bluuebunny/crossref_metadata_2025 huggingface dataset:
Magnetic anisotropy in heterogeneous amorphous thin films: insights from thickness- and temperature-driven spin-reorientation
Authors: Masood Ansar , Belova L , Ström V
Published: May 2024

Magnetization orientation in thin films is intricately influenced by multiple anisotropy components, with the dominant anisotropy serving as a key determinant. This complexity becomes particularly intriguing when considering thin films composed of subnanometer-scale heterogeneous amorphous structures. Our investigation builds upon this foundation, specifically focusing on the Fe–Ni–B–Nb alloy system, known for its moderate glass-forming ability and susceptibility to nanocrystallization. In this study, we present thickness- and temperature-driven spin-reorientation (SRT) transition, attributed to competing magnetic anisotropy energies in thin films featuring a heterogeneous amorphous structure. Thermogravimetric investigations unveiled a unique heterogeneous amorphous structure, a revelation unattainable through conventional structural analysis methods. The observed spontaneous perpendicular magnetization in amorphous films, as evidenced by transcritical hysteresis loops and magnetic stripe domains, is ascribed to the pronounced residual stress arising from the substantial magnetostriction of the alloy system. The temperature-driven SRT is correlated to the order-disorder magnetic transition of the heterogeneous amorphous phase, characterized by a Curie temperature of ∼225 K. This transformative magnetic state of the heterogeneous amorphous matrix limits the exchange interaction among the densely distributed α-Fe nuclei regions, ultimately governing the dynamic magnetic responses with varying temperature. This work provides valuable insights into the dynamic magnetic orientation of thin films, especially those with heterogeneous amorphous structures, contributing to the broader understanding of the underlying mechanisms of magnetization reversals.
Insight of hydrogen evolution reaction in slab SnO2 loaded with transition metal atoms
Authors: Sun Xueqin , Huang Le , Liao Haijun , Xiao Wenbo , Li Jingbo
Published: May 2024

The utilization of hydrogen energy has emerged as a promising solution for clean and sustainable energy sources. The development of cost-effective catalysts with high activity and stability is crucial for efficient hydrogen production. In this work, we investigated the hydrogen evolution reaction (HER) catalytic activity of single transition metal atom (TM = V, Cr, Mn, Fe, Co, Ni) on slab SnO2 by using density functional theory. Our results revealed that the catalytic activity of the slab SnO2 can be significantly enhanced by loading the transition atom. By calculating the Gibbs free energies and exchange current densities in different adsorption configurations of TM-SnO2, single-atom catalyst (SAC) of Mn-loaded SAC exhibits excellent catalytic performance, characterized by a low Gibbs free energy barrier (−0.05 eV). Introducing a TM on the SnO2 surface breaks its local symmetry, while the strong coupling between the metal and H atoms enhances catalytic performance. The synergetic effect of symmetry breaking and metal-H interaction boosts overall catalytic activity. This work not only proposes a novel non-platinum HER catalyst based on SnO2 but also lays a solid foundation for future applications of SnO2-based catalysts.
Improved performance of ternary organic solar cells based on both bulk and pseudo-planar heterojunction active layer
Authors: Zheng Qiao , Zhou Hui , Guo Zhaohuang , Zhuang Jinyong , Deng Hui , Wu Jionghua , Zhang Caixia , Wang Weihuang , Cheng Shuying
Published: May 2024

The high photovoltaic conversion efficiency (PCE) of ternary organic solar cells (OSCs) based on PTB7-Th, PC71BM and IEICO-4F material is obtained, the short-circuit current density (J
SC), fill factor (FF), and open-circuit voltage is 25.90 mA cm−2, 73.20% and 0.71 V, respectively. PCE is as high as 13.53%. It is the highest PCE of ternary OSCs based on PTB7-Th, PC71BM and IEICO-4F materials for all we know. The narrow bandgap material of IEICO-4F is deposited on PTB7-Th:PC71BM bulk heterojunction (BHJ) by layer-by-layer process. We constructed the dual bandgap active layer both BHJ and pseudo-planar heterojunction (P-PHJ), it could be defined as ternary BHJ/P-PHJ of OSCs. This type of OSCs is not only the complementary bandgap material of the active layer, but also increasing the donor/acceptor (D/A) interface. The excitons generation and collection of the device are increased leading a higher J
SC and FF. The semitransparent OSCs (ST-OSCs) is prepared by varying the thickness of Ag electrode and PCE can reach 9.70%, and the average visible light transmittance and light use efficiency of ST-OSCs are improved effectively.
Absolutely continuous invariant measures for random dynamical systems of beta-transformations
Authors: Suzuki Shintaro
Published: May 2024

We consider an independent and identically distributed (i.i.d.) random dynamical system of simple linear transformations on the unit interval

T

β

(
x
)
=
β
x

(mod 1),

x
∈
[
0
,
1
]

, β > 0, which are the so-called beta-transformations. For such a random dynamical system, including the case that it is generated by uncountably many maps, we give an explicit formula for the density function of a unique stationary measure under the assumption that the random dynamics is expanding in mean. As an application, in the case that the random dynamics is generated by finitely many maps and the maps are chosen according to a Bernoulli measure, we show that the density function is analytic as a function of parameter in the Bernoulli measure and give its derivative explicitly. Furthermore, for a non-i.i.d. random dynamical system of beta-transformations, we also give an explicit formula for the random densities of a unique absolutely continuous invariant measure under a certain strong expanding condition or under the assumption that the maps randomly chosen are close to the beta-transformation for a non-simple number in the sense of parameter β.
Numerical investigation of two-dimensional Fokker-Planck equation in inflationary models: importance of slow-roll parameters
Authors: Hong Deog Ki , Jiang Jie , Yeom Dong-han
Published: May 2024

In this study, we generalize the Fokker-Planck equation to two-dimensional cases, including potential functions with periodic boundary conditions and piecewise-defined structures, to analyze the probability distribution in multi-field inflationary models. We employ the spectral method for spatial derivatives and the Crank-Nicolson method for the time evolution to solve the equation numerically for the slow-roll inflation. We find that the distribution in the Fokker-Planck equation was determined by the two-dimensional potential combined slow-roll parameters. And the volume weighting effect makes the distribution in the Fokker-Planck Volume equation is determined by the potential.
Analysis of BOSS galaxy data with weighted skew-spectra
Authors: Chen Shu-Fan , Chakraborty Priyesh , Dvorkin Cora
Published: May 2024

We present the first application of the weighted skew-spectra to analyze non-Gaussian
information in galaxy survey data. Using the tree-level galaxy skew-spectra together with the
one-loop power spectrum multipoles, we analyze the Sloan Digital Sky Survey (SDSS)-III Baryon
Oscillation Spectroscopic Survey (BOSS) galaxy clustering data, and target our search towards the
equilateral bispectrum shape of primordial non-Gaussianity. We use the Effective Field Theory
model for the galaxy power spectrum and bispectrum, and account for systematic effects, such as
the survey geometry. From our likelihood analysis, we find f
NL
equil 
= -34+296
-334 at 68% CL, consistent with previous works, while systematic errors
from our treatment of the survey geometry lead to an unreliable estimation of f
NL
ortho.
We further constrain the bias and counterterm parameters, while keeping the cosmology
fixed to Planck 2018 values. As a check, we also validate our analysis pipeline using the
Nseries simulation suite.
Impact of half-wave plate systematics on the measurement of CMB B-mode polarization
Authors: Monelli Marta , Komatsu Eiichiro , Ghigna Tommaso , Matsumura Tomotake , Pisano Giampaolo , Takaku Ryota
Published: May 2024

Polarization of the cosmic microwave background (CMB) can help probe the fundamental physics behind cosmic inflation via the measurement of primordial B modes.
As this requires exquisite control over instrumental systematics, some next-generation CMB experiments plan to use a rotating half-wave plate (HWP) as polarization modulator.
However, the HWP non-idealities, if not properly treated in the analysis, can result in additional systematics.
In this paper, we present a simple, semi-analytical end-to-end model to propagate the HWP non-idealities through the macro-steps that make up any CMB experiment (observation of multi-frequency maps, foreground cleaning, and power spectra estimation) and compute the HWP-induced bias on the estimated tensor-to-scalar ratio, r.
We find that the effective polarization efficiency of the HWP suppresses the polarization signal, leading to an underestimation of r.
Laboratory measurements of the properties of the HWP can be used to calibrate this effect, but we show how gain calibration of the CMB temperature can also be used to partially mitigate it.
On the basis of our findings, we present a set of recommendations for the HWP design that can help maximize the benefits of gain calibration.
From inflation to dark matter halo profiles: the impact of primordial non-Gaussianities on the central density cusp
Authors: Stahl Clément , Mai Nicolas , Famaey Benoit , Dubois Yohan , Ibata Rodrigo
Published: May 2024

It has recently been shown that local primordial non-Gaussianities (PNG) with significant amplitude (|f
NL| ∼ 1000), at small (Mpc) scales, can help in forming simulated galaxies with more disky baryonic kinematics than in the Gaussian case, while generating matter power spectra that can differ by up to 20% from the Gaussian case at non-linear scales. Here, we explore in detail the consequences of such small-scale PNG on the dark matter halo profiles. We show in particular that, for negative f
NL, dark matter halos formed in collisionless simulations are not always well described by the traditional Navarro-Frenk-White (NFW) profiles, as supported by their sparsity distribution. We conclude that NFW profiles are not as clear attractors for the density profiles of dark matter halos in the presence of PNG than in the case of a Gaussian contrast density field. We show how alternatives to the NFW profile can describe halos both in the Gaussian and non-Gaussian cases. From the combination of our sparsity analysis and the quality of the adjustments of the density profiles with a minimal extension to NFW, we conclude that z = 1 halos carry the most interesting information about PNG.
Steel surface defect detection algorithm based on ESI-YOLOv8
Authors: Zhang Xinrong , Wang Yanlong , Fang Huaisong
Published: May 2024

To enhance the precision of detecting defects on steel plate surfaces and diminish the incidences of false detection and leakage, the ESI-YOLOv8 algorithm is introduced. This algorithm introduces a novel EP module and integrates the large separation convolutional attention module and the spatial pyramid pooling module to propose the SPPF-LSKA module. Additionally, the original CIOU loss function is replaced with the INNER-CIOU loss function. The EP module minimizes redundant computations and model parameters to optimize efficiency and simultaneously increases the multi-scale fusion mechanism to expand the sensory field. The SPPF-LSKA module reduces computational complexity, accelerates model operation speed, and improves detection accuracy. Additionally, the INNER-CIOU loss function can improve detection speed and model accuracy by controlling the scale size of the auxiliary border.The results of the experiment indicate that, following the improvements made, the algorithm’s detection accuracy has increased to 78%, which is 3.7% higher than the original YOLOv8. Furthermore, the model parameters were reduced, and the verification was conducted using the CoCo dataset, resulting in an average accuracy of 77.8%. In conclusion, the algorithm has demonstrated its ability to perform steel plate surface defect detection with efficiency and accuracy.
Phase I quality control framework for monitoring organ-at-risk dose
Authors: Sivabhaskar Sruthi , Buatti Jacob S , Yeh Arthur B , Papanikolaou Niko , Roy Arkajyoti
Published: May 2024

Objective. The aim of this work was to develop a Phase I control chart framework for the recently proposed multivariate risk-adjusted Hotelling’s

T

2

chart. Although this control chart alone can identify most patients receiving extreme organ-at-risk (OAR) dose, it is restricted by underlying distributional assumptions, making it sensitive to extreme observations in the sample, as is typically found in radiotherapy plan quality data such as dose-volume histogram (DVH) points. This can lead to slightly poor-quality plans that should have been identified as out-of-control (OC) to be signaled in-control (IC). Approach. We develop a robust iterative control chart framework to identify all OC patients with abnormally high OAR dose and improve them via re-optimization to achieve an IC sample prior to establishing the Phase I control chart, which can be used to monitor future treatment plans. Main Results. Eighty head-and-neck patients were used in this study. After the first iteration, P14, P67, and P68 were detected as OC for high brainstem dose, warranting re-optimization aimed to reduce brainstem dose without worsening other planning criteria. The DVH and control chart were updated after re-optimization. On the second iteration, P14, P67, and P68 were IC, but P40 was identified as OC. After re-optimizing P40’s plan and updating the DVH and control chart, P40 was IC, but P14* (P14’s re-optimized plan) and P62 were flagged as OC. P14* could not be re-optimized without worsening target coverage, so only P62 was re-optimized. Ultimately, a fully IC sample was achieved. Multiple iterations were needed to identify and improve all OC patients, and to establish a more robust control limit to monitor future treatment plans. Significance. The iterative procedure resulted in a fully IC sample of patients. With this sample, a more robust Phase I control chart that can monitor OAR doses of new plans was established.
Vision-aided grasp classification: design and evaluation of compact CNN for prosthetic hands
Authors: Sharma Udit , Vasamsetti Srikanth , Chander Sekar Anup , Datta Banibrata
Published: May 2024

Powered prosthetic hands capable of executing various grasp patterns are highly sought-after solutions for upper limb amputees. A crucial requirement for such prosthetic hands is the accurate identification of the intended grasp pattern and subsequent activation of the prosthetic digits accordingly. Vision-based grasp classification techniques offer improved coordination between amputees and prosthetic hands without physical contact. Deep learning methods, particularly Convolutional Neural Networks (CNNs), are utilized to process visual information for classification. The key challenge lies in developing a model that can effectively generalize across various object shapes and accurately classify grasp classes. To address this, a compact CNN model named GraspCNet is proposed, specifically designed for grasp classification in prosthetic hands. The use of separable convolutions reduces the computational burden, making it potentially suitable for real-time applications on embedded systems. The GraspCNet model is designed to learn and generalize from object shapes, allowing it to effectively classify unseen objects beyond those included in the training dataset. The proposed model was trained and tested using various standard object data sets. A cross-validation strategy has been adopted to perform better in seen and unseen object class scenarios. The average accuracy achieved was 82.22% and 75.48% in the case of seen, and unseen object classes respectively. In computer-based real-time experiments, the GraspCNet model achieved an accuracy of 69%. A comparative analysis with state-of-the-art techniques revealed that the proposed GraspCNet model outperformed most benchmark techniques and demonstrated comparable performance with the DcnnGrasp method. The compact nature of the GraspCNet model suggests its potential for integration with other sensing modalities in prosthetic hands.
Machine learning-aided evaluation of oxidative strength of cold atmospheric plasma-treated water
Authors: Irmak Seyma Ecem , Ozdemir Gizem Dilara , Ozdemir Mehmet Akif , Ercan Utku Kürşat
Published: May 2024

Plasma medicine is gaining attraction in the medical field, particularly the use of cold atmospheric plasma (CAP) in biomedicine. The chemistry of the plasma is complex, and the reactive oxygen species (ROS) within it are the basis for the biological effect of CAP on the target. Understanding how the oxidative power of ROS responds to diverse plasma parameters is vital for standardizing the effective application of CAP. The proven applicability of machine learning (ML) in the field of medicine is encouraging, as it can also be applied in the field of plasma medicine to correlate the oxidative strength of plasma-treated water (PTW) according to different parameters. In this study, plasma-treated water was mixed with potassium iodide-starch reagent for color formation that could be linked to the oxidative capacity of PTW. Corresponding images were captured resulting from the exposure of the color-forming agent to water treated with plasma for different time points. Several ML models were trained to distinguish the color changes sourced by the oxidative strength of ROS. The AdaBoost Classifier (ABC) algorithm demonstrated better performance among the classification models used by extracting color-based features from the images. Our results, with a test accuracy of 63.5%, might carry a potential for future standardization in the field of plasma medicine with an automated system that can be created to interpret the oxidative properties of ROS in different plasma treatment parameters via ML.
Unraveling the environmental consequences of trade openness in South Africa: a novel approach using ARDL modeling
Authors: Lanhui Wang , Ibrahim Abubakar Sadiq
Published: May 2024

Free trade and environmental sustainability are currently top economic and environmental research priorities. While numerous theories connect trade openness with environmental quality, empirical evidence often fails to support these claims. Using data spanning from 1980 to 2020, our study examines the effect of trade openness on CO2 emissions in South Africa. By employing a novel ARDL modeling framework, our analysis confirms the presence of the Environmental Kuznets Curve (EKC) hypothesis in South Africa. Our findings reveal that while GDP square enhances environmental quality, trade openness and economic growth have a degrading effect over time. Additionally, the study identifies that energy consumption, FDI, and value-added activities all contribute to environmental degradation. Findings also highlights the influence of institutional quality on the environment, demonstrating that political stability and control of corruption lead to increased CO2 emissions, while the rule of law reduces CO2 emissions. The research suggested that the potential of green economies should be leveraged in developing renewable energy, sustainable development, the recycling industry, and green financing sectors. A shift in economic activity in this direction will thus foster long-term economic growth and sustainable development.
Beam shaping in light-sheet microscopy: an experimental analysis
Authors: Hüpfel Manuel , Nienhaus Gerd Ulrich
Published: May 2024

Thanks to its unique optical sectioning capability, light-sheet fluorescence microscopy has proven to be a powerful technique for volumetric imaging of entire model organisms with high spatial and temporal resolution. For light sheet generation with scanned laser beams, holographic beam shaping offers precise control over the optical fields exciting the fluorescence. Various illumination schemes have been proposed, aiming for best image quality with regard to axial resolution, optical sectioning, illumination homogeneity and photobleaching while at the same time retaining a large field of view. Here, we have engineered and characterized a variety of beams and analyzed their imaging performance by using phantom samples and zebrafish embryos. These data may assist researchers to select the light sheet best suited to the imaging application at hand.
Fault detection through discrete wavelet transforms and radial basis function neural network in shunt compensated distribution systems
Authors: Joshi Minesh K , Patel R R
Published: May 2024

This paper discusses a critical study of fault detection, classification, and identification in distribution systems compensated through a distribution static synchronous compensator (D-STATCOM) using discrete wavelet transforms (DWT) and a radial basis function neural network (RBFNN). The efficacy of the proportional integral (PI) controller is discussed in the simulation during normal, voltage sag, and swell conditions. Then, the Daubechies mother wavelet (db4) is used here to extract and decompose the fault current signals because of its high accuracy of detection with less processing time. The models are subjected to different conditions of faults, such as line to ground (LG), line to line (LL), double line to ground (LLG), and three phases (LLL and LLLG) with different fault resistance. The novelty of the scheme is that DWT and RBFNN techniques were compared and proven effective in demonstrating the faulty conditions. To validate the proposed approach, a simulation study is carried out in MATLAB with various operating conditions, and it is shown that the proposed method can depend on abundantly protecting the distribution grid from faulty conditions.
Transient state analysis of rehabilitated RC beams using finite element modelling and prediction using an artificial neural network
Authors: R Surya Prakash , N Parthasarathi
Published: May 2024

The present research develops and verifies a simpler numerical approach for analyzing the thermal transient state of rehabilitated concrete beams reinforced with various types of FRP (fiber-reinforced polymer) subjected to high temperatures and specifically built as under-reinforced concrete beams. This approach offers a straightforward, efficient, and exact instrument for numerical analysis. The proposed analytical technique has been validated by load-displacement curves and cross-section temperature data, indicating its dependability and practicality. Subsequently, the validated approach was used to examine the impact of significant variables on the outcome and restoration of FRP-reinforced concrete beams at high temperatures. The methodology gives the Comparing conventional and CFRP, GFRP, AFRP reinforced beams using beam, truss, and shell elements. Thermal and UDL loads were applied, mesh at 25 mm × 25 mm. Transient analysis contrasts performance via displacement and temperature. The temperature versus displacement curve shows the FRP comparisons. Identifying the critical temperature before failure is crucial, emphasizing the curve’s significance in assessing structural performance and potential failure points. Nodal temperatures ranged 939 °C–963 °C (rehabilitated) versus 958 °C (conventional). 200 °C difference affects thermal boundary conditions for structural analysis and Conventional peaks at 320 °C, while AFRP, GFRP, and CFRP reach 358 °C, 385 °C, and 390 °C respectively. CFRP lasts 2400 min. Neural network models demonstrate effective generalizability, enabling satisfactory predictions of RC beam rehabilitation with CFRP laminates within the study’s parameter range.
On-demand quantum light sources for underwater communications
Authors: Scognamiglio Dominic , Gale Angus , Al-Juboori Ali , Toth Milos , Aharonovich Igor
Published: May 2024

Quantum communication has been at the forefront of modern research for decades, however it is severely hampered in underwater applications, where the properties of water absorb nearly all useful optical wavelengths and prevent them from propagating more than, in most cases, a few metres. This research reports on-demand quantum light sources, suitable for underwater optical communication. The single photon emitters, which can be engineered using an electron beam, are based on impurities in hexagonal boron nitride. They have a zero phonon line at ∼436 nm, near the minimum value of water absorption and are shown to suffer negligible transmission and purity loss when travelling through water channels. These emitters are also shown to possess exceptional underwater transmission properties compared to emitters at other optical wavelengths and are utilised in a completely secure quantum key distribution experiment with rates of kbits s−1.
Prioritizing genomic variants through neuro-symbolic, knowledge-enhanced learning
Authors: Althagafi Azza , Zhapa-Camacho Fernando , Hoehndorf Robert
Published: May 2024

Motivation

Whole-exome and genome sequencing have become common tools in diagnosing patients with rare diseases. Despite their success, this approach leaves many patients undiagnosed. A common argument is that more disease variants still await discovery, or the novelty of disease phenotypes results from a combination of variants in multiple disease-related genes. Interpreting the phenotypic consequences of genomic variants relies on information about gene functions, gene expression, physiology, and other genomic features. Phenotype-based methods to identify variants involved in genetic diseases combine molecular features with prior knowledge about the phenotypic consequences of altering gene functions. While phenotype-based methods have been successfully applied to prioritizing variants, such methods are based on known gene–disease or gene–phenotype associations as training data and are applicable to genes that have phenotypes associated, thereby limiting their scope. In addition, phenotypes are not assigned uniformly by different clinicians, and phenotype-based methods need to account for this variability.

Results

We developed an Embedding-based Phenotype Variant Predictor (EmbedPVP), a computational method to prioritize variants involved in genetic diseases by combining genomic information and clinical phenotypes. EmbedPVP leverages a large amount of background knowledge from human and model organisms about molecular mechanisms through which abnormal phenotypes may arise. Specifically, EmbedPVP incorporates phenotypes linked to genes, functions of gene products, and the anatomical site of gene expression, and systematically relates them to their phenotypic effects through neuro-symbolic, knowledge-enhanced machine learning. We demonstrate EmbedPVP’s efficacy on a large set of synthetic genomes and genomes matched with clinical information.

Availability and implementation

EmbedPVP and all evaluation experiments are freely available at https://github.com/bio-ontology-research-group/EmbedPVP.
Service Utilisation of an Innovative Mental Health Counselling Clinic
Authors: Fang Lin , Lung Yu , Hui Gilda , Pang Nelson , Smith Malik , Azizi Tamana
Published: May 2024

Responding to the increasing challenges to mental health equity, Talk It Out Counseling Clinic (the Clinic), an innovative, public-facing counselling service, was established at the University of Toronto during the pandemic. Operating on the principles of anti-oppression and trauma-informed care, the Clinic trains Master of Social Work students to deliver mental health counselling to populations encountering multiple barriers to mental health equity through phone or video. Guided by a quality improvement framework, this study used chart reviews to examine the demographic characteristics, initial mental health status and service utilisation of clients (N = 116) who completed services at the Clinic during its inaugural year. Three-quarters of the clients identified as Black or other racialised individuals, and over 70 per cent rated their general mental health as poor or fair. Nearly 80 per cent of clients referred to the Clinic proceeded to an intake, amongst whom 69.6 per cent successfully completed the services. Warm handoff was associated with service engagement, whilist men and older clients were more likely to terminate the services prematurely. The study underscores the mental health needs of communities confronting multiple challenges and illuminates the processes conducive to client engagement and service delivery within an innovative, school-run mental health clinic.
Sebaceous gland organoid engineering
Authors: Liu Yiqiong , Gao Huanhuan , Chen Huating , Ji Shuaifei , Wu Lu , Zhang Hongliang , Wang Yujia , Fu Xiaobing , Sun Xiaoyan
Published: May 2024

Sebaceous glands (SGs), as holocrine-secreting appendages, lubricate the skin and play a central role in the skin barrier. Large full-thickness skin defects cause overall architecture disruption and SG loss. However, an effective strategy for SG regeneration is lacking. Organoids are 3D multicellular structures that replicate key anatomical and functional characteristics of in vivo tissues and exhibit great potential in regenerative medicine. Recently, considerable progress has been made in developing reliable procedures for SG organoids and existing SG organoids recapitulate the main morphological, structural and functional features of their in vivo counterparts. Engineering approaches empower researchers to manipulate cell behaviors, the surrounding environment and cell–environment crosstalk within the culture system as needed. These techniques can be applied to the SG organoid culture system to generate functionally more competent SG organoids. This review aims to provide an overview of recent advancements in SG organoid engineering. It highlights some potential strategies for SG organoid functionalization that are promising to forge a platform for engineering vascularized, innervated, immune-interactive and lipogenic SG organoids. We anticipate that this review will not only contribute to improving our understanding of SG biology and regeneration but also facilitate the transition of the SG organoid from laboratory research to a feasible clinical application.
Follow-up of immune response in patients with common variable immunodeficiency following SARS-CoV-2 vaccination
Authors: Gutiérrez-Bautista Juan Francisco , Díaz-Alberola Irene , Tarriño María , Aguilera María , Cobo Fernando , Reguera Juan Antonio , Rodríguez-Granger Javier , Mendoza Joaquín , López-Nevot Miguel Ángel , Sampedro Antonio
Published: May 2024

The COVID-19 pandemic highlighted the importance of effective vaccination strategies in controlling the spread of infectious diseases. SARS-CoV-2 vaccine has demonstrated high efficacy in preventing COVID-19 infection in the general population. However, the efficacy of this vaccine in patients with predominantly antibody deficiencies, such as common variable immunodeficiency (CVID) and X-linked agammaglobulinemia (XLA), should be closely monitored. CVID and XLA are rare genetic disorders that impair the immune system’s ability to produce antibodies, which are crucial for fighting infections. Patients with these disorders have a higher risk of severe disease and mortality from COVID-19 due to their compromised immune systems. In this study, we evaluated the humoral and cellular immune responses after four doses of mRNA-1273 and one BNT162b2 bivalent vaccine in a cohort of patients with CVID and XLA. The response in this population was lower than in the control group. However, the administration of the third dose improved the number of patients with seroconversion and the intensity of the humoral response, as well as the number of patients with a positive cellular response. Finally, the administration of the fourth and fifth doses improves the antibody titer and neutralization against wild type variant, but not against the prevalent XBB1.5 variant.
Cortical dysmorphology and reduced cortico-collicular projections in an animal model of autism spectrum disorder
Authors: Kosmer Kara , Kulesza Randy
Published: May 2024

Autism spectrum disorder is a neurodevelopmental disability that includes sensory disturbances. Hearing is frequently affected and ranges from deafness to hypersensitivity. In utero exposure to the antiepileptic valproic acid is associated with increased risk of autism spectrum disorder in humans and timed valproic acid exposure is a biologically relevant and validated animal model of autism spectrum disorder. Valproic acid-exposed rats have fewer neurons in their auditory brainstem and thalamus, fewer calbindin-positive neurons, reduced ascending projections to the midbrain and thalamus, elevated thresholds, and delayed auditory brainstem responses. Additionally, in the auditory cortex, valproic acid exposure results in abnormal responses, decreased phase-locking, elevated thresholds, and abnormal tonotopic maps. We therefore hypothesized that in utero, valproic acid exposure would result in fewer neurons in auditory cortex, neuronal dysmorphology, fewer calbindin-positive neurons, and reduced connectivity. We approached this hypothesis using morphometric analyses, immunohistochemistry, and retrograde tract tracing. We found thinner cortical layers but no changes in the density of neurons, smaller pyramidal and non-pyramidal neurons in several regions, fewer neurons immunoreactive for calbindin-positive, and fewer cortical neurons projecting to the inferior colliculus. These results support the widespread impact of the auditory system in autism spectrum disorder and valproic acid-exposed animals and emphasize the utility of simple, noninvasive auditory screening for autism spectrum disorder.
Quantitative proteomics of dorsolateral prefrontal cortex reveals an early pattern of synaptic dysmaturation in children with idiopathic autism
Authors: Fatemi S Hossein , Eschenlauer Arthur , Aman Justin , Folsom Timothy D , Chekouo Thierry
Published: May 2024

Autism spectrum disorder (ASD) is a developmental disorder with a rising prevalence and unknown etiology presenting with deficits in cognition and abnormal behavior. We hypothesized that the investigation of the synaptic component of prefrontal cortex may provide proteomic signatures that may identify the biological underpinnings of cognitive deficits in childhood ASD. Subcellular fractions of synaptosomes from prefrontal cortices of age-, brain area-, and postmortem-interval-matched samples from children and adults with idiopathic ASD vs. controls were subjected to HPLC-tandem mass spectrometry. Analysis of data revealed the enrichment of ASD risk genes that participate in slow maturation of the postsynaptic density (PSD) structure and function during early brain development. Proteomic analysis revealed down regulation of PSD-related proteins including AMPA and NMDA receptors, GRM3, DLG4, olfactomedins, Shank1-3, Homer1, CaMK2α, NRXN1, NLGN2, Drebrin1, ARHGAP32, and Dock9 in children with autism (FDR-adjusted P < 0.05). In contrast, PSD-related alterations were less severe or unchanged in adult individuals with ASD. Network analyses revealed glutamate receptor abnormalities. Overall, the proteomic data support the concept that idiopathic autism is a synaptopathy involving PSD-related ASD risk genes. Interruption in evolutionarily conserved slow maturation of the PSD complex in prefrontal cortex may lead to the development of ASD in a susceptible individual.
Neuroanatomy of autism: what is the role of the cerebellum?
Authors: Baizer Joan S
Published: May 2024

Autism (or autism spectrum disorder) was initially defined as a psychiatric disorder, with the likely cause maternal behavior (the very destructive “refrigerator mother” theory). It took several decades for research into brain mechanisms to become established. Both neuropathological and imaging studies found differences in the cerebellum in autism spectrum disorder, the most widely documented being a decreased density of Purkinje cells in the cerebellar cortex. The popular interpretation of these results is that cerebellar neuropathology is a critical cause of autism spectrum disorder. We challenge that view by arguing that if fewer Purkinje cells are critical for autism spectrum disorder, then any condition that causes the loss of Purkinje cells should also cause autism spectrum disorder. We will review data on damage to the cerebellum from cerebellar lesions, tumors, and several syndromes (Joubert syndrome, Fragile X, and tuberous sclerosis). Collectively, these studies raise the question of whether the cerebellum really has a role in autism spectrum disorder. Autism spectrum disorder is now recognized as a genetically caused developmental disorder. A better understanding of the genes that underlie the differences in brain development that result in autism spectrum disorder is likely to show that these genes affect the development of the cerebellum in parallel with the development of the structures that do underlie autism spectrum disorder.
Differences in mid-gestational and early postnatal neonatal cytokines and chemokines are associated with patterns of maternal autoantibodies in the context of autism
Authors: McLellan Janna , Croen Lisa A , Iosif Ana-Maria , Ashwood Paul , Yoshida Cathleen , Berger Kimberly , Van de Water Judy
Published: May 2024

Associations between maternal immune dysregulation (including autoimmunity and skewed cytokine/chemokine profiles) and offspring neurodevelopmental disorders such as autism have been reported. In maternal autoantibody-related autism, specific maternally derived autoantibodies can access the fetal compartment to target eight proteins critical for neurodevelopment. We examined the relationship between maternal autoantibodies to the eight maternal autoantibody-related autism proteins and cytokine/chemokine profiles in the second trimester of pregnancy in mothers of children later diagnosed with autism and their neonates’ cytokine/chemokine profiles. Using banked maternal serum samples from 15 to 19 weeks of gestation from the Early Markers for Autism Study and corresponding banked newborn bloodspots, we identified three maternal/offspring groups based on maternal autoantibody status: (1) mothers with autoantibodies to one or more of the eight maternal autoantibody-related autismassociated proteins but not a maternal autoantibody-related autism-specific pattern, (2) mothers with a known maternal autoantibody-related autism pattern, and (3) mothers without autoantibodies to any of the eight maternal autoantibody-related autism proteins. Using a multiplex platform, we measured maternal second trimester and neonatal cytokine/chemokine levels. This combined analysis aimed to determine potential associations between maternal autoantibodies and the maternal and neonatal cytokine/chemokine profiles, each of which has been shown to have implications on offspring neurodevelopment independently.
Infants’ reorienting efficiency depends on parental autistic traits and predicts future socio-communicative behaviors
Authors: Ronconi Luca , Cantiani Chiara , Riva Valentina , Franchin Laura , Bettoni Roberta , Gori Simone , Bulf Herman , Valenza Eloisa , Facoetti Andrea
Published: May 2024

Attentional reorienting is dysfunctional not only in children with autism spectrum disorder (ASD), but also in infants who will develop ASD, thus constituting a potential causal factor of future social interaction and communication abilities. Following the research domain criteria framework, we hypothesized that the presence of subclinical autistic traits in parents should lead to atypical infants’ attentional reorienting, which in turn should impact on their future socio-communication behavior in toddlerhood. During an attentional cueing task, we measured the saccadic latencies in a large sample (total enrolled n = 89; final sample n = 71) of 8-month-old infants from the general population as a proxy for their stimulus-driven attention. Infants were grouped in a high parental traits (HPT; n = 23) or in a low parental traits (LPT; n = 48) group, according to the degree of autistic traits self-reported by their parents. Infants (n = 33) were then longitudinally followed to test their socio-communicative behaviors at 21 months. Results show a sluggish reorienting system, which was a longitudinal predictor of future socio-communicative skills at 21 months. Our combined transgenerational and longitudinal findings suggest that the early functionality of the stimulus-driven attentional network—redirecting attention from one event to another—could be directly connected to future social and communication development.
Atypical functional connectivity between the amygdala and visual, salience regions in infants with genetic liability for autism
Authors: Liu Janelle , Girault Jessica B , Nishino Tomoyuki , Shen Mark D , Kim Sun Hyung , Burrows Catherine A , Elison Jed T , Marrus Natasha , Wolff Jason J , Botteron Kelly N , Estes Annette M , Dager Stephen R , Hazlett Heather C , McKinstry Robert C , Schultz Robert T , Snyder Abraham Z , Styner Martin , Zwaigenbaum Lonnie , Pruett Jr John R , Piven Joseph , Gao Wei
Published: May 2024

The amygdala undergoes a period of overgrowth in the first year of life, resulting in enlarged volume by 12 months in infants later diagnosed with ASD. The overgrowth of the amygdala may have functional consequences during infancy. We investigated whether amygdala connectivity differs in 12-month-olds at high likelihood (HL) for ASD (defined by having an older sibling with autism), compared to those at low likelihood (LL). We examined seed-based connectivity of left and right amygdalae, hypothesizing that the HL and LL groups would differ in amygdala connectivity, especially with the visual cortex, based on our prior reports demonstrating that components of visual circuitry develop atypically and are linked to genetic liability for autism. We found that HL infants exhibited weaker connectivity between the right amygdala and the left visual cortex, as well as between the left amygdala and the right anterior cingulate, with evidence that these patterns occur in distinct subgroups of the HL sample. Amygdala connectivity strength with the visual cortex was related to motor and communication abilities among HL infants. Findings indicate that aberrant functional connectivity between the amygdala and visual regions is apparent in infants with genetic liability for ASD and may have implications for early differences in adaptive behaviors.
CED-6/GULP and components of the clathrin-mediated endocytosis machinery act redundantly to correctly display CED-1 on the cell membrane in Caenorhabditis elegans
Authors: Harders Rikke Hindsgaul , Morthorst Tine H , Landgrebe Line E , Lande Anna D , Fuglsang Marie Sikjær , Mortensen Stine Bothilde , Feteira-Montero Verónica , Jensen Helene Halkjær , Wesseltoft Jonas Bruhn , Olsen Anders
Published: May 2024

CED-1 (cell death abnormal) is a transmembrane receptor involved in the recognition of “eat-me” signals displayed on the surface of apoptotic cells and thus central for the subsequent engulfment of the cell corpse in Caenorhabditis elegans. The roles of CED-1 in engulfment are well established, as are its downstream effectors. The latter include the adapter protein CED-6/GULP and the ATP-binding cassette family homolog CED-7. However, how CED-1 is maintained on the plasma membrane in the absence of engulfment is currently unknown. Here, we show that CED-6 and CED-7 have a novel role in maintaining CED-1 correctly on the plasma membrane. We propose that the underlying mechanism is via endocytosis as CED-6 and CED-7 act redundantly with clathrin and its adaptor, the Adaptor protein 2 complex, in ensuring correct CED-1 localization. In conclusion, CED-6 and CED-7 impact other cellular processes than engulfment of apoptotic cells.
Genome-wide patterns of noncoding and protein-coding sequence variation in the major fungal pathogen Aspergillus fumigatus
Authors: Brown Alec , Steenwyk Jacob L , Rokas Antonis
Published: May 2024

Aspergillus fumigatus is a deadly fungal pathogen, responsible for >400,000 infections/year and high mortality rates. A. fumigatus strains exhibit variation in infection-relevant traits, including in their virulence. However, most A. fumigatus protein-coding genes, including those that modulate its virulence, are shared between A. fumigatus strains and closely related nonpathogenic relatives. We hypothesized that A. fumigatus genes exhibit substantial genetic variation in the noncoding regions immediately upstream to the start codons of genes, which could reflect differences in gene regulation between strains. To begin testing this hypothesis, we identified 5,812 single-copy orthologs across the genomes of 263 A. fumigatus strains. In general, A. fumigatus noncoding regions showed higher levels of sequence variation compared with their corresponding protein-coding regions. Focusing on 2,482 genes whose protein-coding sequence identity scores ranged between 75 and 99%, we identified 478 total genes with signatures of positive selection only in their noncoding regions and 65 total genes with signatures only in their protein-coding regions. Twenty-eight of the 478 noncoding regions and 5 of the 65 protein-coding regions under selection are associated with genes known to modulate A. fumigatus virulence. Noncoding region variation between A. fumigatus strains included single-nucleotide polymorphisms and insertions or deletions of at least a few nucleotides. These results show that noncoding regions of A. fumigatus genes harbor greater sequence variation than protein-coding regions, raising the hypothesis that this variation may contribute to A. fumigatus phenotypic heterogeneity.
Does Social Intelligence Training Improve Daily Well-Being and Responsiveness to Daily Negative and Positive Events in Custodial Grandmothers?
Authors: Infurna Frank J , Castro Saul A , Webster Britney A , Dolbin-MacNab Megan L , Smith Gregory C , Crowley D Max , Musil Carol
Published: May 2024

Objectives

Custodial grandparents are grandparents who raise grandchildren on a full-time basis in absence of the grandchild’s birth parents. Compared to noncaregiving grandparents, custodial grandparents report poorer mental and physical health and stronger changes in daily well-being when experiencing negative and positive events. We examine whether an online social intelligence training (SIT) program improves custodial grandmothers’ (CGM) daily well-being, socioemotional skills, and changes in well-being when confronted with daily negative and positive events.

Methods

Multilevel models were applied to 200 CGM who were recruited from across the United States and completed a daily survey for 14 consecutive days prior to and following participation in a randomized clinical trial. Participants were randomized into the SIT program or an attention control condition focusing on healthy living habits. The outcomes of interest were daily well-being, social connectedness, emotional awareness, and perspective-taking.

Results

Multilevel analyses revealed that participants who participated in the SIT program, compared to the attention control condition, exhibited stronger emotional responsiveness (i.e., improvements) to daily positive events in the outcomes of positive affect, social engagement, and perspective-taking.

Discussion

Our findings illustrate that SIT improves key components of daily functioning in CGM, which may serve as a pathway linking the demands of custodial grandparenting to poorer mental and physical health. Our discussion focuses on the utility and accessibility of the SIT program for helping improve outcomes for this disadvantaged population.

Clinical Trials Registration Number: NCT03239977