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Place cells and head direction cells in the rodent brain encode spatial position and orientation, forming the neural basis for navigation and cognitive map construction. Inspired by these mechanisms, RatSLAM simulates their roles to achieve biologically inspired visual SLAM. However, traditional RatSLAM struggles with robust feature extraction in visually complex or dynamic environments, where features may be unstable or non-distinct. To address this, we integrate the AKAZE algorithm into the RatSLAM framework. AKAZE combines accelerated techniques with nonlinear diffusion filtering to construct a multi-scale nonlinear scale space, enabling efficient extraction of robust, scale-invariant features across spatial scales. These features are incorporated into RatSLAM's local view module to improve loop closure detection and mitigate odometry drift. Traditional evaluation approaches rely on real-time pose trajectories and cannot evaluate the trajectories based on the fully optimized experience maps, leading to inaccurate mapping performance assessments. Thus, we further propose a novel Ray-Based Map Metric Error Evaluation Method, which can directly compare the final experience maps generated by RatSLAM. Experiments on the KITTI dataset demonstrate that, compared with both ORB-RatSLAM and the ORB-SLAM3, the proposed AKAZE-RatSLAM achieves higher loop closure recall and mapping accuracy while maintaining a lightweight computational profile. In particular, CPU and memory measurements show that AKAZE-RatSLAM requires significantly less computational resources than ORB-SLAM3, confirming its suitability for real-time deployment on resource-limited robotic platforms. Furthermore, neuro-inspired analyses reveal that the pose cell network exhibits spatially localized and direction-selective firing patterns analogous to hippocampal place cells and head direction cells in rodents. Specifically, cells along the same row encode adjacent spatial regions, forming continuous place-field-like activations, whereas cells in the same column show distinct preferred orientations, indicating directional tuning. These biological characteristics confirm that the proposed AKAZE-RatSLAM not only enhances mapping performance and efficiency but also preserves the neurobiological plausibility of spatial representation, advancing the development of brain-inspired visual SLAM systems.

In surgical procedures, surgeons can suffer from spontaneous hand tremors that can affect the accuracy of surgical robots. Therefore, it is necessary to measure and model the tremor signal by sensors to suppress hand tremor. This paper proposes a prediction method based on deep learning that integrates long-term and short-term features to achieve this goal. The long-term features of tremor signals are extracted using a bidirectional Long-short-term memory network, while the short-term features are extracted using a Temporal Convolutional Network. By integrating the long-term and short-term characteristics of tremor signals, this approach provides rich temporal information for signal estimation. In addition, genetic algorithm is used to obtain the optimal time step-size to fully explore the temporal correlation of signals, and an end data compensation strategy is adopted to ensure that the tremor filtering covers the entire process. The performance of the proposed method is evaluated by training and testing on the same dataset as other methods, and conducting suture experiments in a virtual surgical environment. The results show that our proposed model is superior to the existing methods, effectively reducing the tremor signals estimation error. This method can provide better tremor estimation and compensation performance, effectively suppressing the hand tremors and improving the surgical accuracy.

Context: Benzofuran derivatives are important structural motifs found in natural products, often exhibiting significant biological activities. Ruta graveolens L. is a plant source known for containing diverse bioactive compounds.

Objective: This study aimed to isolate and characterize compounds from the aerial parts of R. graveolens, confirm their structures through synthesis, develop a novel synthetic methodology, and evaluate their potential anti-inflammatory effects and monoamine oxidase inhibitory activity.

Materials and methods: The structures of benzofuran enantiomers were elucidated using integrated NMR, HRMS, and ECD analyses. (±)-Rutacycoumarins A and B were synthesized via a novel direct C3 alkylation of coumarin bearing phenolic hydroxyl groups. Biological evaluation assessed the anti-inflammatory effects of (±)-Rutacycoumarins A and B in LPS-stimulated HepG2 cells by measuring liver biomarkers and pro-inflammatory cytokines, and their inhibitory activity against monoamine oxidase B (MAO-B).

Results: Two novel Z/E pairs of benzofuran enantiomers, (±)-Rutacycoumarins A and B, featuring fused cyclopropane motifs, were isolated and structurally confirmed. Their synthesis employed a novel catalytic EDA complex (DIPEA/potassium ethyl xanthate donor, NHPI ester acceptor). (±)-Rutacycoumarins A and B reduced liver biomarkers and pro-inflammatory cytokines in LPS-treated HepG2 cells, and all four enantiomers inhibited MAO-B.

Conclusions: This study isolated two novel benzofuran enantiomer pairs with fused cyclopropane motifs from R. graveolens Their structures were confirmed via a new catalytic EDA complex synthesis. Racemic mixtures reduced LPS-induced liver/cellular damage and cytokines in HepG2 cells, while all enantiomers inhibited MAO-B.

The increasing prevalence of non-communicable diseases like chronic kidney disease signals the need for a deeper understanding of the impact of the intra-uterine milieu on developmental programming and its impact on health outcomes through the lifespan of an individual. Maternal health in the pre-gestational and gestational phases, including nutrition, exposure to drugs, environmental toxins, infectious and non-infectious diseases, and socio-economic conditions influence the overall development of the fetus as well as the fetal kidney. The small, vulnerable newborn, born from an adverse developmental environment, is predisposed to low nephron number and is at risk for acute kidney injury in the neonatal period. Developmental programming has far-reaching consequences, including a higher risk for cardio-kidney-metabolic diseases, including hypertension and chronic kidney disease, and pregnancy complications, which perpetuates an intergenerational cycle of non-communicable disease risk. This risk can be mitigated by optimizing the care of individuals in the reproductive age group, identifying high-risk pregnancies early, and providing optimal treatment and monitoring. Care of the small vulnerable neonate includes prevention of acute kidney injury and life-long surveillance and modulation of cardio-kidney-metabolic risk. The review focuses on highlighting the influence of maternal health in the pre-gestational and gestational phases on kidney health from the neonatal period to adulthood.

Background: Accurate glomerular filtration rate estimation (eGFR) is essential for managing pediatric kidney transplant recipients. Given the physiology of pediatric patients receiving adult-donor kidneys, identifying the most appropriate plasma creatinine (PCr)-based formula-pediatric or adult-specific-is crucial.

Methods: This cross-sectional study included pediatric kidney transplant recipients (age 1-18 years) who received adult-donor kidneys. We compared agreement thresholds of various pediatric and adult PCr-based GFR equations with CKiD 2012 combined PCr‒cystatin C (PCr-CystC) equation via intraclass correlation coefficients (ICCs), concordance correlation coefficients (CCCs), total deviation index (TDI), P30 performance metric (P30), Bland-Altman plots, and receiver-operating characteristic (ROC) analysis. Correlation between CKiD under 25 (U25) PCr-CystC and reference CKiD 2012 equation was also evaluated.

Results: One hundred twenty samples were collected from 23 recipients (mean age = 14.2 ± 3.4 years) and donors (mean age = 31.7 ± 10.0 years). Schwartz-Lyon equation demonstrated the highest performance with the reference (ICC = 0.913, CCC = 0.911, TDI = 14.0 mL/min/1.73 m², P30 = 99.2%). U25 (ICC = 0.922, CCC = 0.882, P30 = 93.3%), full age spectrum (FAS)-height (ICC = 0.897, CCC = 0.877, P30 = 96.7%), and Bedside Schwartz equations (ICC = 0.850, CCC = 0.819, P30 = 89.2%) showed comparable performance. Bland-Altman plots revealed proportional bias (p < 0.05), leading to ROC analysis, which identified eGFR < 70 mL/min/1.73 m² for Schwartz-Lyon, U25, and FAS-height, and < 60 mL/min/1.73 m² for Bedside Schwartz as optimal agreement thresholds, beyond which each equation showed increased bias. Subgroup analyses also showed better performance in patients aged 10-18 years. Additionally, U25 PCr-CystC equation showed excellent agreement with the reference (ICC = 0.993, CCC = 0.990, P30 = 100%).

Conclusions: Schwartz-Lyon equation demonstrated the highest performance among PCr-based equations with the reference in pediatric kidney transplant recipients, particularly when eGFR was < 70 mL/min/1.73 m² and in patients aged 10-18 years. U25 PCr-CystC equation showed best overall agreement with the reference and should be preferred where CystC measurement is feasible.

Background: The native kidney biopsy is an important diagnostic procedure in pediatric nephrology. Recent meta-analyses did not find the size of the needle as a risk factor for bleeding complications, but they were predominantly based on adult studies. There are few papers comparing the safety and core adequacy in pediatric native kidney biopsy.

Methods: We present a large single-center retrospective study performed in a tertiary pediatric nephrology center. Data of children who received a real-time ultrasound-guided native kidney biopsy with a 16- or an 18-gauge needle from 2018 to 2024 were analyzed.

Results: Overall, 1040 children (644 boys) were included, with a median age of 10.25 (6.6; 14.23) years. One hundred three (9.9%) patients experienced bleeding complications. Perinephric hematoma was reported in 86 (8.3%) cases, gross hematuria in 18 (1.7%), and 3 (0.3%) children required transfusion. Multivariate regression analysis revealed the needle size (OR for 16-gauge 2.06, 95% CI 1.22-3.47, p = 0.007) as a risk factor for complications in the overall cohort and in children under 12 years old. The needle size did not affect complication rates in children aged 12-18 years. Inadequate kidney cores were reported in 37 (4.5%) cases; OR for 18-gauge needles (OR 5.08, 95% CI 1.07-24.21, p = 0.041) was found.

Conclusions: Use of a 16-gauge needle reduces the risk of obtaining an inadequate core in comparison with an 18-gauge. An 18G needle has a safety advantage over a 16G needle in children younger than 12 years. A 16G needle is as safe as an 18G needle and should be used for native kidney biopsy in children older than 12 years.

Background: Measures of early postnatal fluid balance may be associated with severe intraventricular hemorrhage (sIVH) and/or death in extremely preterm infants in the first postnatal week.

Methods: A single-center, retrospective cohort study including actively treated inborn infants weighing ≥ 400 g and 22-27 weeks' gestation from 2014-2021. Longitudinal mixed effect models compared daily fluid balance covariates including serum sodium, percent weight change, total fluid intake, urine output, and fluid balance (daily weight - birth weight /birth weight × 100) among infants with and without sIVH or death, during the first seven postnatal days. Multiple regression and machine learning models were developed to predict sIVH and/or death. Variables that were incorporated into the models included measures of fluid balance, gestational age, birth weight, antenatal corticosteroids, multiples, and sex.

Results: We included 932 infants with mean ± SD gestational age of 25w2d ± 11d and birth weight of 746 ± 212 g of whom 195 (20.9%) had sIVH and/or death. Lower percentage weight change (p < 0.001), higher total fluid intake (p = 0.007), higher sodium (p = 0.007), and positive early fluid balance (p < 0.001) were associated with sIVH and/or death even after adjustment for baseline characteristics. The area under the receiver-operating curve (AUC) for regression models predicting sIVH and/or death incorporating baseline characteristics improved after adding fluid balance measures from 0.75 to 0.80, while the AUC for machine learning models improved from 0.72 to 0.84.

Conclusions: In extremely preterm infants, early fluid status measures were associated with risk of sIVH and/or death. The addition of fluid status measures improves the performance of models predicting sIVH and/or death.