Intelligent analysis and measurement of semicircular canal spatial attitude.

Objective: The primary aim of this investigation was to devise an intelligent approach for interpreting and measuring the spatial orientation of semicircular canals based on cranial MRI. The ultimate objective is to employ this intelligent method to construct a precise mathematical model that accurately represents the spatial orientation of the semicircular canals. Methods: Using a dataset of 115 cranial MRI scans, this study employed the nnDetection deep learning algorithm to perform automated segmentation of the semicircular canals and the eyeballs (left and right). The center points of each semicircular canal were organized into an ordered structure using point characteristic analysis. Subsequently, a point-by-point plane fit was performed along these centerlines, and the normal vector of the semicircular canals was computed using the singular value decomposition method and calibrated to a standard spatial coordinate system whose transverse planes were the top of the common crus and the bottom of the eyeballs. Results: The nnDetection target recognition segmentation algorithm achieved Dice values of 0.9585 and 0.9663. The direction angles of the unit normal vectors for the left anterior, lateral, and posterior semicircular canal planes were [80.19°, 124.32°, 36.08°], [169.88°, 100.04°, 91.32°], and [79.33°, 130.63°, 137.4°], respectively. For the right side, the angles were [79.03°, 125.41°, 142.42°], [171.45°, 98.53°, 89.43°], and [80.12°, 132.42°, 44.11°], respectively. Conclusion: This study successfully achieved real-time automated understanding and measurement of the spatial orientation of semicircular canals, providing a solid foundation for personalized diagnosis and treatment optimization of vestibular diseases. It also establishes essential tools and a theoretical basis for future research into vestibular function and related diseases.

The spatial orientation of crista ampullaris: implications for BPPV diagnosis and treatment.

Objective: This study aimed to provide a comprehensive understanding of the spatial orientation of the crista ampullaris within the inner ear and its implications for the diagnosis and management of benign paroxysmal positional vertigo (BPPV). Methods: Using high-resolution MRI scans of 55 normal inner ears, 3D models of the semicircular canals were segmented. These were complemented by detailed membrane labyrinth models from micro-CT scans of human temporal bones, accessed via the Comparative Ear Bank (www.earbank.org). A statistical shape model of inner ears and eyeballs was established, and a standardized 3D spatial coordinate system was created. The horizontal plane was defined using the top of the common crus and the bottom of the eyeballs. This calibrated reference system allowed for precise quantification of crista ampullaris orientations by calculating angles between the defined crista planes and coordinate planes. Results: The plane of the ampulla and the corresponding semicircular canal plane are nearly perpendicular to each other. In the upright position, the posterior semicircular canal crista ampullaris formed an angle of 48.9° with the horizontal plane. The relative orientations of the crista ampullaris of the lateral and superior canals were also defined. Furthermore, we identified "zero-point planes" representing crista orientations perpendicular to gravity, which resulted in minimal ampullary stimulation. A 6.2° tilt to the left in the supine position resulted in the plane of the left lateral semicircular canal crista ampullaris being parallel to the direction of gravity. Conclusion: This study elucidates the precise spatial orientation of the crista ampullaris, thereby providing an anatomical basis for understanding BPPV pathophysiology and improving the accuracy of diagnostic and therapeutic maneuvers. The findings have the potential to significantly enhance the management of BPPV and other inner ear disorders.

Small-size temperature/high-pressure integrated sensor via flip-chip method.

Hydraulic technology with smaller sizes and higher reliability trends, including fault prediction and intelligent control, requires high-performance temperature and pressure-integrated sensors. Current designs rely on planar wafer- or chip-level integration, which is limited by pressure range, chip size, and low reliability. We propose a small-size temperature/high-pressure integrated sensor via the flip-chip technique. The pressure and temperature units are arranged vertically, and the sensing signals of the two units are integrated into one plane through silicon vias and gold-gold bonding, reducing the lateral size and improving the efficiency of signal transmission. The flip-chip technique ensures a reliable electrical connection. A square diaphragm with rounded corners is designed and optimised with simulation to sense high pressure based on the piezoresistive effect. The temperature sensing unit with a thin-film platinum resistor measures temperature and provides back-end high-precision compensation, which will improve the precision of the pressure unit. The integrated chip is fabricated by MEMS technology and packaged to fabricate the extremely small integrated sensor. The integrated sensor is characterised, and the pressure sensor exhibits a sensitivity and sensitivity drift of 7.97 mV/MPa and -0.19% FS in the range of 0-20 MPa and -40 to 120 °C. The linearity, hysteresis, repeatability, accuracy, basic error, and zero-time drift are 0.16% FS, 0.04% FS, 0.06% FS, 0.18% FS, ±0.23% FS and 0.04% FS, respectively. The measurement error of the temperature sensor and temperature coefficient of resistance is less than ±1 °C and 3142.997 ppm/°C, respectively. The integrated sensor has broad applicability in fault diagnosis and safety monitoring of high-end equipment such as automobile detection, industrial equipment, and oil drilling platforms.

Effects of immune cells on ischemic stroke and the mediating roles of metabolites.

Objective: Previous studies have not shown an association between IgD-CD24-B-cell absolute count (IgD-CD24-AC) and ischemic stroke (IS). Our study aimed to assess the causal effect of IgD-CD24-AC on IS and to explore the role of ascorbic acid 2-sulfate (AA2S) as a potential mediator. Methods: Our study was based on the largest available genome-wide association study (GWAS). Inverse variance weighting (IVW), MR-Egger, weighted median (WMN), simple mode, and weighted mode methods were used to assess causal effects, with IVW as the primary outcome. Subsequently, we further performed a two-step MR analysis to evaluate whether AA2S mediated this causal effect. In addition, several sensitivity analyses were conducted to evaluate heterogeneity, including Cochran's Q test, the MR-Egger intercept test, the MR-PRESSO global test, and the leave-one-out analysis. Results: Using the IVW approach, the risk ratio of IgD-CD24-AC to IS was estimated to be 1.216 (95% CI = 1.079-1.371, p = 0.001). This result was supported by the WMN method (OR = 1.204, 95% CI = 1.020-1.421, p = 0.028) and the MR-Egger method (OR = 1.177, 95% CI = 0.962-1.442, p = 0.133). We also observed the same trend with the simple model and weighted model. Furthermore, the proportion of genetically predicted IgD-CD24-AC mediated through AA2S levels was 3.73%. Conclusion: Our study revealed a causal relationship between IgD-CD24-AC and IS, a small part of which was mediated by AA2S. These findings offer critical insights for developing immune-targeted therapies in the future and lay a strong foundation for advancements in precision medicine.

Association between the systemic immuno-inflammation index and hearing loss: result from NHANES 2009-2018.

Background: A novel inflammatory marker that measures the degree of systemic immunoinflammation, the systemic immuno-inflammation index (SII) is frequently used to forecast a number of illnesses. According to earlier studies, inflammation may play a role in the pathophysiology of hearing loss (HL). Methods: A sample from the National Health and Nutrition Examination Survey (NHANES) covering the years 2009 to 2018 was used in the current cross-sectional survey. Subgroup analysis and weighted multiple linear regression models were used to examine the independent linear correlation between SII and HL. Fitted smoothed curve analyses were also conducted to show the non-linear relationship between the two variables. Results: Among the 8,535 participants, the mean age was 40.92 ± 18.6 years, with 49.01% being male. Notably, individuals with hearing loss demonstrated an SII of 530.00 ± 320.72, while those with normal hearing displayed an SII of 491.21 ± 265.15. The mean ± SD values of low-frequency, speech-frequency, and high-frequency Pure Tone Average (PTA) hearing thresholds were 10.33 ± 9.79, 12.20 ± 11.11, and 22.48 ± 19.49 dB, respectively. A positive dose-response relationship between higher SII and hearing thresholds was observed after adjusting for potential confounders. Furthermore, the interaction analysis did not reveal any significant impact on this positive correlation. Conclusion: The results of our investigation suggest that the Systemic Inflammatory Index may serve as a potential biomarker for the likelihood of hearing loss. However, additional research is required to further elucidate the nature of this association.

Association Between Composite Dietary Antioxidant Index and Cognitive Function Among Aging Americans from NHANES 2011-2014.

Background: Antioxidant diets are considered to be protective factors for cognitive function. However, comprehensive measures of antioxidant diets are lacking. Objective: To examine the association between the Composite Dietary Antioxidant Index (CDAI) and cognitive function in the elderly. Methods: This cross-sectional study included a total of 2,456 participants (≥60 years old) from NHANES 2011-2014. Calculation of CDAI based on 6 minerals and vitamins (manganese, selenium, zinc, vitamins A, C, and E). Cognitive function was measured by the Consortium to Establish a Registry for Alzheimer's Disease (CERAD) Word Learning sub-test, Animal Fluency Test (AFT), and Digit Symbol Substitution Test (DSST). We also created a composite cognitive z-score to represent global cognition. The statistical analyses we used included multiple linear regression analyses, subgroup analyses, curve-fitting analyses, and threshold effects analyses. Results: After controlling for demographic characteristics, lifestyle factors, and disease history, multivariate linear regression analyses showed that increased CDAI was positively associated with scores on global cognitive function and each cognitive domain (p < 0.05), with subgroup analyses suggesting that this association was more pronounced in stroke patients (p for interaction < 0.05). Curve-fitting analyses and threshold effect analyses showed saturation effects between CDAI and CREAD Test, AFT, and composite Z-score, and an inverted U-shaped relationship with DSST, with inflection points of -1.89, 0.79, 1.13, and 1.77, respectively. Conclusions: Our findings support that higher levels of CDAI are correlated with significantly elevated cognitive function. Maintaining CDAI in an appropriate range may contribute to cognitive health in elderly.

Semi-supervised image segmentation using a residual-driven mean teacher and an exponential Dice loss.

Semi-supervised segmentation plays an important role in computer vision and medical image analysis and can alleviate the burden of acquiring abundant expert-annotated images. In this paper, we developed a residual-driven semi-supervised segmentation method (termed RDMT) based on the classical mean teacher (MT) framework by introducing a novel model-level residual perturbation and an exponential Dice (eDice) loss. The introduced perturbation was integrated into the exponential moving average (EMA) scheme to enhance the performance of the MT, while the eDice loss was used to improve the detection sensitivity of a given network to object boundaries. We validated the developed method by applying it to segment 3D Left Atrium (LA) and 2D optic cup (OC) from the public LASC and REFUGE datasets based on the V-Net and U-Net, respectively. Extensive experiments demonstrated that the developed method achieved the average Dice score of 0.8776 and 0.7751, when trained on 10% and 20% labeled images, respectively for the LA and OC regions depicted on the LASC and REFUGE datasets. It significantly outperformed the MT and can compete with several existing semi-supervised segmentation methods (i.e., HCMT, UAMT, DTC and SASS).

An L-shaped association between composite dietary antioxidant index and stroke: Evidence from NHANES 2011-2020.

OBJECTIVES: Antioxidant diets are considered to be protective factors against stroke. However, comprehensive measurement and evaluation of antioxidant diets are lacking. This study aimed to investigate the correlation between the Composite Dietary Antioxidant Index (CDAI) and stroke in adults. MATERIALS AND METHODS: In this study, based on the National Health and Nutrition Examination Survey (NHANES) 2011-2020 data, multivariate logistic regression, smoothing curve fitting, and threshold effect analysis were used to explore the relationship between CDAI and stroke. Subgroup analyses and interaction tests were conducted to assess the stability of this association within the population. RESULTS: Among 12,922 U.S. adults, there was a significant negative correlation between CDAI and the prevalence of stroke. In the fully adjusted model, the risk of stroke was reduced by 4 % for each 1-unit increase in CDAI (OR [95% CI] = 0.96 [0.93, 0.99]). Participants in the highest quartile of the CDAI had a 37 % lower risk of stroke than those in the lowest quartile (OR [95% CI] = 0.63 [0.47, 0.84]). This negative correlation remained stable across subgroups. Furthermore, the study revealed an L-shaped association between CDAI and stroke through smoothing curve fitting. The threshold effect analysis further identified the inflection point as -1.55. CONCLUSIONS: This study revealed an L-shaped relationship between CDAI and stroke. Keeping CDAI in the proper range may help prevent stroke in the general population.

Advances in high-performance MEMS pressure sensors: design, fabrication, and packaging.

Pressure sensors play a vital role in aerospace, automotive, medical, and consumer electronics. Although microelectromechanical system (MEMS)-based pressure sensors have been widely used for decades, new trends in pressure sensors, including higher sensitivity, higher accuracy, better multifunctionality, smaller chip size, and smaller package size, have recently emerged. The demand for performance upgradation has led to breakthroughs in sensor materials, design, fabrication, and packaging methods, which have emerged frequently in recent decades. This paper reviews common new trends in MEMS pressure sensors, including minute differential pressure sensors (MDPSs), resonant pressure sensors (RPSs), integrated pressure sensors, miniaturized pressure chips, and leadless pressure sensors. To realize an extremely sensitive MDPS with broad application potential, including in medical ventilators and fire residual pressure monitors, the "beam-membrane-island" sensor design exhibits the best performance of 66 µV/V/kPa with a natural frequency of 11.3 kHz. In high-accuracy applications, silicon and quartz RPS are analyzed, and both materials show ±0.01%FS accuracy with respect to varying temperature coefficient of frequency (TCF) control methods. To improve MEMS sensor integration, different integrated "pressure + x" sensor designs and fabrication methods are compared. In this realm, the intercoupling effect still requires further investigation. Typical fabrication methods for microsized pressure sensor chips are also reviewed. To date, the chip thickness size can be controlled to be <0.1 mm, which is advantageous for implant sensors. Furthermore, a leadless pressure sensor was analyzed, offering an extremely small package size and harsh environmental compatibility. This review is structured as follows. The background of pressure sensors is first presented. Then, an in-depth introduction to MEMS pressure sensors based on different application scenarios is provided. Additionally, their respective characteristics and significant advancements are analyzed and summarized. Finally, development trends of MEMS pressure sensors in different fields are analyzed.

Selective Sensing of Volatile Organic Compounds Using an Electrostatically Formed Nanowire Sensor Based on Automatic Machine Learning.

With the development of Internet of Things technology, various sensors are under intense development. Electrostatically formed nanowire (EFN) gas sensors are multigate Si sensors based on CMOS technology and have the unique advantages of ultralow power consumption and very large-scale integration (VLSI) compatibility for mass production. In order to achieve selectivity, machine learning is required to accurately identify the detected gas. In this work, we introduce automatic learning technology, by which the common algorithms are sorted and applied to the EFN gas sensor. The advantages and disadvantages of the top four tree-based model algorithms are discussed, and the unilateral training models are ensembled to further improve the accuracy of the algorithm. The analyses of two groups of experiments show that the CatBoost algorithm has the highest evaluation index. In addition, the feature importance of the classification is analyzed from the physical meaning of electrostatically formed nanowire dimensions, paving the way for model fusion and mechanism exploration.

Mechanism Affecting the Pore Differentiation Characteristics of Fine-Grained Tight Sandstones: A Case Study of Permian Shanxi Formation in Ordos Basin.

In this study, the pore-throat structure and lithological and fractal characteristics of fine-grained sandstone reservoirs of Permian Shanxi Formation in Ordos Basin are investigated using various experiments, including casting thin section, scanning electron microscopy (SEM), high-pressure mercury injection (HPMI), and nuclear magnetic resonance (NMR). The relation between rock type difference and pore structure difference is explored, and the controlling effect of pore-throat structure on physical properties of fine-grained sandstone reservoir is studied. The results show that the sandstone sample can be categorized into quartz arenites, sublitharenite, and lithic sandstone. The average porosity and permeability are, respectively, 4.46% and 0.129 mD. The pores are mainly of intergranular and intercrystalline types, and the throats are lamellar and tubular types. Furthermore, the fine-grained sandstone is typically characterized by a binary pore structure. Micropore-throat, as the main reservoir space, is the dominant factor of the reservoir physical property difference. In addition, the correlation between fractal dimension and rock composition is studied with pore-throat morphology being comprehensively analyzed. The results indicate that the quartz arenite is dominated by quartz intergranular lamellar throats, and there are numerous intergranular pores and tubular throats connecting them in litharenite and sublitharenite. Moreover, the content of pores and throats play major roles in the change of fractal dimension. The characteristics, causes, and main controlling factors of micropore and throat types should be emphatically analyzed to predict the physical properties of fine-grained sandstone.

Design and analysis of HSC-BPPV diagnostic maneuver based on virtual simulation.

Background: The preferred supine roll test for the diagnosis of horizontal semicircular canal BPPV has several disadvantages, including difficulty in locating the affected ear, inconsistent nystagmus performance on repeated testing, and lack of a typical latency period, resulting in insensitive diagnosis. Objectives: To investigate novel diagnostic techniques with more scientific design, more accessible application, and better diagnostic sensitivity and specificity. Materials and methods: Based on clinical microscopic CT data, we created a virtual simulation model of BPPV using Unity software. The physical simulation of the traditional supine roll test was performed to observe and analyse the movement of the otoliths, whose initial position was the typical stable position. In addition, the normal vectors of the plane and crista ampullaris of the horizontal semicircular canal were measured using 3D Slicer software. Based on this, we analyzed the critical steps for designing diagnostic maneuvers for BPPV in the horizontal semicircular canal. For a more accurate diagnosis of horizontal semicircular canal BPPV, it is critical to rotate the horizontal semicircular canal to be parallel to gravity. It is also necessary to move the otolith by swinging the head. As a result, we developed two diagnostic maneuvers: the 60° roll test and the prone roll test. We also performed simulations to observe otolith movement and predict nystagmus performance. Conclusions: The 60° roll test and the prone roll test can complement the supine roll test. Compared to the supine roll test, they not only effectively differentiate canalolithiasis from cupulolithiasis, but also make it easier to determine the position of the otoliths, and the characteristics of the nystagmus are more pronounced. Significant diagnostic features have significant potential benefits for home and telemedicine.

The effectiveness of the modified Epley maneuver for the treatment of posterior semicircular canal benign paroxysmal positional vertigo.

Objective: To compare the repositioning effect of the modified Epley maneuver and the traditional Epley maneuver for posterior semicircular canal benign paroxysmal positional vertigo (PC-BPPV). Methods: Sixty-five patients with unilateral PC-BPPV were randomly divided into two groups. The control group received the traditional Epley maneuver, while the experimental group received the modified Epley maneuver, which prolonged the time in the healthy side lying position and the final bowing position. The number of successful repositions after one, two, and three attempts and the total number of successful repositions were recorded and compared between the two groups. A BPPV virtual simulation model was used to analyze the mechanism of the modified Epley maneuver. Results: The first repositioning success rate of the experimental group was significantly higher than that of the control group (85% vs. 63%, p = 0.040). The experimental group achieved 100% repositioning success rate after two attempts, while the control group needed three attempts to reach 86% repositioning success rate. Four cases in the control group experienced canal switching during the repositioning process, while none in the experimental group did. The BPPV virtual simulation model showed that the modified Epley maneuver could facilitate the passage of otoliths through the posterior arm of the posterior semicircular canal, especially through the location of obstruction. Conclusion: The modified Epley maneuver is more effective than the traditional Epley maneuver in improving the single repositioning success rate and reducing the canal switching rate for PC-BPPV. This study provides a new option for the treatment of BPPV.

Simulation Study of Canal Switching in BPPV.

The objective of this research was to investigate the mechanism of canal switching in benign paroxysmal positional vertigo through a virtual simulation model. Using Unity 3D software and a built-in NVIDIA Physx physics engine, the virtual simulation software is developed using a browser-server architecture, and different models are imported. Based on the benign paroxysmal positional vertigo virtual simulation model, we constructed five different virtual reality scenes of diagnosis and treatment, set otoliths in different positions of the semicircular canals, and analyzed the effects of diagnostic and therapeutic procedures on otolith location. Through the analysis of otolith movement in five virtual scenes, we found that canal switching may be caused by otoliths in the utricle entering the semicircular canal in the supine position. Then, we used different methods to reposition the otolith, improved the repositioning maneuver, and explored in depth the mechanism of the canal switching. The results showed that the main reason for the canal switch is that in the supine position, the otolith in the utricle enters the semicircular canal. The repositioning maneuvers, including the Epley maneuver and Barbecue maneuver, will not directly lead to the canal switch in the ipsilateral inner ear. The supine roll maneuver leads to the otolith in the utricle entering the posterior or lateral semicircular canal, which is the most likely mechanism for canal switching.

Simulation Study of BPPV Fatigability.

To analyze the mechanism and clinical significance of Benign paroxysmal positional vertigo (BPPV) fatigability and discuss how to eliminate BPPV fatigability. A physical simulation model of BPPV was developed to observe the effect of the Dix-Hallpike test on otolith location and explore strategies to eliminate fatigability. Dix-Hallpike test can keep the otoliths in the lower arm of the posterior semicircular canal away from the ampulla. When the head is tilted 30° forward, the otolith slides to the lower arm near the ampulla, which is sufficient to ensure that the starting position of the otolith is consistent when the Dix-Hallpike test is repeated. When the head is tilted 60° forward, the otolith can enter the ampulla and reach the bottom of the crista ampullaris, which leads to long latency because the otolith sliding in the ampulla does not cause an obvious hydrodynamic effect during the Dix-Hallpike test. The otoliths located on the short arm side of the posterior semicircular canal will break away from the short arm side and enter the utricle when the head is tilted 120° forward. The stable and consistent nystagmus induced by the improved diagnostic test may be a more important feature of BPPV.

Measurement of Human Semicircular Canal Spatial Attitude.

Located deep in the temporal bone, the semicircular canal is a subtle structure that requires a spatial coordinate system for measurement and observation. In this study, 55 semicircular canal and eyeball models were obtained by segmentation of MRI data. The spatial coordinate system was established by taking the top of the common crus and the bottom of the eyeball as the horizontal plane. First, the plane equation was established according to the centerline of the semicircular canals. Then, according to the parameters of the plane equation, the plane normal vectors were obtained. Finally, the average unit normal vector of each semicircular canal plane was obtained by calculating the average value of the vectors. The standard normal vectors of the and left posterior semicircular canal, superior semicircular canal and lateral semicircular canal were [-0.651, 0.702, 0.287], [0.749, 0.577, 0.324], [-0.017, -0.299, 0.954], [0.660, 0.702, 0.266], [-0.739, 0.588, 0.329], [0.025, -0.279, 0.960]. The different angles for the different ways of calculating the standard normal vectors of the right and left posterior semicircular canal, superior semicircular canal and lateral semicircular canal were 0.011, 0.028, 0.008, 0.011, 0.024, and 0.006 degrees. The technology for measuring the semicircular canal spatial attitudes in this study are reliable, and the measurement results can guide vestibular function examinations and help with guiding the diagnosis and treatment of BPPV.

Deep attention branch networks for skin lesion classification.

BACKGROUND AND OBJECTIVE: The skin lesion usually covers a small region of the dermoscopy image, and the lesions of different categories might own high similarities. Therefore, it is essential to design an elaborate network for accurate skin lesion classification, which can focus on semantically meaningful lesion parts. Although the Class Activation Mapping (CAM) shows good localization capability of highlighting the discriminative parts, it cannot be obtained in the forward propagation process. METHODS: We propose a Deep Attention Branch Network (DABN) model, which introduces the attention branches to expand the conventional Deep Convolutional Neural Networks (DCNN). The attention branch is designed to obtain the CAM in the training stage, which is then utilized as an attention map to make the network focus on discriminative parts of skin lesions. DABN is applicable to multiple DCNN structures and can be trained in an end-to-end manner. Moreover, a novel Entropy-guided Loss Weighting (ELW) strategy is designed to counter class imbalance influence in the skin lesion datasets. RESULTS: The proposed method achieves an Average Precision (AP) of 0.719 on the ISIC-2016 dataset and an average area under the ROC curve (AUC) of 0.922 on the ISIC-2017 dataset. Compared with other state-of-the-art methods, our method obtains better performance without external data and ensemble learning. Moreover, extensive experiments demonstrate that it can be applied to multi-class classification tasks and improves mean sensitivity by more than 2.6% in different DCNN structures. CONCLUSIONS: The proposed method can adaptively focus on the discriminative regions of dermoscopy images and allows for effective training when facing class imbalance, leading to the performance improvement of skin lesion classification, which could also be applied to other clinical applications.

Radiomics model of dual-time 2-[18F]FDG PET/CT imaging to distinguish between pancreatic ductal adenocarcinoma and autoimmune pancreatitis.

OBJECTIVES: Pancreatic ductal adenocarcinoma (PDAC) and autoimmune pancreatitis (AIP) are diseases with a highly analogous visual presentation that are difficult to distinguish by imaging. The purpose of this research was to create a radiomics-based prediction model using dual-time PET/CT imaging for the noninvasive classification of PDAC and AIP lesions. METHODS: This retrospective study was performed on 112 patients (48 patients with AIP and 64 patients with PDAC). All cases were confirmed by imaging and clinical follow-up, and/or pathology. A total of 502 radiomics features were extracted from the dual-time PET/CT images to develop a radiomics decision model. An additional 12 maximum intensity projection (MIP) features were also calculated to further improve the radiomics model. The optimal radiomics feature set was selected by support vector machine recursive feature elimination (SVM-RFE), and the final classifier was built using a linear SVM. The performance of the proposed dual-time model was evaluated using nested cross-validation for accuracy, sensitivity, specificity, and area under the curve (AUC). RESULTS: The final prediction model was developed from a combination of the SVM-RFE and linear SVM with the required quantitative features. The multimodal and multidimensional features performed well for classification (average AUC: 0.9668, accuracy: 89.91%, sensitivity: 85.31%, specificity: 96.04%). CONCLUSIONS: The radiomics model based on 2-[18F]fluoro-2-deoxy-D-glucose (2-[18F]FDG) PET/CT dual-time images provided promising performance for discriminating between patients with benign AIP and malignant PDAC lesions, which shows its potential for use as a diagnostic tool for clinical decision-making. KEY POINTS: • The clinical symptoms and imaging visual presentations of PDAC and AIP are highly similar, and accurate differentiation of PDAC and AIP lesions is difficult. • Radiomics features provided a potential noninvasive method for differentiation of AIP from PDAC. • The diagnostic performance of the proposed radiomics model indicates its potential to assist doctors in making treatment decisions.

Involvement of miR-337 in high glucose-suppressed osteogenic differentiation in bone marrow mesenchymal stem cells via negative regulation of Rap1A.

This study aims to investigate the inhibitory effect of microRNA-337 (miR-337) on osteogenic differentiation in bone marrow mesenchymal stem cells and its action of mechanisms. Overexpression and knockdown of miR-337 were performed in bone marrow mesenchymal stem cells (BMSCs). Cell proliferation was assessed by using a cell counting kit-8 (CCK-8), mineralization assay was performed by alizarin red staining, and alkaline phosphatase activity was then measured. Luciferase reporter assay was applied to verify miR-337 binding to Ras-related protein 1A (Rap1A) mRNA. Reverse transcription and quantitative polymerase chain reaction (RT-qPCR) was applied to measure the expressions of runt-related transcription factor 2 (Runx2), alkaline phosphatase (ALP), osteocalcin (OCN), osteopontin (OPN), bone morphogenetic protein (BMP2), and miR-337. Then the protein level of Rap1A was determined by western blot analysis. High glucose inhibited osteogenic differentiation but increased the level of miR-337. Overexpression of miR-337 inhibited osteogenic differentiation in high glucose-treated BMSCs, while the knockdown of miR-337 reversed this process. Luciferase reporter assay confirmed that the presumed pairing binding site of miRNA-337 was in the 3'-UTR of the Rap1A WT. In addition, the knockdown of Rap1A distinctly repressed osteogenic differentiation, which blocked the effect of miR-337-knockdown on osteogenic differentiation in high glucose-treated BMSCs. MiR-337 could repress osteogenic differentiation in high glucose-treated BMSCs directly targeting Rap1A, thus provide a potential therapeutic strategy for patients with diabetic osteoporosis in clinic.

Virtual simulation of otolith movement for the diagnosis and treatment of benign paroxysmal positional vertigo.

Benign paroxysmal positional vertigo (BPPV) is a clinical condition. The existing diagnostic methods cannot determine the specific location of otolith on the short or long brachial sides. Thus, visual and quantitative evaluation of the existing clinical standard diagnostic modality Dix-Hallpike test is needed to improve medical efficiency. Our goal was to develop a real-time virtual simulation system to assess a BPPV treatment manipulation. In this study, we used the proposed simulation system to observe otolith movement during a posterior semicircular canal BPPV diagnostic test, and to analyze the diagnostic mechanisms and strategies. Through visual cluster analysis of otolith position and analysis of otolith movement time in the standard Dix-Hallpike test, we can find that the positions of otoliths are relatively scattered, especially on the z-axis (z 1 = 10.67 ± 3.98), and the fall time of otoliths at different positions has relatively large changes (t 1 = 22.21 ± 1.40). But in the modified experiment z 2 = 4.93 ± 0.32 and t 2 = 26.21 ± 0.28. The experimental results show that the simulation system could track the state and the movement of otolith in real-time, which is of great significance for understanding the diagnostic mechanisms of BPPV evaluations and improving the diagnostic method.