bluuebunny/crossref_metadata_2025 huggingface dataset:
CD4 T cells restricted to DRB1*15:01 recognize two Epstein–Barr virus glycoproteins capable of intracellular antigen presentation
Authors: Drosu Natalia , Anderson Monique , Bilodeau Philippe A. , Nishiyama Shuhei , Mikami Takahisa , Bobrowski-Khoury Natasha , Cabot Jackson , Housman David , Levy Michael
Published: October 2024

Both genetic and environmental factors contribute to multiple sclerosis (MS) risk. Infection with the Epstein–Barr virus (EBV) is the strongest environmental risk factor, and HLA-DR15 is the strongest genetic risk factor for MS. We employed computational methods and in vitro assays for CD4 T cell activation to investigate the DR15-restricted response to EBV. Using a machine learning-based HLA ligand predictor, the EBV glycoprotein B (gB) was predicted to be enriched in epitopes restricted to presentation by DRB1*15:01. In DR15-positive individuals, two epitopes comprised the major CD4 T cell response to gB. Surprisingly, the expression of recombinant gB in a DR15-homozygous B cell line or primary autologous B cells elicited a CD4 T cell response, indicating that intracellular gB was loaded onto HLA class II molecules. By deleting the signal sequence of gB, we determined that this pathway for direct activation of CD4 T cells was dependent on trafficking to the endoplasmic reticulum (ER) within the B cell. We screened seven recombinant EBV antigens from the ER compartment for immune responses in DR15-negative vs. DR15-homozygous individuals. In addition to gB, gH was a key CD4 T cell target in individuals homozygous for DR15. Compared to non-DR15 controls, DR15-homozygotes had significantly higher T cell responses to both gB and gH but not to EBV latent or lytic antigens overall. Responses to gB and gH were slightly elevated in DR15 homozygotes with MS. Our results link MS environmental and genetic risk factors by demonstrating that HLA-DR15 dictates CD4 T cell immunity to EBV antigens.
High-fidelity remote entanglement between superconducting fixed-frequency qubits
Authors: Ohfuchi Mari , Sato Shintaro
Published: October 2024

Highly accurate quantum state transfer and remote entanglement between superconducting fixed-frequency qubits have not yet been realized. In this study, we calculate the characteristics of a transmission path with a 1- or 0.25 m superconducting coaxial cable and use the characteristics to perform time evolution simulations of quantum state transfer and remote entanglement between superconducting fixed-frequency qubits. We find that remote entanglement, or half-quantum state transfer, can achieve a high fidelity

>

99
%

even in the presence of a qubit frequency detuning caused by manufacturing fluctuations, while a small qubit frequency detuning substantially reduces the efficiency of quantum state transfer. Quantum circuit simulations modeling proposed remote entanglement demonstrate that teleportation of a logical qubit with a

3

×

3

surface code, as an example of computation using remote entanglement, attains nearly the same fidelity as in-node computation for both 1- and 0.25 m cable lengths.
Research on influence of stress concentration on metal magnetic memory signal for stress evaluation
Authors: Luo Yuanqing , Liu Bin , He Peng
Published: October 2024

Based on the magneto-mechanical effect and stress concentration effect, this paper takes the failure of ferromagnetic components caused by stress concentration as the research background, artificially creates stress concentration by prefabricating U-shaped defects, and discusses the H

p
(y) signal distribution law of prefabricated U-shaped defect samples and the difference in H

p
(y) signal between specimens with different tip SCFs. Results show that the H

p
(y) signal has an apparent mutation in the stress concentration area, and when the stress concentration factor was the same, the magnetic field intensity gradient K becomes higher as tensile load increasing. As stress concentration factor increasing, the K value of the stress concentration area also increases gradually. Based on theoretical model of H

p
(y) signal, it can be known that the K value can be used to judge the sample stress concentration degree with the results in this study.
Intensify the hindrance to gas entrapment on the construction of Al 5356 thin-walled structure by tuning the WAAM process parameters
Authors: Saravana Kumar M , Jeyaprakash N , Yang Che-Hua
Published: October 2024

Compared to other metallic additive manufacturing methods, Wire Arc Additive Manufacturing (WAAM) has a number of advantages, such as less equipment capital required and more material composition flexibility. However, uneven welding and feed rates, as well as inadequate gas flow, can result in flaws such oxidation, gas entrapment, and humping. This study aims to reduce gas entrapment, maximize tensile strength, and reduced elastic modulus of the WAAM Al5356 wall by optimizing gas flow rate (13, 16 and 19 l min−1) in conjunction with welding and feed rates. The study highlighted gas flow rate as the most important component in pore formation and used the Entropy approach in conjunction with the COmplex PRoportional ASsessment (COPRAS) tool to identify ideal settings. The reduction in gas entrapment to 0.02%, as shown in the confirmation studies, resulted in a 33.9% rise in tensile strength and a 64.7% rise in elastic modulus. To verify these ideal parameters, elastic modulus mapping was done on the printed WAAM Al5356 wall. Moreover, the damage processes connected to gas entrapment and humping development were examined using fractography. Consequently, the research determined the ideal conditions to generate a multi-layer structure free of defects, improving its practicality in aerospace and automotive sectors.
Poly(o-anisidine) and poly(o-anisidine-co-aniline) polymers synthesized on the ZnFeNi alloy coated steel surface
Authors: Akdag Abdurrahman
Published: October 2024

ZnFeNi alloy was synthesized on the carbon steel surface in a sulfate bath using the galvanostatic method at a constant current of 1.5 mA for 300 s. Poly(o-anisidine) homopolymer and poly(o-anisidine-co-aniline) copolymer were synthesized on the ZnFeNi coated electrode surface. Poly(o-anisidine) homopolymer was synthesized in 0.05 M o-anisidine+0.2 M sodium oxalate medium, and poly(o-anisidine-co-aniline) copolymer was synthesized in 0.05 M o-anisidine+0.05 M aniline+0.2 M sodium oxalate medium. Electrochemical synthesis was carried out by cyclic voltammetry technique. The synthesized materials were characterized by electrochemical impedance spectroscopy, linear sweep voltammetry, open circuit potential-time, and anodic polarization curves. The open circuit potential–time curves showed that polymer coatings had higher open circuit potential. By the linear sweep voltammetry measurements, it was determined that ZnFeNi alloys were present at the base of the polymer layers after polymer synthesis. It was understood from the anodic polarization curves that the polymer coated electrodes had lower current values ​​than the uncoated ZnFeNi coated electrode, and the poly(o-anisidine) coated electrode had lower current values ​​than the poly(o-anisidine-co-aniline) coated electrode. The electrochemical impedance spectroscopy measurements showed that the polarization resistance of polymer-coated electrodes was higher than the polymer-free electrode during long periods of waiting in 3.5% corrosive solution. Among the polymer-coated electrodes, it was understood that the homopolymer poly(o-anisidine) showed better corrosion performance than the poly(o-anisidine-co-aniline) copolymer.
Enhanced absorption in SnS/SnSe, SnS/ZnS, and SnS/ZnSe vdW heterostructures for optoelectronic applications: DFT insights
Authors: Raturi Ashish , Mittal Poornima , Choudhary Sudhanshu
Published: October 2024

The electronic and optical properties of monolayers of tin monochalcogenides and zinc monochalcogenides are elucidated by utilizing density functional theory. The calculated results indicate that the monolayers of tin monochalcogenides (SnS and SnSe) have low bandgap and significant absorption in some segments of the visible region (∼400 nm to ∼500 nm). However, the monolayers of zinc monochalcogenides (ZnS and ZnSe) have wide bandgap and negligible absorption in the visible region, which limits their optical performance. Despite low absorption in visible region, ZnS and ZnSe exhibit fascinating properties such as wide band gap, cheapness, low toxicity, earth abundance, structural stability, and high refractive index. To identify the combined potential of zinc and tin, the van der Waals heterostructures SnS/SnSe, SnS/ZnS, and SnS/ZnSe are formed, and their optical and electronic properties are calculated. The calculated results illustrate that the formed heterostructures exhibit bandgap lowering and enhanced visible light absorption. The optical absorption is entirely shifted towards the visible region due to the formation of heterostructure (redshift). The enhanced visible light absorption and narrowed bandgap of the formed heterostructures make them a potential candidate for the fabrication of optoelectronic devices and solar cells.
Design of ultra-broadband long-wave to ultra-long-wave infrared absorber based on machine learning
Authors: Ali Riaz , Su Wei , Ding Zhipeng , Ali Muhammad , Ismail Hina , Saif Zainab , Ali Jawad , Yao Hongbing
Published: October 2024

long-wave infrared (LWIR) and ultra-long-wave infrared (ULWIR) radiation find extensive utility in atmospheric monitoring, night reconnaissance, deep space exploration, and various other fields. However, achieving ultra-wideband absorption within these spectral ranges has persistently posed a significant challenge for researchers. Metasurfaces have attracted great interest due to their ability to manipulate electromagnetic (EM) waves with unprecedented precision and efficiency. In this paper, a metasurface absorber with a simple structure is proposed. Combined with machine learning (ML) of Random Forest (RF) algorithm for design optimization, the absorber achieves ultra-wideband perfect absorption of 42.54 μm within the LWIR-ULWIR band. Furthermore, the stability and accuracy of the RF algorithm in absorber design are also evaluated and compared with other classical ML algorithms. The successful realization of this work can offer the advancement of thermal imaging, sensing, and communication systems operating within the LWIR and ULWIR spectra.
An exactly solvable model for RNA polymerase during the elongation stage
Authors: Ngoc Ngo P N , Belitsky Vladimir , Schütz Gunter M
Published: October 2024

We consider a Markovian model for the kinetics of RNA Polymerase (RNAP) which provides a physical explanation for the phenomenon of cooperative pushing during transcription elongation observed in biochemical experiments on Escherichia coli and yeast RNAP. To study how backtracking of RNAP affects cooperative pushing we incorporate into this model backward (upstream) RNAP moves. With a rigorous mathematical treatment of the model we derive conditions on the mutual static and kinetic interactions between RNAP under which backtracking preserves cooperative pushing. This is achieved by exact computation of several key properties in the steady state of this model, including the distribution of headway between two RNAP along the DNA template and the average RNAP velocity and flux.
High-pulse-energy ultrafast 3 µm laser generation through OPG/DFG in PPMgLN
Authors: Chen Hongxin , Zhang Yongchang , Shen Yonghang
Published: October 2024

We report high-pulse-energy ultrafast 3 µm laser generation through optical parametric generation/difference frequency generation (OPG/DFG) in periodically poled magnesium-oxide-doped lithium niobate (PPMgLN). A commercial 1030 nm femtosecond laser is applied as the pump light and a homemade broadband nanosecond pulse laser around 1580 nm is used as the signal light in DFG. The broadband 1580 nm laser has a master oscillator power amplifier (MOPA) structure with a directly modulated superluminescent light-emitting diode (SLED) as the pulse seed and three stages of Er/Yb fiber amplifiers to lift its average power. A portion of the 1030 nm output pulse is converted to an electronic pulse via a pin detector, which is used as the trigger signal of the SLED driving circuit to ensure synchronization between the signal and the 1030 nm pump pulse. When injecting 2.12 W pump light into the PPMgLN, a broadband mid-infrared (MIR) output of 280 mW can be achieved directly through OPG with a center wavelength around 2.94 μm, a pulse width of 1.38 ps and a pulse repetition frequency of 500 kHz. The corresponding MIR pulse energy is 0.56 µJ. When injecting 2.62 W signal light simultaneously, a MIR output of 300 mW is achieved through the DFG process at the same pulse repetition frequency, corresponding to a pulse energy of 0.6 µJ. The conversion efficiency of the ultrafast pump laser to MIR reaches 14.1%. This high-pulse-energy 3 μm ultrafast laser has great prospects for applications in biological tissue ablation.
Analytic continuation in the coupling constant for resonances in
Be*
Authors: Zhang 张 Hantao 涵韬 , Bai 柏 Dong 栋 , Ren 任 Zhongzhou 中洲
Published: October 2024

The application scope of the analytic continuation in the coupling constant (ACCC) can be extended to the exchange parameters of the effective nucleon-nucleon interaction in the microscopic cluster model. Based on such an exchange parameter dependent ACCC (abbreviated as EPD-ACCC), we examine the

Be system in the framework of the

microscopic cluster model. The particle emission from excited states of

are investigated, and the corresponding resonant energies are obtained via EPD-ACCC. Furthermore, the complex scaling method (CSM) is applied for comparison. A good agreement between these two theoretical approaches is obtained. This study demonstrates EPD-ACCC to be a reliable method for estimating multi-cluster resonances in light hypernuclei.
Revisiting the Velocity Dispersion–Size Relation in Molecular Cloud Structures
Authors: Feng Haoran , Chen Zhiwei , Jiang Zhibo , Ma Yuehui , Yang Yang , Yu Shuling , Ge Dongqing , Zhou Wei , Du Fujun , Wang Chen , Zhang Shiyu , Su Yang , Yang Ji
Published: October 2024

Structures in molecular ISM are observed to follow a power-law relation between the velocity dispersion and spatial size, known as Larson’s first relation, which is often attributed to the turbulent nature of molecular ISM and imprints the dynamics of molecular cloud structures. Using the 13CO (J = 1–0) data from the Milky Way Imaging Scroll Painting survey, we built a sample with 360 structures having relatively accurate distances obtained from either the reddened background stars with Gaia parallaxes or associated maser parallaxes, spanning from 0.4 to ∼15 kpc. Using this sample and about 0.3 million pixels, we analyzed the correlations between velocity dispersion, surface/column density, and spatial scales. Our structure-wise results show power-law indices smaller than 0.5 in both the σ

v
–R
eff and σ

v
–R
eff · Σ relations. In the pixel-wise results, the

σ

v

pix

is statistically scaling with the beam physical size (R
s ≡ ΘD/2) in form of

σ

v

pix

∝

R

s

0.43
±
0.03

. Meanwhile,

σ

v

pix

in the inner Galaxy is statistically larger than the outer side. We also analyzed correlations between

σ

v

pix

and the H2 column density N(H2), finding that

σ

v

pix

stops increasing with N(H2) after ≳1022 cm−2. The structures with and without high-column-density (>1022 cm−2) pixels show different

σ

v

pix

∝
N

(

H

2

)

ξ

relations, where the mean (std) ξ values are 0.38 (0.14) and 0.62 (0.27), respectively.
Adversarial artifact detection in EEG-based brain–computer interfaces
Authors: Chen Xiaoqing , Meng Lubin , Xu Yifan , Wu Dongrui
Published: October 2024

Objective. machine learning has achieved significant success in electroencephalogram (EEG) based brain–computer interfaces (BCIs), with most existing research focusing on improving the decoding accuracy. However, recent studies have shown that EEG-based BCIs are vulnerable to adversarial attacks, where small perturbations added to the input can cause misclassification. Detecting adversarial examples is crucial for both understanding this phenomenon and developing effective defense strategies. Approach. this paper, for the first time, explores adversarial detection in EEG-based BCIs. We extend several popular adversarial detection approaches from computer vision to BCIs. Two new Mahalanobis distance based adversarial detection approaches, and three cosine distance based adversarial detection approaches, are also proposed, which showed promising performance in detecting three kinds of white-box attacks. Main results. we evaluated the performance of eight adversarial detection approaches on three EEG datasets, three neural networks, and four types of adversarial attacks. Our approach achieved an area under the curve score of up to 99.99% in detecting white-box attacks. Additionally, we assessed the transferability of different adversarial detectors to unknown attacks. Significance. through extensive experiments, we found that white-box attacks may be easily detected, and differences exist in the distributions of different types of adversarial examples. Our work should facilitate understanding the vulnerability of existing BCI models and developing more secure BCIs in the future.
Long sequence Hopfield memory*
Authors: Tahir Chaudhry Hamza , Zavatone-Veth Jacob A , Krotov Dmitry , Pehlevan Cengiz
Published: October 2024

Sequence memory is an essential attribute of natural and artificial intelligence that enables agents to encode, store, and retrieve complex sequences of stimuli and actions. Computational models of sequence memory have been proposed where recurrent Hopfield-like neural networks are trained with temporally asymmetric Hebbian rules. However, these networks suffer from limited sequence capacity (maximal length of the stored sequence) due to interference between the memories. Inspired by recent work on Dense Associative Memories, we expand the sequence capacity of these models by introducing a nonlinear interaction term, enhancing separation between the patterns. We derive novel scaling laws for sequence capacity with respect to network size, significantly outperforming existing scaling laws for models based on traditional Hopfield networks, and verify these theoretical results with numerical simulation. Moreover, we introduce a generalized pseudoinverse rule to recall sequences of highly correlated patterns. Finally, we extend this model to store sequences with variable timing between states’ transitions and describe a biologically-plausible implementation, with connections to motor neuroscience.
High-dimensional asymptotics of denoising autoencoders*
Authors: Cui Hugo , Zdeborová Lenka
Published: October 2024

We address the problem of denoising data from a Gaussian mixture using a two-layer non-linear autoencoder with tied weights and a skip connection. We consider the high-dimensional limit where the number of training samples and the input dimension jointly tend to infinity while the number of hidden units remains bounded. We provide closed-form expressions for the denoising mean-squared test error. Building on this result, we quantitatively characterize the advantage of the considered architecture over the autoencoder without the skip connection that relates closely to principal component analysis. We further show that our results accurately capture the learning curves on a range of real data sets.
Open climate science is brave climate science
Authors: Thöle Lena M , Wegmann Martin
Published: October 2024

The pivotal role of climate science in advancing the UN Sustainable Development Goals underscores the urgent need for ample and open climate data sharing. While numerous large-scale endeavours highlight the efficacy of open climate data, we often encounter personal reservations in our scientific community. Here we argue that beyond infrastructure and service availability, a framework of acceptance and courage is needed in progressing data visibility.
Scaffold-based tissue engineering strategies for urethral repair and reconstruction
Authors: Jin Yangwang , Yang Ming , Zhao Weixin , Liu Meng , Fang Wenzhuo , Wang Yuhui , Gao Guo , Wang Ying , Fu Qiang
Published: October 2024

Urethral strictures are common in urology; however, the reconstruction of long urethral strictures remains challenging. There are still unavoidable limitations in the clinical application of grafts for urethral injuries, which has facilitated the advancement of urethral tissue engineering. Tissue-engineered urethral scaffolds that combine cells or bioactive factors with a biomaterial to mimic the native microenvironment of the urethra, offer a promising approach to urethral reconstruction. Despite the recent rapid development of tissue engineering materials and techniques, a consensus on the optimal strategy for urethral repair and reconstruction is still lacking. This review aims to collect the achievements of urethral tissue engineering in recent years and to categorize and summarize them to shed new light on their design. Finally, we visualize several important future directions for urethral repair and reconstruction.
Functional properties of expanded austenite generated on AISI 316L by plasma nitrocarburizing using different active screen materials
Authors: M Jafarpour S , Mandel M , Krüger L , Biermann H , Dalke A
Published: October 2024

This study investigates the functional properties of the expanded austenite layers generated on AISI 316L austenitic stainless steel resulting from active screen plasma nitrocarburizing using different active screen materials, i.e. steel or solid carbon. Treatments were conducted at 460 °C for 5 h in a nitrogen-hydrogen feed gas, whereas for the treatments using a steel active screen, methane was added as a carbon precursor. Additionally, the bias plasma conditions applied at the samples were varied between 0 kW and 1.25 kW. Samples were characterized by complementary microstructural and compositional investigations, surface roughness and hardness measurements, pin-on-disk tribological tests as well as potentiodynamic polarization tests in H2SO4 and NaCl electrolytes. The functional properties of the case are discussed based on the contents of nitrogen and carbon in the expanded austenite and their effective diffusion depths. The results show that the usage of a carbon screen generally produces surfaces with uniform layer thickness, high hardness, improved wear resistance and a delayed tendency to pitting corrosion independent of the bias condition applied to the samples. When applying both screen materials at non-biased condition, the general corrosion resistance is slightly reduced under the conditions used, however, the layers generated using the carbon screen have a wear rate that is 3 times lower. It can be concluded that the carbon screen represents a robust treatment variant for austenitic stainless steels to produce sufficiently thick and wear-resistant surface layers in a short treatment duration, which still have the potential to maintain the corrosion resistance in different environments.
Procedure for reducing cross-resonance gate errors using pulse-level control
Authors: Danin David , Tennie Felix
Published: October 2024

Current implementations of superconducting qubits are often limited by the low fidelities of multi-qubit gates. We present a reproducible and runtime-efficient pulse-level approach for calibrating an improved cross-resonance gate CR(θ) for arbitrary θ. This CR(θ) gate can be used to produce a wide range of other two-qubit gates via the application of standard single-qubit gates. By performing an interleaved randomised benchmarking sequence, we demonstrate that our approach leads to significantly lower incoherent errors than the circuit-level approach currently used by IBM. Hence, our procedure provides a genuine improvement for applications where noise remains a limiting factor.
Gap-filling of land surface temperature in arid regions by combining Landsat 8 and 9 imageries
Authors: Arabi Aliabad Fahime , Ghaderpour Ebrahim , Mazidi Ahmad , Houshmandzade Fatemeh
Published: October 2024

Land surface temperature (LST) is an important factor in land monitoring studies, but due to the presence of clouds, dust and sensor issues, there are missing values. The aims of this research are to determine the optimal parameters for the reconstruction of Landsat-LST images, required in many applications, by the harmonic analysis of time series algorithm (HANTS) and to investigate the possibility of improving LST reconstruction accuracy using Landsat 8 and 9 images simultaneously. For these aims, 91 Landsat 8 and 9 images with 100 m spatial resolution in 2022 and 2023 are employed, covering Yazd-Ardakan plain in Iran. Three methods are used for evaluation. In method one, a part of LST image is considered as a gap and is compared with the initial value after reconstruction. In method two, on a cloudy day and a cloudless day, surface temperature values are measured using thermometers at fifty points in plain lands, and the difference between gap-filled satellite measurements and ground measurements is calculated. In method three, all the reconstructed LST images are compared with the original images. In method one, the root mean square error (RMSE) of reconstructed LST reduces by 1.3 °C when using the combined Landsat 8 and 9 images. In method two, RMSEs of reconstructed LST images are 6.1 °C when using Landsat 8 and 5.4 °C when using the combined Landsat 8 and 9. Method three shows that 41% of the study region has RMSE of less than 2 °C when using only Landsat 8, while this value becomes 72% when combining Landsat 8 and 9. In general, the combined use of Landsat 8 and 9 LST images improves the accuracy of reconstruction using HANTS. The findings of this research are crucial for regional applications and remote monitoring of surface temperature in areas with limited weather stations.
Exploring the potential of contemporary deep learning methods in purifying polluted information
Authors: Wang Mingyu , Li Jianping
Published: October 2024

Accurately predicting chaotic dynamical systems is a crucial task in various fields, and recent advancements have leveraged deep learning for this purpose. However, in the era of big data, the inevitable challenge of data contamination caused by invalid information from other interfering systems becomes increasingly prominent and complicates accurate predictions. Although contemporary deep learning methods have shown their potential, very few studies have focused on developing algorithms specifically designed to address the problem posed by such data contamination. Thus, exploring the ability of contemporary deep learning methods to purify polluted information fills an important gap in the current body of research. This study explores the performance and stability of several modern deep learning techniques for predicting chaotic systems using datasets polluted by invalid information. Our findings reveal that while most of the state-of-the-art deep learning methods exhibit reduced and unstable predictive performance owing to such contamination, the dynamical system deep learning (DSDL) method stands out, remaining unaffected by any interference. This breakthrough illustrates DSDL’s unique ability to purify invalid data and uncover the inherent rules of chaotic systems. As we move forward, DSDL paves the way for a more reliable and interpretable model, ensuring that we can confidently predict chaotic systems with precision even in the most challenging environments.
Revisiting the epidemiological role of a native vector in Northern California vineyards
Authors: Daugherty Matthew P , Cooper Monica L , Smith Rhonda J , Varela Lucia G , Almeida Rodrigo P P
Published: October 2024

Effective disease management hinges on an accurate understanding of the ecological and epidemiological underpinnings of the pathosystem. New epidemics may prompt consideration of whether knowledge gaps or changes to the pathosystem warrant revision of management strategies. Pierce’s disease of grapevines is highly episodic in coastal Northern California vineyards, with modest incidence in most years punctuated by occasionally severe epidemics. To better understand what was driving a developing epidemic in the region, we revaluated what is known about the ecology and epidemiological role of the dominant vector, the blue-green sharpshooter Graphocephala atropunctata. We monitored vector spatiotemporal dynamics at 32 vineyards over three years, surveyed plant community composition in the adjacent habitat to understand its link to vector recruitment, and quantified patterns of natural infectivity for the pathogen Xylella fastidiosa. Overall, the results were consistent with past studies of G. atropunctata ecology. For example, the scale of dispersal from source habitat and seasonal patterns in activity were generally similar to those documented in prior studies. The results also confirmed the influence of adjacent plant community composition on G. atropunctata activity in vineyards, and the role of riparian habitat and select plant taxa as vector sources. Nonetheless, further consideration of the epidemiological significance of certain features of the pathosystem may be warranted, especially those related to seasonality in X. fastidiosa infection in vectors. A marked increase in infected G. atropunctata late in the season likely reflects pathogen acquisition from infected grapevines, which may have implications for disease management strategies.
Periconceptional omega-6 and omega-3 polyunsaturated fatty acid intake plane and postpartum depression: a nationwide birth cohort—the Japan Environment and Children’s Study
Authors: Matsumura Kenta , Hamazaki Kei , Tsuchida Akiko ,   the Japan Environment and Children’s Study (JECS) Group, Inadera Hidekuni
Published: October 2024

Intake of omega-3 polyunsaturated fatty acids (PUFAs) has favorable effects on the prevention of postpartum depression, but fish, the principal source of omega-3 PUFAs, are becoming a depleted resource. We therefore examined whether lower periconceptional intake of omega-6 PUFAs, whose metabolic pathways are antagonistic to those of omega-3 PUFAs, is associated with lower prevalence of postpartum depression while simultaneously considering omega-3 PUFA intake. The participants were 92,595 mothers involved in the ongoing Japan Environment and Children's Study. Periconceptional intakes of omega-6 and -3 PUFA were measured using a food frequency questionnaire. Postpartum depression was assessed using the Edinburgh Postnatal Depression Scale. Generalized additive mixed model analysis was used to draw contour plots of postpartum depression on a plane with omega-6 and omega-3 PUFA intakes on the x- and y-axes, respectively. The adjusted prevalence ranged from 11.0% to 26.3% within the respective 1st to 99th percentile intake ranges and monotonously decreased with decreasing omega-6 PUFA intake. In contrast, the prevalence decreased with increasing omega-3 PUFA intake, but the trend almost disappeared above 2 g/day. Our results highlight the potential importance of focusing on omega-6 PUFAs as well as omega-3 PUFAs prior to conception to reduce postpartum depression.
Recognition Subtests for Form B of the Repeatable Battery for the Assessment of Neuropsychological Status: Preliminary Validation
Authors: Duff Kevin , Turok Nora Grace , Piryatinsky Irene
Published: October 2024

Objective

Develop and preliminarily validate recognition subtests for Form B of the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS).

Method

49 older adults with no cognitive impairment were compared to 53 individuals with a primary neurocognitive disorder (e.g., dementia, mild cognitive impairment, and traumatic brain injury) and 22 individuals with a primary psychiatric disorder (e.g., depression and anxiety) on three recognition subtests (list, story, and figure) for Form B of the RBANS in this observational study.

Results

The individuals with a primary neurocognitive disorder performed significantly poorer on most of the recognition scores compared to those with no cognitive impairment and those with a primary psychiatric disorder, with these latter two groups being largely comparable. In the entire sample, for the recognition subtests, education only correlated with figure recognition scores, and neither age nor gender influenced recognition scores. The RBANS indexes correlated with most of the recognition scores in the expected directions.

Conclusions

The group differences in performance on these recognition subtests preliminarily validate these scores on Form B, which were not previously available. Furthermore, these scores tended to not be influenced by age, education, or gender, although they were related to overall cognitive functioning. Additional validation is needed in larger, better clinically-defined, and more diverse samples. Nonetheless, these findings support the inclusion of the newly-developed Form B recognition subtests in future clinical practice and research settings to enhance the accuracy of diagnoses and treatment recommendations.
Paper and Textile Encounters in the Pacific
Authors: Fowler Caroline
Published: October 2024

This essay focuses on an eighteenth-century book, A Catalogue of the Different Specimens of Cloth Collected in the Three Voyages of Captain Cook to the Southern Hemisphere, which opens up alternative histories of paper in the early modern world. The work consists of a letterpress pamphlet describing the production of bark cloth (tapa), bound with samples of tapa, which were acquired from one of Captain Cook’s naval officers. In placing paper and bark cloth into relationship with one another, the work offers another vantage point from which to theorise not only the material history of paper but also the ways in which paper was dependent on an ability to ‘invisibly occupy’. Paper’s material invisibility is both part of its strength while also demonstrating the intellectual blind spots that can occur in attending solely to material histories of paper worlds.
Statistical analysis of multiple regions-of-interest in multiplexed spatial proteomics data
Authors: Samorodnitsky Sarah , Wu Michael C
Published: October 2024

Multiplexed spatial proteomics reveals the spatial organization of cells in tumors, which is associated with important clinical outcomes such as survival and treatment response. This spatial organization is often summarized using spatial summary statistics, including Ripley’s K and Besag’s L. However, if multiple regions of the same tumor are imaged, it is unclear how to synthesize the relationship with a single patient-level endpoint. We evaluate extant approaches for accommodating multiple images within the context of associating summary statistics with outcomes. First, we consider averaging-based approaches wherein multiple summaries for a single sample are combined in a weighted mean. We then propose a novel class of ensemble testing approaches in which we simulate random weights used to aggregate summaries, test for an association with outcomes, and combine the $P$-values. We systematically evaluate the performance of these approaches via simulation and application to data from non-small cell lung cancer, colorectal cancer, and triple negative breast cancer. We find that the optimal strategy varies, but a simple weighted average of the summary statistics based on the number of cells in each image often offers the highest power and controls type I error effectively. When the size of the imaged regions varies, incorporating this variation into the weighted aggregation may yield additional power in cases where the varying size is informative. Ensemble testing (but not resampling) offered high power and type I error control across conditions in our simulated data sets.
A two-task predictor for discovering phase separation proteins and their undergoing mechanism
Authors: Zhou Yetong , Zhou Shengming , Bi Yue , Zou Quan , Jia Cangzhi
Published: October 2024

Liquid–liquid phase separation (LLPS) is one of the mechanisms mediating the compartmentalization of macromolecules (proteins and nucleic acids) in cells, forming biomolecular condensates or membraneless organelles. Consequently, the systematic identification of potential LLPS proteins is crucial for understanding the phase separation process and its biological mechanisms. A two-task predictor, Opt_PredLLPS, was developed to discover potential phase separation proteins and further evaluate their mechanism. The first task model of Opt_PredLLPS combines a convolutional neural network (CNN) and bidirectional long short-term memory (BiLSTM) through a fully connected layer, where the CNN utilizes evolutionary information features as input, and BiLSTM utilizes multimodal features as input. If a protein is predicted to be an LLPS protein, it is input into the second task model to predict whether this protein needs to interact with its partners to undergo LLPS. The second task model employs the XGBoost classification algorithm and 37 physicochemical properties following a three-step feature selection. The effectiveness of the model was validated on multiple benchmark datasets, and in silico saturation mutagenesis was used to identify regions that play a key role in phase separation. These findings may assist future research on the LLPS mechanism and the discovery of potential phase separation proteins.
Neurodegenerative fluid biomarkers are enriched in human cervical lymph nodes
Authors: Al-Diwani Adam , Provine Nicholas M , Murchison Andrew , Laban Rhiannon , Swann Owen J , Koychev Ivan , Sheerin Fintan , Da Mesquita Sandro , Heslegrave Amanda , Zetterberg Henrik , Klenerman Paul , Irani Sarosh R
Published: October 2024

In animal models, brain neurodegeneration biomarkers drain into cervical lymph nodes (CLNs), and this drainage function is reduced with ageing. If this occurred in humans, CLNs may provide a readily accessible measure of this aspect of protein clearance. We tested this hypothesis in people using ultrasound-guided fine needle aspiration.

We measured amyloid-beta 40 and 42, phosphorylated tau 181 (pTau181), glial fibrillary acidic protein and neurofilament light using single molecule array in CLN aspirates and plasma from: (i) a discovery cohort of 25 autoimmune patients; and (ii) plasma, CLNs and capillary blood in four healthy volunteers, an optimization cohort.

Ultrasound-guided fine needle aspiration was well-tolerated by all participants. In both cohorts, all biomarkers were detected in all plasma and CLN samples, other than neurofilament light (8/17 of discovery cohort). CLN biomarker concentrations were significantly greater than plasma concentrations for all except neurofilament light, most markedly for pTau181 (266-fold; P < 0.02), whose CLN concentrations decreased with age (Spearman r = −0.66, P = 0.001).

This study presents the first evidence that neurodegenerative biomarkers are detectable in human CLNs. Raised CLN:plasma biomarker ratios suggest their concentration in CLNs may offer a distinct compartment for minimally-invasive measurement of brain clearance and lymphatic drainage, with potential applicability to study of ageing and future clinical trials.
Modularity based community detection in hypergraphs
Authors: Kamiński Bogumił , Misiorek Paweł , Prałat Paweł , Théberge François
Published: October 2024

In this paper, we propose a scalable community detection algorithm using hypergraph modularity function, h–Louvain. It is an adaptation of the classical Louvain algorithm in the context of hypergraphs. We observe that a direct application of the Louvain algorithm to optimize the hypergraph modularity function often fails to find meaningful communities. We propose a solution to this issue by adjusting the initial stage of the algorithm via carefully and dynamically tuned linear combination of the graph modularity function of the corresponding two-section graph and the desired hypergraph modularity function. The process is guided by Bayesian optimization of the hyper-parameters of the proposed procedure. Various experiments on synthetic as well as real-world networks are performed showing that this process yields improved results in various regimes.
Dietary salt, vascular dysfunction, and cognitive impairment
Authors: Faraco Giuseppe
Published: October 2024

Excessive salt consumption is a major health problem worldwide leading to serious cardiovascular events including hypertension, heart disease, and stroke. Additionally, high-salt diet has been increasingly associated with cognitive impairment in animal models and late-life dementia in humans. High-salt consumption is harmful for the cerebral vasculature, disrupts blood supply to the brain, and could contribute to Alzheimer’s disease pathology. Although animal models have advanced our understanding of the cellular and molecular mechanisms, additional studies are needed to further elucidate the effects of salt on brain function. Furthermore, the association between excessive salt intake and cognitive impairment will have to be more thoroughly investigated in humans. Since the harmful effects of salt on the brain are independent by its effect on blood pressure, in this review, I will specifically discuss the evidence, available in experimental models and humans, on the effects of salt on vascular and cognitive function in the absence of changes in blood pressure. Given the strong effects of salt on the function of immune cells, I will also discuss the evidence linking salt consumption to gut immunity dysregulation with particular attention to the ability of salt to disrupt T helper 17 (Th17) cell homeostasis. Lastly, I will briefly discuss the data implicating IL-17A, the major cytokine produced by Th17 cells, in vascular dysfunction and cognitive impairment.
Altitude and ground brightness explain interpopulation variation in dorsal coloration in a lizard
Authors: Cuervo José J , Durán-García María C , Belliure Josabel
Published: October 2024

Non-signaling functions of coloration include thermoregulation (thermal melanism hypothesis), protection against ultraviolet radiation (photoprotection hypothesis), and concealment from predators (crypsis hypothesis). We investigated whether dorsal coloration in 19 populations of spiny-footed lizards, Acanthodactylus erythrurus, across the Iberian Peninsula varies according to these functions. We captured adult males and females in each population and calculated standardized dorsum brightness estimates from photographs. We also calculated standardized ground luminosity estimates and gathered information on latitude, altitude, mean annual temperature, and mean annual solar radiation for each location. Males showed a higher percentage of black coloration and a more contrasted dorsum than females, suggesting different selection pressures on dorsal coloration in both sexes. Furthermore, males showed a darker dorsum and a higher percentage of black coloration at higher altitudes and when the ground was darker. In contrast, females exhibited a darker dorsum only when the ground was darker and a higher percentage of black coloration only at higher altitudes. We also observed that the variation of dorsum luminosity within males and the variation of dorsum luminosity among females within populations were both positively related to the variation of ground luminosity among different points within locations. Latitude, temperature, and solar radiation were not significantly related to dorsal coloration in either sex. Our results support the photoprotection and crypsis hypotheses in males and, to some extent, in females, whereas the thermal melanism hypothesis is weakly supported in both sexes. These findings suggest that there is local adaptation in the dorsal coloration of the spiny-footed lizard.
Principal component analysis revisited: fast multitrait genetic evaluations with smooth convergence
Authors: Ahlinder Jon , Hall David , Suontama Mari , Sillanpää Mikko J
Published: October 2024

A cornerstone in breeding and population genetics is the genetic evaluation procedure, needed to make important decisions on population management. Multivariate mixed model analysis, in which many traits are considered jointly, utilizes genetic and environmental correlations between traits to improve the accuracy. However, the number of parameters in the multitrait model grows exponentially with the number of traits which reduces its scalability. Here, we suggest using principal component analysis to reduce the dimensions of the response variables, and then using the computed principal components as separate responses in the genetic evaluation analysis. As principal components are orthogonal to each other so that phenotypic covariance is abscent between principal components, a full multivariate analysis can be approximated by separate univariate analyses instead which should speed up computations considerably. We compared the approach to both traditional multivariate analysis and factor analytic approach in terms of computational requirement and rank lists according to predicted genetic merit on two forest tree datasets with 22 and 27 measured traits, respectively. Obtained rank lists of the top 50 individuals were in good agreement. Interestingly, the required computational time of the approach only took a few seconds without convergence issues, unlike the traditional approach which required considerably more time to run (7 and 10 h, respectively). The factor analytic approach took approximately 5–10 min. Our approach can easily handle missing data and can be used with all available linear mixed effect model softwares as it does not require any specific implementation. The approach can help to mitigate difficulties with multitrait genetic analysis in both breeding and wild populations.
Comparative Genomics of the World's Smallest Mammals Reveals Links to Echolocation, Metabolism, and Body Size Plasticity
Authors: Cossette Marie-Laurence , Stewart Donald T , Shafer Aaron B A
Published: October 2024

Originating 30 million years ago, shrews (Soricidae) have diversified into around 400 species worldwide. Shrews display a wide array of adaptations, with some species having developed distinctive traits such as echolocation, underwater diving, and venomous saliva. Accordingly, these tiny insectivores are ideal to study the genomic mechanisms of evolution and adaptation. We conducted a comparative genomic analysis of four shrew species and 16 other mammals to identify genomic variations unique to shrews. Using two existing shrew genomes and two de novo assemblies for the maritime (Sorex maritimensis) and smoky (Sorex fumeus) shrews, we identified mutations in conserved regions of the genomes, also known as accelerated regions, gene families that underwent significant expansion, and positively selected genes. Our analyses unveiled shrew-specific genomic variants in genes associated with the nervous, metabolic, and auditory systems, which can be linked to unique traits in shrews. Notably, genes suggested to be under convergent evolution in echolocating mammals exhibited accelerated regions in shrews, and pathways linked to putative body size plasticity were detected. These findings provide insight into the evolutionary mechanisms shaping shrew species, shedding light on their adaptation and divergence over time.