Qualitative and quantitative gastric ultrasound assessment in highly skilled regional anesthesiologists

Background Pulmonary aspiration is a major complication in anesthesia, and various studies have shown that gastric sonography can reliably provide valuable information relative to both the qualitative and quantitative aspects of gastric content. This study aimed to determine the accuracy of ultrasound assessment of gastric content compared between two novice anesthesiologist gastric sonographers. Methods This prospective cohort study of two anesthesiologists learning to perform qualitative and quantitative ultrasound assessment of gastric content on healthy volunteers was conducted at Siriraj Hospital (Bangkok, Thailand). This trial was registered with ClinicalTrials.gov (reg. no. NCT04760106). Results Of the 50 enrolled participants, three were excluded due to study protocol violation. Each anesthesiologist performed a qualitative assessment on 47 participants for an overall total of 94 scans. There were 15 males and 32 females (age 42 ± 11.7 years, weight 61.2 ± 13.1 kg, height 160.7 ± 7.3 cm, and BMI 23.6 ± 4.3 kg/m2). The overall success rate for all gastric content categories was approximately 96%. From antral cross-sectional area measurement, as the ingested volume increased, there was a tendency toward increased deviation from the actual ingested volume. Interrater agreement between anesthesiologists was analyzed using intraclass correlation coefficients (ICCs). A larger fluid volume was found to be associated with a lower level of agreement between the two anesthesiologists. The ICCs were 0.706 (95% CI: −0.125 to 0.931), 0.669 (95% CI: −0.254 to 0.920), 0.362 (95% CI: −0.498 to 0.807) for the 100 ml, 200 ml, and 300 ml fluid volumes, respectively. The mean duration to perform an ultrasound examination for each gastric content category and for the entire examination did not differ significantly between anesthesiologists (p > 0.05). Conclusion Our results indicate that qualitative ultrasound assessment of gastric content is highly accurate and can be easily learned. In contrast, quantification of gastric volume by novice gastric sonographers is more complex and requires more training. Trial registration ClinicalTrials.gov no. NCT04760106 Date registered on Feb 11, 2021. Prospectively registered.

The 24-chain core-shell nanostructure of wood cellulose microfibrils in seed plants

Wood cellulose microfibrils (CMFs) are the most abundant organic substance on earth, but their nanostructures are poorly understood. There are controversies regarding the glucan chain number (N) of CMFs during initial synthesis and whether they become fused afterwards. Here, we combined small-angle X-ray scattering (SAXS), solid-state nuclear magnetic resonance (ssNMR) and X-ray diffraction (XRD) analyses to resolve these controversies. We successfully developed SAXS measurement methods for the cross-section aspect ratio and area of the crystalline-ordered CMF core, which showed higher density than the semi-disordered shell. The 1:1 aspect ratio suggested that CMFs remain mostly segregated, not fused. The area measurement revealed the chain number in the core zone (Ncore). The ratio of ordered cellulose over total cellulose, termed Roc, was determined by ssNMR. Using the formula N = Ncore / Roc, we found that the majority of wood CMFs contain 24 chains, conserved between gymnosperm and angiosperm trees. The average wood CMF has a crystalline-ordered core of ~2.2 nm diameter and a semi-disordered shell of ~0.5 nm thickness. In naturally and artificially aged wood, we only observed CMF aggregation (contact without crystalline continuity) but not fusion (forming conjoined crystalline unit). This further argued against the existence of partially fused CMFs in new wood, overturning the recently proposed 18-chain fusion hypothesis. Our findings are important for advancing wood structural knowledge and more efficient utilization of wood resources in sustainable bio-economies.

An integrated analysis of clinical and morphometric indications of atrophic forms of age-related macular degeneration

The atrophic form of late age-related macular degeneration (AMD) is a common cause of severe vision loss. Recently, a new classification system has been proposed, which identifies two types of atrophy in the late stage of AMD that require a more detailed study: (1) drusenassociated geographic atrophy (GA), which is the final stage of progression of dry AMD, and (2) macular atrophy (MA), which occurs in wet AMD, including the period of AMD treatment with angiogenesis inhibitors. Purpose: an integrated analysis of clinical and morphometric signs of atrophic AMD forms. Material and methods. 48 people (61eyes) aged 48–84 with GA (group 1) and MA (group 2) and a control group, recruited from age-matching 25 healthy volunteers (35 eyes), underwent standard ophthalmological examinations, fundus autofluorescence (FAF) with lesion area measurement, fundus photography, optical coherence tomography (OCT) in the standard mode and Enhanced Depth Imagine Mode, Multicolor, and OCT angiography. Results. The comparative analysis of two atrophic AMD forms showed that in GA eyes, foci of atrophy capturing the fovea were significantly more common, while, contrariwise in MA eyes atrophic foci not capturing the fovea were more frequent (p < 0.05). Photoreceptor tubulation was diagnosed mainly in eyes with GA (p < 0.05). The morphometric analysis showed a significant decrease in the subfoveal thickness of the choroid in the groups with GA and MA as compared to the control (p < 0.05), whilst no significant differences between two groups were noted. The assessment of the frequency of occurrence of types of fundus AF patterns in groups 1 and 2 followed by a comparative analysis, showed the presence of all types of patterns in GA patients, including the heterogeneous and the bordering pattern (p < 0.05). In the MA group, diffuse and focal types of patterns were revealed, while the frequency of the diffuse pattern turned out to be significantly more frequent (p < 0.05). Conclusion. The integrated analysis revealed the main semiological signs and morphometric parameters, their features and prevalence in GA and MA, which may have diagnostic and prognostic importance for the management and treatment of patients with AMD.

Modelling Wind Damage to Southeastern U.S. Trees: Effects of Wind Profile, Gaps, Neighborhood Interactions, and Wind Direction

Tree damage from a variety of types of wind events is widespread and of great ecological and economic importance. In terms of areas impacted, tropical storms have the most widespread effects on tropical and temperate forests, with southeastern U.S. forests particularly prone to tropical storm damage. This impact motivates attempts to understand the tree and forest characteristics that influence levels of damage. This study presents initial findings from a spatially explicit, individual-based mechanistic wind severity model, ForSTORM, parameterized from winching research on trees in southeastern U.S. This model allows independent control of six wind and neighborhood parameters likely to influence the patterns of wind damage, such as gap formation, the shape of the vertical wind profile, indirect damage, and support from neighbors. We arranged the subject trees in two virtual stands orientations with identical positions relative to each other, but with one virtual stand rotated 90 degrees from the other virtual stand – to explore the effect of wind coming from two alternative directions. The model reproduces several trends observed in field damage surveys, as well as analogous CWS models developed for other forests, and reveals unexpected insights. Wind profiles with higher extinction coefficients, or steeper decrease in wind speed from canopy top to lower levels, resulted in significantly higher critical wind speeds, thus reducing level of damage for a given wind speed. Three alternative formulations of wind profiles also led to significant differences in critical wind speed (CWS), although the effect of profile was less than effect of different extinction coefficients. The CWS differed little between the two alternative stand orientations. Support from neighboring trees resulted in significantly higher critical wind speeds, regardless of type of wind profile or spatial arrangement of trees. The presence or absence of gaps caused marginally significant different in CWS, while inclusion of indirect damage along with direct damage did not significantly change CWS from those caused by direct damage alone. Empirical research that could most benefit this modelling approach includes improving crown area measurement, refining drag coefficients, and development of a biomechanical framework for neighbor support.

Identification and Area Calculation of the Egg Mass of Spodoptera Frugiperda Based on Faster-RCNN

Spodoptera frugiperda is a migratory and destructive crop pest. The number of eggs is an important method to evaluate the pest situation, which can be estimated by the area of egg mass. The traditional manual method is inefficient, but the new method of egg mass image recognition improves the efficiency of eggs number estimation. In this paper, the optimized Faster-RCNN target detection algorithm was used to recognize the egg mass image of Spodoptera frugiperda. The Maximum Between-Class Variance method (Otsu) was used for threshold segmentation to obtain the position, shape and size of the egg mass and calculate the area of the egg mass. The mean value of the relative error of the egg mass area in the test samples was -0.02032, and the minimum value was -0.00047. The experimental results show that the egg area calculation method proposed in this paper is fast and accurate, which can meet the requirements of egg area measurement.

Calculation of northern hemisphere sea ice area using recurrent neural networks

Ice covering water surfaces causes difficulties for ship traffic in the northern regions. Developing a sustainable logistics system that describes and manages ship traffic requires consideration of many factors, one of which is the area of sea ice covering the waterways. Most of the volume of sea ice in the northern hemisphere is concentrated in the Arctic zone. The paper describes the process and results of data preparation and development of a recurrent neural network to determine the value of ice area change in the next 50 days relative to the last day of sea ice area measurement. The prediction is made based on the previous 30 measured values of sea ice area and a user-specified value of the day for which the prediction will be made. The work uses NSIDC open dataset on sea ice area for the northern hemisphere. This model allows us to calculate the change of sea ice area for 1 day ahead with an accuracy of 0.581%. For the 50-day prediction of ice area, the accuracy is 4.017%.