bluuebunny/crossref_metadata_2025 huggingface dataset:
Seed germination responses to temperature and water availability in weedy rice
Authors: Fukuda Monrawee , Imaizumi Toshiyuki , Koarai Akira
Published: October 2022

BACKGROUND

Weedy rice is one of the main agricultural weeds infesting transplanted and direct‐seeded rice cultures across Japan. However, the environmental factors that facilitate its proliferation are largely unknown. This study investigated the effects of temperature and water availability on seed germination of Japanese weedy and cultivated rice strains differing in degree of seed dormancy and after‐ripening. This information could help predict weedy rice infestation and design efficacious control measures.

RESULTS

The germination responses of weedy rice to temperature and water availability varied among strains and after‐ripening duration. The germination rate varied inversely with the degree of dormancy, increased with water availability, and fluctuated between low and high temperatures. The shallow‐dormant tropical japonica‐derived strawhull weedy rice (TRJ) germinated at 10 °C unlike the temperate japonica‐derived weedy rice strains, namely, the intermediate‐dormant blackhull (BH) and the deep‐dormant strawhull (SH). Seeds of all plant strains germinated below the permanent wilting point of clay loam soil, but the germination rates were higher for TRJ and BH than for cultivated rice. SH germination was more synchronous with rice than the other weedy rice strains.

CONCLUSION

This study has confirmed the overall robustness of germination cold tolerance at 10 °C in TRJ, high germinability at low‐water availability and high temperature in TRJ and BH, and relatively more synchronous germination between SH and cultivated rice in seeds grown in different years. These observed characteristics are considered advantageous to the coexistence of weedy rice with cultivated rice. © 2022 Society of Chemical Industry.
Factors impacting the detection of weed seed contaminants in seed lots
Authors: Buddenhagen Christopher E , Hackell Deborah , Henderson Harold V , Wynne‐Jones Ben
Published: October 2022

BACKGROUND

The setting and following of phytosanitary standards for weed seeds can lessen the impacts of weeds on agriculture. Standards adopted by seed companies, laboratories and regulators ensure the contamination rates do not exceed some thresholds. Globally sample size standards are set based on the amount needed to obtain a contaminant in a random sample of the seed lot, not detectability. New Zealand requires a 95% confidence that the maximum pest limit of 0.01% of quarantine weed seed contamination is not exceeded in an imported seed lot. We examined 24 samples each containing approximately 150 000 seeds of either perennial ryegrass (12 samples) or white clover seeds (12 samples) that were then spiked with seeds (contaminants) from 12 non‐crop species (3–8 seeds of each). We considered factors that may impact detection rates: shape, color, size, and texture relative to the crop, and technician (including a commercial seed laboratory).

RESULTS

A linear mixed model fitted to the data indicated significant observer, crop, and seed color, shape, and size effects on detection. Detectability increased by 20% ± 7.7 (± standard error) when seeds had a distinct shape or color (28% ± 8.1), or were larger (23% ± 8.7) rather than smaller, relative to the crop. Commercial laboratory identifications were usually correct at the level of genus, and species for common weeds, but some misidentifications occurred.

CONCLUSION

Sample sizes for border inspections should be based on detectability of regulated weed seeds in the crop in combination with weed risk for the crop and location. © 2022 The Authors. Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.
Aliovalent Calcium Substitution: An Effective Way to Enhance the Magnetoelectric Coupling Properties of Multiferroic BiFeO3
Authors: Mohan Manoj , Al-Omari Imaddin A. , Al-Harthi Salim H. , Myint Myo T. Z. , Jacob Bibin , Dhanyaprabha K. C. , Thomas Hysen
Published: October 2022

Kinetics of magnetoelectric coupling in bismuth ferrite (BiFeO3) with the substitution of aliovalent calcium ion is investigated. The resulting structural, dielectric, magnetic, and magnetoelectric (ME) coupling properties are explained in terms of chemical pressure originating from the substituent ion. Substitution of calcium finds to reduce the oxygen vacancies. Two important substitution concentrations find to be critical in ferroelectric (FE) and ME coupling properties. At 10 at% calcium, highest remanent polarization is obtained and maximum ME coupling coefficient is observed at 20 at%, which suggests calcium concentration between 10% and 20% can be optimized to obtain good electrical and ME coupling properties of BiFeO3. Maximum ME coupling coefficient at calcium concentration 20 at% is close to numerical calculations reported in the literature. Magnetic properties are also favorably modified by the substitution; a coupled antiferromagnetic and weak ferromagnetic ordering is obtained. Also, a variation in blocking temperature and spin relaxation is observed with respect to the substituent ion concentration.
High‐Performance Organic Photodetectors Using SnO2 as Interfacial Layer with Optimal Thickness
Authors: Yan Xianwen , Wang Xin , Gao Shijia , Qiao Wenqiang
Published: October 2022

A photodiode‐type photodetector with bulk heterojunction is built with an ITO/SnO2/P3HT:PC61BM/MoO3/Al structure. By evaluating SnO2 interfacial layer thicknesses of 15, 19, 22, 26, and 29 nm, the effect of thickness on the photodetector response is investigated. The results show that the carrier extraction can reach saturation at −1 V. In addition, the device with interlayer thickness of 22 nm achieves the lowest dark current density (1.6 × 10−6 A cm−2), highest specific detectivity (1.3 × 1011 Jones), widest linear dynamic range (LDR, 43.7 dB), and fastest response (raising/falling time of 1.81/2.22 μs). Hence, the performance of the organic photodetectors can be greatly improved by adopting the proper thickness of the SnO2 interfacial layer.
Dynamic Magnetic Features of a Mixed‐Spin‐2 and Spin‐5/2 Ising Ferrimagnetic System under a Time‐Dependent Oscillating Magnetic Field: Path Probability Method Approach
Authors: Gençaslan Mustafa , Özlü Mustafa , Keskin Mustafa
Published: October 2022

A study, within the path probability method, of the dynamic magnetic features of the mixed spin (2, 5/2) Ising ferrimagnetic system on a hexagonal lattice under the presence of a sinusoidal external magnetic field is presented. The Hamiltonian of the system contains intersublattice, intrasublattice, and crystal‐field interactions. The intersublattice interaction is taken as antiferromagnetic. The time variations of average dynamic magnetizations and the thermal behavior of the dynamic magnetizations are investigated to obtain the phases in the system and to characterize the nature of the dynamic phase transitions and find the dynamic phase transition temperature points. The dynamic phase diagrams in six different phase planes are presented, in which they contain the paramagnetic (p) phase, three different ferrimagnetic (i
1, i
2, i
3) fundamentals, and the p + i
1, i
1 + 
i
2, and i
2 + 
i
3 mixed phases as well as the dynamic tricritical point and the dynamic double critical end point, depending on the interaction parameters. The dynamic compensation behavior is also examined and only N‐type behaviors are observed. Some of the obtained dynamic phase diagrams are in qualitatively good agreement within some works on the dynamics of mixed‐spin Ising system.
Intergenerational Transmission of Dyslexia: How do Different Identification Methods of Parental Difficulties Influence the Conclusions Regarding Children's Risk for Dyslexia?
Authors: Khanolainen Daria , Salminen Jenni , Eklund Kenneth , Lerkkanen Marja‐Kristiina , Torppa Minna
Published: October 2022

By investigating children whose parents have dyslexia, family risk (FR) studies are expanding our understanding of the intergenerational transmission of dyslexia. These studies, however, vary in their identification of FR, and how the use of different identification methods influences research findings and conclusions is yet to be systematically investigated. This study aims to evaluate the association between two FR identification methods—parental self‐reports and direct skill assessments—and their unique contributions in the prediction of children's reading. The study employed two datasets: a prospective FR sample (half of the parents in the sample had dyslexia and the remaining half did not) and an unselected sample. Parental self‐reports and direct skill assessments correlated strongly (.60) in the prospective FR sample and moderately (.42) in the unselected sample. Moreover, both FR identification methods were almost equally predictive of children's reading (explaining 5%–9% of the variance at different time points) in the prospective FR sample only. In the prediction of the children's skills, the two methods complemented each other only for some of the measures. At the same time, in the unselected sample, parental skills were not predictive of children's reading, whereas self‐reports were. The two FR identification methods seem to have equally high predictive power when the variability in parental data is high. However, they lose their predictive power when either the lower or higher end of the parental reading distribution is underrepresented.
Cell‐Taxi: Mesenchymal Cells Carry and Transport Clusters of Cancer Cells
Authors: Zarubova Jana , Hasani‐Sadrabadi Mohammad Mahdi , Norris Sam C. P. , Majedi Fatemeh Sadat , Xiao Crystal , Kasko Andrea M. , Li Song
Published: October 2022

Cell clusters that collectively migrate from primary tumors appear to be far more potent in forming distant metastases than single cancer cells. A better understanding of the collective cell migration phenomenon and the involvement of various cell types during this process is needed. Here, an in vitro platform based on inverted‐pyramidal microwells to follow and quantify the collective migration of hundreds of tumor cell clusters at once is developed. These results indicate that mesenchymal stromal cells (MSCs) or cancer‐associated fibroblasts (CAFs) in the heterotypic tumor cell clusters may facilitate metastatic dissemination by transporting low‐motile cancer cells in a Rac‐dependent manner and that extracellular vesicles secreted by mesenchymal cells only play a minor role in this process. Furthermore, in vivo studies show that cancer cell spheroids containing MSCs or CAFs have faster spreading rates. These findings highlight the active role of co‐traveling stromal cells in the collective migration of tumor cell clusters and may help in developing better‐targeted therapies.
Effects of state‐of‐the‐art residual stress models on the member and local stability behaviour
Authors: Schaper Lukas , Tankova Trayana , da Silva Luís Simões , Knobloch Markus
Published: October 2022

Residual stresses have considerable effect on both the local and the member stability behaviour of steel structures. Previous studies have shown that the structural stability behaviour depends on both the distribution and the amplitude of the residual stresses. The residual stress distribution is affected by the cross‐section geometry, the steel grade and the manufacturing process, e.g. flame cutting and the welding procedure. A realistic consideration of residual stresses is necessary for an efficient and safe design of steel structures.

This article presents an experimental and numerical study on the influence of residual stresses on the stability behaviour of structural members, i.e. steel columns and beams considering a variety of cross‐sectional slenderness, i.e. plastic, compact and slender cross‐sections are taken into account. A novel residual stress model for welded I‐shaped sections was developed and evaluated using test data. This model takes into account the main influencing parameters, i.e. the cross‐sections geometry, the steel grade as well as manufacturing process with thermal cuts or non‐thermal cuts of the steel plates. The novel residual stress model is then used to investigate the stability behaviour in terms of a numerical simulation study. The result of the study allows to propose an improvement of the buckling curve selection for welded high strength steel columns and beams.
Long‐term behavior of sustainable self‐compacting concrete with high volume of recycled concrete aggregates and industrial by‐products
Authors: Qin Daqiang , Zong Zhenyu , Dong Chunru , Guo Zhanggen , Tang LiuYang , Chen Chuan , Zhang Lei
Published: October 2022

The addition of recycled concrete aggregates together with industrial by‐products for the concrete production is an effective solution to the environmental problems in terms of excess waste materials and massive nonrenewable natural resources consumption. This article investigates the long‐term behavior and microstructure of sustainable self‐compacting concrete (SCC) by substantially substituting natural coarse aggregate with recycled coarse aggregates (RCA) and cement with supplementary cementitious materials (SCM). The influences of RCA and SCM content as well as SCM combination type (fly ash, ground granulated blast furnace slag and/or silica fume) on the mechanical properties and long‐term deformation of recycled aggregate SCC (RA‐SCC) were assessed in detail. Furthermore, scanning electron microscope and x‐ray diffraction were implemented to justify the reasons for improvement on mechanical properties and long‐term behavior of RA‐SCC. The results indicate that the addition of RCA reduces the compressive strength and elastic modulus of RA‐SCC, and increases the creep and shrinkage deformations. However, incorporating SCM with a combination of fly ash, ground granulated blast furnace slag and silica fume compensates for the detrimental effect of RCA and makes considerable improvement in strength and reduction in the long‐term deformations. Microstructure analysis confirms the reasons of improvement, which is mainly attributed to the addition of SCM by adopting a combination type, resulting in a more compact microstructure such as stronger interfacial transition zone. Based on the experimental results, the correction factors of RCA and SCM were introduced in conjunction with fib Model Code 2010 model to evaluate the creep coefficient of RA‐SCC.
Identification of dementia and MCI cases in health information systems: An Italian validation study
Authors: Bacigalupo Ilaria , Lombardo Flavia L. , Bargagli Anna Maria , Cascini Silvia , Agabiti Nera , Davoli Marina , Scalmana Silvia , Palma Annalisa Di , Greco Annarita , Rinaldi Marina , Giordana Roberta , Imperiale Daniele , Secreto Piero , Golini Natalia , Gnavi Roberto , Lovaldi Franca , Biagini Carlo A. , Gualdani Elisa , Francesconi Paolo , Magliocchetti Natalia , Fiandra Teresa Di , Vanacore Nicola
Published: October 2022

Introduction

The identification of dementia cases through routinely collected health data represents an easily accessible and inexpensive method to estimate the prevalence of dementia. In Italy, a project aimed at the validation of an algorithm was conducted.

Methods

The project included cases (patients with dementia or mild cognitive impairment [MCI]) recruited in centers for cognitive disorders and dementias and controls recruited in outpatient units of geriatrics and neurology. The algorithm based on pharmaceutical prescriptions, hospital discharge records, residential long‐term care records, and information on exemption from health‐care co‐payment, was applied to the validation population.

Results

The main analysis was conducted on 1110 cases and 1114 controls. The sensitivity, specificity, and positive and negative predictive values in discerning cases of dementia were 74.5%, 96.0%, 94.9%, and 79.1%, respectively, whereas in detecting cases of MCI these values were 29.7%, 97.5%, 92.2%, and 58.1%, respectively. The variables associated with misclassification of cases were also identified.

Discussion

This study provided a validated algorithm, based on administrative data, which can be used to identify cases with dementia and, with lower sensitivity, also early onset dementia but not cases with MCI.
Radiotherapy reimagined: Integrating nanomedicines into radiotherapy clinical trials
Authors: DuRoss Allison N. , Phan Jack , Lazar Alexander J. , Walker Joshua M. , Guimaraes Alexander R. , Baas Carole , Krishnan Sunil , Thomas Charles R. , Sun Conroy , Bagley Alexander F.
Published: October 2022

Radioenhancing nanoparticles (NPs) are being evaluated in ongoing clinical trials for various cancers including head and neck, lung, esophagus, pancreas, prostate, and soft tissue sarcoma. Supported by decades of preclinical investigation and recent randomized trial data establishing clinical activity, these agents are poised to influence future multimodality treatment paradigms involving radiotherapy. Although the physical interactions between NPs and ionizing radiation are well characterized, less is known about how these agents modify the tumor microenvironment, particularly regarding tumor immunogenicity. In this review, we describe the key multidisciplinary considerations related to radiation, surgery, immunology, and pathology for designing radioenhancing NP clinical trials.

This article is categorized under:

Therapeutic Approaches and Drug Discovery > Nanomedicine for Oncologic Disease
Love symmetry
Authors: Charalambous Panagiotis , Dubovsky Sergei , Ivanov Mikhail M.
Published: October 2022

Abstract

Perturbations of massless fields in the Kerr-Newman black hole background enjoy a (“Love”) SL(2, ℝ) symmetry in the suitably defined near zone approximation. We present a detailed study of this symmetry and show how the intricate behavior of black hole responses in four and higher dimensions can be understood from the SL(2, ℝ) representation theory. In particular, static perturbations of four-dimensional black holes belong to highest weight SL(2, ℝ) representations. It is this highest weight properety that forces the static Love numbers to vanish. We find that the Love symmetry is tightly connected to the enhanced isometries of extremal black holes. This relation is simplest for extremal charged spherically symmetric (Reissner-Nordström) solutions, where the Love symmetry exactly reduces to the isometry of the near horizon AdS2 throat. For rotating (Kerr-Newman) black holes one is lead to consider an infinite-dimensional SL(2, ℝ) ⋉ $$ \hat{\textrm{U}}{(1)}_{\mathcal{V}} $$

U
̂

1

V

extension of the Love symmetry. It contains three physically distinct subalgebras: the Love algebra, the Starobinsky near zone algebra, and the near horizon algebra that becomes the Bardeen-Horowitz isometry in the extremal limit. We also discuss other aspects of the Love symmetry, such as the geometric meaning of its generators for spin weighted fields, connection to the no-hair theorems, non-renormalization of Love numbers, its relation to (non-extremal) Kerr/CFT correspondence and prospects of its existence in modified theories of gravity.
Boostless cosmological collider bootstrap
Authors: Pimentel Guilherme L. , Wang Dong-Gang
Published: October 2022

Abstract

Cosmological correlation functions contain valuable information about the primordial Universe, with possible signatures of new massive particles at very high energies. Recent developments, including the cosmological bootstrap, bring new perspectives and powerful tools to study these observables. In this paper, we systematically classify inflationary three-point correlators of scalar perturbations using the bootstrap method. For the first time, we derive a complete set of single-exchange cosmological collider bispectra with new shapes and potentially detectable signals. Specifically, we focus on the primordial scalar bispectra generated from the exchange of massive particles with all possible boost-breaking interactions during inflation. We introduce three-point “seed” functions, from which we bootstrap the inflationary bispectra of scalar and spinning exchanges using weight-shifting and spin-raising operators. The computation of the seed function requires solving an ordinary differential equation in comoving momenta, a boundary version of the equation of motion satisfied by a propagator that linearly mixes a massive particle with the external light scalars. The resulting correlators are presented in analytic form, for any kinematics. These shapes are of interest for near-future cosmological surveys, as the primordial non-Gaussianity in boost-breaking theories can be large. We also identify new features in these shapes, which are phenomenologically distinct from the de Sitter invariant cases. For example, the oscillatory shapes around the squeezed limit have different phases. Furthermore, when the massive particle has much lower speed of sound than the inflaton, oscillatory features appear around the equilateral configuration.
Holographic Einstein ring of a charged AdS black hole
Authors: Liu Yuxuan , Chen Qian , Zeng Xiao-Xiong , Zhang Hongbao , Zhang Wenliang
Published: October 2022

Abstract

Taking into account that the real quantum materials are engineered generically at a finite chemical potential, we investigate the Einstein ring structure for the lensed response of the complex scalar field as a probe wave on the charged AdS black hole in the context of AdS/CFT. On the one hand, we find that the resulting Einstein ring radius has no variation with the chemical potential, which is similar to the behavior for the weakly interacting quantum system. On the other hand, not only can such a ring exist well within the screen, but also the temperature dependence of its radius exhibits a distinct feature in the sense that it displays an appreciable increase at low temperatures while the ring keeps unchanged right at the edge of the screen for the weakly interacting system. Note that such a Einstein ring emerges in the large frequencies and can be well captured by the photon sphere away from the black hole horizon in the geometric optics approximation, thus such a distinct feature may be regarded as a universal behavior associated with the high energy modes of the strongly coupled system which has a gravity dual.
Convergence Theorems for Varying Measures Under Convexity Conditions and Applications
Authors: Marraffa Valeria , Satco Bianca
Published: October 2022

In this paper, convergence theorems involving convex inequalities of Copson’s type (less restrictive than monotonicity assumptions) are given for varying measures, when imposing convexity conditions on the integrable functions or on the measures. Consequently, a continuous dependence result for a wide class of differential equations with many interesting applications, namely measure differential equations (including Stieltjes differential equations, generalized differential problems, impulsive differential equations with finitely or countably many impulses and also dynamic equations on time scales) is provided.
Tubb3 expression levels are sensitive to neuronal activity changes and determine microtubule growth and kinesin-mediated transport
Authors: Radwitz Jennifer , Hausrat Torben J. , Heisler Frank F. , Janiesch Philipp C. , Pechmann Yvonne , Rübhausen Michael , Kneussel Matthias
Published: October 2022

Microtubules are dynamic polymers of α/β-tubulin. They regulate cell structure, cell division, cell migration, and intracellular transport. However, functional contributions of individual tubulin isotypes are incompletely understood. The neuron-specific β-tubulin Tubb3 displays highest expression around early postnatal periods characterized by exuberant synaptogenesis. Although Tubb3 mutations are associated with neuronal disease, including abnormal inhibitory transmission and seizure activity in patients, molecular consequences of altered Tubb3 levels are largely unknown. Likewise, it is unclear whether neuronal activity triggers Tubb3 expression changes in neurons. In this study, we initially asked whether chemical protocols to induce long-term potentiation (cLTP) affect microtubule growth and the expression of individual tubulin isotypes. We found that growing microtubules and Tubb3 expression are sensitive to changes in neuronal activity and asked for consequences of Tubb3 downregulation in neurons. Our data revealed that reduced Tubb3 levels accelerated microtubule growth in axons and dendrites. Remarkably, Tubb3 knockdown induced a specific upregulation of Tubb4 gene expression, without changing other tubulin isotypes. We further found that Tubb3 downregulation reduces tubulin polyglutamylation, increases KIF5C motility and boosts the transport of its synaptic cargo N-Cadherin, which is known to regulate synaptogenesis and long-term potentiation. Due to the large number of tubulin isotypes, we developed and applied a computational model based on a Monte Carlo simulation to understand consequences of tubulin expression changes in silico. Together, our data suggest a feedback mechanism with neuronal activity regulating tubulin expression and consequently microtubule dynamics underlying the delivery of synaptic cargoes.
Extended phenotypes can underlie trade-offs: a case of social spiders
Authors: Parthasarathy Bharat , Bouchard Michelle , Schneider Jutta M.
Published: October 2022

Extended phenotypes engineered by animals can potentially improve safety and/or foraging. Whether the well-known trade-off between safety and foraging applies for extended phenotypes, and if so, how it is resolved has not been determined. Spiders build elaborate silk structures that serve as traps for their insect prey and often attach silken retreats (nests) to their capture webs. These extended phenotypes of spiders are made of silk that is considered costly since it is made of protein. Using the Indian social spider, Stegodyphus sarasinorum, we examined how simple proximal factors, like colony hunger state and group size, shape trade-offs in collectively built extended phenotypes that offer shelter and food. We found that well-fed colonies showed greater investment in retreat silk than starved colonies. However, the two groups did not differ in their investment in capture webs. Hence, our findings validate the starvation-risk taking hypothesis in an extended phenotypic paradigm by showing that hungry colonies trade-off retreat size for capture web, irrespective of group size.
Toward children-centric AI: a case for a growth model in children-AI interactions
Authors: La Fors Karolina
Published: October 2022

This article advocates for a hermeneutic model for children-AI (age group 7–11 years) interactions in which the desirable purpose of children’s interaction with artificial intelligence (AI) systems is children's growth. The article perceives AI systems with machine-learning components as having a recursive element when interacting with children. They can learn from an encounter with children and incorporate data from interaction, not only from prior programming. Given the purpose of growth and this recursive element of AI, the article argues for distinguishing the interpretation of bias within the artificial intelligence (AI) ethics and responsible AI discourse. Interpreting bias as a preference and distinguishing between positive (pro-diversity) and negative (discriminative) bias is needed as this would serve children's healthy psychological and moral development. The human-centric AI discourse advocates for an alignment of capacities of humans and capabilities of machines by a focus both on the purpose of humans and on the purpose of machines for humans. The emphasis on mitigating negative biases through data protection, AI law, and certain value-sensitive design frameworks demonstrates that the purpose of the machine for humans is prioritized over the purpose of humans. These top–down frameworks often narrow down the purpose of machines to do-no-harm and they miss accounting for the bottom-up views and developmental needs of children. Therefore, applying a growth model for children-AI interactions that incorporates learning from negative AI-mediated biases and amplifying positive ones would positively benefit children’s development and children-centric AI innovation. Consequently, the article explores:What challenges arise from mitigating negative biases and amplifying positive biases in children-AI interactions and how can a growth model address these?To answer this, the article recommends applying a growth model in open AI co-creational spaces with and for children. In such spaces human–machine and human–human value alignment methods can be collectively applied in such a manner that children can (1) become sensitized toward the effects of AI-mediated negative biases on themselves and others; (2) enable children to appropriate and imbue top-down values of diversity, and non-discrimination with their meanings; (3) enforce children’s right to identity and non-discrimination; (4) guide children in developing an inclusive mindset; (5) inform top-down normative AI frameworks by children’s bottom-up views; (6) contribute to design criteria for children-centric AI. Applying such methods under a growth model in AI co-creational spaces with children could yield an inclusive co-evolution between responsible young humans in the loop and children-centric AI systems.
The COVID-19 pandemic and Asian American employment
Authors: Honoré Bo E. , Hu Luojia
Published: October 2022

Recent studies have documented the disparate impact of the COVID-19 pandemic on labor market outcomes for different racial groups. This paper adds to this literature by documenting that the employment of Asian Americans—in particular those with no college education—has been especially hard hit by the economic crisis associated with the onset of the pandemic. This can only partly be explained by differences in demographics, local market conditions, and job characteristics, and it also cannot be entirely explained by possible different selection into education levels across ethnic groups. The burden on Asian Americans is primarily borne by those who are not US-born.
Respiratory effects of oral mitragynine and oxycodone in a rodent model
Authors: Henningfield Jack E. , Rodricks Joseph V. , Magnuson Aaron M. , Huestis Marilyn A.
Published: October 2022

Rationale

Kratom derives from Mitragyna speciosa (Korth.), a tropical tree in the genus Mitragyna (Rubiaceae) that also includes the coffee tree. Kratom leaf powders, tea-like decoctions, and commercial extracts are taken orally, primarily for health and well-being by millions of people globally. Others take kratom to eliminate opioid use for analgesia and manage opioid withdrawal and use disorder. There is debate over the possible respiratory depressant overdose risk of the primary active alkaloid, mitragynine, a partial μ-opioid receptor agonist, that does not signal through ß-arrestin, the primary opioid respiratory depressant pathway.

Objectives

Compare the respiratory effects of oral mitragynine to oral oxycodone in rats with the study design previously published by US Food and Drug Administration (FDA) scientists for evaluating the respiratory effects of opioids (Xu et al., Toxicol Rep 7:188–197, 2020).

Methods

Blood gases, observable signs, and mitragynine pharmacokinetics were assessed for 12 h after 20, 40, 80, 240, and 400 mg/kg oral mitragynine isolate and 6.75, 60, and 150 mg/kg oral oxycodone hydrochloride.

Findings

Oxycodone administration produced significant dose-related respiratory depressant effects and pronounced sedation with one death each at 60 and 150 mg/kg. Mitragynine did not yield significant dose-related respiratory depressant or life-threatening effects. Sedative-like effects, milder than produced by oxycodone, were evident at the highest mitragynine dose. Maximum oxycodone and mitragynine plasma concentrations were dose related.

Conclusions

Consistent with mitragynine’s pharmacology that includes partial µ-opioid receptor agonism with little recruitment of the respiratory depressant activating β-arrestin pathway, mitragynine produced no evidence of respiratory depression at doses many times higher than known to be taken by humans.
Intracortical facilitation and inhibition in human primary motor cortex during motor skill acquisition
Authors: Ho Kelly , Cirillo John , Ren April , Byblow Winston D.
Published: October 2022

The primary motor cortex (M1) is critical for movement execution, but its role in motor skill acquisition remains elusive. Here, we examine the role of M1 intracortical circuits during skill acquisition. Paired-pulse transcranial magnetic stimulation (TMS) paradigms of short-interval intracortical facilitation (SICF) and inhibition (SICI) were used to assess excitatory and inhibitory circuits, respectively. We hypothesised that intracortical facilitation and inhibition circuits in M1 would be modulated to support acquisition of a novel visuomotor skill. Twenty-two young, neurologically healthy adults trained with their nondominant hand on a skilled and non-skilled sequential visuomotor isometric finger abduction task. Electromyographic recordings were obtained from the nondominant first dorsal interosseous (FDI) muscle. Corticomotor excitability, SICF, and SICI were examined before, at the midway point, and after the 10-block motor training. SICI was assessed using adaptive threshold-hunting procedures. Task performance improved after the skilled, but not non-skilled, task training, which likely reflected the increase in movement speed during training. The amplitudes of late SICF peaks were modulated with skilled task training. There was no modulation of the early SICF peak, SICI, and corticomotor excitability with either task training. There was also no association between skill acquisition and SICF or SICI. The findings indicate that excitatory circuitries responsible for the generation of late SICF peaks, but not the early SICF peak, are modulated in motor skill acquisition for a sequential visuomotor isometric finger abduction task.
Traditions, anomalies, mistakes and recommendations in infrared spectrum measurement for wood
Authors: Tolvaj Laszlo
Published: October 2022

This paper deals with the difficulties of infrared spectroscopy measurement and suggests ways of dealing with them. Many problems appear when applying ATR (attenuated total reflection) measurement for determining the absorbance spectrum of wood, especially the highly porous nature of wood which does not fulfil the requirements of ATR measurement. Correct ATR spectrum determination requires wavelength dependence correction, but some authors miss out doing this. Normalisation of the infrared (IR) spectrum is a useful data manipulation method for correct evaluation of the spectra, but the incorrect normalisation can destroy the spectrum preventing the evaluation of the spectrum appropriately. Examples are given to teach the correct normalisation process. The difference spectrum method is an excellent tool to present the changes in IR spectra, but only a few scientists use it. Usage of wavenumbers during IR spectrum presentation is a traditional method nowadays. However, the usage of wavelength gives a more expressive spectrum presentation than wavenumber if the whole wavelength interval is presented in one diagram.
Role of brain 2-[18F]fluoro-2-deoxy-D-glucose-positron-emission tomography as survival predictor in amyotrophic lateral sclerosis
Authors: Canosa Antonio , Martino Alessio , Manera Umberto , Vasta Rosario , Grassano Maurizio , Palumbo Francesca , Cabras Sara , Di Pede Francesca , Arena Vincenzo , Moglia Cristina , Giuliani Alessandro , Calvo Andrea , Chiò Adriano , Pagani Marco
Published: October 2022

Purpose

The identification of prognostic tools in amyotrophic lateral sclerosis (ALS) would improve the design of clinical trials, the management of patients, and life planning. We aimed to evaluate the accuracy of brain 2-[18F]fluoro-2-deoxy-D-glucose-positron-emission tomography (2-[18F]FDG-PET) as an independent predictor of survival in ALS.

Methods

A prospective cohort study enrolled 418 ALS patients, who underwent brain 2-[18F]FDG-PET at diagnosis and whose survival time was available. We discretized the survival time in a finite number of classes in a data-driven fashion by employing a k-means-like strategy. We identified “hot brain regions” with maximal power in discriminating survival classes, by evaluating the Laplacian scores in a class-aware fashion. We retained the top-m features for each class to train the classification systems (i.e., a support vector machine, SVM), using 10% of the ALS cohort as test set.

Results

Data were discretized in three survival profiles: 0–2 years, 2–5 years, and > 5 years. SVM resulted in an error rate < 20% for two out of three classes separately. As for class one, the discriminant clusters included left caudate body and anterior cingulate cortex. The most discriminant regions were bilateral cerebellar pyramid in class two, and right cerebellar dentate nucleus, and left cerebellar nodule in class three.

Conclusion

Brain 2-[18F]FDG-PET along with artificial intelligence was able to predict with high accuracy the survival time range in our ALS cohort. Healthcare professionals can benefit from this prognostic tool for planning patients’ management and follow-up. 2-[18F]FDG-PET represents a promising biomarker for individual patients’ stratification in clinical trials. The lack of a multicentre external validation of the model warrants further studies to evaluate its generalization capability.
State and physiology behind personality in arthropods: a review
Authors: Rádai Zoltán , Kiss Johanna , Nagy Nikoletta A. , Somogyi Anna Ágnes , Fülöp Attila , Tóth Zsófia , Babits Melinda Alexáné , Németh Zoltán
Published: October 2022

In the endeavour to understand the causes and consequences of the variation in animal personality, a wide range of studies were carried out, utilising various aspects to make sense of this biological phenomenon. One such aspect integrated the study of physiological traits, investigating hypothesised physiological correlates of personality. Although many of such studies were carried out on vertebrates (predominantly on birds and mammals), studies using arthropods (mainly insects) as model organisms were also at the forefront of this area of research. In order to review the current state of knowledge on the relationship between personality and the most frequently studied physiological parameters in arthropods, we searched for scientific articles that investigated this relationship. In our review, we only included papers utilising a repeated-measures methodology to be conceptually and formally concordant with the study of animal personality. Based on our literature survey, metabolic rate, thermal physiology, immunophysiology, and endocrine regulation, as well as exogenous agents (such as toxins) were often identified as significant affectors shaping animal personality in arthropods. We found only weak support for state-dependence of personality when the state is approximated by singular elements (or effectors) of condition. We conclude that a more comprehensive integration of physiological parameters with condition may be required for a better understanding of state’s importance in animal personality. Also, a notable knowledge gap persists in arthropods regarding the association between metabolic rate and hormonal regulation, and their combined effects on personality. We discuss the findings published on the physiological correlates of animal personality in arthropods with the aim to summarise current knowledge, putting it into the context of current theory on the origin of animal personality.
Fully-automated deep learning-based flow quantification of 2D CINE phase contrast MRI
Authors: Pradella Maurice , Scott Michael B. , Omer Muhammad , Hill Seth K. , Lockhart Lisette , Yi Xin , Amir-Khalili Alborz , Sojoudi Alireza , Allen Bradley D. , Avery Ryan , Markl Michael
Published: October 2022

Objectives

Time-resolved, 2D-phase-contrast MRI (2D-CINE-PC-MRI) enables in vivo blood flow analysis. However, accurate vessel contour delineation (VCD) is required to achieve reliable results. We sought to evaluate manual analysis (MA) compared to the performance of a deep learning (DL) application for fully-automated VCD and flow quantification and corrected semi-automated analysis (corSAA).

Methods

We included 97 consecutive patients (age = 52.9 ± 16 years, 41 female) with 2D-CINE-PC-MRI imaging on 1.5T MRI systems at sinotubular junction (STJ), and 28/97 also received 2D-CINE-PC at main pulmonary artery (PA). A cardiovascular radiologist performed MA (reference) and corSAA (built-in tool) in commercial software for all cardiac time frames (median: 20, total contours per analysis: 2358 STJ, 680 PA). DL-analysis automatically performed VCD, followed by net flow (NF) and peak velocity (PV) quantification. Contours were compared using Dice similarity coefficients (DSC). Discrepant cases (> ± 10 mL or > ± 10 cm/s) were reviewed in detail.

Results

DL was successfully applied to 97% (121/125) of the 2D-CINE-PC-MRI series (STJ: 95/97, 98%, PA: 26/28, 93%). Compared to MA, mean DSC were 0.91 ± 0.02 (DL), 0.94 ± 0.02 (corSAA) at STJ, and 0.85 ± 0.08 (DL), 0.93 ± 0.02 (corSAA) at PA; this indicated good to excellent DL-performance. Flow quantification revealed similar NF at STJ (p = 0.48) and PA (p > 0.05) between methods while PV assessment was significantly different (STJ: p < 0.001, PA: p = 0.04). A detailed review showed noisy voxels in MA and corSAA impacted PV results. Overall, DL analysis compared to human assessments was accurate in 113/121 (93.4%) cases.

Conclusions

Fully-automated DL-analysis of 2D-CINE-PC-MRI provided flow quantification at STJ and PA at expert level in > 93% of cases with results being available instantaneously.

Key Points

• Deep learning performed flow quantification on clinical 2D-CINE-PC series at the sinotubular junction and pulmonary artery at the expert level in > 93% of cases.

• Location detection and contouring of the vessel boundaries were performed fully-automatic with results being available instantaneously compared to human assessments which approximately takes three minutes per location.

• The evaluated tool indicates usability in daily practice.
SAM-X: sorting algorithm for musculoskeletal x-ray radiography
Authors: Hinterwimmer Florian , Consalvo Sarah , Wilhelm Nikolas , Seidl Fritz , Burgkart Rainer H. H. , von Eisenhart-Rothe Rüdiger , Rueckert Daniel , Neumann Jan
Published: October 2022

Objective

To develop a two-phased deep learning sorting algorithm for post-X-ray image acquisition in order to facilitate large musculoskeletal image datasets according to their anatomical entity.

Methods

In total, 42,608 unstructured and pseudonymized radiographs were retrieved from the PACS of a musculoskeletal tumor center. In phase 1, imaging data were sorted into 1000 clusters by a self-supervised model. A human-in-the-loop radiologist assigned weak, semantic labels to all clusters and clusters with the same label were merged. Three hundred thirty-two non-musculoskeletal clusters were discarded. In phase 2, the initial model was modified by “injecting” the identified labels into the self-supervised model to train a classifier. To provide statistical significance, data split and cross-validation were applied. The hold-out test set consisted of 50% external data. To gain insight into the model’s predictions, Grad-CAMs were calculated.

Results

The self-supervised clustering resulted in a high normalized mutual information of 0.930. The expert radiologist identified 28 musculoskeletal clusters. The modified model achieved a classification accuracy of 96.2% and 96.6% for validation and hold-out test data for predicting the top class, respectively. When considering the top two predicted class labels, an accuracy of 99.7% and 99.6% was accomplished. Grad-CAMs as well as final cluster results underlined the robustness of the proposed method by showing that it focused on similar image regions a human would have considered for categorizing images.

Conclusion

For efficient dataset building, we propose an accurate deep learning sorting algorithm for classifying radiographs according to their anatomical entity in the assessment of musculoskeletal diseases.

Key Points

• Classification of large radiograph datasets according to their anatomical entity.

• Paramount importance of structuring vast amounts of retrospective data for modern deep learning applications.

• Optimization of the radiological workflow and increase in efficiency as well as decrease of time-consuming tasks for radiologists through deep learning.
Pectus excavatum in motion: dynamic evaluation using real-time MRI
Authors: Gräfe Daniel , Lacher Martin , Martynov Illya , Hirsch Franz Wolfgang , Voit Dirk , Frahm Jens , Busse Harald , Sesia Sergio Bruno , Krämer Sebastian , Zimmermann Peter
Published: October 2022

Objectives

The breathing phase for the determination of thoracic indices in patients with pectus excavatum is not standardized. The aim of this study was to identify the best period for reliable assessments of morphologic indices by dynamic observations of the chest wall using real-time MRI.

Methods

In this prospective study, patients with pectus excavatum underwent morphologic evaluation by real-time MRI at 3 T between January 2020 and June 2021. The Haller index (HI), correction index (CI), modified asymmetry index (AI), and modified eccentricity index (EI) were determined during free, quiet, and forced breathing respectively. Breathing-related differences in the thoracic indices were analyzed with the Wilcoxon signed-rank test. Motion of the anterior chest wall was analyzed as well.

Results

A total of 56 patients (11 females and 45 males, median age 15.4 years, interquartile range 14.3–16.9) were included. In quiet expiration, the median HI in the cohort equaled 5.7 (4.5–7.2). The median absolute differences (Δ) in the thoracic indices between peak inspiration and peak expiration were ΔHI = 1.1 (0.7–1.6, p < .001), ΔCI = 4.8% (1.3–7.5%, p < .001), ΔAI = 3.0% (1.0–5.0%, p < .001), and ΔEI = 8.0% (3.0–14.0%, p < .05). The indices varied significantly during different inspiratory phases, but not during expiration (p > .05 each). Furthermore, the dynamic evaluation revealed three distinctive movement patterns of the funnel chest.

Conclusions

Real-time MRI reveals patterns of chest wall motion and indicate that thoracic indices of pectus excavatum should be assessed in the end-expiratory phase of quiet expiration.

Key Points

• The thoracic indices in patients with pectus excavatum depend on the breathing phase.

• Quiet expiration represents the best breathing phase for determining thoracic indices.

• Real-time MRI can identify different chest wall motion patterns in pectus excavatum.