Emergence and Spread of Basal Lineages of Yersinia pestis during the Neolithic Decline.

Between 5,000 and 6,000 years ago, many Neolithic societies declined throughout western Eurasia due to a combination of factors that are still largely debated. Here, we report the discovery and genome reconstruction of Yersinia pestis, the etiological agent of plague, in Neolithic farmers in Sweden, pre-dating and basal to all modern and ancient known strains of this pathogen. We investigated the history of this strain by combining phylogenetic and molecular clock analyses of the bacterial genome, detailed archaeological information, and genomic analyses from infected individuals and hundreds of ancient human samples across Eurasia. These analyses revealed that multiple and independent lineages of Y. pestis branched and expanded across Eurasia during the Neolithic decline, spreading most likely through early trade networks rather than massive human migrations. Our results are consistent with the existence of a prehistoric plague pandemic that likely contributed to the decay of Neolithic populations in Europe.

GABA-edited MEGA-PRESS at 3 T: Does a measured macromolecule background improve linear combination modeling?

PURPOSE: The J-difference edited γ-aminobutyric acid (GABA) signal is contaminated by other co-edited signals-the largest of which originates from co-edited macromolecules (MMs)-and is consequently often reported as "GABA+." MM signals are broader and less well-characterized than the metabolites, and are commonly approximated using a Gaussian model parameterization. Experimentally measured MM signals are a consensus-recommended alternative to parameterized modeling; however, they are relatively under-studied in the context of edited MRS. METHODS: To address this limitation in the literature, we have acquired GABA-edited MEGA-PRESS data with pre-inversion to null metabolite signals in 13 healthy controls. An experimental MM basis function was derived from the mean across subjects. We further derived a new parameterization of the MM signals from the experimental data, using multiple Gaussians to accurately represent their observed asymmetry. The previous single-Gaussian parameterization, mean experimental MM spectrum and new multi-Gaussian parameterization were compared in a three-way analysis of a public MEGA-PRESS dataset of 61 healthy participants. RESULTS: Both the experimental MMs and the multi-Gaussian parameterization exhibited reduced fit residuals compared to the single-Gaussian approach (p = 0.034 and p = 0.031, respectively), suggesting they better represent the underlying data than the single-Gaussian parameterization. Furthermore, both experimentally derived models estimated larger MM fractional contribution to the GABA+ signal for the experimental MMs (58%) and multi-Gaussian parameterization (58%), compared to the single-Gaussian approach (50%). CONCLUSIONS: Our results indicate that single-Gaussian parameterization of edited MM signals is insufficient and that both experimentally derived GABA+ spectra and their parameterized replicas improve the modeling of GABA+ spectra.

Optimization of the flip angles of narrow-band editing pulses in J-difference edited MRS of lactate at 3T.

PURPOSE: Application of highly selective editing RF pulses provides a means of minimizing co-editing of contaminants in J-difference MRS (MEGA), but it causes reduction in editing yield. We examined the flip angles (FAs) of narrow-band editing pulses to maximize the lactate edited signal with minimal co-editing of threonine. METHODS: The effect of editing-pulse FA on the editing performance was examined, with numerical and phantom analyses, for bandwidths of 17.6-300 Hz in MEGA-PRESS editing of lactate at 3T. The FA and envelope of 46 ms Gaussian editing pulses were tailored to maximize the lactate edited signal at 1.3 ppm and minimize co-editing of threonine. The optimized editing-pulse FA MEGA scheme was tested in brain tumor patients. RESULTS: Simulation and phantom data indicated that the optimum FA of MEGA editing pulses is progressively larger than 180° as the editing-pulse bandwidth decreases. For 46 ms long 17.6 Hz bandwidth Gaussian pulses and other given sequence parameters, the lactate edited signal was maximum at the first and second editing-pulse FAs of 241° and 249°, respectively. The edit-on and difference-edited lactate peak areas of the optimized FA MEGA were greater by 43% and 25% compared to the 180°-FA MEGA, respectively. In-vivo data confirmed the simulation and phantom results. The lesions of the brain tumor patients showed elevated lactate and physiological levels of threonine. CONCLUSION: The lactate MEGA editing yield is significantly increased with editing-pulse FA much larger than 180° when the editing-pulse bandwidth is comparable to the lactate quartet frequency width.

Genetic legacies of mega-landslides: Cycles of isolation and contact across flank collapses in an oceanic island.

Catastrophic flank collapses are recognized as important drivers of insular biodiversity dynamics, through the disruption of species ranges and subsequent allopatric divergence. However, little empirical data supports this conjecture, with their evolutionary consequences remaining poorly understood. Using genome-wide data within a population genomics and phylogenomics framework, we evaluate how mega-landslides have impacted evolutionary and demographic history within a species complex of weevils (Curculionidae) within the Canary Island of Tenerife. We reveal a complex genomic landscape, within which individuals of single ancestry were sampled in areas characterized by long-term geological stability, relative to the timing of flank collapses. In contrast, individuals of admixed ancestry were almost exclusively sampled within the boundaries of flank collapses. Estimated divergence times among ancestral populations aligned with the timings of mega-landslide events. Our results provide first evidence for a cyclical dynamic of range fragmentation and secondary contact across flank collapse landscapes, with support for a model where this dynamic is mediated by Quaternary climate oscillations. The context within which we reveal climate and topography to interact cyclically through time to shape the geographic structure of genetic variation, together with related recent work, highlights the importance of topoclimatic phenomena as an agent of diversification within insular invertebrates.

Phylogenomics of mulberries (Morus, Moraceae) inferred from plastomes and single copy nuclear genes.

Mulberries (genus Morus), belonging to the order Rosales, family Moraceae, are important woody plants due to their economic values in sericulture, as well as for nutritional benefits and medicinal values. However, the taxonomy and phylogeny of Morus, especially for the Asian species, remains challenging due to its wide geographical distribution, morphological plasticity, and interspecific hybridization. To better understand the evolutionary history of Morus, we combined plastomes and a large-scale nuclear gene analyses to investigate their phylogenetic relationships. We assembled the plastomes and screened 211 single-copy nuclear genes from 13 Morus species and related taxa. The plastomes of Morus species were relatively conserved in terms of genome size, gene content, synteny, IR boundary and codon usage. Using nuclear data, our results elucidated identical topologies based on coalescent and concatenation methods. The genus Morus was supported as monophyletic, with M. notabilis as the first diverging lineage and the two North American Morus species, M. microphylla and M. rubra, as sister to the other Asian species. In the Asian Morus species, interspecific relationships were completely resolved. However, cyto-nuclear discordances and gene tree-species tree conflicts were detected in the phylogenies of Morus, with multiple evidences supporting hybridization/introgression as the main cause of discordances between nuclear and plastid phylogenies, while gene tree-species tree conflicts were mainly caused by ILS.

Impact of acquisition and modeling parameters on the test-retest reproducibility of edited GABA.

Literature values vary widely for within-subject test-retest reproducibility of gamma-aminobutyric acid (GABA) measured with edited magnetic resonance spectroscopy (MRS). Reasons for this variation remain unclear. Here, we tested whether three acquisition parameters-(1) sequence complexity (two-experiment MEscher-GArwood Point RESolved Spectroscopy [MEGA-PRESS] vs. four-experiment Hadamard Encoding and Reconstruction of MEGA-Edited Spectroscopy [HERMES]); (2) editing pulse duration (14 vs. 20 ms); and (3) scanner frequency drift (interleaved water referencing [IWR] turned ON vs. OFF)-and two linear combination modeling variations-(1) three different coedited macromolecule models (called "1to1GABA", "1to1GABAsoft", and "3to2MM" in the Osprey software package); and (2) 0.55- versus 0.4-ppm spline baseline knot spacing-affected the within-subject coefficient of variation of GABA + macromolecules (GABA+). We collected edited MRS data from the dorsal anterior cingulate cortex from 20 participants (mean age: 30.8 ± 9.5 years; 10 males). Test and retest scans were separated by removing the participant from the scanner for 5-10 min. Each acquisition consisted of two MEGA-PRESS and two HERMES sequences with editing pulse durations of 14 and 20 ms (referred to here as MEGA-14, MEGA-20, HERMES-14, and HERMES-20; all TE = 80 ms, 224 averages). We identified the best test-retest reproducibility following postprocessing with a composite model of the 0.9- and 3-ppm macromolecules ("3to2MM"); this model performed particularly well for the HERMES data. Furthermore, sparser (0.55- compared with 0.4-ppm) spline baseline knot spacing yielded generally better test-retest reproducibility for GABA+. Replicating our prior results, linear combination modeling in Osprey compared with simple peak fitting in Gannet resulted in substantially better test-retest reproducibility. However, reproducibility did not consistently differ for MEGA-PRESS compared with HERMES, for 14- compared with 20-ms editing pulses, or for IWR-ON versus IWR-OFF. These results highlight the importance of model selection for edited MRS studies of GABA+, particularly for clinical studies that focus on individual patient differences in GABA+ or changes following an intervention.

GABA, glutamatergic dynamics and BOLD contrast assessed concurrently using functional MRS during a cognitive task.

A recurring issue in functional neuroimaging is how to link task-driven haemodynamic blood oxygen level dependent functional MRI (BOLD-fMRI) responses to underlying neurochemistry at the synaptic level. Glutamate and γ-aminobutyric acid (GABA), the major excitatory and inhibitory neurotransmitters respectively, are typically measured with MRS sequences separately from fMRI, in the absence of a task. The present study aims to resolve this disconnect, developing acquisition and processing techniques to simultaneously assess GABA, glutamate and glutamine (Glx) and BOLD in relation to a cognitive task, at 3 T. Healthy subjects (N = 81) performed a cognitive task (Eriksen flanker), which was presented visually in a task-OFF, task-ON block design, with individual event onset timing jittered with respect to the MRS readout. fMRS data were acquired from the medial anterior cingulate cortex during task performance, using an adapted MEGA-PRESS implementation incorporating unsuppressed water-reference signals at a regular interval. These allowed for continuous assessment of BOLD activation, through T2 *-related changes in water linewidth. BOLD-fMRI data were additionally acquired. A novel linear model was used to extract modelled metabolite spectra associated with discrete functional stimuli, building on well established processing and quantification tools. Behavioural outcomes from the flanker task, and activation patterns from the BOLD-fMRI sequence, were as expected from the literature. BOLD response assessed through fMRS showed a significant correlation with fMRI, specific to the fMRS-targeted region of interest; fMRS-assessed BOLD additionally correlated with lengthening of response time in the incongruent flanker condition. While no significant task-related changes were observed for GABA+, a significant increase in measured Glx levels (~8.8%) was found between task-OFF and task-ON periods. These findings verify the efficacy of our protocol and analysis pipelines for the simultaneous assessment of metabolite dynamics and BOLD. As well as establishing a robust basis for further work using these techniques, we also identify a number of clear directions for further refinement in future studies.

New insights into plant autophagy: molecular mechanisms and roles in development and stress responses.

Autophagy is an evolutionarily conserved eukaryotic intracellular degradation process. Although the molecular mechanisms of plant autophagy share similarities with those in yeast and mammals, certain unique mechanisms have been identified. Recent studies have highlighted the importance of autophagy during vegetative growth stages as well as in plant-specific developmental processes, such as seed development, germination, flowering, and somatic reprogramming. Autophagy enables plants to adapt to and manage severe environmental conditions, such as nutrient starvation, high-intensity light stress, and heat stress, leading to intracellular remodeling and physiological changes in response to stress. In the past, plant autophagy research lagged behind similar studies in yeast and mammals; however, recent advances have greatly expanded our understanding of plant-specific autophagy mechanisms and functions. This review summarizes current knowledge and latest research findings on the mechanisms and roles of plant autophagy with the objective of improving our understanding of this vital process in plants.

Magnetic Resonance Spectroscopy Spectral Registration Using Deep Learning.

BACKGROUND: Deep learning-based methods have been successfully applied to MRI image registration. However, there is a lack of deep learning-based registration methods for magnetic resonance spectroscopy (MRS) spectral registration (SR). PURPOSE: To investigate a convolutional neural network-based SR (CNN-SR) approach for simultaneous frequency-and-phase correction (FPC) of single-voxel Meshcher-Garwood point-resolved spectroscopy (MEGA-PRESS) MRS data. STUDY TYPE: Retrospective. SUBJECTS: Forty thousand simulated MEGA-PRESS datasets generated from FID Appliance (FID-A) were used and split into the following: 32,000/4000/4000 for training/validation/testing. A 101 MEGA-PRESS medial parietal lobe data retrieved from the Big GABA were used as the in vivo datasets. FIELD STRENGTH/SEQUENCE: 3T, MEGA-PRESS. ASSESSMENT: Evaluation of frequency and phase offsets mean absolute errors were performed for the simulation dataset. Evaluation of the choline interval variance was performed for the in vivo dataset. The magnitudes of the offsets introduced were -20 to 20 Hz and -90° to 90° and were uniformly distributed for the simulation dataset at different signal-to-noise ratio (SNR) levels. For the in vivo dataset, different additional magnitudes of offsets were introduced: small offsets (0-5 Hz; 0-20°), medium offsets (5-10 Hz; 20-45°), and large offsets (10-20 Hz; 45-90°). STATISTICAL TESTS: Two-tailed paired t-tests for model performances in the simulation and in vivo datasets were used and a P-value <0.05 was considered statistically significant. RESULTS: CNN-SR model was capable of correcting frequency offsets (0.014 ± 0.010 Hz at SNR 20 and 0.058 ± 0.050 Hz at SNR 2.5 with line broadening) and phase offsets (0.104 ± 0.076° at SNR 20 and 0.416 ± 0.317° at SNR 2.5 with line broadening). Using in vivo datasets, CNN-SR achieved the best performance without (0.000055 ± 0.000054) and with different magnitudes of additional frequency and phase offsets (i.e., 0.000062 ± 0.000068 at small, -0.000033 ± 0.000023 at medium, 0.000067 ± 0.000102 at large) applied. DATA CONCLUSION: The proposed CNN-SR method is an efficient and accurate approach for simultaneous FPC of single-voxel MEGA-PRESS MRS data. EVIDENCE LEVEL: 4 TECHNICAL EFFICACY: Stage 2.

Anatomy of a mega-radiation: Biogeography and niche evolution in Astragalus.

PREMISE: Astragalus (Fabaceae), with more than 3000 species, represents a globally successful radiation of morphologically highly similar species predominant across the northern hemisphere. It has attracted attention from systematists and biogeographers, who have asked what factors might be behind the extraordinary diversity of this important arid-adapted clade and what sets it apart from close relatives with far less species richness. METHODS: Here, for the first time using extensive phylogenetic sampling, we asked whether (1) Astragalus is uniquely characterized by bursts of radiation or whether diversification instead is uniform and no different from closely related taxa. Then we tested whether the species diversity of Astragalus is attributable specifically to its predilection for (2) cold and arid habitats, (3) particular soils, or to (4) chromosome evolution. Finally, we tested (5) whether Astragalus originated in central Asia as proposed and (6) whether niche evolutionary shifts were subsequently associated with the colonization of other continents. RESULTS: Our results point to the importance of heterogeneity in the diversification of Astragalus, with upshifts associated with the earliest divergences but not strongly tied to any abiotic factor or biogeographic regionalization tested here. The only potential correlate with diversification we identified was chromosome number. Biogeographic shifts have a strong association with the abiotic environment and highlight the importance of central Asia as a biogeographic gateway. CONCLUSIONS: Our investigation shows the importance of phylogenetic and evolutionary studies of logistically challenging "mega-radiations." Our findings reject any simple key innovation behind high diversity and underline the often nuanced, multifactorial processes leading to species-rich clades.

Severity of prematurity and age impact early postnatal development of GABA and glutamate systems.

Gamma-aminobutyric acid (GABA) and glutamatergic system perturbations following premature birth may explain neurodevelopmental deficits in the absence of structural brain injury. Using GABA-edited spectroscopy (MEscher-GArwood Point Resolved Spectroscopy [MEGA-PRESS] on 3 T MRI), we have described in-vivo brain GABA+ (+macromolecules) and Glx (glutamate + glutamine) concentrations in term-born infants. We report previously unavailable comparative data on in-vivo GABA+ and Glx concentrations in the cerebellum, the right basal ganglia, and the right frontal lobe of preterm-born infants without structural brain injury. Seventy-five preterm-born (gestational age 27.8 ± 2.9 weeks) and 48 term-born (39.6 ± 0.9 weeks) infants yielded reliable MEGA-PRESS spectra acquired at post-menstrual age (PMA) of 40.2 ± 2.3 and 43.0 ± 2 weeks, respectively. GABA+ (median 2.44 institutional units [i.u.]) concentrations were highest in the cerebellum and Glx higher in the cerebellum (5.73 i.u.) and basal ganglia (5.16 i.u.), with lowest concentrations in the frontal lobe. Metabolite concentrations correlated positively with advancing PMA and postnatal age at MRI (Spearman's rho 0.2-0.6). Basal ganglia Glx and NAA, and frontal GABA+ and NAA concentrations were lower in preterm compared with term infants. Moderate preterm infants had lower metabolite concentrations than term and extreme preterm infants. Our findings emphasize the impact of premature extra-uterine stimuli on GABA-glutamate system development and may serve as early biomarkers of neurodevelopmental deficits.

Evaluating three strategies of genome-wide association analysis for integrating data from multiple populations.

In livestock, genome-wide association studies (GWAS) are usually conducted in a single population (single-GWAS) with limited sample size and detection power. To enhance the detection power of GWAS, meta-analysis of GWAS (meta-GWAS) and mega-analysis of GWAS (mega-GWAS) have been proposed to integrate data from multiple populations at the level of summary statistics or individual data, respectively. However, there is a lack of comparison for these different strategies, which makes it difficult to guide the best practice of GWAS integrating data from multiple study populations. To maximize the comparison of different association analysis strategies across multiple populations, we conducted single-GWAS, meta-GWAS, and mega-GWAS for the backfat thickness of 100 kg (BFT_100) and days to 100 kg (DAYS_100) within each of the three commercial pig breeds (Duroc, Yorkshire, and Landrace). Based on controlling the genome inflation factor to one, we calculated corrected p-values (pC ). In Yorkshire, with the largest sample size, mega-GWAS, meta-GWAS and single-GWAS detected 149, 38 and 20 significant SNPs (pC < 1E-5) associated with BFT_100, as well as 26, four, and one QTL, respectively. Among them, pC of SNPs from mega-GWAS was the lowest, followed by meta-GWAS and single-GWAS. The correlation of pC among the three GWAS strategies ranged from 0.60 to 0.75 and the correlation of SNP effect values between meta-GWAS and mega-GWAS was 0.74, all showing good agreement. Collectively, even though there are differences in the integration of individual data or summary statistics, integrating data from multiple populations is an effective means of genetic argument for complex traits, especially mega-GWAS versus single-GWAS.

Association between perceived neighborhood environment and depression among residents living in mega-communities in Guiyang, China: a cross-sectional study.

BACKGROUND: Little was known about the relationship between perceived neighborhood environment and depression among residents living in mega-communities. Furthermore, the mediating effects of physical activity (PA) and anxiety in this relationship have not been investigated. Thus, this study aimed to comprehensively examine the association between perceived neighborhood environment and depression among residents living in mega-communities, and test whether PA and anxiety mediated the association. METHODS: A cross-sectional study on perceived neighborhood environment and depression was conducted among individuals who lived in mega-communities (n = 665) in Guiyang, China from July to August 2022. Perceived neighborhood environment was assessed from the following six aspects: traffic, building quality, accessibility, neighborhood, indoor, and pollution. Depression was measured by the Patients Health Questionnaire-9. Structural equation model was used to evaluate the association between perceived neighborhood environment and depression, and test the mediating effect of PA and anxiety in this association. RESULTS: We found that neighborhood (ß = -0.144, p = 0.002) and PA (ß = -0.074, p < 0.001) were both negatively associated with depression, while anxiety was positively associated with depression (ß = 0.447, p < 0.001). Married residents were less likely to experience depression than residents of other marital status. PA played a mediator role in the relationship between accessibility and depression (ß = 0.014, p = 0.033). PA mediated the relationship between neighborhood and depression (ß = -0.032, p = 0.015). The mediating effect of anxiety in the relationship between perceived neighborhood environment and depression was not significant. CONCLUSIONS: This study demonstrated that neighborhood, which was assessed by satisfaction with safety, hygiene, parking, greening, lighting, and building shape, was negatively associated with depression, and PA mediated the relationship.

Utilizing social media for community risk communication in megacities: analysing the impact of WeChat group information interaction and perception on communication satisfaction during the COVID-19 pandemic in Shanghai.

BACKGROUND: Against the backdrop of the global public health crisis, the COVID-19 pandemic has exposed significant disparities in the supply and demand of risk information related to public health crises, posing severe challenges to risk governance in megacities. Shanghai, China, introduced community WeChat groups for community communication, effectively facilitating the dissemination and response of grassroots information and providing a new path for interactive governance in the community. METHODS: This study collected 1006 questionnaires from residents of 350 communities in Shanghai through an online survey between June 10 and July 10, 2022. Multiple linear regression analysis was conducted to examine the impact of different participants (including the community, core residents, and the combined community and core residents) on community risk communication, perceived communication quality, and dissemination themes related to COVID-19 on community communication satisfaction. Additionally, in-depth interviews were conducted with 20 core residents from different types of communities, focusing on the specific methods of risk communication through community WeChat groups and their ability to disseminate information, respond to, and solve problems. RESULTS: Perceived information coverage and perceived response efficiency are significantly positively correlated with communication satisfaction. Notably, the speed of community information response has the greatest impact on communication satisfaction. Regarding COVID-19-related information dissemination themes, "community outbreaks, supplies, nucleic acids, outbreak prevention measures, and scientific content" all have a significant impact on communication effectiveness, with "nucleic acid testing information" having the greatest impact. Although the statistical data indicate that the participation of core residents in risk communication does not significantly affect communication satisfaction, it seems to be related to the size of the community, and the interview results further validate this conclusion. CONCLUSION: In the future, grassroots communities should consider the affordances of social media, recognize the significant correlation between risk communication and grassroots trust, and formulate more detailed and targeted risk communication strategies. In particular, incorporating core residents into "semiformal" grassroots organizations can improve community service quality, thereby enhancing community resilience in the face of public health emergencies.

Syndrome of megalencephaly, mega corpus callosum, and complete lack of motor development: an unusual case and a literature review.

The syndrome of megalencephaly, mega corpus callosum (MEG-MegaCC) accompanied by complete lack of motor development is a rare condition with only few sporadic cases having been reported in the literature. In this paper, we describe a child from non-consanguineous parents presenting with MegaCC, psychomotor retardation, and language impairment linked to MEG-MegaCC syndrome. Genetic analysis, radiological findings, and detailed neurological phenotype of MEG-MegaCC syndrome with its overlapping syndromes would allow for a better classification of the disease spectrum.

Multi-location evaluation of field pea in Indian climates: eco-phenological dynamics, crop-environment relationships, and identification of mega-environments.

Characterization of crop-growing environments in relation to crop's genotypic performance is crucial to harness positive genotype-by-environment interactions (GEI) in systematic breeding programs. Given that, the study aimed to delineate the impact of diverse environments on crop phenology and yield traits of dwarf-statured field pea, pinpointing location(s) favoring higher yield and distinctiveness within breeding lines. We tested twelve field pea breeding lines across twenty locations in India, covering Central Zone (CZ), North Western Plain Zone (NWPZ), North Eastern Plain Zone (NEPZ), and Northern Hill Zone (NHZ). Across these locations, maximum and minimum temperatures during flowering (TMAXF, TMINF) and reproductive period (TMAXRP, TMINRP) ranged 18.9-28.3, 3.3-18.0, 15.0-30.8, and 7.9-22.1oC, respectively. Meanwhile, notable variations in phenological and agronomic traits (coefficient of variation) were observed: flowering (31%), days to maturity (21%), reproductive period (18%), grain yield (48%), and 100-seed weight (18%). Combined ANOVA demonstrated an oversized impact of environment (81%) on yield, while genotype and GEI effects were 2% and 14%, respectively. The variables TMINF, TMINRP, and cumulative growing degree-day showed positive correlations with yield, while extended vegetative and maturity durations negatively influenced yield (p < 0.05). Additionally, linear mixed-models and PCA results explained that instability in crop phenology had significant influence on field pea yield. Seed weight was markedly varied within the locations (9.9-20.8 g) and both higher and lower seed weights were associated with lower yields (Optimal = 17.1 g). HA-GGE biplot-based on environment focus-scaling demonstrated three mega-environments and specific locations viz. Kota (CZ), SK Nagar (CZ), Raipur (CZ), Sehore (CZ), and Pantnagar (NWPZ) as the ideal testing-environments with high efficiency in selecting new genotypes with wider adaptability. The study findings highlight distinct impact of environments on crop phenology and agronomic traits of field pea (dwarf-type), hold substantial value in designing efficient field pea (dwarf-type) breeding program at mega-environment scale.

Caching Policy in Low Earth Orbit Satellite Mega-Constellation Information-Centric Networking for Internet of Things.

Information-Centric Networking (ICN) is the emerging next-generation internet paradigm. The Low Earth Orbit (LEO) satellite mega-constellation based on ICN can achieve seamless global coverage and provide excellent support for Internet of Things (IoT) services. Additionally, in-network caching, typically characteristic of ICN, plays a paramount role in network performance. Therefore, the in-network caching policy is one of the hotspot problems. Especially, compared to caching traditional internet content, in-networking caching IoT content is more challenging, since the IoT content lifetime is small and transient. In this paper, firstly, the framework of the LEO satellite mega-constellation Information-Centric Networking for IoT (LEO-SMC-ICN-IoT) is proposed. Then, introducing the concept of "viscosity", the proposed Caching Algorithm based on the Random Forest (CARF) policy of satellite nodes combines both content popularity prediction and satellite nodes location prediction, for achieving good cache matching between the satellite nodes and content. And using the matching rule, the Random Forest (RF) algorithm is adopted to predict the matching relationship among satellite nodes and content for guiding the deployment of caches. Especially, the content is cached in advance at the future satellite to maintain communication with the current ground segment at the time of satellite switchover. Additionally, the policy considers both the IoT content lifetime and the freshness. Finally, a simulation platform with LEO satellite mega-constellation based on ICN is developed in Network Simulator 3 (NS-3). The simulation results show that the proposed caching policy compared with the Leave Copy Everywhere (LCE), the opportunistic (OPP), the Leave Copy down (LCD), and the probabilistic algorithm which caches each content with probability 0.5 (prob 0.5) yield a significant performance improvement, such as the average number of hops, i.e., delay, cache hit rate, and throughput.

Meta-analysis in a digitalized world: A step-by-step primer.

In recent years, much research and many data sources have become digital. Some advantages of digital or Internet-based research, compared to traditional lab research (e.g., comprehensive data collection and storage, availability of data) are ideal for an improved meta-analyses approach.In the meantime, in meta-analyses research, different types of meta-analyses have been developed to provide research syntheses with accurate quantitative estimations. Due to its rich and unique palette of corrections, we recommend to using the Schmidt and Hunter approach for meta-analyses in a digitalized world. Our primer shows in a step-by-step fashion how to conduct a high quality meta-analysis considering digital data and highlights the most obvious pitfalls (e.g., using only a bare-bones meta-analysis, no data comparison) not only in aggregation of the data, but also in the literature search and coding procedure which are essential steps in any meta-analysis. Thus, this primer of meta-analyses is especially suited for a situation where much of future research is headed to: digital research. To map Internet-based research and to reveal any research gap, we further synthesize meta-analyses on Internet-based research (15 articles containing 24 different meta-analyses, on 745 studies, with 1,601 effect sizes), resulting in the first mega meta-analysis of the field. We found a lack of individual participant data (e.g., age and nationality). Hence, we provide a primer for high-quality meta-analyses and mega meta-analyses that applies to much of coming research and also basic hands-on knowledge to conduct or judge the quality of a meta-analyses in a digitalized world.

Dimensionality and optimal combination of autonomic fear-conditioning measures in humans.

Fear conditioning, also termed threat conditioning, is a commonly used learning model with clinical relevance. Quantification of threat conditioning in humans often relies on conditioned autonomic responses such as skin conductance responses (SCR), pupil size responses (PSR), heart period responses (HPR), or respiration amplitude responses (RAR), which are usually analyzed separately. Here, we investigate whether inter-individual variability in differential conditioned responses, averaged across acquisition, exhibits a multi-dimensional structure, and the extent to which their linear combination could enhance the precision of inference on whether threat conditioning has occurred. In a mega-analytic approach, we re-analyze nine data sets including 256 individuals, acquired by the group of the last author, using standard routines in the framework of psychophysiological modeling (PsPM). Our analysis revealed systematic differences in effect size between measures across datasets, but no evidence for a multidimensional structure across various combinations of measures. We derive the statistically optimal weights for combining the four measures and subsets thereof, and we provide out-of-sample performance metrics for these weights, accompanied by bias-corrected confidence intervals. We show that to achieve the same statistical power, combining measures allows for a relevant reduction in sample size, which in a common scenario amounts to roughly 24%. To summarize, we demonstrate a one-dimensional structure of threat conditioning measures, systematic differences in effect size between measures, and provide weights for their optimal linear combination in terms of maximal retrodictive validity.

The mega-evolution of life with its three memory systems depends on sender-receiver communication and problem-solving. A narrative review.

It should be the ultimate goal of any theory of evolution to delineate the contours of an integrative system to answer the question: How does life (in all its complexity) evolve (which can be called mega-evolution)? But how to plausibly define 'life'? My answer (1994-2023) is: 'life' sounds like a noun, but denotes an activity, and thus is a verb. Life (L) denotes nothing else than the total sum (∑) of all acts of communication (transfer of information) (C) executed by any type of senders-receivers at all their levels (up to at least 15) of compartmental organization: L = ∑C. The 'communicating compartment' is better suited to serve as the universal unit of structure, function and evolution than the cell, the smallest such unit. By paying as much importance to communication activity as to the Central Dogma of molecular biology, a wealth of new insights unfold. The major ones are as follows. (1) Living compartments have not only a genetic memory (DNA), but also a still enigmatic cognitive and an electrical memory system (and thus a triple memory system). (2) Complex compartments can have up to three types of progeny: genetic descendants/children, pupils/learners and electricians. (3) Of particular importance to adaptation, any act of communication is a problem-solving act because all messages need to be decoded. Hence through problem-solving that precedes selection, life itself is the driving force of its own evolution (a very clever but counterintuitive and unexpected logical deduction). Perhaps, this is the 'vital force' philosopher and Nobel laureate (in 1927) Henri Bergson searched for but did not find.