bluuebunny/crossref_metadata_2025 huggingface dataset:
Roles of N-linked glycosylation and glycan-binding proteins in placentation: trophoblast infiltration, immunomodulation, angiogenesis, and pathophysiology
Authors: Huang Zhengyuan , Lai Pei F. , Cocker Alexander T. H. , Haslam Stuart M. , Dell Anne , Brady Hugh J. M. , Johnson Mark R.
Published: March 2023

Protein N-linked glycosylation is a structurally diverse post-translational modification that stores biological information in a larger order of magnitude than other post-translational modifications such as phosphorylation, ubiquitination and acetylation. This gives N-glycosylated proteins a diverse range of properties and allows glyco-codes (glycan-related information) to be deciphered by glycan-binding proteins (GBPs). The intervillous space of the placenta is richly populated with membrane-bound and secreted glycoproteins. Evidence exists to suggest that altering the structural nature of their N-glycans can impact several trophoblast functions, which include those related to interactions with decidual cells. This review summarizes trophoblast-related activities influenced by N-glycan–GBP recognition, exploring how different subtypes of trophoblasts actively adapt to characteristics of the decidualized endometrium through cell-specific expression of N-glycosylated proteins, and how these cells receive decidua-derived signals via N-glycan–GBP interactions. We highlight work on how changes in N-glycosylation relates to the success of trophoblast infiltration, interactions of immunomodulators, and uterine angiogenesis. We also discuss studies that suggest aberrant N-glycosylation of trophoblasts may contribute to the pathogenesis of pregnancy complications (e.g. pre-eclampsia, early spontaneous miscarriages and hydatidiform mole). We propose that a more in-depth understanding of how N-glycosylation shapes trophoblast phenotype during early pregnancy has the potential to improve our approach to predicting, diagnosing and alleviating poor maternal/fetal outcomes associated with placental dysfunction.
Loop and distillation: Attention weights fusion transformer for fine‐grained representation
Authors: Fayou Sun , Ngo Hea Choon , Meng Zuqiang , Sek Yong Wee
Published: March 2023

Learning subtle discriminative feature representation plays a significant role in Fine‐Grained Visual Categorisation (FGVC). The vision transformer (ViT) achieves promising performance in the traditional image classification filed due to its multi‐head self‐attention mechanism. Unfortunately, ViT cannot effectively capture critical feature regions for FGVC due to only focusing on classification token and adopting the strategy of one‐time image input. Besides, the advantage of attention weights fusion is not applied to ViT. To promote the performance of capturing vital regions for FGVC, the authors propose a novel model named RDTrans, which proposes discriminative region with top priority in a recurrent learning way. Specifically, proposed vital regions at each scale will be cropped and amplified as the next input parameters to finally locate the most discriminative region. Furthermore, a distillation learning method is employed to provide better supervision for elevating the generalisation ability. Concurrently, RDTrans can be easily trained end‐to‐end in a weakly‐supervised learning way. Extensive experiments demonstrate that RDTrans yields state‐of‐the‐art performance on four widely used fine‐grained benchmarks, including CUB‐200‐2011, Stanford Cars, Stanford Dogs, and iNat2017.
An unusually powerful and long-lasting water maser flare phenomenon in IRAS 16293-2422
Authors: Volvach A. E. , Volvach L. N. , Larionov M. G.
Published: March 2023

Aims. Our goal is to obtain new detailed observational data on the water maser flare phenomenon, unprecedented in power and duration, that occurred in IRAS 16293-2422 and determine the physical characteristics of the individual flares.

Methods. We used the ground-based 22 m radio telescope to conduct long-term observations of the water maser features near – 1.5 km s−1 in IRAS 16293-2422. The movement of the radio telescope, collection of observational data, and processing were performed automatically. We used spectral-temporal data analysis to identify water maser flares in a complex flare phenomenon and determine their physical parameters.

Results. The detected maser emission came from the largest structure of maser spots, the high density of which resulted in their partial overlap in time. There were a total of ten individual powerful flares in the phenomenon. The existence of such a complex configuration of emitting maser spots with very similar radial velocities has been confirmed for the first time. We were able to determine that masers of the powerful flares were in an unsaturated state due to a cascade pumping of radiation from several masers located in the observer’s line of sight. We obtained new important physical parameters of maser flares: the detailed shape of flares, the state of the water maser during flares, the H2O kinetic temperature, the density of the medium, the degree of ionization, and the velocities of the maser spots responsible for the flares.
A fictitious-play finite-difference method for linearly solvable mean field games
Authors: Inoue Daisuke , Ito Yuji , Kashiwabara Takahito , Saito Norikazu , Yoshida Hiroaki
Published: March 2023

An iterative finite difference scheme for mean field games (MFGs) is proposed. The target MFGs are derived from control problems for multidimensional systems with advection terms. For such MFGs, linearization using the Cole-Hopf transformation and iterative computation using fictitious play are introduced. This leads to an implementation-friendly algorithm that iteratively solves explicit schemes. The convergence properties of the proposed scheme are mathematically proved by tracking the error of the variable through iterations. Numerical calculations show that the proposed method works stably for both one- and two-dimensional control problems.
Real-time monitoring of the plasma density distribution in low-pressure plasmas using a flat-cutoff array sensor
Authors: Yeom H. J. , Yoon Min Young , Chae Gwang-Seok , Kim Jung Hyung , You ShinJae , Lee Hyo-Chang
Published: March 2023

In the industrial semiconductor plasma processing, plasma density and its spatial distribution are critical for the understanding of discharge physics and the enhancement of the processing yield via monitoring of the status of plasma processing. Thus, real-time monitoring of plasma density and uniformity in the wafer region during wafer processing have been receiving significant attention. In this study, we developed an electrode-embedded flat-cutoff array sensor for the real-time measurement of electron density uniformity during wafer processing. We measured the spatial distribution of electron density on the wafer surface, compared it with the results measured in the bulk plasma region, and found different plasma distributions between the two where this difference can be attributed to local electron kinetics. We also performed plasma etching of amorphous carbon materials, which showed a clear correlation with the electron density distribution measured by the flat-cutoff array sensor. This indicates that the electron density distribution on the wafer surface is crucial for the process result. Thus, the array sensor developed in this study can be applied not only to measure plasma uniformity but also to predict the wafer process beforehand, making it highly significant for industrial plasma processing methods, such as virtual metrology.
Sequence-dependent model of allosteric communication
Authors: Guarnera Enrico , Berezovsky Igor N.
Published: March 2023

The omnipresence and diversity of allosteric regulation in proteins and protein associations complemented by the potential for the design of allosterically acting biologics and drugs call for the development of a new generation of computational models for the analysis of allostery and rational engineering/design of desired signaling and effector molecules determining it. One of the most important challenges is the consideration of the role of amino acid sequence in forming the protein’s allosteric communication, including the mode and strength of the allosteric signal that is communicated to the regulated functional site. Here, we present the network-based model with a sequence dependence added in consideration of allosteric communication by combining the structure-based statistical mechanical model of allostery with the Miyazawa-Jernigan residue–residue potential. Applying the model in the analysis of five classical allosteric proteins, we found that it is necessary to consider the following two major determinants: (i) the free energy exerted by the allosteric site on the regulated one and (ii) the background (average) change in dynamics of the overall structure. We show that working together these two components determine the allosteric modulation, calling one to study their dependence on structures, oligomerization states, and sequence divergence in different proteins.
Wildfire aerial thermal image segmentation using unsupervised methods: a multilayer level set approach
Authors: Garcia Tiago , Ribeiro Ricardo , Bernardino Alexandre
Published: March 2023

Background and aims Infrared thermal images of a propagating wildfire taken by manned or unmanned aerial vehicles can help firefighting authorities with combat planning. Segmenting these images into regions of different fire temperatures is a necessary step to measure the fire perimeter and determine the location of the fire front. Methods This work proposes a multilayer segmentation method based on level sets, which have the property of handling topology, making them suitable to segment images that contain scattered fire areas. The experimental results were compared using hand-drawn labels over a set of images provided by the Portuguese Air Force as ground truth. These labels were carefully drawn by the authors to ensure that they complied with the requirements indicated by the Portuguese National Authority for Emergency and Civil Protection. The proposed method was optimised to ensure contour smoothness and reliability, as well as reduce computation time. Key results The proposed method can surpass other common unsupervised methods in terms of intersection over union, although it has not yet been able to perform real-time segmentation. Conclusions Although falling out of use in relation to supervised and deep learning methods, unsupervised segmentation can still be very useful when annotated datasets are unavailable.
About hysteresis in Shaker: Response to note by Villalba-Galea
Authors: Chanda Baron , Cowgill John
Published: March 2023

In this issue, Villalba-Galea (2023. J. Gen. Physiol.https://doi.org/10.1085/jgp.202313371) expresses interest in our recently published work (Cowgill and Chanda. 2023. J. Gen. Physiol.https://doi.org/10.1085/jgp.202112883). Our response points out the deficiencies in the alternative explanation proposed by Villalba-Galea to account for our findings on hysteresis (or lack thereof) in steady state charge–voltage curves of Shaker potassium channel.
Joint optimal measurement for locating two incoherent optical point sources near the Rayleigh distance
Authors: Shi Yingying , Lu Xiao-Ming
Published: March 2023

Simultaneously optimizing the estimation of the centroid and separation of two incoherent optical point sources is constrained by a tradeoff relation determined by an incompatibility coefficient. At the Rayleigh distance, the incompatibility coefficient vanishes and thus the tradeoff relation no longer restricts the simultaneous optimization of measurement for a joint estimation. We construct such a joint optimal measurement by an elaborated analysis on the operator algebra of the symmetric logarithmic derivative. Our work not only confirms the existence of a joint optimal measurement for this specific imaging model, but also gives a promising method to characterize the condition on measurement compatibility for general multiparameter estimation problems.
Three-dimensional potential energy surface for fission of 236U within covariant density functional theory*
Authors: Zhou Ming-Hui , Li Ze-Yu , Chen Sheng-Yuan , Chen Yong-Jing , Li Zhi-Pan
Published: March 2023

We calculate the three-dimensional potential energy surface (PES) for the fission of the compound nucleus

U using covariant density functional theory with constraints on the axial quadrupole and octupole deformations

as well as the nucleon number in the neck

. By considering the additional degree of freedom

, the coexistence of the elongated and compact fission modes is predicted for

. Remarkably, the PES becomes shallow across a large range of quadrupole and octupole deformations for small

, and consequently, the scission line in the

plane extends to a shallow band, leading to fluctuations of several to ten MeV in the estimated total kinetic energies and of several to approximately ten nucleons in the fragment masses.
Localization Method for the Pointing Observation with the Collimated Telescopes of Insight-HXMT
Authors: Luo Qi , Liao Jin-Yuan , Nang Yi , Li Cheng-Kui , Wang Chen , Sai Na , Guan Ju , Chen Yu-Peng , Guo Cheng-Cheng , Liu Yuan , Zhang Shu , Zhang Shuang-Nan
Published: March 2023

An accurate target source position is sometimes useful for the pointing observation with the collimated telescopes of the Hard X-ray Modulation Telescope (Insight-HXMT), which is determined by the reliability of the instrumental response. Insight-HXMT has the unique design that all three main payloads (LE, ME and HE) consist of detector groups with three fields of views (FOVs) whose orientations differ by 60°. As the point-spread functions are different at different positions in the FOV coordinates, the count rate ratios between the detector groups depend on the position of an X-ray source in the FOVs. Based on the multi-FOV design, we develop a localization method for an X-ray source in the pointing observation of Insight-HXMT. The accuracy of the method is investigated with the pointing observations of the Crab with different exposures. We find that the statistical error decreases with the exposure, and the systematic error is dominant for the exposure >128 s. With the exposure of 1024 s, the total error is 0.°015 for the Crab. This method can effectively distinguish the Rapid Burster H 1730–333 and Slow Burster GX 354–0, which are only 0.°5 apart and can both contribute to bursts in the light curve obtained by Insight-HXMT. We also apply the pointing observation localization method to locate the X-ray counterpart of FRB 200428 with high precision. The located position is consistent with SGR J1935+2154 within 1σ uncertainty of 10′, which provides important evidence that fast radio bursts can originate from magnetars.
An RFI Mitigation Pipeline for CRAFTS Multi-beam Data Based on Signal Cross-Correlation Function and SumThreshold Algorithm
Authors: Chen Zong-Hao , You Shan-Ping , Yu Xu-Hong , Wang Pei , Li Di , Xie Xiao-Yao , Liu Zhi-Jie , Wang Chun-Qing , Zeng Peng , Zhang Bin
Published: March 2023

The increasing radio frequency interference (RFI) is a well-recognized problem in radio astronomy research. Pulsars and Fast Radio Bursts (FRBs) are high-priority science targets of the ongoing Commercial Radio Astronomy FAST Survey (CRAFTS). To improve the quality of RFI removal in searches of pulsars and FRBs based on CRAFTS multi-beam data, we here propose an intuitive but powerful RFI mitigation pipeline (CCF-ST). The “CCF-ST” is a spatial filter constructed by signal cross-correlation function (CCF) and Sum-Threshold (ST) algorithm. The RFI marking result is saved in a “mask” file, a binary format for RFI masks in PRESTO. Three known pulsars, PSR B0525-21, PSR B0621-04, and PSR J0943 + 2252 from CRAFTS L-band 19 beams data are used for evaluation of the performance of CCF-ST in comparison with other methods, such as PRESTO’s “rfifind”, ArPLS-ST and ArPLS-SF. The result shows that CCF-ST can reduce effective data loss rate and improves the detected signal-to-noise ratio of the pulsations by ∼26% and ∼18% respectively compared with PRESTO’s “rfifind” and ArPLS-ST. The CCF-ST also has the advantage of low computational cost, e.g., reducing the time consumption by ∼40% and memory consumption by ∼90% compared with ArPLS-SF. We expect that the new RFI mitigation and analysis toolkit (CCF-ST) demonstrated in this paper can be applied to CRAFTS and other multi-beam telescope observations to improve the data quality and efficiency of pulsar and FRB searches.
An in-depth Exploration of LAMOST Unknown Spectra Based on Density Clustering
Authors: Yang Hai-Feng , Yin Xiao-Na , Cai Jiang-Hui , Yang Yu-Qing , Luo A-Li , Bai Zhong-Rui , Zhou Li-Chan , Zhao Xu-Jun , Xun Ya-Ling
Published: March 2023

Large sky Area Multi-Object fiber Spectroscopic Telescope (LAMOST) has completed the observation of nearly 20 million celestial objects, including a class of spectra labeled “Unknown.” Besides low signal-to-noise ratio, these spectra often show some anomalous features that do not work well with current templates. In this paper, a total of 637,889 “Unknown” spectra from LAMOST DR5 are selected, and an unsupervised-based analytical framework of “Unknown” spectra named SA-Frame (Spectra Analysis-Frame) is provided to explore their origins from different perspectives. The SA-Frame is composed of three parts: NAPC-Spec clustering, characterization and origin analysis. First, NAPC-Spec (Nonparametric density clustering algorithm for spectra) characterizes different features in the “unknown” spectrum by adjusting the influence space and divergence distance to minimize the effects of noise and high dimensionality, resulting in 13 types. Second, characteristic extraction and representation of clustering results are carried out based on spectral lines and continuum, where these 13 types are characterized as regular spectra with low S/Ns, splicing problems, suspected galactic emission signals, contamination from city light and un-gregarious type respectively. Third, a preliminary analysis of their origins is made from the characteristics of the observational targets, contamination from the sky, and the working status of the instruments. These results would be valuable for improving the overall data quality of large-scale spectral surveys.
Delaying feedback during pre-device training facilitates the retention of novel myoelectric skills: a laboratory and home-based study
Authors: Stuttaford Simon A , Dupan Sigrid S G , Nazarpour Kianoush , Dyson Matthew
Published: March 2023

Objective. The objective of this study was to assess the impact of delayed feedback training on the retention of novel myoelectric skills, and to demonstrate the use of this training approach in the home environment. Approach. We trained limb-intact participants to use a motor learning-based upper-limb prosthesis control scheme called abstract decoding. A delayed feedback paradigm intended to prevent within-trial adaptation and to facilitate motor learning was used. We conducted two multi-day experiments. Experiment 1 was a laboratory-based study consisting of two groups trained over a 4 day period with concurrent or delayed feedback. An additional follow-up session took place after 18 days to assess the retention of motor skills. Experiment 2 was a home-based pilot study that took place over five consecutive days to investigate delayed feedback performance when using bespoke training structures. Main Results. Approximately 35 000 trials were collected across both experiments. Experiment 1 found that the retention of motor skills for the delayed feedback group was significantly better than that of their concurrent feedback counterparts. In addition, the delayed feedback group improved their retention of motor skills across days, whereas the concurrent feedback group did not. Experiment 2 demonstrated that by using a bespoke training protocol in an environment that is more conducive to learning, it is possible for participants to become highly accurate in the absence of feedback. Significance. These results show that with delayed feedback training, it is possible to retain novel myoelectric skills. Using abstract decoding participants can activate four distinct muscle patterns without using complex algorithms. The accuracy achieved in the pilot study supports the feasibility of motor learning-based upper-limb prosthesis control after home-based myoelectric training.
Pretty good state transfer in discrete-time quantum walks
Authors: Chan Ada , Zhan Hanmeng
Published: March 2023

We establish the theory for pretty good state transfer in discrete-time quantum walks. For a class of walks, we show that pretty good state transfer is characterized by the spectrum of certain Hermitian adjacency matrix of the graph; more specifically, the vertices involved in pretty good state transfer must be strongly cospectral relative to this matrix, and the arccosines of its eigenvalues must satisfy some number theoretic conditions. Using normalized adjacency matrices, cyclic covers, and the theory on linear relations between geodetic angles, we construct several infinite families of walks that exhibits this phenomenon.
Hazard-selfsimilarity of diffusions’ first passage times
Authors: Eliazar Iddo
Published: March 2023

A recent study introduced a novel approach to the exploration of diffusions’ first-passage times (FPTs): selfsimilarity. Specifically, consider a general diffusion process that runs over the non-negative half-line; initiating the diffusion at fixed positive levels, further consider the diffusion’s FPTs to the origin. Selfsimilarity means that the FPTs are spanned by an intrinsic scaling of their initial levels. The recent study addressed two types of selfsimilarity: stochastic, scaling the FPTs in ‘real space’; and Laplace, scaling the FPTs in ‘Laplace space’. The Laplace selfsimilarity manifests an underlying sum-like structure. Shifting from the sum-like structure to a max-like structure—a-la the shift from the Central Limit Theorem to Extreme Value Theory—this study addresses a third type of selfsimilarity: hazard, scaling the FPTs in ‘hazard space’. A comprehensive analysis of hazard-selfsimilarity is established here, including: the universal distribution of the FPTs; the dramatically different statistical behaviors that the universal distribution exhibits, and the statistical phase transition between the different behaviors; the characterization of the generative diffusion dynamics, and their universal Langevin representation; and the universal Poissonian statistics that emerge when the initial levels are scattered according to the statistical steady-state of the generative diffusion dynamics. The analysis unveils the following linkages: of the universal distribution to the Gumbel, Gompertz, and Frechet laws; of the universal Langevin representation to diffusion in quadratic and logarithmic potentials; and of the universal Poissonian statistics to non-normalizable densities, to the maxima of the exponential law, and to the harmonic Poisson process.
Construction of a three-dimensional urothelium on-chip with barrier function based on urinary flow microenvironment
Authors: Hou Changhao , Gu Yubo , Yuan Wei , Zhang Wukai , Xiu Xianjie , Lin Jiahao , Gao Yue , Liu Peichuan , Chen Xiang , Song Lujie
Published: March 2023

The urothelium covers the inner surface of the urinary tract, forming a urinary tract barrier. Impairment of the integrity and dysfunction of the urinary tract barrier is associated with the occurrence and development of various diseases. The development of a three-dimensional model of the urothelium is critical for pathophysiological studies of this site, especially under physiological fluid shear stress stimulated by the urinary flow. In this study, a urothelium on-chip is fabricated with micromilling and replica molding techniques, which contains a microfluidic chip for cell culture and a pump-based fluid perfusion system. The mechanical properties of the human urinary tract are simulated by adjusting the concentration and degree of amino substitution of the gelatin methacrylate hydrogel. The matrix stiffness is similar to the natural urinary tract. Pulsatile flow and periodic flow are provided to simulate the fluid environment of the upper and lower urinary tracts, respectively. The results show that the physiological fluid shear stress could promote the differentiation and maturation of urothelial cells. The model could simulate the three-dimensional structure of urothelium and urinary flow microenvironment, showing morphological structure close to the natural urothelium, specific differentiation and maturation markers (uroplakin 2, cytokeratin 20), and urothelial barrier function.
Supervised learning of random quantum circuits via scalable neural networks
Authors: Cantori Simone , Vitali David , Pilati Sebastiano
Published: March 2023

Predicting the output of quantum circuits is a hard computational task that plays a pivotal role in the development of universal quantum computers. Here we investigate the supervised learning of output expectation values of random quantum circuits. Deep convolutional neural networks (CNNs) are trained to predict single-qubit and two-qubit expectation values using databases of classically simulated circuits. These circuits are built using either a universal gate set or a continuous set of rotations plus an entangling gate, and they are represented via properly designed encodings of these gates. The prediction accuracy for previously unseen circuits is analyzed, also making comparisons with small-scale quantum computers available from the free IBM Quantum program. The CNNs often outperform these quantum devices, depending on the circuit depth, on the network depth, and on the training set size. Notably, our CNNs are designed to be scalable. This allows us exploiting transfer learning and performing extrapolations to circuits larger than those included in the training set. These CNNs also demonstrate remarkable resilience against noise, namely, they remain accurate even when trained on (simulated) expectation values averaged over very few measurements.
Quantum mixed state compiling
Authors: Ezzell Nic , Ball Elliott M , Siddiqui Aliza U , Wilde Mark M , Sornborger Andrew T , Coles Patrick J , Holmes Zoë
Published: March 2023

The task of learning a quantum circuit to prepare a given mixed state is a fundamental quantum subroutine. We present a variational quantum algorithm (VQA) to learn mixed states which is suitable for near-term hardware. Our algorithm represents a generalization of previous VQAs that aimed at learning preparation circuits for pure states. We consider two different ansätze for compiling the target state; the first is based on learning a purification of the state and the second on representing it as a convex combination of pure states. In both cases, the resources required to store and manipulate the compiled state grow with the rank of the approximation. Thus, by learning a lower rank approximation of the target state, our algorithm provides a means of compressing a state for more efficient processing. As a byproduct of our algorithm, one effectively learns the principal components of the target state, and hence our algorithm further provides a new method for principal component analysis. We investigate the efficacy of our algorithm through extensive numerical implementations, showing that typical random states and thermal states of many body systems may be learnt this way. Additionally, we demonstrate on quantum hardware how our algorithm can be used to study hardware noise-induced states.
Selection of optimal hyperparameter for detecting multiple contacts from large-area tactile sensors based on electrical impedance tomography
Authors: Chen Ying , Jin Leizhi , Wang Peng , Liu Haibin
Published: March 2023

Large-area tactile sensors based on the technique of electrical impedance tomography (EIT) has drawn considerable interest in human-robot interactions. However, due to the ill-posed condition, it is challenging to differentiate between the real contacts and the artifacts from the reconstructed image. To address this issue, a new method to select an optimal hyperparameter that tunes the amount of regularization is developed in the context of tactile sensing. The optimal hyperparameter is determined to be the minimum value to obtain a stabilized number of sub-regions in the reconstructed image. The proposed method not only guarantees a correct detection on the number of multiple contacts at the minimum amount of regularization, but also provides a proper range of hyperparameters. The optimal hyperparameter is found in a chair-shape relation with the boundary signal-to-noise ratio (SNR), by varying the noise level of the hardware in simulation. The optimal hyperparameter decreases significantly when the boundary SNR increases between 5 ∼ 10 dB and 25 ∼ 35 dB, and keeps almost unchanged when SNR is between 10 ∼ 25 dB. The chair-shape relation also holds for contact conditions with varied intensities and sizes. Experimental validations on the proposed method are conducted on a compliant piezoresistive tactile sensor made of exfoliated graphite polymer composites. By varying the number of contacts in experiments, the relation between the optimal hyperparameter and the boundary SNR is consistent with the chair-shape curve. The investigation made in this work helps improve the performance of identifying multiple contacts from tactile sensors based on electrical impedance tomography.
On partial uniqueness of complete non-compact Ricci flat metrics
Authors: Wang Yuanqi
Published: March 2023

Using techniques for Caccioppoli inequality, on a fairly general class of complete non-compact Kähler manifolds with sub-quadratic volume growth, we show uniqueness of boundedC1,1C^{1,1}solution to Monge-Ampere equation. This does not a priori require any decay of the solution.
Life-history characteristics and historical factors are important to explain regional variation in reproductive traits and genetic diversity in perennial mosses
Authors: Bisang Irene , Ehrlén Johan , Hedenäs Lars
Published: March 2023

Background and Aims

Plants have evolved an unrivalled diversity of reproductive strategies, including variation in the degree of sexual vs. clonal reproduction. This variation has important effects on the dynamics and genetic structure of populations. We examined the association between large-scale variation in reproductive patterns and intraspecific genetic diversity in two moss species where sex is manifested in the dominant haploid generation and sex expression is irregular. We predicted that in regions with more frequent realized sexual reproduction, populations should display less skewed sex ratios, should more often express sex and should have higher genetic diversity than in regions with largely clonal reproduction.

Methods

We assessed reproductive status and phenotypic sex in the dioicous long-lived Drepanocladus trifarius and D. turgescens, in 248 and 438 samples across two regions in Scandinavia with frequent or rare realized sexual reproduction, respectively. In subsets of the samples, we analysed genetic diversity using nuclear and plastid sequence information and identified sex with a sex-specific molecular marker in non-reproductive samples.

Key Results

Contrary to our predictions, sex ratios did not differ between regions; genetic diversity did not differ in D. trifarius and it was higher in the region with rare sexual reproduction in D. turgescens. Supporting our predictions, relatively more samples expressed sex in D. trifarius in the region with frequent sexual reproduction. Overall, samples were mostly female. The degree of sex expression and genetic diversity differed between sexes.

Conclusions

Sex expression levels, regional sex ratios and genetic diversity were not directly associated with the regional frequency of realized sexual reproduction, and relationships and variation patterns differed between species. We conclude that a combination of species-specific life histories, such as longevity, overall degree of successful sexual reproduction and recruitment, and historical factors are important to explain this variation. Our data on haploid-dominated plants significantly complement plant reproductive biology.
Homeostatic normalization of alpha brain rhythms within the default-mode network and reduced symptoms in post-traumatic stress disorder following a randomized controlled trial of electroencephalogram neurofeedback
Authors: Nicholson Andrew A , Densmore Maria , Frewen Paul A , Neufeld Richard W J , Théberge Jean , Jetly Rakesh , Lanius Ruth A , Ros Tomas
Published: March 2023

Collective research has identified a key electroencephalogram signature in patients with post-traumatic stress disorder, consisting of abnormally reduced alpha (8–12 Hz) rhythms. We conducted a 20-session, double-blind, randomized controlled trial of alpha desynchronizing neurofeedback in patients with post-traumatic stress disorder over 20 weeks. Our objective was to provide mechanistic evidence underlying potential clinical improvements by examining changes in aberrant post-traumatic stress disorder brain rhythms (namely, alpha oscillations) as a function of neurofeedback treatment. We randomly assigned participants with a primary diagnosis of post-traumatic stress disorder (n = 38) to either an experimental group (n = 20) or a sham-control group (n = 18). A multichannel electroencephalogram cap was used to record whole-scalp resting-state activity pre- and post-neurofeedback treatment, for both the experimental and sham-control post-traumatic stress disorder groups. We first observed significantly reduced relative alpha source power at baseline in patients with post-traumatic stress disorder as compared to an age/sex-matched group of neurotypical healthy controls (n = 32), primarily within regions of the anterior default mode network. Post-treatment, we found that only post-traumatic stress disorder patients in the experimental neurofeedback group demonstrated significant alpha resynchronization within areas that displayed abnormally low alpha power at baseline. In parallel, we observed significantly decreased post-traumatic stress disorder severity scores in the experimental neurofeedback group only, when comparing baseline to post-treatment (Cohen’s d = 0.77) and three-month follow-up scores (Cohen’s d = 0.75), with a remission rate of 60.0% at the three-month follow-up. Overall, our results indicate that neurofeedback training can rescue pathologically reduced alpha rhythmicity, a functional biomarker that has repeatedly been linked to symptoms of hyperarousal and cortical disinhibition in post-traumatic stress disorder. This randomized controlled trial provides long-term evidence suggesting that the ‘alpha rebound effect’ (i.e. homeostatic alpha resynchronization) occurs within key regions of the default mode network previously implicated in post-traumatic stress disorder.
A vertigo network derived from human brain lesions and brain stimulation
Authors: Li Yanran , Qi Lei , Schaper Frédéric L W V J , Wu Di , Friedrich Maximilian , Du Jialin , Yu Tao , Wang Qiao , Wang Xiaopeng , Wang Di , Jin Guangyuan , Liu Aihua , Fan Chunqiu , Wang Yuping , Fox Michael D , Ren Liankun
Published: March 2023

Vertigo is a common neurological complaint, which can result in significant morbidity and decreased quality of life. While pathology to peripheral and subtentorial brain structures is a well-established cause of vertigo, cortical lesions have also been linked to vertigo and may lend insight into relevant neuroanatomy. Here, we investigate the supratentorial lesion locations associated with vertigo and test whether they map to a common brain network. We performed a systematic literature search and identified 23 cases of supratentorial brain lesions associated with vertigo. We mapped the lesion locations to a standard brain template and computed the network of brain regions functionally connected to each lesion location, using a ‘wiring diagram’ of the human brain termed the human connectome (n = 1000). Sensitivity was assessed by identifying the most common connection to lesion locations associated with vertigo, and specificity was assessed through comparison with control lesions associated with symptoms other than vertigo (n = 68). We found that functional connectivity between lesion locations and the bilateral ventral posterior insula was both sensitive (22/23 lesions) and specific (voxel-wise family-wise error-corrected P < 0.05) for lesion-induced vertigo. We computed connectivity with this hub region to define a lesion-based vertigo network, which included regions in the bilateral insula, somatosensory cortex, higher-level visual areas, cingulate sulcus, thalamus and multiple cerebellar regions in the territory of the posterior inferior cerebellar artery. Next, we used stereo-electroencephalography (80 stimulation sites across 17 patients) to test whether stimulation sites associated with vertigo mapped to this same network. We found that 36/42 (86%) of stimulation sites eliciting vertigo fell within the lesion-based vertigo network in contrast to 16/39 (41%) of stimulation sites that did not elicit vertigo. Connectivity between stimulation sites and our lesion-based hub in the ventral posterior insula was also significantly associated with vertigo (P < 0.0001). We conclude that cortical lesions and direct electrical stimulation sites associated with vertigo map to a common brain network, offering insights into the causal neuroanatomical substrate of vertigo.
FungiProteomeDB: a database for the molecular weight and isoelectric points of the fungal proteomes
Authors: Rashid Muhammad , Omar Muhammad , Mohanta Tapan Kumar
Published: March 2023

Proteins’ molecular weight (MW) and isoelectric point (pI) are crucial for their subcellular localization and subsequent function. These are also useful in 2D gel electrophoresis, liquid chromatography–mass spectrometry and X-ray protein crystallography. Moreover, visualizations like a virtual 2D proteome map of pI vs. MW are worthwhile to discuss the proteome diversity among different species. Although the genome sequence data of the fungi kingdom improved enormously, the proteomic details have been poorly elaborated. Therefore, we have calculated the MW and pI of the fungi proteins and reported them in, FungiProteomeDB, an online database (DB) https://vision4research.com/fungidb/. We analyzed the proteome of 685 fungal species that contain 7 127 141 protein sequences. The DB provides an easy-to-use and efficient interface for various search options, summary statistics and virtual 2D proteome map visualizations. The MW and pI of a protein can be obtained by searching the name of a protein, a keyword or a list of accession numbers. It also allows querying protein sequences. The DB will be helpful in hypothesis formulation and in various biotechnological applications.

Database URL https://vision4research.com/fungidb/
Multiorgan evaluation of perfusion and congestion using ultrasound in patients with shock
Authors: Tavazzi Guido , Spiegel Rory , Rola Philippe , Price Susanna , Corradi Francesco , Hockstein Maxwell
Published: March 2023

There is increasing evidence on the role of ultrasound in the evaluation of multiorgan hypoperfusion and congestion in patients with cardiocirculatory shock both to identify the underlying pathophysiological mechanism and to drive and monitor the treatment. The cardiac and lung ultrasound is included as an integrated multiparametric approach to the very early phase of patients with haemodynamic instability/cardiogenic shock. Splanchnic ultrasound has been mainly applied in heart failure and predominant circulatory failure. Although poorly validated in the critically ill, many ultrasound parameters have a strong physiological background to support their use in the acute setting those that apply either for heart/lung and for splanchnic organ evaluation. This review summarizes the ultrasonographic parameters that have shown evidence in literature in the diagnostic/therapeutic pathway to define the congestion/perfusion profile of the organs that are involved in the pathophysiological cascade of cardiocirculatory shock.
An evolutionary perspective on genetic load in small, isolated populations as informed by whole genome resequencing and forward-time simulations
Authors: Mathur Samarth , Tomeček John M , Tarango-Arámbula Luis A , Perez Robert M , DeWoody J Andrew
Published: March 2023

Small populations are vulnerable to increased genetic load and drift that can lead to reductions in fitness and adaptive potential. By analyzing 66 individual whole genomes of Montezuma Quail (Cyrtonyx montezumae) from multiple populations, we illustrate how genetic load is dynamic over evolutionary time. We show that Montezuma Quail are evolving like a ring species, where the terminal extant populations from Arizona and Texas have been separated for ~16,500 years. The Texas populations have remained small but stable since the separation, whereas the Arizona population is much larger today but has been contracting for thousands of years. Most deleterious mutations across the genome are young and segregating privately in each population and a greater number of deleterious alleles are present in the larger population. Our data indicate that ancestral load is purged during strong bottlenecks, but the reduced efficiency of selection in small populations means that segregating deleterious mutations are more likely to rise in frequency over time. Forward-time simulations indicate that severe population declines in historically large populations is more detrimental to individual fitness, whereas long-term small populations are more at risk for reduced adaptive potential and population-level fitness. Our study highlights the intimate connections among evolutionary history, historical demography, genetic load, and evolutionary potential in wild populations.
A novel method for jointly modeling the evolution of discrete and continuous traits
Authors: Boyko James D , O’Meara Brian C , Beaulieu Jeremy M
Published: March 2023

The correlated evolution of multiple characters is a crucial aspect of evolutionary change. If change in a particular character influences the evolution of a separate trait, then modeling these features independently can mislead our understanding of the evolutionary process. Progress toward jointly modeling several characters has involved modeling multivariate evolution of the same class of character, but there are far fewer options when jointly modeling traits when one character is discrete and the other is continuous. Here, we develop such a framework to explicitly estimate the joint likelihood for discrete and continuous characters. Specifically, our model combines the probability of observing the continuous character under a generalized OU process with the probability of the discrete character under a hidden Markov model, linked by a shared underlying regime. We use simulation studies to demonstrate that this approach, hOUwie, can accurately evaluate parameter values across a broad set of models. We then apply our model to test whether fleshy and dry fruits of Ericaceae lineages are correlated with their climatic niche evolution as represented by the aridity index. Consistent with expectations, we find that the climatic niche of lineages with fleshy fruits is more conserved while lineages with dry fruits have higher rates of climatic niche evolution and a more humid climatic optimum.
The “comfort timing” strategy: a potential pathway for the cultivation of uncultured microorganisms and a possible adaptation for environmental colonisation
Authors: Laugier Jamie
Published: March 2023

Efforts to isolate uncultured microorganisms over the last century and a half, as well as the advanced ‘omics’ technologies developed over the last three decades, have greatly increased the knowledge and resources of microbiology. However, many cellular functions such as growth remain unknown in most of the microbial diversity identified through genomic sequences from environmental samples, as evidenced by the increasingly precise observations of the phenomenon known as the ‘great plate count anomaly’. Faced with the many microbial cells recalcitrant to cultivation present in environmental samples, Epstein proposed the ‘scout’ model, characterised by a dominance of dormant cells whose awakening would be strictly stochastic. Unfortunately, this hypothesis leaves few exploitable possibilities for microbial cultivation. This review proposes that many microorganisms follow the ‘comfort timing’ strategy, characterised by an exit from dormancy responding to a set of environmental conditions close to optimal for growth. This ‘comfort timing’ strategy offers the possibility of designing culture processes that could isolate a larger proportion of uncultured microorganisms. Two methods are briefly proposed in this article. In addition, the advantages of dormancy, of the ‘scout’ model and of the ‘comfort timing’ strategy for survival under difficult conditions, but also for colonisation of environments, are discussed.
Adults Older Than Age 55 Engage in Less Diverse Activities Than Those 18 Years Ago
Authors: Lee Soomi , Koffer Rachel , Drewelies Johanna
Published: March 2023

Objectives

Life-span perspectives have long acknowledged that individual functioning is shaped by historical and sociocultural contexts. Secular increases favoring recent cohorts are widely documented. However, little is known about secular trends in day-to-day activities and whether historical changes have occurred in younger and older adults alike.

Methods

We compared data from 2 independent cohort samples of the daily diary portion of the Midlife in the United States Study obtained 18 years apart (1995/1996 cohort: n = 1,499 vs 2013/2014 cohort: n = 782) and identified case-matched cohorts (n = 757 per cohort) based on age, gender, education, and race. An activity diversity score was calculated based on 7 common daily activities, using Shannon’s entropy method. We additionally examined the roles of age and other sociodemographic and health characteristics in cohort differences in activity diversity.

Results

Results revealed that the 2013/2014 cohort experienced lower daily activity diversity than the 1995/1996 cohort. Age was positively associated with activity diversity in the 1995/1996 cohort, whereas age was negatively associated with activity diversity in the 2013/2014 cohort. These associations were significant for those who were older than age 55. Cohorts also differed in the types of most dominant activities and average time spent on those activities.

Discussion

Findings show changes in the lifestyles and daily activities of U.S. adults across 2 decades. Contrasting to the common belief that today’s adults may be healthier and more active, they seem engaging in less diverse daily activities, which can be a risk for future health outcomes.