Relapsing COVID-19 in a Patient With Non-Hodgkin Lymphoma on Chemotherapy

Hematologic malignancies and chemotherapy are risk factors for COVID-19 progression and mortality. Immunocompromised hosts, particularly those with severe B-cell depletion, can shed viable viruses for extended periods, which can lead to persistent infection. We present the case of a 73-year-old male with diffuse large B-cell lymphoma (stage IV-B) under curative immunochemotherapy with rituximab, cyclophosphamide, doxorubicin, vincristine, and prednisone (R-CHOP). After the first episode of mild COVID-19, he developed two severe relapses following the third and fourth cycles of R-CHOP. Lung CT scans performed in both episodes showed new-onset ground-glass infiltrates and fibrosis of previously affected pulmonary segments. In light of similar semiquantitative SARS-CoV-2 viral loads between episodes, without further risk exposure or microbiological findings, persistent COVID-19 with severe clinical relapses was assumed and successfully treated with polyclonal immunoglobulin and remdesivir. Whole-genome sequencing was performed in all samples, confirming the same specimen, which belonged to the B.1.177 lineage. This case stands out for the unusually long viral persistence and the various relapses of severe COVID-19 related to the worsening immune status with each immunochemotherapy cycle.info:eu-repo/semantics/publishedVersio

Globally Optimal Fetoscopic Mosaicking Based on Pose Graph Optimisation With Affine Constraints

Fetoscopic laser ablation surgery could be guided using a high-quality panorama of the operating site, representing a map of the placental vasculature. This can be achieved during the initial inspection phase of the procedure using image mosaicking techniques. Due to the lack of camera calibration in the operating room, it has been mostly modelled as an affine registration problem. While previous work mostly focuses on image feature extraction for visual odometry, the challenges related to large-scale reconstruction (re-localisation, loop closure, drift correction) remain largely unaddressed in this context. This letter proposes using pose graph optimisation to produce globally optimal image mosaics of placental vessels. Our approach follows the SLAM framework with a front-end for visual odometry and a back-end for long-term refinement. Our front-end uses a recent state-of-the-art odometry approach based on vessel segmentation, which is then managed by a key-frame structure and the bag-of-words (BoW) scheme to retrieve loop closures. The back-end, which is our key contribution, models odometry and loop closure constraints as a pose graph with affine warpings between states. This problem in the special Euclidean space cannot be solved by existing pose graph algorithms and available libraries such as G2O. We model states on affine Lie group with local linearisation in its Lie algebra. The cost function is established using Mahalanobis distance with the vectorisation of the Lie algebra. Finally, an iterative optimisation algorithm is adopted to minimise the cost function. The proposed pose graph optimisation is first validated on simulation data with a synthetic trajectory that has different levels of noise and different numbers of loop closures. Then the whole system is validated using real fetoscopic data that has three sequences with different numbers of frames and loop closures. Experimental results validate the advantage of the proposed method compared with baselines

Engineering education in a technology-dependent world

Education is the core of any nation development, of a community or personal. It is for sure a society that is depending on technology for deployment of information, communication, and network in real time. In a short period of time, social technologies have given social interactions the speed and scale of the Internet. It affects the way people work, live and make business.This work intends just to show a little of INTERTECH an event that is happening for more than 24 years and its contributions for engineering and technology education. An endeavor of manyscientists in order to provide a breeding ground for discussions about engineering and technology education so important aspects for the formation of professionals and researchers prepared to face the future. The theme of the congress is Engineering Education in a Technology-Dependent World and it has raised a considerable amount of papers of great valuable

AutoFB: Automating Fetal Biometry Estimation from Standard Ultrasound Planes

During pregnancy, ultrasound examination in the second trimester can assess fetal size according to standardized charts. To achieve a reproducible and accurate measurement, a sonographer needs to identify three standard 2D planes of the fetal anatomy (head, abdomen, femur) and manually mark the key anatomical landmarks on the image for accurate biometry and fetal weight estimation. This can be a time-consuming operator-dependent task, especially for a trainee sonographer. Computer-assisted techniques can help in automating the fetal biometry computation process. In this paper, we present a unified automated framework for estimating all measurements needed for the fetal weight assessment. The proposed framework semantically segments the key fetal anatomies using state-of-the-art segmentation models, followed by region fitting and scale recovery for the biometry estimation. We present an ablation study of segmentation algorithms to show their robustness through 4-fold cross-validation on a dataset of 349 ultrasound standard plane images from 42 pregnancies. Moreover, we show that the network with the best segmentation performance tends to be more accurate for biometry estimation. Furthermore, we demonstrate that the error between clinically measured and predicted fetal biometry is lower than the permissible error during routine clinical measurements

AutoFB: Automating Fetal Biometry Estimation from Standard Ultrasound Planes

During pregnancy, ultrasound examination in the second trimester can assess fetal size according to standardized charts. To achieve a reproducible and accurate measurement, a sonographer needs to identify three standard 2D planes of the fetal anatomy (head, abdomen, femur) and manually mark the key anatomical landmarks on the image for accurate biometry and fetal weight estimation. This can be a time-consuming operator-dependent task, especially for a trainee sonographer. Computer-assisted techniques can help in automating the fetal biometry computation process. In this paper, we present a unified automated framework for estimating all measurements needed for the fetal weight assessment. The proposed framework semantically segments the key fetal anatomies using state-of-the-art segmentation models, followed by region fitting and scale recovery for the biometry estimation. We present an ablation study of segmentation algorithms to show their robustness through 4-fold cross-validation on a dataset of 349 ultrasound standard plane images from 42 pregnancies. Moreover, we show that the network with the best segmentation performance tends to be more accurate for biometry estimation. Furthermore, we demonstrate that the error between clinically measured and predicted fetal biometry is lower than the permissible error during routine clinical measurements

Dimensionless Squared Jerk - An Objective Differential to Assess Experienced and Novice Probe Movement in Obstetric Ultrasound

Objective: Widely accepted, validated and objective measures of ultrasound competency have not been established for clinical practice. Outcomes of training curricula are often based on arbitrary thresholds, such as the number of clinical cases completed. We aimed to define metrics against which competency could be measured. Method: We undertook a prospective, observational study of obstetric sonographers at a UK University Teaching Hospital. Participants were either experienced in fetal ultrasound (n = 10, >200 ultrasound examinations) or novice operators (n = 10, <25 ultrasound examinations). We recorded probe motion data during the performance of biometry on a commercially available mid‐trimester phantom. Results: We report that Dimensionless squared jerk, an assessment of deliberate hand movements, independent of movement duration, extent, spurious peaks and dimension differed significantly different between groups, 19.26 (SD 3.02) for experienced and 22.08 (SD 1.05, p = 0.01) for novice operators, respectively. Experienced operator performance, was associated with a shorter time to task completion of 176.46 s (SD 47.31) compared to 666.94 s (SD 490.36, p = 0.0004) for novice operators. Probe travel was also shorter for experienced operators 521.23 mm (SD 27.41) versus 2234.82 mm (SD 188.50, p = 0.007) when compared to novice operators. Conclusion: Our results represent progress toward an objective assessment of technical skill in obstetric ultrasound. Repeating this methodology in a clinical environment may develop insight into the generalisability of these findings into ultrasound education

FetReg: Placental Vessel Segmentation and Registration in Fetoscopy Challenge Dataset

Fetoscopy laser photocoagulation is a widely used procedure for the treatment of Twin-to-Twin Transfusion Syndrome (TTTS), that occur in mono-chorionic multiple pregnancies due to placental vascular anastomoses. This procedure is particularly challenging due to limited field of view, poor manoeuvrability of the fetoscope, poor visibility due to fluid turbidity, variability in light source, and unusual position of the placenta. This may lead to increased procedural time and incomplete ablation, resulting in persistent TTTS. Computer-assisted intervention may help overcome these challenges by expanding the fetoscopic field of view through video mosaicking and providing better visualization of the vessel network. However, the research and development in this domain remain limited due to unavailability of high-quality data to encode the intra- and inter-procedure variability. Through the \textit{Fetoscopic Placental Vessel Segmentation and Registration (FetReg)} challenge, we present a large-scale multi-centre dataset for the development of generalized and robust semantic segmentation and video mosaicking algorithms for the fetal environment with a focus on creating drift-free mosaics from long duration fetoscopy videos. In this paper, we provide an overview of the FetReg dataset, challenge tasks, evaluation metrics and baseline methods for both segmentation and registration. Baseline methods results on the FetReg dataset shows that our dataset poses interesting challenges, offering large opportunity for the creation of novel methods and models through a community effort initiative guided by the FetReg challenge

Concentrações séricas de proteínas totais em ovinos alimentados com dietas contendo urucum em níveis crescentes de inclusão.

O presente estudo foi conduzido com o objetivo de se determinar as concentrações séricas de proteínas totais em ovinos alimentados com dietas contendo urucum integral em níveis crescentes de inclusão (0,0%; 9,72%; 22,07% e 34,32%) em função dos tempos de coleta pós-prandial. Foram utilizados dezesseis ovinos, machos, castrados alojados em gaiolas metabólicas recebendo dietas compostas de feno de pasto nativo, milho, farelo de soja e urucum integral. A coleta de sangue foi feita por pução na veia jugular em quatro tempos pré-estabelecidos (zero, duas, cinco e oito horas pós-prandial). Utilizou-se delineamento inteiramente casualizado em esquema de parcelas subdivididas, tendo nas parcelas os níveis de inclusão de urucum integral e nas sub-parcelas os tempos de coleta com quatro repetições. As médias obtidas foram comparadas pelo teste SNK (P<0,05). Não houve interação significativa entre os níveis de inclusão de urucum integral e os tempos de coleta de sangue. A inclusão de urucum integral as dietas apresenta restrições quanto sua utilização para ovinos. Abstract: This study was conducted in order to determine serum concentrations of total protein in sheep fed diets containing annatto integral in increasing levels of inclusion (0.0%, 9.72%, 22.07% and 34 32%) as a function of collection time post-prandial. We used sixteen sheep, castrated male housed in metabolic cages and fed diets composed of native grass hay, corn, soybean meal and whole annatto. Blood collection was done by netting in the jugular vein in four pre-set times (zero, two, five and eight hours postprandial). We used a randomized design in split plots, and plots the levels of annatto full inclusion in the sub-plots and the collection times with four replications. The averages were compared by SNK test (P <0.05). No significant interaction between the inclusions of annatto and full time for blood collection. The inclusion of full annatto diets has restrictions on its use for sheep

Goma manchada producida en Brasil para madera maciza estructural: una caracterización física y mecánica

Muchas maderas aún requieren una evaluación detallada para comprender su potencial estructural. La madera maciza de goma manchada se encuentra entre esas especies en las que también se requiere conocimiento de sus propiedades para la construcción. El presente estudio examinó 16 propiedades físico-mecánicas de la madera de goma manchada (Corymbia maculata) para promover su uso en la producción de edificios de base biológica más sostenibles. Utilizando el código de la norma brasileña NBR7190, se evaluaron dos niveles estables de contenido de humedad para conocer el comportamiento de la madera, el primero en el punto de saturación del 30 % y el segundo en el punto seco estandarizado del 12 %. Se recolectaron 13 árboles de goma manchada de diferentes edades de diferentes plantaciones en Brasil para obtener muestras de sus troncos. Así, se analizaron 1959 determinaciones para evaluar los resultados de la prueba t con un nivel de significancia del 5 %. De nuestros análisis significativos, estadísticos y comparativos, se confirmó que la goma manchada es apta para usos estructurales, siendo una madera potencial en regiones tropicales y subtropicales de América Latina