer cells. In this article, we summarize recent studies applying ingredients derived from reptiles in cancer therapy and discuss the difficulties and prospective development of natural product research.

Endoplasmin regulates differentiation of tonsil-derived mesenchymal stem cells into chondrocytes through ERK signaling.

It is well-known that some species of lizard have an exceptional ability known as caudal autotomy (voluntary self-amputation of the tail) as an anti-predation mechanism. After amputation occurs, they can regenerate their new tails in a few days. The new tail section is generally shorter than the original one and is composed of cartilage rather than vertebrae bone. In addition, the skin of the regenerated tail distinctly differs from its original appearance. We performed a proteomics analysis for extracts derived from regenerating lizard tail tissues after amputation and found that endoplasmin (ENPL) was the main factor among proteins up-regulated in expression during regeneration. Thus, we performed further experiments to determine whether ENPL could induce chondrogenesis of tonsil-derived mesenchymal stem cells (T-MSCs). In this study, we found that chondrogenic differentiation was associated with an increase of ENPL expression by ER stress. We also found that ENPL was involved in chondrogenic differentiation of T-MSCs by suppressing extracellular signal-regulated kinase (ERK) phosphorylation. [BMB Reports 2022; 55(5): 226-231].

G9a Knockdown Suppresses Cancer Aggressiveness by Facilitating Smad Protein Phosphorylation through Increasing BMP5 Expression in Luminal A Type Breast Cancer.

Epigenetic abnormalities affect tumor progression, as well as gene expression and function. Among the diverse epigenetic modulators, the histone methyltransferase G9a has been focused on due to its role in accelerating tumorigenesis and metastasis. Although epigenetic dysregulation is closely related to tumor progression, reports regarding the relationship between G9a and its possible downstream factors regulating breast tumor growth are scarce. Therefore, we aimed to verify the role of G9a and its presumable downstream regulators during malignant progression of breast cancer. G9a-depleted MCF7 and T47D breast cancer cells exhibited suppressed motility, including migration and invasion, and an improved response to ionizing radiation. To identify the possible key factors underlying these effects, microarray analysis was performed, and a TGF-ß superfamily member, BMP5, was selected as a prominent target gene. It was found that BMP5 expression was markedly increased by G9a knockdown. Moreover, reduction in the migration/invasion ability of MCF7 and T47D breast cancer cells was induced by BMP5. Interestingly, a G9a-depletion-mediated increase in BMP5 expression induced the phosphorylation of Smad proteins, which are the intracellular signaling mediators of BMP5. Accordingly, we concluded that the observed antitumor effects may be based on the G9a-depletion-mediated increase in BMP5 expression and the consequent facilitation of Smad protein phosphorylation.

Enhanced Soft 3D Reconstruction Method with an Iterative Matching Cost Update Using Object Surface Consensus.

In this paper, we propose a multi-view stereo matching method, EnSoft3D (Enhanced Soft 3D Reconstruction) to obtain dense and high-quality depth images. Multi-view stereo is one of the high-interest research areas and has wide applications. Motivated by the Soft3D reconstruction method, we introduce a new multi-view stereo matching scheme. The original Soft3D method is introduced for novel view synthesis, while occlusion-aware depth is also reconstructed by integrating the matching costs of the Plane Sweep Stereo (PSS) and soft visibility volumes. However, the Soft3D method has an inherent limitation because the erroneous PSS matching costs are not updated. To overcome this limitation, the proposed scheme introduces an update process of the PSS matching costs. From the object surface consensus volume, an inverse consensus kernel is derived, and the PSS matching costs are iteratively updated using the kernel. The proposed EnSoft3D method reconstructs a highly accurate 3D depth image because both the multi-view matching cost and soft visibility are updated simultaneously. The performance of the proposed method is evaluated by using structured and unstructured benchmark datasets. Disparity error is measured to verify 3D reconstruction accuracy, and both PSNR and SSIM are measured to verify the simultaneous enhancement of view synthesis.

Inhibitory effect of ginsenoside Rg3 on cancer stemness and mesenchymal transition in breast cancer via regulation of myeloid-derived suppressor cells.

Ginsenoside Rg3 (Rg3) has been studied in several cancer models and is suggested to act through various pharmacological effects. We investigated the anticancer properties of Rg3 through myeloid-derived suppressor cell (MDSC) modulation in FM3A mouse mammary carcinoma cells. The effects of Rg3 on MDSCs and consequent changes in cancer stem-like cells (CSCs) and epithelial-mesenchymal transition (EMT) were evaluated by diverse methods. MDSCs promoted cancer by enhancing breast cancer stemness and promoting EMT. Rg3 at a dose without obvious cytotoxicity downregulated MDSCs and repressed MDSC-induced cancer stemness and EMT. Mechanistic investigations suggested that these inhibitory effects of Rg3 on MDSCs and corresponding cancer progression depend upon suppression of the STAT3-dependent pathway, tumor-derived cytokines, and the NOTCH signaling pathway. In a mouse model, MDSCs accelerated tumor progression, and Rg3 delayed tumor growth, which is consistent with the results of in vitro experiments. These results indicated that Rg3 could effectively inhibit the progression of breast cancer. The anticancer effect of Rg3 might be partially due to its downregulation of MDSCs and consequent repression of cancer stemness and EMT in breast cancer. Hence, we suggest the regulation of MDSCs through Rg3 treatment as an effective therapeutic strategy for breast cancer patients.

Extrinsic Calibration between Camera and LiDAR Sensors by Matching Multiple 3D Planes.

This paper proposes a simple extrinsic calibration method for a multi-sensor system which consists of six image cameras and a 16-channel 3D LiDAR sensor using a planar chessboard. The six cameras are mounted on a specially designed hexagonal plate to capture omnidirectional images and the LiDAR sensor is mounted on the top of the plates to capture 3D points in 360 degrees. Considering each camera-LiDAR combination as an independent multi-sensor unit, the rotation and translation between the two sensor coordinates are calibrated. The 2D chessboard corners in the camera image are reprojected into 3D space to fit to a 3D plane with respect to the camera coordinate system. The corresponding 3D point data that scan the chessboard are used to fit to another 3D plane with respect to the LiDAR coordinate system. The rotation matrix is calculated by aligning normal vectors of the corresponding planes. In addition, an arbitrary point on the 3D camera plane is projected to a 3D point on the LiDAR plane, and the distance between the two points are iteratively minimized to estimate the translation matrix. At least three or more planes are used to find accurate external parameters between the coordinate systems. Finally, the estimated transformation is refined using the distance between all chessboard 3D points and the LiDAR plane. In the experiments, quantitative error analysis is done using a simulation tool and real test sequences are also used for calibration consistency analysis.

Extracellular Microenvironmental Change by B16F10 Melanoma-derived Proteins Induces Cancer Stem-like Cell Properties from NIH3T3 Cells.

Cancer stem-like cells (CSCs) can generate solid tumors through the properties of stem cells such as self-renewal and differentiation and they cause drug resistance, metastasis and recurrence. Therefore, establishing CSC lines is necessary to conduct various studies such as on the identification of CSC origin and specific targeted therapies. In this study, we stimulated NIH3T3 fibroblasts to exhibit the characteristics of CSCs using the whole protein lysates of B16F10 melanoma cells. As a result, we induced colony formation that displayed self-renewal and differentiation capacities through anchorage-independent culture and re-attached culture. Moreover, colonies showed drug resistance by being maintained in the G0/G1 state. Colonies expressed various CSC markers and displayed high-level drug efflux capacity. Additionally, colonies clearly demonstrated tumorigenic ability by forming a solid tumor in vivo. These results show that proteins of cancer cells could transform normal cells into CSCs by increasing expression of CSC markers. This study argues the tremendous importance of the extracellular microenvironmental effect on the generation of CSCs. It also provides a simple experimental method for deriving CSCs that could be based on the development of targeted therapy techniques.

Gekkonidae, Lizard tail extracts elicit apoptotic response against non-small cell lung cancer via inhibiting Akt signaling.

The genes of Gekkonidae, a lizard, are known to be very similar to human genes. According to previous research, lizard extracts inhibit angiogenesis and show anticancer activity against various cancers. In this regard, this study assessed whether lizard tail extracts (LTE) cause anticancer activity against lung cancer in mouse and human lung cancer cell lines. The results showed that LTE exhibited anticancer activity against lung cancer in vitro and in vivo. In vitro, cell viability and proliferation decreased in two lung cancer cell lines, while annexin V and single-stranded DNA both increased, showing apoptotic activity caused by LTE. We also found that LTE induced apoptosis in a caspase-3/7 cascade-dependent manner and inhibited the phosphorylation of Akt by participating in the PI3k/Akt pathway. In vivo, LTE decreased tumor volume in LLC bearing mice. Our results demonstrate the potential of LTE as a natural-derived anticancer drug to overcome the chemotherapy side effects during cancer treatment and contribute to the discovery of candidate substances.

Lizard Tail Extracts Exert Protective Effect Against Oxidative Stress-Induced Cellular Senescence in Human Fibroblasts.

Lizards are the evolutionarily closest animals to humans among the self-renewable species. Recent reports show that lizard tail extracts (LTE) inhibit the proliferation and angiogenesis of cancer cells but do not show any toxicity against human fibroblast cells. Nevertheless, few scientific studies investigated the effects of LTE on the treatment of skin diseases, especially oxidative stress aging. Therefore, we explored the effect of LTE on the anti-aging activity of human fibroblasts. We confirmed the anti-aging effect of LTE by SA-ß-galactosidase staining. In addition, the hydrogen peroxide-induced reactive oxygen species (ROS) were decreased by the LTE, as measured by staining with the 2',7'-dichlorofluorescein diacetate reagent. We performed Western blot analysis to examine the signaling pathways. In conclusion, the LTE can prevent cellular senescence through the suppression of ROS and the downregulation of p21.

Deep vector-based convolutional neural network approach for automatic recognition of colonies of induced pluripotent stem cells.

Pluripotent stem cells can potentially be used in clinical applications as a model for studying disease progress. This tracking of disease-causing events in cells requires constant assessment of the quality of stem cells. Existing approaches are inadequate for robust and automated differentiation of stem cell colonies. In this study, we developed a new model of vector-based convolutional neural network (V-CNN) with respect to extracted features of the induced pluripotent stem cell (iPSC) colony for distinguishing colony characteristics. A transfer function from the feature vectors to the virtual image was generated at the front of the CNN in order for classification of feature vectors of healthy and unhealthy colonies. The robustness of the proposed V-CNN model in distinguishing colonies was compared with that of the competitive support vector machine (SVM) classifier based on morphological, textural, and combined features. Additionally, five-fold cross-validation was used to investigate the performance of the V-CNN model. The precision, recall, and F-measure values of the V-CNN model were comparatively higher than those of the SVM classifier, with a range of 87-93%, indicating fewer false positives and false negative rates. Furthermore, for determining the quality of colonies, the V-CNN model showed higher accuracy values based on morphological (95.5%), textural (91.0%), and combined (93.2%) features than those estimated with the SVM classifier (86.7, 83.3, and 83.4%, respectively). Similarly, the accuracy of the feature sets using five-fold cross-validation was above 90% for the V-CNN model, whereas that yielded by the SVM model was in the range of 75-77%. We thus concluded that the proposed V-CNN model outperforms the conventional SVM classifier, which strongly suggests that it as a reliable framework for robust colony classification of iPSCs. It can also serve as a cost-effective quality recognition tool during culture and other experimental procedures.

Lactoferrin Protects Human Mesenchymal Stem Cells from Oxidative Stress-Induced Senescence and Apoptosis.

Mesenchymal stem cells (MSCs) have been suggested as a primary candidate for cell therapy applications because they have self-renewal and differentiation capabilities. Although they can be expanded in ex vivo system, clinical application of these cells is still limited because they survive poorly and undergo senescence or apoptosis when transplanted and exposed to environmental factors such as oxidative stress. Thus, reducing oxidative stress is expected to improve the efficacy of MSC therapy. The milk protein lactoferrin is a multifunctional iron-binding glycoprotein that plays various roles, including reduction of oxidative stress. Thus, we explored the effect of lactoferrin on oxidative stress-induced senescence and apoptosis of human MSCs (hMSCs). Measurement of reactive oxygen species (ROS) revealed that lactoferrin inhibited the production of hydrogen peroxide-induced intracellular ROS, suggesting lactoferrin as a good candidate as an antioxidant in hMSCs. Pretreatment of lactoferrin suppressed hydrogen peroxide-induced senescence of hMSCs. In addition, lactoferrin reduced hydrogen peroxide-induced apoptosis via inhibition of caspase-3 and Akt activation. These results demonstrate that lactoferrin can be a promising factor to protect hMSCs from oxidative stress-induced senescence and apoptosis, thus increasing the efficacy of MSC therapy.

Real-Time External Respiratory Motion Measuring Technique Using an RGB-D Camera and Principal Component Analysis.

Accurate tracking and modeling of internal and external respiratory motion in the thoracic and abdominal regions of a human body is a highly discussed topic in external beam radiotherapy treatment. Errors in target/normal tissue delineation and dose calculation and the increment of the healthy tissues being exposed to high radiation doses are some of the unsolicited problems caused due to inaccurate tracking of the respiratory motion. Many related works have been introduced for respiratory motion modeling, but a majority of them highly depend on radiography/fluoroscopy imaging, wearable markers or surgical node implanting techniques. We, in this article, propose a new respiratory motion tracking approach by exploiting the advantages of an RGB-D camera. First, we create a patient-specific respiratory motion model using principal component analysis (PCA) removing the spatial and temporal noise of the input depth data. Then, this model is utilized for real-time external respiratory motion measurement with high accuracy. Additionally, we introduce a marker-based depth frame registration technique to limit the measuring area into an anatomically consistent region that helps to handle the patient movements during the treatment. We achieved a 0.97 correlation comparing to a spirometer and 0.53 mm average error considering a laser line scanning result as the ground truth. As future work, we will use this accurate measurement of external respiratory motion to generate a correlated motion model that describes the movements of internal tumors.

Synergistically enhanced selective intracellular uptake of anticancer drug carrier comprising folic acid-conjugated hydrogels containing magnetite nanoparticles.

Targeted drug delivery has long been extensively researched since drug delivery and release at the diseased site with minimum dosage realizes the effective therapy without adverse side effects. In this work, to achieve enhanced intracellular uptake of anticancer drug carriers for efficient chemo-therapy, we have designed targeted multifunctional anticancer drug carrier hydrogels. Temperature-responsive poly(N-isopropylacrylamide) (PNIPAm) hydrogel core containing superparamagnetic magnetite nanoparticles (MNP) were prepared using precipitation polymerization, and further polymerized with amine-functionalized copolymer shell to facilitate the conjugation of targeting ligand. Then, folic acid, specific targeting ligand for cervical cancer cell line (HeLa), was conjugated on the hydrogel surface, yielding the ligand conjugated hybrid hydrogels. We revealed that enhanced intracellular uptake by HeLa cells in vitro was enabled by both magnetic attraction and receptor-mediated endocytosis, which were contributed by MNP and folic acid, respectively. Furthermore, site-specific uptake of the developed carrier was confirmed by incubating with several other cell lines. Based on synergistically enhanced intracellular uptake, efficient cytotoxicity and apoptotic activity of HeLa cells incubated with anticancer drug loaded hybrid hydrogels were successfully achieved. The developed dual-targeted hybrid hydrogels are expected to provide a platform for the next generation intelligent drug delivery systems.

Distributional Variations in the Quantitative Cortical and Trabecular Bone Radiographic Measurements of Mandible, between Male and Female Populations of Korea, and its Utilization.

It is important to investigate the irregularities in aging-associated changes in bone, between men and women for bone strength and osteoporosis. The purpose of this study was to characterize the changes and associations of mandibular cortical and trabecular bone measures of men and women based on age and to the evaluation of cortical shape categories, in a large Korean population. Panoramic radiographs of 1047 subjects (603 women and 444 men) aged between 15 to 90 years were used. Mandibular cortical width (MCW), mandibular cortical index (MCI), and fractal dimensions (FD) of the molar, premolar, and anterior regions of the mandibular trabecular bone were measured. Study subjects were grouped into six 10-years age groups. A local linear regression smoothing with bootstrap resampling for robust fitting of data was used to estimate the relationship between radiographic mandibular variables and age groups as well as genders. The mean age of women (49.56 ± 19.5 years) was significantly higher than that of men (45.57 ± 19.6 years). The MCW of men and women (3.17mm and 2.91mm, respectively, p < 0.0001) was strongly associated with age and MCI. Indeed, trabecular measures also correlated with age in men (r > -0.140, p = 0.003), though not as strongly as in women (r > -0.210, p < 0.0001). In men aged over 55 years, only MCW was significantly associated (r = -0.412, p < 0.0001). Furthermore, by comparison of mandibular variables from different age groups and MCI categories, the results suggest that MCW was detected to be strongly associated in both men and women for the detection of bone strength and osteoporosis. The FD measures revealed relatively higher association with age among women than men, but not as strong as MCW.

Automatic detection of osteoporosis based on hybrid genetic swarm fuzzy classifier approaches.

OBJECTIVES: This study proposed a new automated screening system based on a hybrid genetic swarm fuzzy (GSF) classifier using digital dental panoramic radiographs to diagnose females with a low bone mineral density (BMD) or osteoporosis. METHODS: The geometrical attributes of both the mandibular cortical bone and trabecular bone were acquired using previously developed software. Designing an automated system for osteoporosis screening involved partitioning of the input attributes to generate an initial membership function (MF) and a rule set (RS), classification using a fuzzy inference system and optimization of the generated MF and RS using the genetic swarm algorithm. Fivefold cross-validation (5-FCV) was used to estimate the classification accuracy of the hybrid GSF classifier. The performance of the hybrid GSF classifier has been further compared with that of individual genetic algorithm and particle swarm optimization fuzzy classifiers. RESULTS: Proposed hybrid GSF classifier in identifying low BMD or osteoporosis at the lumbar spine and femoral neck BMD was evaluated. The sensitivity, specificity and accuracy of the hybrid GSF with optimized MF and RS in identifying females with a low BMD were 95.3%, 94.7% and 96.01%, respectively, at the lumbar spine and 99.1%, 98.4% and 98.9%, respectively, at the femoral neck BMD. The diagnostic performance of the proposed system with femoral neck BMD was 0.986 with a confidence interval of 0.942-0.998. The highest mean accuracy using 5-FCV was 97.9% with femoral neck BMD. CONCLUSIONS: The combination of high accuracy along with its interpretation ability makes this proposed automatic system using hybrid GSF classifier capable of identifying a large proportion of undetected low BMD or osteoporosis at its early stage.