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Current Deep Learning (DL)-based methods for vertebra localization in biplanar X-ray images mainly focus on two-dimensional (2D) information and neglect the projective geometry, limiting the accuracy of 3D navigation in X-ray-guided spine surgery. A 3D vertebra localization method from calibrated biplanar X-ray images is highly desired to address the problem. In this study, a projective-geometry-aware network for localizing 3D vertebrae in calibrated biplanar X-ray images, referred to as ProVLNet, is proposed. The network design of ProVLNet features three components: a Siamese 2D feature extractor to extract local appearance features from the biplanar X-ray images, a spatial alignment fusion module to incorporate the projective geometry in fusing the extracted 2D features in 3D space, and a 3D landmark regression module to regress the 3D coordinates of the vertebrae from the 3D fused features. Evaluated on two typical and challenging datasets acquired from the lumbar and the thoracic spine, ProVLNet achieved an identification rate of 99.53% and 98.98% and a point-to-point error of 0.64 mm and 1.38 mm, demonstrating superior performance of our proposed approach over the state-of-the-art (SOTA) methods.

Geochemical reactions are crucial for in situ CO2 mineralization underground associated with CO2‐enhanced oil recovery (CO2‐EOR) in a hydrocarbon reservoir. However, the presence of formation water and adsorbed oil on rocks generates physical barriers to CO2's access to mineral surfaces, which may yield impedance to CO2 mineral trapping that has yet to be accounted for. In this study, we mimic the dynamic oil detachment process using molecular dynamic (MD) simulation and analyze the influence of an adsorbed oil film on supercritical CO2 (scCO2) diffusion toward the mineral surface in the presence and absence of a water phase. Our results demonstrated a negative impact of water on oil film detachment by scCO2, which may weaken mineral reactions and is unfavorable for mineralized CO2 storage underground. Plain Language Summary Carbon dioxide emission has been identified as one of the primary factors influencing global climate change. Storing CO2 underground while enhancing oil recovery is a promising technology that can effectively reduce costs for carbon capture, utilization, and storage (CCUS). Mineral trapping, that is, converting CO2 to carbonate minerals through CO2‐water‐mineral surface reactions, is one of the major mechanisms for CO2 storage. However, residual oil adsorbed on rock surfaces after CO2 injection into an oil reservoir yields a physical barrier for CO2 approaching mineral surfaces. CO2‐water‐oil‐mineral interactions have yet to be thoroughly understood. Therefore, we conducted a series of molecular dynamics simulations to mimic the dynamic oil detachment process and unveil the impact of water on oil film detachment by supercritical CO2. We found that the presence of water strengthens the interactions between the oil and rock surface, which may give rise to a substantial delay in oil film detachment and weaken mineral reactions. Our results provide significant implications for the mineralized storage of CO2 in a depleted oil reservoir and CO2‐enhanced oil recovery and its consequent sequestration. Key Points CO2‐water‐oil‐rock interactions are investigated using molecular dynamics simulations scCO2 can collapse the oil film and channel out a path for CO2 diffusion Water exhibits a negative impact on oil film detachment by scCO2

Periacetabular osteotomy (PAO) is an effective approach for the surgical treatment of developmental dysplasia of the hip (DDH). However, due to the complex anatomical structure around the hip joint and the limited field of view (FoV) during the surgery, it is challenging for surgeons to perform a PAO surgery. To solve this challenge, we propose a robot-assisted, augmented reality (AR)-guided surgical navigation system for PAO. The system mainly consists of a robot arm, an optical tracker, and a Microsoft HoloLens 2 headset, which is a state-of-the-art (SOTA) optical see-through (OST) head-mounted display (HMD). For AR guidance, we propose an optical marker-based AR registration method to estimate a transformation from the optical tracker coordinate system (COS) to the virtual space COS such that the virtual models can be superimposed on the corresponding physical counterparts. Furthermore, to guide the osteotomy, the developed system automatically aligns a bone saw with osteotomy planes planned in preoperative images. Then, it provides surgeons with not only virtual constraints to restrict movement of the bone saw but also AR guidance for visual feedback without sight diversion, leading to higher surgical accuracy and improved surgical safety. Comprehensive experiments were conducted to evaluate both the AR registration accuracy and osteotomy accuracy of the developed navigation system. The proposed AR registration method achieved an average mean absolute distance error (mADE) of 1.96 ± 0.43 mm. The robotic system achieved an average center translation error of 0.96 ± 0.23 mm, an average maximum distance of 1.31 ± 0.20 mm, and an average angular deviation of 3.77 ± 0.85°. Experimental results demonstrated both the AR registration accuracy and the osteotomy accuracy of the developed system.

The goal of visual place recognition (VPR) is to determine the location of a query image by identifying its place in a collection of image databases. Visual sensor technologies are crucial for visual place recognition as they allow for precise identification and location of query images within a database. Global descriptor-based VPR methods face the challenge of accurately capturing the local specific regions within a scene; consequently, it leads to an increasing probability of confusion during localization in such scenarios. To tackle feature extraction and feature matching challenges in VPR, we propose a modified patch-NetVLAD strategy that includes two new modules: a context-aware patch descriptor and a context-aware patch matching mechanism. Firstly, we propose a context-driven patch feature descriptor to overcome the limitations of global and local descriptors in visual place recognition. This descriptor aggregates features from each patch’s surrounding neighborhood. Secondly, we introduce a context-driven feature matching mechanism that utilizes cluster and saliency context-driven weighting rules to assign higher weights to patches that are less similar to densely populated or locally similar regions for improved localization performance. We further incorporate both of these modules into the patch-NetVLAD framework, resulting in a new approach called contextual patch-NetVLAD. Experimental results are provided to show that our proposed approach outperforms other state-of-the-art methods to achieve a Recall@10 score of 99.82 on Pittsburgh30k, 99.82 on FMDataset, and 97.68 on our benchmark dataset.

In robot-assisted ultrasound-guided needle biopsy, it is essential to conduct calibration of the ultrasound probe and to perform hand-eye calibration of the robot in order to establish a link between intra-operatively acquired ultrasound images and robot-assisted needle insertion. Based on a high-precision optical tracking system, novel methods for ultrasound probe and robot hand-eye calibration are proposed. Specifically, we first fix optically trackable markers to the ultrasound probe and to the robot, respectively. We then design a five-wire phantom to calibrate the ultrasound probe. Finally, an effective method taking advantage of steady movement of the robot but without an additional calibration frame or the need to solve the AX=XB equation is proposed for hand-eye calibration. After calibrations, our system allows for in situ definition of target lesions and aiming trajectories from intra-operatively acquired ultrasound images in order to align the robot for precise needle biopsy. Comprehensive experiments were conducted to evaluate accuracy of different components of our system as well as the overall system accuracy. Experiment results demonstrated the efficacy of the proposed methods.

Pedicle screw insertion with robot assistance dramatically improves surgical accuracy and safety when compared with manual implantation. In developing such a system, hand–eye calibration is an essential component that aims to determine the transformation between a position tracking and robot-arm systems. In this paper, we propose an effective hand–eye calibration method, namely registration-based hand–eye calibration (RHC), which estimates the calibration transformation via point set registration without the need to solve the AX=XB equation. Our hand–eye calibration method consists of tool-tip pivot calibrations in two-coordinate systems, in addition to paired-point matching, where the point pairs are generated via the steady movement of the robot arm in space. After calibration, our system allows for robot-assisted, image-guided pedicle screw insertion. Comprehensive experiments are conducted to verify the efficacy of the proposed hand–eye calibration method. A mean distance deviation of 0.70 mm and a mean angular deviation of 0.68° are achieved by our system when the proposed hand–eye calibration method is used. Further experiments on drilling trajectories are conducted on plastic vertebrae as well as pig vertebrae. A mean distance deviation of 1.01 mm and a mean angular deviation of 1.11° are observed when the drilled trajectories are compared with the planned trajectories on the pig vertebrae.

Histone lactylation is a metabolic stress‐related histone modification. However, the role of histone lactylation in the development of sepsis‐associated acute kidney injury (SA‐AKI) remains unclear. Here, histone H3K18 lactylation (H3K18la) is elevated in SA‐AKI, which is reported in this study. Furthermore, this lactate‐dependent histone modification is enriched at the promoter of Ras homolog gene family member A (RhoA) and positively correlated with the transcription. Correction of abnormal lactate levels resulted in a reversal of abnormal histone lactylation at the promoter of RhoA. Examination of related mechanism revealed that histone lactylation promoted the RhoA/Rho‐associated protein kinase (ROCK) /Ezrin signaling, the activation of nuclear factor‐κB (NF‐κB), inflammation, cell apoptosis, and aggravated renal dysfunction. In addition, Ezrin can undergo lactylation modification. Multiple lactylation sites are identified in Ezrin and confirmed that lactylation mainly occurred at the K263 site. The role of histone lactylation is revealed in SA‐AKI and reportes a novel post‐translational modification in Ezrin. Its potential role in regulating inflammatory metabolic adaptation of renal proximal tubule epithelial cells is also elucidated. The results provide novel insights into the epigenetic regulation of the onset of SA‐AKI. H3K18la is elevated and positively correlated with the RhoA transcription in SA‐AKI. Mechanistically, histone lactylation promotes the RhoA/ROCK/Ezrin signaling pathway, NF‐κB activation, inflammation, and cell apoptosis and aggravates renal dysfunction. In addition, exogenous lactate promotes Ezrin lactylation, which mainly occurs at the K263 site.

Background Joint analysis of multiple phenotypes in studies of biological systems such as Genome-Wide Association Studies is critical to revealing the functional interactions between various traits and genetic variants, but growth of data in dimensionality has become a very challenging problem in the widespread use of joint analysis. To handle the excessiveness of variables, we consider the sliced inverse regression (SIR) method. Specifically, we propose a novel SIR-based association test that is robust and powerful in testing the association between multiple predictors and multiple outcomes. Results We conduct simulation studies in both low- and high-dimensional settings with various numbers of Single-Nucleotide Polymorphisms and consider the correlation structure of traits. Simulation results show that the proposed method outperforms the existing methods. We also successfully apply our method to the genetic association study of ADNI dataset. Both the simulation studies and real data analysis show that the SIR-based association test is valid and achieves a higher efficiency compared with its competitors. Conclusion Several scenarios with low- and high-dimensional responses and genotypes are considered in this paper. Our SIR-based method controls the estimated type I error at the pre-specified level α .

Deoxyadenosine triphosphate (dATP) is an important biochemical molecule. In this paper, the synthesis of dATP from deoxyadenosine monophosphate (dAMP), catalyzed by Saccharomyces cerevisiae, was studied. By adding chemical effectors, an efficient ATP regeneration and coupling system was constructed to achieve efficient synthesis of dATP. Factorial and response surface designs were used to optimize process conditions. Optimal reaction conditions were as follows: dAMP 1.40 g/L, glucose 40.97 g/L, MgCl2·6H2O 4.00 g/L, KCl 2.00 g/L, NaH2PO4 31.20 g/L, yeast 300.00 g/L, ammonium chloride 0.67 g/L, acetaldehyde 11.64 mL/L, pH 7.0, temperature 29.6 °C. Under these conditions, the substrate conversion was 93.80% and the concentration of dATP in the reaction system was 2.10 g/L, which was 63.10% higher than before optimization, and the concentration of product was 4 times higher than before optimization. The effects of glucose, acetaldehyde, and temperature on the accumulation of dATP were analyzed.

Background Chronic musculoskeletal pain (CMP) is a complex condition that is mainly treated with analgesic drugs. However, antidepressant intervention is also an important factor in the treatment of CMP. Duloxetine is an effective treatment option for patients with CMP as its antidepressant effect. The purpose of this article is to evaluate the efficacy and safety of duloxetine in treating CMP. Databases and data treatment We searched PubMed, Web of Science, Embase, Cochrane Library from inception to May, 2022. Randomized controlled trials (RCTs) evaluating the efficacy and safety of duloxetine versus placebo in patients with CMP were included. We identified 13 articles and studied a population of 4201 participants in 4 countries. Results This meta-analysis showed that the duloxetine has statistically significant compared with the placebo control, benefits on 24-hour average pain, living quality, physical function, and global impressions and there was no difference in the incidence of serious adverse event. In general, duloxetine can improve mood and pain level at the same time. Conclusions This review shows a significant contribution of duloxetine to CMP symptom relief. This meta-analysis improved that duloxetine can significantly reduce the pain level of patients, improve depressive symptoms and global impression, and has no obvious serious adverse reactions. However, additional studies are required to confirm the relationship between psychological diseases and chronic pain and explore their internal links.