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Recent advances in microCT are facilitating the investigation of microstructures in spiders and insects leading to an increased number of studies investigating their neuroanatomy. Although microCT is a powerful tool, its effectiveness depends on appropriate tissue preparation and scan settings, particularly for soft, non-sclerotized tissues, such as muscles, organs, and neural tissues. As the application of microCT in spiders is only in its infancy, published protocols are often difficult to implement due to substantial size variation of the specimens. The present study was initiated to determine how to account for this variation. Our work builds on previous methods using microCT to image spider brains, with the aim to consolidate current knowledge and reduce time spent troubleshooting appropriate methodology, thereby facilitating future studies of spiders and their central nervous systems (CNS). We tested three different preparation and imaging techniques based on published protocols with minor modifications using 216 spiders with prosoma lengths ranging from 1.25 mm (small spiders) to 13.33 mm (large spiders). We compared the efficacy of the various specimen preparations, staining methods, and scan settings by categorizing the quality of dorsal and lateral microCT scans. We observed that only the phosphotungstic acid (PTA) staining agent resulted in complete staining of the prosoma and the CNS, allowing the CNS structures to be distinguished for small, medium, and large spiders. The use of image averaging, increased number of projections, image exposure timing, and detector binning did not greatly affect image quality for small and larger spiders but reduced noise. These settings did help improve image quality for medium spiders in conjunction with higher resolutions and an aluminum filter. We discussed the suitability of methods concerning spider size, effort, chemical risk, and image quality.
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http://dx.doi.org/10.1002/cne.70017 | DOI Listing |
Circ Arrhythm Electrophysiol
September 2025
Department of Congenital Heart Disease, Evelina London Children's Hospital, United Kingdom (S. Chivers, T.V., V.Z., S.M., G.M., W.R., E.R., D.F.A.L., T.G.D., O.I.M., G.K.S., J.M.S.).
Background: Fetal tachycardias can cause adverse fetal outcomes including ventricular dysfunction, hydrops, and fetal demise. Postnatally, ECG is the gold standard, but, in fetal practice, echocardiography is used most frequently to diagnose and monitor fetal arrhythmias. Noninvasive extraction of the fetal ECG (fECG) may provide additional information about the electrophysiological mechanism and monitoring of intermittent arrhythmias.
View Article and Find Full Text PDFACS Sens
September 2025
Institute of Applied Mechanics, National Taiwan University, Taipei 106, Taiwan.
In recent AI-driven disease diagnosis, the success of models has depended mainly on extensive data sets and advanced algorithms. However, creating traditional data sets for rare or emerging diseases presents significant challenges. To address this issue, this study introduces a direct-self-attention Wasserstein generative adversarial network (DSAWGAN) designed to improve diagnostic capabilities in infectious diseases with limited data availability.
View Article and Find Full Text PDFMagn Reson Med
September 2025
Centre for Integrative Neuroimaging, FMRIB Division, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK.
Purpose: To develop a deep learning-based reconstruction method for highly accelerated 3D time-of-flight MRA (TOF-MRA) that achieves high-quality reconstruction with robust generalization using extremely limited acquired raw data, addressing the challenge of time-consuming acquisition of high-resolution, whole-head angiograms.
Methods: A novel few-shot learning-based reconstruction framework is proposed, featuring a 3D variational network specifically designed for 3D TOF-MRA that is pre-trained on simulated complex-valued, multi-coil raw k-space datasets synthesized from diverse open-source magnitude images and fine-tuned using only two single-slab experimentally acquired datasets. The proposed approach was evaluated against existing methods on acquired retrospectively undersampled in vivo k-space data from five healthy volunteers and on prospectively undersampled data from two additional subjects.
MAGMA
September 2025
Department of Medical Imaging, (766), Radboud University Medical Center, Geert Grooteplein 10Radboudumc, P.O. Box 9101, 6500 HB, Nijmegen, the Netherlands.
Objective: To improve B field homogeneity in prostate MR imaging and spectroscopy using a custom-designed 16-channel external local shim coil array.
Methods: In vivo prostate imaging was performed in seven healthy volunteers (mean age: 40.7 years) without bowel preparation.
J Cancer Res Clin Oncol
September 2025
Department of Radiology, Guizhou Provincial People's Hospital, No. 83 East Zhongshan Road, Guiyang, 550002, Guizhou, China.
Purpose: Targeted therapy with lenvatinib is a preferred option for advanced hepatocellular carcinoma, however, predicting its efficacy remains challenging. This study aimed to build a nomogram integrating clinicoradiological indicators and radiomics features to predict the response to lenvatinib in patients with hepatocellular carcinoma.
Methods: This study included 211 patients with hepatocellular carcinoma from two centers, who were allocated into the training (107 patients), internal test (46 patients) and external test set(58 patients).