Size Measurements Research Articles

A Meta-Analysis of Self-Management Interventions in Teaching Daily Living Skills to Autistic Individuals.

The current study aimed to conduct a systematic review and meta-analysis of self-management interventions for teaching daily living skills to autistic individuals. This study accessed the corresponding studies by doing a search in six databases. 14 articles and one dissertation met the inclusion criteria. The included studies were first analyzed descriptively and coded according to quality indicators using What Works Clearinghouse (WWC) standards. Second, the effect sizes of the included studies were calculated using two different effect size measures (i.e., Tau-U and performance-criteria-based effect size values [PCES]). Third, these analyses were also conducted for generalization and maintenance data. Of 15 studies included in this review, nine met the WWC standards with and without reservations. Tau-U analyses were conducted for 14 studies, whereas PCES values were calculated for only eight studies with mastery criteria. The findings indicated that the self-management interventions had a .93 CI95 (.80, 1) overall effect size for Tau-U with a very large effect. On the other hand, the overall effect size for the PCES values indicated a moderate effect with .99. The weighted effect sizes in generalization and maintenance phases were very large for Tau-U; however, moderate to high effects for PCES. Although self-management interventions showed diversity, one of the domains of daily living skills (i.e., community living skills) has not been studied in the field. Notably, among the studiesin our review, the last ones are from 2019. Detailed findings from descriptive analyses and two different effect size calculations are discussed, and recommendations for future studies are given.

Synthesis and characterization of polyaniline-based composites using cellulose nanocrystals as biological templates.

Polyaniline (PANI) is considered as an ideal electrode material due to its remarkable Faradaic activity, exceptional conductivity, and ease of processing. However, the agglomeration and poor cycling stability of PANI largely limit its practical utilization in energy storage devices. To address these challenges, PANI was synthesized via a facile one-pot, two-step process using cellulose nanocrystals (CNCs) as bio-templates in this work. Zeta potential and particle size measurements revealed that the CNC template could impart improved dispersion stability to the synthesized PANI, which exhibited a decrease in average particle size from 1100 nm to 300 nm as a function of 10 % CNCs. Furthermore, the effect of CNC loadings on the performance of PANI was systematically investigated. The results showed that the specific capacitance of PANI/CNC increased from 102.52 F·g-1 to 138.12 F·g-1 with the CNC loading increase from 0 to 10 wt%. Particularly, the PANI/CNC composite film with a 1:9 ratio (C-P-10 %) demonstrated a capacity retention of 84.45 % after 6000 cycles and an outstanding conductivity of 526 S·m-1. This work generally offers an effective solution for the preparation of high-performance PANI-based composites, which might hold great promise in energy storage device applications.

Machine-learning and mechanistic modeling of metastatic breast cancer after neoadjuvant treatment.

Clinical trials involving systemic neoadjuvant treatments in breast cancer aim to shrink tumors before surgery while simultaneously allowing for controlled evaluation of biomarkers, toxicity, and suppression of distant (occult) metastatic disease. Yet neoadjuvant clinical trials are rarely preceded by preclinical testing involving neoadjuvant treatment, surgery, and post-surgery monitoring of the disease. Here we used a mouse model of spontaneous metastasis occurring after surgical removal of orthotopically implanted primary tumors to develop a predictive mathematical model of neoadjuvant treatment response to sunitinib, a receptor tyrosine kinase inhibitor (RTKI). Treatment outcomes were used to validate a novel mathematical kinetics-pharmacodynamics model predictive of perioperative disease progression. Longitudinal measurements of presurgical primary tumor size and postsurgical metastatic burden were compiled using 128 mice receiving variable neoadjuvant treatment doses and schedules (released publicly at https://zenodo.org/records/10607753). A non-linear mixed-effects modeling approach quantified inter-animal variabilities in metastatic dynamics and survival, and machine-learning algorithms were applied to investigate the significance of several biomarkers at resection as predictors of individual kinetics. Biomarkers included circulating tumor- and immune-based cells (i.e., circulating tumor cells and myeloid-derived suppressor cells) as well as immunohistochemical tumor proteins (i.e., CD31 and Ki67). Our computational simulations show that neoadjuvant RTKI treatment inhibits primary tumor growth but has little efficacy in preventing (micro)-metastatic disease progression after surgery and treatment cessation. Machine learning algorithms that included support vector machines, random forests, and artificial neural networks, confirmed a lack of definitive biomarkers, which shows the value of preclinical modeling studies to identify potential failures that should be avoided clinically.

Investigation of optical properties of molybdenum trioxide (MoO3) thin films using neural networks

Nowadays, transition metal oxide, the semiconductor molybdenum trioxide (MoO3), is a favorable choice because it has several industrial applications and alluring qualities. It has a significant role as an industrial catalyst due to its electrochromic properties. The optical behavior of the MoO3 thin film onto various substrates of the powder of MoO3 was investigated. x-ray diffraction analysis revealed an orthorhombic structure. Measurements of the average crystallite size and dislocation density were obtained, which were 132.8 nm and 5.7× 10–4 nm−2, respectively. Spectrophotometric measurements of transmittance (T) and reflectance (R) at normal incidence in the 300–1400 nm wavelength range of the film onto various substrates were examined. The dispersion and indirect optical transitions and nonlinear optical parameters were identified for glass and quartz substrates. An estimation of the optical behavior of the MoO3 thin film using the artificial neural network (ANN) model was carried out. Experimental data were used as inputs. The optical characterization of ANN modeling outputs provides excellent results. Error values support the success of the modeling process, with a mean squared error value of < 10−1. Moreover, the theoretical equation describing the experimental results was obtained depending on the ANN model, representing the relation between the inputs and outputs. According to the findings of this research, the ANN model can be utilized as an efficient tool to simulate and predict the optical parameters of the MoO3 thin film. Additionally, it can establish strong connections between theoretical and experimental fields.

Mechanical Dewatering of Homogeneous and Segregated Filter Cakes by Vibration Compaction

The solid volume fraction of a slurry requiring solid–liquid separation often fluctuates in industrial cake filtration processes. For low solid volume fractions, particle segregation arises, resulting in an inhomogeneous filter cake structure. Particle segregation has significant impacts on cake formation such as a longer cake formation time compared to homogeneous cakes. This work addresses the impact of this effect on vibration compaction, which is an alternative deliquoring method applying oscillatory shears to the filter cake. The dewatering results of homogeneous and segregated cakes made of the same material with a broad particle size distribution are compared. Although cake deliquoring is achievable despite particle segregation, vibration compaction is more effective for homogeneous cakes. The reason is that no particle size homogenization within segregated cakes occurs due to oscillatory shear, as particle size analyses indicate. The particle size measurements of cakes before and after vibration compaction reveal that the material’s particle size distribution is preserved despite vibration application. Vibration compaction achieves higher deliquoring than the common compaction method by squeezing, as elastic recovery effects after squeezing lead to the reabsorbing of liquid, already expressed and stored in the filter cloth. This demonstrates that vibration compaction is a real alternative for cake deliquoring.

Abstract PO5-27-02: A Tumor Emboli Platform for Morphometric Analysis, Drug screening and for Intravital Optical Imaging in a Murine Model to Simulate Clinicopathological Features of Inflammatory Breast Cancer

Abstract Background: Inflammatory breast cancer (IBC) is distinguished by the presence of tumor emboli, clusters of tumor cells, found within breast parenchyma and dermal lymphatic vessels. These emboli serve as a crucial clinicopathological hallmark, believed to underlie the characteristic diffuse growth pattern and aggressive progression observed in IBC patients, with nearly 30% of patients presenting with metastatic disease at diagnosis. However, the rarity of this cancer and the absence of a solid tumor mass pose challenges in obtaining biospecimens, particularly those with evidence of tumor emboli. To address this pressing need for preclinical models that replicate this distinctive tumor growth pattern, we describe a tumor emboli culture platform that facilitates live imaging, enables compound screening by assessing various phenotypes of the emboli, and permits evaluation of emboli in an in vivo murine model. Methods: The tumor emboli culture system was evaluated for physiological measurements corresponding to dermal lymphatic vessels and subsequently employed to generate tumor emboli from diverse patient-derived cell lines and PDX. Confocal microscopy was employed to characterize cellular information across multiple slices of the tumor emboli. This provided a comprehensive, multi-parametric analysis of single-cell and spheroid phenotypes, including measurements of number, size, shape, and viability of the organoids. Furthermore, we developed imaging algorithms to evaluate phenotypic changes in tumor emboli in response to anti-cancer drug treatment. We also optimized a technique that allows for in vivo tumor emboli implantation including in a transgenic mice with red fluorescent lymphatic vasculature that were surgically implanted with a dorsal skin window chamber. This allowed for intravital optical imaging of the local tumor microenvironment and adjacent skin. Results: Our culture platform enables live imaging of the tumor emboli generated over a span of 7-10 days, maintaining key parameters including kinematic and dynamic viscosity, density along with sheer wall stress within the reported physiological range for lymphatics. Through higher resolution confocal image acquisition and multi-parametric analysis, we conducted particle counting and classification, providing statistically significant insights into the integrity of tumor emboli over time. Additionally, the developed algorithms allowed for quantitative analysis of images from tumor emboli cultures subjected to anti-cancer drugs, revealing disparities in drug efficacy on tumor emboli integrity and dispersion including inter-cluster space within the emboli. Intravital optical imaging, coupled with quantitative analysis of dispersion characteristics of the tumor emboli implanted in the murine model over 5-6 days, demonstrated a diffuse spread reminiscent of observations in IBC patients. Furthermore, immunohistochemistry staining showed marked Ki67, CD45, F4-80 revealing a proliferative tumor microenvironment with high levels of macrophage infiltration. Conclusions: As of now specific targeted therapies for IBC patients remain elusive. Our culture platform for tumor emboli, when combined with advanced imaging techniques both in vitro and in vivo and traditional approaches like immunohistochemistry and genomic evaluation, forms a powerful toolkit for assessing the phenotype and dispersion characteristics of this unique pathological feature in IBC. This preclinical model offers crucial insights, potentially paving the way for precision medicine strategies in the treatment of this understudied cancer. Funding in part from American Cancer Society Mission Boost MBG-20-141-01-MBG grant (GRD), Department of Defense W81XWH-20-1-0153 (GRD), Duke Consortium for Inflammatory Breast Cancer Education (AB, CW, RE). Citation Format: Dorababu Sannareddy, Theresa Charity, Alexandra Bennion, Caroline Way, Edwin Yu, Ralph Erdmann, Gregory M Palmer, Gayathri R Devi. A Tumor Emboli Platform for Morphometric Analysis, Drug screening and for Intravital Optical Imaging in a Murine Model to Simulate Clinicopathological Features of Inflammatory Breast Cancer [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO5-27-02.

Abstract PS02-09: Nurse-led individualized follow-up versus regular physician-led visits after early breast cancer (MyHealth) - a randomized, controlled trial

Abstract Background: Follow-up after breast cancer with regular specialist-led visits has failed to prove superiority over other strategies in terms of recurrence detection and survival, but it is still a cornerstone in breast cancer follow-up in many healthcare systems. Follow-up provided by the general practitioner or a specialist nurse has been reported more cost-effective and non-inferior in terms of patient-reported health-related quality of life (HRQoL) and in meeting the needs of breast cancer survivors. However, no follow-up strategies have demonstrated indisputable superiority over other strategies. Methods: In this randomized controlled trial (MyHealth), patients who recently completed surgery, and chemo-/radiotherapy if indicated, for stage I–II breast cancer were randomly assigned to intervention or control follow-up at Zealand University Hospital, Denmark. The nurse-led intervention comprised three to five individual self-management sessions during the first six months, and regular reporting of symptoms with nurse navigation to relevant healthcare services during three years of follow-up. The control comprised outpatient visits with oncologist every six months for three years. The primary outcome was breast cancer-specific HRQoL measured by the Trial Outcome Index-Physical/Functional/Breast (TOI-PFB) summary score of the Functional Assessment of Cancer Therapy-Breast (FACT-B) two years after randomization. Secondary outcomes were fear of recurrence, anxiety, depression, and healthcare utilization. Results: From January 2017 to January 2019, 503 patients were randomly assigned to intervention (n=251) or control (n=252) follow-up. At two years, patients in the intervention group reported a significantly higher HRQoL (mean 75·69 (SD 12·27)) than patients in the control group (mean 71·26 (SD 14·08)), a mean difference of 5·05 (95% CI; 3·30–6·79), which is considered clinically relevant. The intervention group also reported significantly less fear of recurrence, anxiety, and depression as shown in Table 1. Furthermore, patients in the intervention group had fewer physician consultations but more nurse contacts, and an unchanged diagnostic imaging pattern as shown in Table 2. The effect on all outcomes was stable through three years of follow up. Conclusions: The MyHealth study suggests a new strategy for follow-up after early breast cancer providing significant improvements in HRQoL, fear of recurrence, anxiety, and depression without inflicting extra expenses to the healthcare system. (Funded by the Danish Cancer Society, Region Zealand and Copenhagen University Hospital; Clinicaltrials.gov number; NCT02949167.) Table 1: Outcome findings by study group at baseline, 6, 12, 24, and 36 months Data are mean (SD) unless otherwise stated. The effect estimates are based on the mixed model assuming no difference between groups at baseline. The QoL and fear of recurrence variables are continuous, and the estimates describe the mean difference in score between patients in the two groups. For anxiety and depression, data were zero-inflated. These estimates describe the exponential coefficients of anxiety and depression scores in the intervention group compared to the control group. Cohen’s d is a measure of effect size, and interpreted as small for Cohen’s d = 0·2, medium for Cohen’s d = 0·5, and large for Cohen’s d = 0·8 Table 2: Number of contacts and diagnostic imaging examinations during the first three years of follow-up by study group Data are numbers and mean (SD) per patient during the first three years of follow-up. 1 Most telephone consultations were scheduled as outpatient visits according to the protocol, but changed to telephone consultations due to the COVID-19 pandemic Citation Format: Lena Saltbæk, Pernille Bidstrup, Randi Karlsen, Beverley Høeg, Trine Horsboel, Federica Belmonte, Elisabeth Andersen, Vibeke Zoffmann, Anne Friberg, Mads Svendsen, Helle Christensen, Vesna Glavicic, Dorte Nielsen, Susanne Dalton, Christoffer Johansen. Nurse-led individualized follow-up versus regular physician-led visits after early breast cancer (MyHealth) - a randomized, controlled trial [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PS02-09.

Niosome gels encapsulate green mangosteen peel extract (Garcinia mangostana L.) as an anti-acne-inducing bacterial and anti-inflammatory activity

This research aims to develop a niosome gel from green mangosteen peel extract (Garcinia mangostana L.) by maceration with an ethanol solvent. The result of the yield percentage was 14.35 ± 0.90. The result of analyzing the phytochemicals by high-performance liquid chromatography (HPLC) was that tannin and xanthone were equal to 0.7483 ± 0.0825 mg per 100 mg of extract and 0.02964 ± 0.0088 mg per 100 mg of extract, respectively. The results of the determination of the effect include anti-inflammatory and anti-bacterial (Cutibacterium acnes) as anti-inflammatory with nitric oxide from LPS-induced macrophage cells up to a maximum equal to 29.10 ± 4.78% as a concentration at 1 mg mL–1 as acetonide can inhibit nitric oxide equal to 33.12 ± 3.62% as a concentration at 1 mg mL–1. and anti-bacterial (Cutibacterium acnes) by broth microdilution and drop plate methods, it was found that clindamycin has a minimum inhibitory concentration (MIC) and a minimum bactericidal concentration (MBC) of 0.08 μg mL–1 and 0.31 μg mL–1, respectively. The development of niosomes consisting of cholesterol, tween 60, and mangosteen peel extract at 1% w w–1 and 2% w w–1 in every formula showed good stability. The reduction of particle size in the formula by an ultrasonic bath at 30 minutes and measurement of particle size with a transmission electron microscope (TEM) were found to be equal to 1,265 and 123 – 219 nm, respectively. The polydispersity index (PDI) was in the range of 0.1 – 0.2, and the zeta potential value was in the range of –26.15 to –28.61 mV. The result of hydration and trans epidermal water loss (TEWL) was found to be that after 4 weeks of use, the formula containing the niosomes of mangosteen peel extract concentrated at 2% w w–1 maximizes skin moisture. It has a value of 346 ± 39.27 and has the least surface water loss. GRAPHICAL ABSTRACT HIGHLIGHTS The green mangosteen peel extract (Garcinia mangostana L.) can inhibiting nitric oxide production from LPS-induced macrophage cells up to 29.10  ± 4.78% at a concentration of 1 mg ml-1, the lowest inhibitory (MIC)  and kill (MBC) concentration of C. acnes bacteria less than 0.24 mg ml-1. The particle size of niosomes encapsulate extracts before reducing particle size equal to 1,265 nm. and after reducing particle size in the range of 123 - 219 nm. The skin hydration value after using product for 4 weeks as niosome gel encapsulate extract 2%w w-1 of extract was maximum moisture and minimal water loss.

Efficacy of psilocybin for treating symptoms of depression: systematic review and meta-analysis

ObjectiveTo determine the efficacy of psilocybin as an antidepressant compared with placebo or non-psychoactive drugs.DesignSystematic review and meta-analysis.Data sourcesFive electronic databases of published literature (Cochrane Central Register of Controlled Trials,...

Software Size Measurement: Bridging Research and Practice

Software Size Measurement: Bridging Research and Practice

Unbiased Real-Time Traffic Sketching

In network measurement, sliding window measurement has the advantage of providing recent and timely measurement results. Recently, sketches have become the most popular method of conducting flow-level network measurements due to their favorable trade-off between small memory overhead and high measurement accuracy. However, it remains a challenge that no current sketches are able to support unbiased estimation toward flow size measurement, which can improve the performance of tasks including network diagnoses, delay measurement and heavy hitter detection. In this paper, we propose the first work that achieves unbiased flow size measurement in sliding windows, namely <bold xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Unbiased Cleaning sketch (UC sketch)</b> . The key technique of the UC sketch is <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Unbiased Cleaning</i> which can remove outdated keys from the sliding windows in a balanced way. Besides, we significantly reduce the variance of flow size by two optimization techniques, namely <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Linear Scaling</i> and <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Column Randomizing</i> . To prove the result, we conduct rigorous mathematical analysis and reasonable experiments. All related source codes are open-sourced at Github anonymously.

Automated Measurement and Three-Dimensional Fitting of Corneal Ulcerations and Erosions via AI-Based Image Analysis

Purpose Artificial intelligence (AI)-tools hold great potential to compensate for missing resources in health-care systems but often fail to be implemented in clinical routine. Intriguingly, no-code and low-code technologies allow clinicians to develop Artificial intelligence (AI)-tools without requiring in-depth programming knowledge. Clinician-driven projects allow to adequately identify and address real clinical needs and, therefore, hold superior potential for clinical implementation. In this light, this study aimed for the clinician-driven development of a tool capable of measuring corneal lesions relative to total corneal surface area and eliminating inaccuracies in two-dimensional measurements by three-dimensional fitting of the corneal surface. Methods Standard slit-lamp photographs using a blue-light filter after fluorescein instillation taken during clinical routine were used to train a fully convolutional network to automatically detect the corneal white-to-white distance, the total fluorescent area and the total erosive area. Based on these values, the algorithm calculates the affected area relative to total corneal surface area and fits the area on a three-dimensional representation of the corneal surface. Results The developed algorithm reached dice scores >0.9 for an automated measurement of the relative lesion size. Furthermore, only 25% of conventional manual measurements were within a ± 10% range of the ground truth. Conclusions The developed algorithm is capable of reliably providing exact values for corneal lesion sizes. Additionally, three-dimensional modeling of the corneal surface is essential for an accurate measurement of lesion sizes. Besides telemedicine applications, this approach harbors great potential for clinical trials where exact quantitative and observer-independent measurements are essential.

Allometric relationships and trade-offs in 11 common Mediterranean-climate grasses.

Biomass allocation in plants is the foundation for understanding dynamics in ecosystem carbon balance, species competition, and plant-environment interactions. However, existing work on plant allometry has mainly focused on trees, with fewer studies having developed allometric equations for grasses. Grasses with different life histories can vary in their carbon investment by prioritizing the growth of specific organs to survive, outcompete co-occurring plants, and ensure population persistence. Further, because grasses are important fuels for wildfire, the lack of grass allocation data adds uncertainty to process-based models that relate plant physiology to wildfire dynamics. To fill this gap, we conducted a greenhouse experiment with 11 common California grasses varying in photosynthetic pathway and growth form. We measured plant sizes and harvested above- and belowground biomass throughout the life cycle of annual species, while for the establishment stage of perennial grasses to quantify allometric relationships for leaf, stem, and root biomass, as well as plant height and canopy area. We used basal diameter as a reference measure of plant size. Overall, basal diameter is the best predictor for leaf and stem biomass, height, and canopy area. Including height as another predictor can improve model accuracy in predicting leaf and stem biomass and canopy area. Fine root biomass is a function of leaf biomass alone. Species vary in their allometric relationships, with most variation occurring for plant height, canopy area, and stem biomass. We further explored potential trade-offs in biomass allocation across species between leaf and fine root, leaf and stem, and allocation to reproduction. Consistent with our expectation, we found that fast-growing plants allocated a greater fraction to reproduction. Additionally, plant height and specific leaf area negatively influenced the leaf-to-stem ratio. However, contrary to our hypothesis, there were no differences in root-to-leaf ratio between perennial and annual or C4 and C3 plants. Our study provides species-specific and functional-type-specific allometry equations for both above- and belowground organs of 11 common California grass species, enabling nondestructive biomass assessment in California grasslands. These allometric relationships and trade-offs in carbon allocation across species can improve ecosystem model predictions of grassland species interactions and environmental responses through differences in morphology.

Drug-loaded polymer-coated silver nanoparticles for lung cancer theranostics.

Lung cancer is the leading cause of death in cancer across the globe. To minimize these deaths, the replacement of traditional chemotherapy with novel strategies is significant. We have developed a nanotheranostic approach using silver nanoparticles for imaging and treatment. Silver nanoparticles (AgNPs) are fabricated by chemical reduction method. The formulation of AgNPs was confirmed by different characterization techniques like stability test, UV-Visible spectroscopy, Confocal Raman Spectroscopy, and Energy-Dispersive X-ray analysis. Further, AgNPs are coated with poly lactic-co-glycolic acid (PLGA) and then loaded with paclitaxel(Pac). Then the drug-loaded PLGA-coated AgNPs were characterized for size and zeta potential measurement by zetasizer, surface morphology study by atomic force microscopy, Fourier transform infrared spectroscopy, and release kinetics study. The imaging and anticancer properties of these nanoformulations are investigated using lung cancer cell lines. The results proved that the particles are in the nanometer range with smooth surface morphology. Moreover, the drug-loaded NPs showed a sustained release of the drug for a longer period of time. Further the formulations showed imaging property with greater anticancer efficacy. Thus, the results suggest the effective use of these nanoformulation in both lung cancer imaging and treatment using a simple and efficient approach.

Improving the efficacy of phenolic extract from Pimpinella affinis in edible oils through nanoencapsulation: Utilizing chitosan and Salvia macrosiphon gum as coating agents

AbstractIn the present study, a phenolic extract derived from the Pimpinella affinis plant underwent nanoencapsulation. The nanoencapsulation process employed chitosan, Salvia macrosiphon gum (SMG), and a chitosan–SMG complex (1:1) (CCS) as coating agents. The evaluation of nanoemulsions encompassed measurements of particle size, polydispersity index (PDI), ζ‐potential, encapsulation efficiency, and intensity distribution parameters. The overall results of these assessments indicated that the nanoemulsion coated with CCS exhibited the most favorable characteristics when compared to other treatments. Subsequently, this specific nanoencapsulated sample was utilized to enhance the oxidative stability of canola oil at concentrations of 100, 200, and 300 ppm (parts per million). Oxidative stability tests, assessed through the total oxidation value (TOTOX) index, highlighted the superior performance of the nanoencapsulated extract, particularly at a concentration of 300 ppm. This enhancement can be attributed to the increased release of phenolic compounds from the CCS coating into the canola oil. The findings illustrate that the nanoencapsulation process can significantly enhance the efficacy of P. affinis extract in improving the oxidative stability of canola oil.

First-trimester fetal size, accelerated growth in utero, and child neurodevelopment in a cohort study.

Early pregnancy is a critical window for neural system programming; however, the association of first-trimester fetal size with children's neurodevelopment remains to be assessed. This study aimed to explore the association between first-trimester fetal size and children's neurodevelopment and to examine whether intrauterine accelerated growth could compensate for the detrimental effects of first-trimester restricted growth on childhood neurodevelopment. The participants were from a birth cohort enrolled from March 2014 to March 2019 in Wuhan, China. A total of 2058 fetuses with crown to rump length (CRL) (a proxy of first-trimester fetal size) measurements in the first trimester and neurodevelopmental assessment at age 2 years were included. We measured the first-trimester CRL and defined three fetal growth patterns based on the growth rate of estimated fetal weight from mid to late pregnancy. The neurodevelopment was assessed using the Bayley Scales of Infant Development of China Revision at 2 years. Each unit (a Z score) increase of first-trimester CRL was associated with increased scores in mental developmental index (MDI) (adjusted beta estimate = 1.19, (95% CI: 0.42, 1.95), P = 0.03) and psychomotor developmental index (PDI) (adjusted beta estimate = 1.36, (95% CI: 0.46, 2.26), P < 0.01) at age 2 years, respectively. No significant association was observed between fetal growth rate and PDI. For children with restricted first-trimester fetal size (the lowest tertile of first-trimester CRL), those with "intrauterine accelerated growth" pattern (higher growth rates) had significantly higher MDI (adjusted beta estimate = 6.14, (95% CI: 3.80, 8.49), P < 0.001) but indistinguishable PDI compared to those with "intrauterine faltering growth" pattern (lower growth rates). Main limitations of this study included potential misclassification of gestational age due to recall bias of the last menstrual period and residual confounding. The current study suggests that restricted first-trimester fetal size is associated with mental and psychomotor developmental delay in childhood. However, in children with restricted first-trimester fetal size, intrauterine accelerated growth was associated with improved mental development but had little effect on psychomotor development. Additional studies are needed to validate the results in diverse populations.

The spatiotemporal richness of hummingbird wing deformations.

Animals exhibit an abundant diversity of forms, and this diversity is even more evident when considering animals that can change shape on demand. The evolution of flexibility contributes to aspects of performance from propulsive efficiency to environmental navigation. It is, however, challenging to quantify and compare body parts that, by their nature, dynamically vary in shape over many time scales. Commonly, body configurations are tracked by labelled markers and quantified parametrically through conventional measures of size and shape (descriptor approach) or non-parametrically through data-driven analyses that broadly capture spatiotemporal deformation patterns (shape variable approach). We developed a weightless marker tracking technique and combined these analytic approaches to study wing morphological flexibility in hoverfeeding Anna's hummingbirds (Calypte anna). Four shape variables explained >95% of typical stroke cycle wing shape variation and were broadly correlated with specific conventional descriptors like wing twist and area. Moreover, shape variables decomposed wing deformations into pairs of in- and out-of-plane components at integer multiples of the stroke frequency. This property allowed us to identify spatiotemporal deformation profiles characteristic of hoverfeeding with experimentally imposed kinematic constraints, including through shape variables explaining <10% of typical shape variation. Hoverfeeding in front of a visual barrier restricted stroke amplitude and elicited increased stroke frequencies together with in- and out-of-plane deformations throughout the stroke cycle. Lifting submaximal loads increased stroke amplitudes at similar stroke frequencies together with prominent in-plane deformations during the upstroke and pronation. Our study highlights how spatially and temporally distinct changes in wing shape can contribute to agile fluidic locomotion.

Executive functions and brain morphology of male and female dominant and subordinate cichlid fish.

Living in a social dominance hierarchy presents different benefits and challenges for dominant and subordinate males and females, which might in turn affect their cognitive needs. Despite the extensive research on social dominance in group-living species, there is still a knowledge gap regarding how social status impacts brain morphology and cognitive abilities. Here, we tested male and female dominants and subordinates of Neolamprologus pulcher, a social cichlid fish species with size-based hierarchy. We ran three executive cognitive function tests for cognitive flexibility (reversal learning test), self-control (detour test), and working memory (object permanence test), followed by brain and brain region size measurements. Performance was not influenced by social status or sex. However, dominants exhibited a brain-body slope that was relatively steeper than that of subordinates. Furthermore, individual performance in reversal learning and detour tests correlated with brain morphology, with some trade-offs among major brain regions like telencephalon, cerebellum, and optic tectum. As individuals' brain growth strategies varied depending on social status without affecting executive functions, the different associated challenges might yield a potential effect on social cognition instead. Overall, the findings highlight the importance of studying the individual and not just species to understand better how the individual's ecology might shape its brain and cognition.

Composites with immobilized bioactive spirulina on an inorganic substrate (yellow clay, hydroxyapatite, SiO2, TiO2, ZnO).

In order to improve the structural properties of clays and composites of powdered spirulina, clay, nanosilica, hydroxyapatite, TiO2 and ZnO were used as an additive for mechanical processing. As a result, composites with natural nanostructured materials (NNM) are prepared with improved structural properties and bioactivity. The mixtures based on NNM with crystalline kaolinite, clays and admixtures were processed in a knife mill. The materials were characterized using FTIR spectroscopy, nitrogen adsorption and desorption, SEM release of bioactive components (anthocyanin 0,004 - 0,07 mg/g; chlorophyll 20 - 29 mg/g), composite toxicity level (below 25%), particle size measurement and surface charge density, zeta potential. Adsorption enthalpies during the formation of an intermolecular complex during the interactions of an anthocyanin molecule with the appropriate component of the composite were also calculated. There are regularities in the characteristics depending on the type of NNM, particle morphology and textural features of solids. The morphological and structural properties of the components changed slighty in the blends because the processing was conducted under relatively low mechanical stress. The morphological, textural and structural characteristics of the composites as well as the transformation to a nanostructured state, assume great bioactive activity of the composites, interesting for practical applications.

Comparison of Inter-Method Agreement and Reliability for Automatic Brain Volumetry Using Three Different Clinically Available Software Packages

Background and Objectives: No comparative study has evaluated the inter-method agreement and reliability between Heuron AD and other clinically available brain volumetric software packages. Hence, we aimed to investigate the inter-method agreement and reliability of three clinically available brain volumetric software packages: FreeSurfer (FS), NeuroQuant® (NQ), and Heuron AD (HAD). Materials and Methods: In this study, we retrospectively included 78 patients who underwent conventional three-dimensional (3D) T1-weighed imaging (T1WI) to evaluate their memory impairment, including 21 with normal objective cognitive function, 24 with mild cognitive impairment, and 33 with Alzheimer’s disease (AD). All 3D T1WI scans were analyzed using three different volumetric software packages. Repeated-measures analysis of variance, intraclass correlation coefficient, effect size measurements, and Bland–Altman analysis were used to evaluate the inter-method agreement and reliability. Results: The measured volumes demonstrated substantial to almost perfect agreement for most brain regions bilaterally, except for the bilateral globi pallidi. However, the volumes measured using the three software packages showed significant mean differences for most brain regions, with consistent systematic biases and wide limits of agreement in the Bland–Altman analyses. The pallidum showed the largest effect size in the comparisons between NQ and FS (5.20–6.93) and between NQ and HAD (2.01–6.17), while the cortical gray matter showed the largest effect size in the comparisons between FS and HAD (0.79–1.91). These differences and variations between the software packages were also observed in the subset analyses of 45 patients without AD and 33 patients with AD. Conclusions: Despite their favorable reliability, the software-based brain volume measurements showed significant differences and systematic biases in most regions. Thus, these volumetric measurements should be interpreted based on the type of volumetric software used, particularly for smaller structures. Moreover, users should consider the replaceability-related limitations when using these packages in real-world practice.