Mass Identification Research Articles

Probabilistic damage detection and identification of coupled structural parameters using Bayesian model updating with added mass

Damage detection inevitably involves uncertainties originated from measurement noise and modeling error. It may cause incorrect damage detection results if not appropriately treating uncertainties. To this end, vibration-based Bayesian model updating (VBMU) is developed to utilize vibration responses or modal parameters to estimate structural parameters and the associated uncertainties of those estimates. However, traditional VBMU often assumes that mass is well known and invariant because simultaneous identification of mass and stiffness may yield an unidentifiable problem due to the coupling effect of the mass and stiffness. In addition, the posterior PDF in VBMU is usually approximated by single Markov Chain Monte Carlo (MCMC), leading to a low acceptance rate and limited capability for complex structures. This paper proposed a novel VBMU to address the coupling effect and identify mass and stiffness by adding known mass. Two vibration data sets are acquired from original and modified systems with added mass, giving the new characteristic equations. Then, the posterior PDF is reformulated by measured data and predicted counterparts from new characteristic equations. For efficiently approximating the posterior PDF, Differential Evolutionary Adaptive Metropolis (DREAM) algorithm is adopted to draw samples by running multiple Markov chains parallelly to enhance acceptance rate and sufficiently explore possible solutions. Finally, a numerical example with a ten-story shear building and a laboratory-scale three-story frame structure are utilized to demonstrate the efficacy of the proposed VBMU framework. The results show that the proposed method can successfully identify both mass and stiffness, and their uncertainties. Reliable probabilistic damage detection can also be achieved.

Biogeochemical Characteristics of Western Tropical Atlantic Ocean Water Masses

Water masses are commonly identified according to their conservative parameters. However, there are also studies that use non-conservative parameters, together with the conservative ones, to refine the water masses identification. The aim of this study was to analyze the chemical properties of the water masses in the western tropical Atlantic Ocean (WTAO) according to their inorganic nutrient concentration: nitrate-NO3–, phosphate-PO43–, and silicic acid-Si(OH)4, to set a regional descriptive framework of the water column in view of future comparative studies. We collected full-depth water column samples from 18 oceanographic stations from a latitudinal transect along 38°W, from 02°S to 15°N during the PIRATA-BR XVII and XVIII campaigns, in November 2017 and 2018. We have also used the regional data available from GLODAPv.2 data product to improve the water masses characterization. Six water masses were identified in the region based on their values of potential temperature, salinity, potential density, and neutral density observed in the study area according to the CTD-O2 data: Tropical Surface Water (TSW); South and North Atlantic Central Water (SACW and NACW, respectively); Antarctic Intermediate Water (AAIW); North Atlantic Deep Water (NADW); and Antarctic Bottom Water (AABW). Regarding the nutrient content within each water mass, our results showed that TSW corresponds to a surface oligotrophic water; NACW and SACW have intermediate nutrient concentration values between TSW and AAIW; AAIW showed the highest concentration of phosphate-PO43– (~ 1.35 µmol kg–1) and nitrate-NO3– (~30 µmol kg–1); AABW, on the other hand, was the water mass with the highest silicic acid-Si(OH)4 concentration (~ 80 µmol kg–1), as well as high nitrate-NO3– (~ 25 µmol kg–1) and phosphate-PO43– (~ 1.80 µmol kg–1) concentrations. Additionally, the water column between 300 and 650 m displays an increase in phosphate-PO43– concentrations north of 5oN, associated to a low dissolved oxygen area coupled to the North Equatorial Under Current (NEUC). Long-term, sustained hydrographic and ocean biogeochemistry observations are key to understand how climate change is affecting the ocean, and this study is a contribution to that.

Classification and Reconstruction of Biomedical Signals Based on Convolutional Neural Network.

The efficient biological signal processing method can effectively improve the efficiency of researchers to explore the work of life mechanism, so as to better reveal the relationship between physiological structure and function, thus promoting the generation of major biological discoveries; high-precision medical signal analysis strategy can, to a certain extent, share the pressure of doctors' clinical diagnosis and assist them to formulate more favorable plans for disease prevention and treatment, so as to alleviate patients' physical and mental pain and improve the overall health level of the society. This article in biomedical signal is very representative of the two types of signals: mammary gland molybdenum target X-ray image (mammography) and the EEG signal as the research object, combined with the deep learning field of CNN; the most representative model is two kinds of biomedical signal classification, and reconstruction methods conducted a series of research: (1) a new classification method of breast masses based on multi-layer CNN is proposed. The method includes a CNN feature representation network for breast masses and a feature decision mechanism that simulates the physician's diagnosis process. By comparing with the objective classification accuracy of other methods for the identification of benign and malignant breast masses, the method achieved the highest classification accuracy of 97.0% under different values of c and gamma, which further verified the effectiveness of the proposed method in the identification of breast masses based on molybdenum target X-ray images. (2) An EEG signal classification method based on spatiotemporal fusion CNN is proposed. This method includes a multi-channel input classification network focusing on spatial information of EEG signals, a single-channel input classification network focusing on temporal information of EEG signals, and a spatial-temporal fusion strategy. Through comparative experiments on EEG signal classification tasks, the effectiveness of the proposed method was verified from the aspects of objective classification accuracy, number of model parameters, and subjective evaluation of CNN feature representation validity. It can be seen that the method proposed in this paper not only has high accuracy, but also can be well applied to the classification and reconstruction of biomedical signals.

Assessment of the Quality of Injectable Antibiotics in Benin.

Substandard and falsified medicines are an enormous threat to global health. Poor quality antibiotic preparations contribute to the development of antimicrobial resistance. In surgery, where the occurrence of healthcare-associated infections is high, healthcare teams need to rely on the quality of antibiotic prophylaxis to prevent infections. We assessed the quality of antibiotics used for surgical infection prophylaxis in Benin. Thirty-three samples were collected from six hospitals located in various departments in Benin. The antibiotics (powders for injection: amoxicillin + clavulanic acid, ampicillin, ceftriaxone; solutions for injection: ciprofloxacin, gentamicin, metronidazole) were assessed using visual inspection, pharmacotechnical tests (including uniformity of mass, pH measure, sterility test, and active pharmaceutical ingredient identification), and assay tests (including a simple analytical method thin layer chromatography) and complex analytical techniques (ultraviolet-visible spectrophotometry, high-performance liquid chromatography-diode-array detection, conductometry). Because the material needed for the methods recommended by the pharmacopeias to assess the dosage of gentamicin was not available, we developed and validated a conductometry method. Results showed that 97% (n = 32) of the samples passed visual inspection; 100% (n = 33) of the samples passed the pharmacotechnical tests, identification of active ingredients, and sterility test; 88% (n = 29) passed the test for percentage of active pharmaceutical ingredients. Overall, 15% of the samples did not pass the quality test (3% on visual inspection and 12% for excess active ingredients). Although most of the samples passed the quality tests, it appears important to perform routine quality control for intravenous medicines.

Development and Validation of a Single Step GC/MS Method for the Determination of 41 Drugs and Drugs of Abuse in Postmortem Blood

A toxicology laboratory often receives a high number of samples from cases (autopsies or clinical) that may require the quick delivery of trustworthy, accurate results. Thus, there is a great need for a fast and reliable method that is capable of identifying and determining a large number of drugs and drugs of abuse in biological matrices, and especially in blood. In the present study, we describe the development of a fast and simple gas chromatography–mass spectrometry (GC-MS) method for the determination of 41 drugs and drugs of abuse (DOA) in blood. Sample pre-treatment by alkaline liquid–liquid extraction (LLE) was studied through the utilization of different solvents and solvent-to-sample ratios (v/v), which aimed to achieve a greater extraction efficiency and detection sensitivity with a decreased need for large sample volumes. Butyl acetate with a sample-to-solvent ratio of 4:1 (1 mL blood: 0.25 mL butyl acetate) was the most efficient. The method was validated for all analytes, and the evaluation parameters were within the acceptance criteria. The coefficient of determination (R2) was between 0.9934 and 1, the limits of detection (LODs) ranged between 1 ng/mL and 113 ng/mL, and the limits of quantification (LOQs) were between 4 ng/mL and 375 ng/mL for all analytes. The determinations were accurate (accuracy% from 84% to 114%) and precise (RSD% from 0.66% to 14.8% for low concentrations). Deconvolution Reporting Software (DRS) for GC-MS was optimized and applied for data analysis to enhance the identification potential, thereby avoiding false identifications (false positives) and increased productivity. The NIST Automated Mass Spectral Deconvolution and Identification Software (AMDIS) and the analytical utility Retention Time Lock (RTL) Database Library assisted in data evaluation. The method was applied to 89 postmortem cases (history of mental disorders and use of psychiatric pharmaceuticals) in which diazepam (0.13 to 4.34 μg/mL), citalopram (0.04 to 0.24 μg/mL), alprazolam (0.01 to 0.12 μg/mL), olanzapine (0.009 to 0.083 μg/mL), mirtazapine (0.01 to 0.33 μg/mL), venlafaxine (0.006 to 0.92 μg/mL), haloperidol (0.007 to 0.13 μg/mL), and zolpidem (0.01 to 0.16 μg/mL) were successfully quantitated.

Breast Cancer Classification Using FCN and Beta Wavelet Autoencoder.

In this paper, a new classification approach of breast cancer based on Fully Convolutional Networks (FCNs) and Beta Wavelet Autoencoder (BWAE) is presented. FCN, as a powerful image segmentation model, is used to extract the relevant information from mammography images. It will identify the relevant zones to model while WAE is used to model the extracted information for these zones. In fact, WAE has proven its superiority to the majority of the features extraction approaches. The fusion of these two techniques have improved the feature extraction phase and this by keeping and modeling only the relevant and useful features for the identification and description of breast masses. The experimental results showed the effectiveness of our proposed method which has given very encouraging results in comparison with the states of the art approaches on the same mammographic image base. A precision rate of 94% for benign and 93% for malignant was achieved with a recall rate of 92% for benign and 95% for malignant. For the normal case, we were able to reach a rate of 100%.

Retrospective Analysis of 136 Patients Operated for a Parotid Global Tumor.

Background:While salivary gland tumors constitute 5-6% of all head and neck tumors, they constitute 2-3% of all trunk tumors. About 3.8 per 100,000 of parotid tumors are diagnosed in the US each year, about 1300 to 1600 cases. The salivary gland cancer rate is 0.9 per 10000. The frequency of salivary gland tumors varies according to localization.Objective:In our study, we aimed to evaluate retrospectively the histopathological results, incidence, surgical treatment modalities and complications of parotid tumors operated in our clinic.Methods:We examined the patients who were operated for parotid gland tumor. The files of 136 patients who were admitted to the Otorhinolaryngology department of Dicle University Medical Faculty Hospital between January 2010 and April 2020 due to a parotid mass and underwent parotidectomy and whose pathology results were reported as benign or malignant parotid tumors were retrospectively scanned and included in the study. Patients’ age, gender, FNAB cytology result, type of surgery, histopathological results after surgery and complications after surgical treatment were recorded.Results:A total of 136 patients, 73 (53.7%) male and 63 (46.3%) female, were included in the study. The mean age of the patients was 48.26±17.37 (min=14, max=83) years. Superficial parotidectomy was performed in 108 (79.4%) patients and total parotidectomy was performed in 28 (20.6%) patients. According to the histopathological results after surgery, 108 (79.4%) benign tumors and 28 (20.6%) malignant tumors were diagnosed. Accordingly, pleomorphic adenoma (47.8%) was the second most common with 65 patients, followed by Whartin tumor (25.7%) with 35 patients. The sensitivity (sensitivity) of FNAB was 85.2%, and the specificity (specificity) was 96.2%. The accuracy of FNAB was found to be 94.0%.Conclusion:Good identification of the parotid mass preoperatively, together with both FNAB and radiological imaging methods, gains much more value in differentiating malignant and benign pathologies. While superficial parotidectomy is mostly sufficient in benign tumors, total parotidectomy-radical parotidectomy in malignant tumors and neck dissection should be considered in high-grade tumors even if there is no neck metastasis. Patients should be evaluated for RT and CT according to the tumor type after surgery.

Accurate Mass Identification of an Interfering Water Adduct and Strategies in Development and Validation of an LC-MS/MS Method for Quantification of MPI8, a Potent SARS-CoV-2 Main Protease Inhibitor, in Rat Plasma in Pharmacokinetic Studies.

MPI8, a peptidyl aldehyde, is a potent antiviral agent against coronavirus. Due to unique tri-peptide bonds and the formyl functional group, the bioassay of MPI8 in plasma was challenged by a strong interference from water MPI8. Using QTOF LC-MS/MS, we identified MPI8•H2O as the major interference form that co-existed with MPI8 in aqueous and biological media. To avoid the resolution of MPI8 and MPI8•H2O observed on reverse phase columns, we found that a Kinetex hydrophilic interaction liquid chromatography (HILIC) column provided co-elution of both MPI8 and MPI8•H2O with a good single chromatographic peak and column retention of MPI8 which is suitable for quantification. Thus, a sensitive, specific, and reproducible LC-MS/MS method for the quantification of MPI8 in rat plasma was developed and validated using a triple QUAD LC-MS/MS. The chromatographic separation was achieved on a Kinetex HILIC column with a flow rate of 0.4 mL/min under gradient elution. The calibration curves were linear (r2 > 0.99) over MPI8 concentrations from 0.5–500 ng/mL. The accuracy and precision are within acceptable guidance levels. The mean matrix effect and recovery were 139% and 73%, respectively. No significant degradation of MPI8 occurred under the experimental conditions. The method was successfully applied to a pharmacokinetic study of MPI8 after administration of MPI8 sulfonate in rats.

Polar and non-polar fraction from Origanum vulgare spp. hirtum methanolic extract – differences in their bioactivity on Chlamydomonas reinhardtii test system

Aim: To compare the bioactivity of both polar and non-polar fraction of Origanum vulgare spp. hirtum methanolic extract on Chlamydomonas reinhardtii. Material and methods: The polar and non-polar fractions were derived from aerial parts of Origanum vulgare ssp. hirtum, collected during the flowering stage from the ex-situ collection of IBER-BAS. GC/MS analysis of both fractions was done following the standard protocol. The measured mass spectra were deconvoluted by the Automated Mass Spectral Deconvolution and Identification System (AMDIS), before comparison with the databases. Chlamydomonas reinhardtii 137C+ (WT) was used as a test system. Spot-test, cell survival fraction (SF), test of “visible mutations” and CFGE (for measurement of induced DNA double-strand breaks (DSBs)) were applied. Results: The polar fraction did not possess genotoxic, mutagenic as well as DNA-damaging effect. The situation with the non-polar fraction was quite different. Even at the lowest concentration of 250 ppm, cell survival was decreased by 60% (SF = 0.41 ± 0.08). Treatment with concentrations equal to/or greater than 500 ppm resulted in around 100% lethality. A mild mutagenic effect was obtained for the concentration of 250 ppm non-polar fraction (IM = 4.83 ± 0.004). Well-expressed and concentration-dependent induction of DSBs for even the strong DNA fragmentation was observed after the treatment with the non-polar fraction. Conclusions: The different bioactivity of the two fractions correlated well with their different chemical composition. The polar fraction, rich in sugars, organic acids and flavonoid glycosides, did not possess genotoxic and mutagenic potential. The strong genotoxic potential of the non-polar fraction might be related to carvacrol content (37.08%), which is not present in the composition of the polar fraction. To the best of our knowledge, this study provides the first information that the carvacrol-rich non-polar fraction of Origanum vulgare spp. hirtum methanolic extract possesses genotoxic, mutagenic and DNA damaging effect on some low eukaryotes, such as C. reinhardtii. Further experiments with carvacrol should be done in order to clarify the exact mechanism of action.

Elasmobranch diversity across a remote coral reef atoll revealed through environmental DNA metabarcoding

Abstract As elasmobranchs are becoming increasingly threatened, efficient methods for monitoring the distribution and diversity of elasmobranch populations are required. Environmental DNA (eDNA) metabarcoding is a progressively applied technique that enables mass identification of entire communities and is an effective method for the detection of rare and elusive species. We performed an eDNA metabarcoding survey for fish communities around a coral reef atoll in the Chagos Archipelago (Central Indian Ocean) and assessed the diversity and distribution of elasmobranch species detected within these communities. Our eDNA survey detected 353 amplicon sequence variants (ASVs) attributed to fishes, 12 of which were elasmobranchs. There were no differences in fish communities based on the presence and absence of ASVs between sample depth (surface and 40 m) or sampling habitat, but communities based on read abundance were significantly different between habitats. The dominant elasmobranch species were grey reef (Carcharhinus amblyrhynchos) and silvertip (C. albimarginatus) sharks, and elasmobranch communities were significantly different between sampling depth and habitat. Overall, we find that eDNA metabarcoding can be used to reveal the diversity of elasmobranchs within broader taxonomic assays, but further research and development of targeted metabarcoding primers may be required before it can be integrated into a toolkit for monitoring these species.

Optimal energy management of fuel cell hybrid electric vehicle based on model predictive control and on-line mass estimation

Energy management strategies with prediction message show great potential in optimizing control objectives for fuel cell hybrid vehicles. This paper presents a novelty model-predictive-control based energy management framework for fuel cell commercial vehicle, in which the vehicle mass is firstly introduced as a variable parameter for controller. A vehicle mass identification model is established and embed in the framework based on recursive least square algorithm, and the influence of variable algorithm parameters on estimator is evaluated. Then the effects of mass varying on vehicle performance is talked about in detail. In addition, the performance for different drive cycles on different loaded is also given. The simulation results show that the fuel consumption is positively correlated with the mass identification error, and the designed controller can reduce the additional fuel consumption to around 0.1%, which is much batter to the deterministic parameters scheme. Finally, the shortcomings of the designed controller are given. This paper provides a reliable theoretical basis to address varying-mass vehicle energy management problems.

THE URGENCY TO IDENTIFY LOW MUSCLE MASS AMONG ELDERLY: COMMUNITY SERVICE IN NURSING HOME

Introduction: Decreased muscle mass in the elderly often occurs due to the aging process. Identification of muscle mass needs to be done to optimize the health status of the elderly. So, this article will identify muscle mass in the elderly. Methods: Community service was carried out to 54 elderly people in a nursing home. For the elderly, health checks are carried out including body composition measurements, especially muscle mass, as well as nutrition education and counseling. The inclusion criteria for the elderly who take part in the activity include (1) healthy and able to stand; (2) fully aware; (3) not bed rest; (4) able to communicate and cooperative. The data presented include age, length of stay, body mass index, and body composition, namely muscle mass. Results: About three-quarters of the elderly are women and have lived in a nursing home for approximately 3 years. The average nutritional status of the elderly is normal (21.6 ± 4.5 kg/m2). As many as 96.3% of the elderly have a low muscle mass index and 53.7% of the elderly have a high fat mass. The muscle mass of older men was higher than that of women (26.2 ± 2.8 vs 21.9 ± 1.9). Conclusion: Almost all the elderly has low muscle mass due to the physiological aging process and decreased activity of the elderly in using muscles. . Elderly women were observed to have lower muscle mass index than that of men. Identification of muscle mass strength is also needed to find out more about sarcopenia in the elderly.

Establishing an Ultrasound Screening Protocol for Chronic Liver Disease with a Handheld Device: A Pilot Project in Southern Ethiopia.

Chronic liver disease (CLD) poses significant challenges in the developing world. The prevalence of this problem and the health burden on local health services are not well understood. The diagnosis and monitoring of CLD are difficult in these settings because of limited access to expensive imaging with limited mobility and/or liver biopsy. The aim of this project was to develop and implement an efficient evidence-based robust ultrasound protocol for the assessment of chronic liver disease using a hand-held ultrasound device that could be effectively used in the developing world. A protocol was established using scoring systems that have established accuracy for the diagnosis of hepatic fibrosis/cirrhosis and hepatic steatosis. Included in the protocol was the identification of hepatic masses, portal venous enlargement, hepatic size and splenic size. Hepatic steatosis was common, identified in 46 of 94 participants (49%). Hepatic fibrosis was observed in only 13 of 94 participants (14%). A significant limitation of the methodology was the inability to validate the results with biopsy or other forms of cross-sectional imaging. The protocol was successfully implemented in a community in a rural setting in South Ethiopia with a mean examination time of around 6 min. It is feasible to use handheld ultrasound for the screening of CLD in remote settings. This project provides an evidence-based framework for further studies in this area.

ASO Visual Abstract: Fluorescence Imaging-Guided Identification of Thymic Masses Using Low-Dose Indocyanine Green

ASO Visual Abstract: Fluorescence Imaging-Guided Identification of Thymic Masses Using Low-Dose Indocyanine Green

Identification of medium mass (A=60–80) ejectiles from 15 MeV/nucleon peripheral heavy-ion collisions with the MAGNEX large-acceptance spectrometer

An approach to identify medium-mass ejectiles from peripheral heavy-ion reactions in the energy region of 15 MeV/nucleon is developed for data obtained with a large acceptance magnetic spectrometer. This spectrometer is equipped with a focal plane multidetector, providing position, angle, energy loss and residual energy of the ions along with measurement of the time-of-flight. Ion trajectory reconstruction is performed at high order and ion mass is obtained with a resolution of better than 1/150. For the unambiguous particle identification however, the reconstruction of both the atomic number Z and the ionic charge q of the ions is critical and it is suggested, within this work, to be performed prior to mass identification. The new proposed method was successfully applied to MAGNEX spectrometer data, for identifying neutron-rich ejectiles related to multinucleon transfer generated in the 70Zn+64Ni collision at 15 MeV/nucleon. This approach opens up the possibility of employing heavy-ion reactions with medium-mass beams below the Fermi energy (i.e., in the region 15–25 MeV/nucleon) in conjunction with large acceptance ray tracing spectrometers, first, to study the mechanism(s) of nucleon transfer in these reactions and, second, to produce and study very neutron-rich or even new nuclides in previously unexplored regions of the nuclear landscape.

Fluorescence Imaging-Guided Identification of Thymic Masses Using Low-Dose Indocyanine Green.

Indocyanine green (ICG) fluorescence imaging has been used to detect many types of tumors during surgery; however, there are few studies on thymic masses and the dose and time of ICG injection have not been optimized. We aimed to evaluate the optimal ICG injection dose and timing for detecting thymic masses during surgery. Forty-nine consecutive patients diagnosed with thymic masses on preoperative computed tomography (CT) and scheduled to undergo thymic cystectomy or thymectomy were included. Patients were administered 1, 2, or 5mg/kg of ICG at different times. Thymic masses were observed during and after surgery using a near-infrared fluorescence imaging system, and the fluorescence signal tumor-to-normal ratio (TNR) was analyzed. Among the 49 patients, 14 patients with thymic cysts showed negative fluorescence signals, 33 patients with thymoma or thymic carcinoma showed positive fluorescence signals, and 2 patients showed insufficient fluorescence signals. The diagnosis of thymic masses based on CT was correct in 32 (65%) of 49 cases; however, the differential diagnosis of thymic masses based on NIR signals was correct in 47 of 49 cases (96%), including 14 cases of thymic cysts (100%) and 33 cases of thymomas or thymic carcinomas (94%). In addition, TNR was not affected by the time or dose of ICG injection, histological type, stage, or tumor size. Low-dose intravenous injection of ICG at flexible time can detect thymic tumors. In addition, thymic cysts can be distinguished from thymomas or thymic carcinomas during surgery by the absence of ICG fluorescence signals.

Mass identification of multiple particles on a doubly clamped resonator

The shift of resonant frequencies is the working mechanism of a mass resonator sensor. The shift is due to the adsorption of particles, which can change the mass, stiffness and damping of the sensor. Based on the Timoshenko beam model, an analytical model and mathematical solution are proposed to explain the frequency shifts due to the adsorption of multiple particles. The model shows a better accuracy in the scenarios of the high order resonance, the vibration in the viscous environment and under high tension. The inverse problem of identifying multi-particle mass is solved by an iteration algorithm, whose performance is also evaluated for the measured noise and adsorption areas. The mass identification of multiple particles shows a better sensitivity and robustness than that of single particle, which is somewhat surprising but beneficial to mass sensing. The results in this study provide a theoretical basis for the mass identification of multiple particles and are of some help to the practical application.

Low muscle mass in COVID-19 critically-ill patients: Prognostic significance and surrogate markers for assessment

IntroductionLow muscle mass is a common condition in the critically ill population and is associated with adverse clinical outcomes. The primary aim of this study was to analyze the prognostic significance of low muscle mass using computed tomography (CT) scans in COVID-19 critically ill patients. A second objective was to determine the accuracy and agreement in low muscle mass identification using diverse markers compared to CT as the gold standard.MethodsThis was a prospective cohort study of COVID-19 critically ill patients. Skeletal muscle area at the third lumbar vertebra was measured. Clinical outcomes (intensive care unit [ICU] and hospital length of stay [LOS], tracheostomy, days on mechanical ventilation [MV], and in-hospital mortality) were assessed. Phase angle, estimated fat-free mass index, calf circumference, and mid-upper arm circumference were measured as surrogate markers of muscle mass.ResultsEighty-six patients were included (mean age ± SD: 48.6 ± 12.9; 74% males). Patients with low muscle mass (48%) had a higher rate of tracheostomy (50 vs 20%, p = 0.01), prolonged ICU (adjusted HR 0.53, 95%CI 0.30–0.92, p = 0.024) and hospital LOS (adjusted HR 0.50, 95% CI 0.29–0.86, p = 0.014). Bedside markers of muscle mass showed poor to fair agreement and accuracy compared to CT-assessed low muscle mass.ConclusionLow muscle mass at admission was associated with prolonged length of ICU and hospital stays. Further studies are needed to establish targeted nutritional interventions to halt and correct the catabolic impact of COVID-19 in critically ill patients, based on standardized and reliable measurements of body composition.

Imaging of Prenatal and Neonatal Intra-abdominal Genitourinary Tumors: a Review of the Literature.

Our goal was to summarize current literature related to imaging of intra-abdominal genitourinary tumors diagnosed in the prenatal or neonatal period. Our specific interests included modalities used, diagnoses made, changing incidence of tumor detection, and proposed future uses of these imaging modalities. Fetal and neonatal MRI have been used as an adjunct to ultrasound for better characterization and assessment of congenital mesoblastic nephroma, juvenile granulosa cell tumor, and other tumors. Despite recent literature describing fetal and neonatal MRI, it is not yet possible to determine whether its use is changing the incidence of tumor detection. Improvements in imaging technology, specifically the use of fetal MRI, have allowed for earlier identification of genitourinary masses with improved capability for diagnosis, surveillance, surgical planning, and sometimes prenatal treatment of the malignancy and related diagnoses, with a goal of preventing pregnancy and delivery complications.

Twin Reversed Arterial Perfusion Sequence.

Twin Reversed Arterial Perfusion Sequence.