Morphological response of the red palm weevil,Rhynchophorus ferrugineus,to a transient low temperature analyzed by computer tomography and holographic microscopy

The red palm weevil (RPW), Rhynchophorus ferrugineus, is one of the worst palm pests worldwide. Our study aims to assess its internal and external morphological response to a sudden but transient decrease in the environmental temperature. Wild pre-pupae were subjected for 7 days to either low (5.0 ± 0.5 °C) or ambient temperature (23 ± 1 °C). Such conditions mimic a thermal anomaly happening in the larval stage most exposed to environmental factors. We quantified the changes undergone at: 1) the internal morphology, by X-Ray Computer Tomography (CT); 2) the 3-D integument’ architecture, by Digital Holographic Microscopy (DHM); and 3) the glucose in hemolymph as a potential endogenous cryoprotectant. From X-ray CT we found that both pre-pupae subjected to cold and those remaining at ambient temperature follow a development where their fat body content decreases while a thick and dense cuticle is formed. There was no difference between both groups in the rate of change of fat body/dense tissues. Nevertheless, the cold group presents a slight developmental delay at the level of hemolymph content. Through DHM we again obtained that pre-pupae subjected to cold have not experienced a stop in their development. However, a more obvious developmental delay is now observed in this group at the level of the integumental roughness. Finally, regarding glucose, we found similar levels in control and ambient temperature larvae, while it was clearly increased in 51,7% of those subjected to cold. Our whole results provide morphological and biochemical evidence showing that the larval-pupal transition of the RPW continues almost undisturbed even during the quiescent state induced by a sudden and severe cold event. Nevertheless, a certain developmental delay is observed in both internal and external morphology. Additionally, the increased glucose level only found in the cold group suggests that glucose is part of the RPW cold tolerance strategy.     

Meniscal lesion detection and characterization in adult knee MRI: A deep learning model approach with external validation

PurposeEvaluation of a deep learning approach for the detection of meniscal tears and their characterization (presence/absence of migrated meniscal fragment).MethodsA large annotated adult knee MRI database was built combining medical expertise of radiologists and data scientists’ tools. Coronal and sagittal proton density fat suppressed-weighted images of 11,353 knee MRI examinations (10,401 individual patients) paired with their standardized structured reports were retrospectively collected. After database curation, deep learning models were trained and validated on a subset of 8058 examinations. Algorithm performance was evaluated on a test set of 299 examinations reviewed by 5 musculoskeletal specialists and compared to general radiologists’ reports. External validation was performed using the publicly available MRNet database. Receiver Operating Characteristic (ROC) curves results and Area Under the Curve (AUC) values were obtained on internal and external databases.ResultsA combined architecture of meniscal localization and lesion classification 3D convolutional neural networks reached AUC values of 0.93 (95% CI 0.82, 0.95) for medial and 0.84 (95% CI 0.78, 0.89) for lateral meniscal tear detection, and 0.91 (95% CI 0.87, 0.94) for medial and 0.95 (95% CI 0.92, 0.97) for lateral meniscal tear migration detection. External validation of the combined medial and lateral meniscal tear detection models resulted in an AUC of 0.83 (95% CI 0.75, 0.90) without further training and 0.89 (95% CI 0.82, 0.95) with fine tuning.ConclusionOur deep learning algorithm demonstrated high performance in knee menisci lesion detection and characterization, validated on an external database.     

Determination of radiation dose and low-dose protocol for digital chest tomosynthesis using radiophotoluminescent (RPL) glass dosimeters

PurposeThis study aimed to determine a low-dose protocol for digital chest tomosynthesis (DTS).MethodsFive simulated nodules with a CT number of approximately 100 HU with size diameter of 3, 5, 8, 10, and 12 mm were inserted into an anthropomorphic chest phantom (N1 Lungman model), and then scanned by DTS system (Definium 8000) with varying tube voltage, copper filter thickness, and dose ratio. Three radiophotoluminescent (RPL) glass dosimeters, type GD-352 M with a dimension of 1.5 × 12 mm, were used to measure the entrance surface air kerma (ESAK) in each protocol. The effective dose (ED) was calculated using the recorded total dose-area-product (DAP). The signal-to-noise ratio (SNR) was determined for qualitative image quality evaluation. The image criteria and nodule detection capability were scored by two experienced radiologists. The selected low-dose protocol was further applied in a clinical study with 30 pulmonary nodule follow-up patients.ResultsThe average ESAK obtained from the standard default protocol was 1.68 ± 0.15 mGy, while an ESAK of 0.47 ± 0.02 mGy was found for a low-dose protocol. The EDs for the default and low-dose protocols were 313.98 ± 0.72 µSv and 100.55 ± 0.28 µSv, respectively. There were small non-significant differences in the image criteria and nodule detection scoring between the low-dose and default protocols interpreted by two radiologists. The effective dose of 98.87 ± 0.08 µSv was obtained in clinical study after applying the low-dose protocol.ConclusionsThe low-dose protocol obtained in this study can substantially reduce radiation dose while preserving an acceptable image quality compared to the standard protocol.     

Investigation of detector uniformity issues for Siemens Inspiration systems

PurposeDetector uniformity is an important parameter in digital mammography to guarantee a level of image quality adequate for early detection of breast cancer.Many problems with digital systems have been determined through the uniformity measurement, primarily as a result of incorrect flat-field calibration and artifacts caused by image receptor defects.The European guidelines suggest a method for the image uniformity assessment based on measurement of Signal-to-Noise ratio (SNR) and Pixel Value (PV) across a uniform image.Nineteen mammography systems from the same manufacturer installed in our organization incorporate an a-Se direct conversion detector. Since their installation, instability and inconsistency of image uniformity has attracted medical physicist attention.A number of different tests have been carried out in order to understand and establish reasons for this instability.MethodsThree different tests have been performed to evaluate the impact of the heel effect, detector temperature and ghosting on the uniformity images. All the tests are based on the acquisition of uniform images as suggested by the European Guidelines for Quality Assurance in Breast Cancer Screening and Diagnosis.ResultsResults show that an increase in detector temperature produces an increase of SNR and decrease of uniformity. A further decrease of uniformity ranging between 20% and 30% is due to the ghosting while a decrease of about 10% is due the heel effect.ConclusionsX-ray tube, system geometry and detector have an impact on the system uniformity and an understanding of the contribution of each is necessary in order to obtain comparable image quality among all the systems.     

Rhodopirellula aestuarii sp. nov., a novel member of the genus Rhodopirellula isolated from brackish sediments collected in the Tagus River estuary,Portugal

Bacteria within the phylum Planctomycetota are biologically relevant due to unique characteristics among prokaryotes. Members of the genus Rhodopirellula can be abundant in marine habitats, however, only six species are currently validly described. In this study, we expand the explored genus diversity by formally describing a novel species. The pink-coloured strain ICT_H3.1^T was isolated from brackish sediments collected in the Tagus estuary (Portugal) and a 16S rRNA gene sequence-based analysis placed this strain into the genus Rhodopirellula (family Pirellulaceae). The closest type strain is Rhodopirellula rubra LF2^T, suggested by a similarity of 98.4% of the 16S rRNA gene sequence. Strain ICT_H3.1^T is heterotrophic, aerobic and able to grow under microaerobic conditions. The strain grows between 15 and 37 °C, over a range of pH 6.5 to 11.0 and from 1 to 8% (w/v) NaCl. Several nitrogen and carbon sources were utilized by the novel isolate. Cells have an elongated pear-shape with 2.0 ± 0.3 × 0.9 ± 0.2 µm in size. Cells of strain ICT_H3.1^T cluster in rosettes through a holdfast structure and divide by budding. Younger cells are motile. Ultrathin cell sections show cytoplasmic membrane invaginations and polar fimbriae. The genome size is 9,072,081 base pairs with a DNA G + C content of 56.1 mol%. Genomic, physiological and morphological comparison of strain ICT_H3.1^T with its relatives suggest that it belongs to a novel species within the genus Rhodopirellula. Hence, we propose the name Rhodopirellula aestuarii sp. nov., represented by ICT_H3.1^T (=CECT30431^T = LMG32464^T) as the type strain of this novel species.16S rRNA gene accession number: GenBank = OK001858.Genome accession number: The Whole Genome Shotgun project has been deposited at DDBJ/ENA/GenBank under the accession JAMQBK000000000. The version described in this paper is version JAMQBK010000000.     

Uncertainties of synchrotron microCT-based digital volume correlation bone strain measurements under simulated deformation

Digital Volume Correlation (DVC) is used to measure internal displacements and strains in bone. Recent studies have shown that Synchrotron radiation micro-computed tomography (SR-microCT) can improve the accuracy and precision of DVC. However, only zero-strain or virtually-moved test have been used to quantify the DVC uncertainties, leading to potential underestimation of the measurement errors.In this study, for the first time, the uncertainties of a global DVC approach have been evaluated on repeated SR-microCT scans of bovine cortical bone (voxel size: 1.6 μm), which were virtually deformed for different magnitudes and along different directions.The results showed that systematic and random errors of the normal strain components along the deformation direction were higher than the errors along unstrained directions. The systematic percentage errors were smaller for larger virtual deformations. The random percentage error was in the order of 10% of the virtual deformation. However, higher errors were localized at the boundary of the volumes of interest, perpendicular to the deformation direction. When only the central region of the samples was considered (100 µm layers removed from the borders where the deformation was applied), the errors in the direction of virtual deformation were comparable to the errors in the unstrained directions.In conclusion, the method presented to estimate the uncertainties of DVC is suitable for testing anisotropic specimens as cortical bone. The good agreement between the uncertainties in measurements of strain components obtained with this approach and with the simpler zero-strain-test suggests that the latter is adequate in the tested deformation scenarios.     

Aerial surveying of grey seal breeding colonies on the Blasket Islands, Co. Kerry, the Inishkea Group, Co. Mayo and the Donegal Coast, Ireland

The status of Ireland's grey seal population and its relationship with that of Britain and Western Europe, are poorly understood. The existing population estimate for grey seals in Ireland is outdated and urgency exists to establish a reliable national population estimate for this species, listed as an Annex II species under the EU Habitats Directive. Prior to the initiation of a survey on a national scale, the success or otherwise of aerial techniques in surveying grey seal breeding habitat on the Irish coastline first needs to be established. Previously, surveys were boat-based and were susceptible to adverse weather conditions frequently encountered during the autumn breeding season. The feasibility of using aerial techniques to survey grey seal breeding colonies in Ireland was tested during the breeding season of 2003.     

Predictive habitat modelling to estimate petrel breeding colony sizes: Sooty shearwaters (Puffinus griseus) and mottled petrels (Pterodroma inexpectata) on Whenua Hou Island

Abstract

Between 2001 and 2006, we systematically sampled the entire coast of Whenua Hou, a rugged offshore island in southern New Zealand, to estimate the population densities of sooty shearwaters (Puffinus griseus) and mottled petrels (Pterodroma inexpectata) by counting the entrances of breeding burrows. A two‐step regression modelling process using binomial errors was used to predict the presence of a colony, and a normal general linear model was used to predict the density of entrances within colonies. Aerial photography, GIS and a Digital Elevation Model were used to extract relevant habitat and location variables, and a combination of both regression models was used to predict the density of breeding burrows within each 5.32 m² pixel on the island. This complex GIS and habitat prediction modelling approach gave population estimates very similar to a more traditional simple area extrapolation method and gave no improvement in precision. However, correction for the slope of the land increased our simple area estimates of population size by 11%. We estimate populations of sooty shearwater and mottled petrel breeding pairs at 173 000 (162 000–190 000) and 160 000 (123 000–197 000) respectively. Based on this number of breeding pairs, we calculate that Whenua Hou supports a total population of 868 000 (554 000–1 270 000) sooty shearwaters. Our estimate of the total mottled petrel population 202 000 pairs (162 000–242 000) is comparable with the only published estimate, but could be an underestimate because mottled petrels are sometimes found in large burrows. More research for robust estimation of population trends is needed to assess the conservation status of mottled petrels.