Miracle-dz/UniFAR-FTUs huggingface dataset:
Wheat Developmental Traits as Affected by the Interaction between Eps-7D and Temperature under Contrasting Photoperiods with Insensitive Ppd-D1 Background

Earliness per se (Eps) genes are important to fine tune adaptation, and studying their probable pleiotropic effect on wheat yield traits is worthwhile. In addition, it has been shown that some Eps genes interact with temperature. We studied two NILs differing in the newly identified Eps-7D but carrying insensitive Ppd-D1 in the background under three temperature regimes (9, 15 and 18 °C) and two photoperiods (12 h and 24 h). Eps-7D affected time to anthesis as expected and the Eps-7D-late allele extended both the period before and after terminal spikelet. The interaction effect of Eps-7D × temperature was significant but not cross-over: the magnitude and level of significance of the difference between NILs with the late or early allele was affected by the growing temperature (i.e. difference was least at 18 °C and largest at 9 °C), and differences in temperature sensitivity was influenced by photoperiod. Rate of leaf initiation was faster in NIL with Eps-7D-early than with the late allele which compensated for the shorter duration of leaf initiation resulting in similar final leaf number between two NILs. Eps-7D-late consistently increased spike fertility through improving floret primordia survival as a consequence of extending the late reproductive phase.
CLPX regulates erythroid heme synthesis by control of mitochondrial heme synthesis enzymes and iron utilization

Heme is a prosthetic group that plays a critical role in catalyzing life-essential redox reactions in all cells, including critical metabolic processes. Heme synthesis must be tightly co-regulated with cellular requirements in order to maximize utilization and minimize toxicity. Terminally differentiating erythroid cells have an extremely high demand for heme for hemoglobin synthesis. While the enzymatic reactions of heme synthesis are extremely well studied, the mechanisms by which the mitochondrial homeostatic machinery interacts with and regulates heme synthesis are poorly understood. Knowledge of these regulatory mechanisms are key to understanding how red cells couple heme production with heme demand. Heme synthesis is tightly regulated by the mitochondrial AAA+ unfoldase CLPX, which has been reported to promote heme synthesis by activation of yeast δ-aminolevulinate synthase (ALAS/Hem1). CLPX was also reported to mediate heme-induced turnover of ALAS1 in human cells. However, a mutation in the ATP binding domain of CLPX that abrogated ATP binding caused an increase in ALAS activity, contrary to previous predictions that CLPX activated ALAS. Using loss-of-function assays in murine cells and zebrafish, we interrogated the mechanisms by which CLPX regulates erythroid heme synthesis. We found that consistent with previous studies, CLPX is required for erythroid heme synthesis. We show that ALAS2 stability and activity were both increased in the absence of CLPX, suggesting that CLPX primarily regulates ALAS2 by control of its turnover. However, we also showed that CLPX is required for PPOX activity and maintenance of FECH levels, likely accounting for the heme deficiency in the absence of CLPX. Lastly, CLPX is required for iron metabolism during erythroid terminal differentiation. Our results show that the role of CLPX in heme synthesis is not conserved across eukaryotes. Our studies reveal a potential mechanism for the role of CLPX in anemia and porphyria, and reveal multiple nodes at which heme synthesis is regulated by the mitochondrial housekeeping machinery.
Does offspring demand affect parental life-history trade-offs?

Life-history trade-offs between the number and size of offspring produced, and the costs of reproduction on future reproduction and survival can all be affected by different levels of parental effort. Because of these trade-offs the parents and the offspring have different optima for the amount of care given to the current brood, which leads to a conflict between parents and offspring. The offspring, as well as the parents, have the ability to affect parental effort, and thus changes in offspring traits have the potential to cause reproductive costs on the parents. Here, we used a repeated cross-fostering design to manipulate offspring demand during juvenile development in the burying beetle Nicrophorus vespilloides to examine whether responding to offspring begging incurs reproductive costs to the parent. After a manipulated first reproductive event, we gave each experimental female, that had been exposed to different levels of offspring demand, a chance to breed again, and monitored their survival. We found that larval demand influences the trade-off between the size and number of offspring produced, but has no impact on the reproductive costs through future reproduction or survival of the parent. The parents do, however, pay an overall fecundity cost for the general success of their first broods, but this cost was not related to the changes in the levels of larval begging. Other traits, including survival showed no costs of reproduction. Survival and the number of larvae successfully raised in the second broods correlated positively, indicating differences in the individual quality of the parents.
Topological Segmentation of Time-Varying Functional Connectivity Highlights the Role of Preferred Cortical Circuits

Functional connectivity (FC) and its time-varying analogue (TVFC) leverage brain imaging data to interpret brain function as patterns of coordinating activity among brain regions. While many questions remain regarding the organizing principles through which brain function emerges from multi-regional interactions, advances in the mathematics of Topological Data Analysis (TDA) may provide new insights into the brain’s spontaneous self-organization. One tool from TDA, “persistent homology”, observes the occurrence and the persistence of n-dimensional holes presented in the metric space over a dataset. The occurrence of n-dimensional holes within the TVFC point cloud may denote conserved and preferred routes of information flow among brain regions. In the present study, we compare the use of persistence homology versus more traditional TVFC metrics at the task of segmenting brain states that differ across a common time-series of experimental conditions. We find that the structures identified by persistence homology more accurately segment the stimuli, more accurately segment volunteer performance during experimentally defined tasks, and generalize better across volunteers. Finally, we present empirical and theoretical observations that interpret brain function as a topological space defined by cyclic and interlinked motifs among distributed brain regions, especially, the attention networks.
A Customizable Low-Cost System for Massively Parallel Zebrafish Behavioral Phenotyping

High-throughput behavioral phenotyping is critical to genetic or chemical screening approaches. Zebrafish larvae are amenable to high-throughput behavioral screening because of their rapid development, small size, and conserved vertebrate brain architecture. Existing commercial behavior phenotyping systems are expensive and not easily modified for new assays. Here, we describe a modular, highly adaptable, and low-cost behavior system. Along with detailed assembly and operation instructions, we provide data acquisition software and a robust, parallel analysis pipeline. We validate our approach by analyzing stimulus response profiles in larval zebrafish, confirming prepulse inhibition phenotypes of two previously isolated mutants, and highlighting best practices for growing larvae prior to behavioral testing. Our new design thus allows rapid construction and streamlined operation of many large-scale behavioral setups with minimal resources and fabrication expertise, with broad applications to other aquatic organisms.
Cachexia is associated with depression, anxiety and quality of life in cancer patients

Objectives This study aimed to compare depression, anxiety and quality of life (QoL) between cachexia and non-cachexia patients, and explore the relationship between cachexia and depression, anxiety and QoL in patients with cancer. Methods A total of 528 patients from cancer centres of four hospitals were enrolled in this cross-sectional study. All patients were divided into cachexia and non-cachexia according to international consensus definition of cachexia. Patient Health Questionnaire-9 (PHQ-9), Generalized Anxiety Disorder-7 (GAD-7) and Quality of Life Questionnaire-Cancer 30 (QLQ-C30) were used to evaluate depression, anxiety and QoL. Results 285 patients (53.98%) were classified as cachexia. The prevalence of depression, anxiety, severe depression and severe anxiety in cachexia was 30.2%, 18.6%, 6.7% and 8.4%, respectively, which were significantly higher than in non-cachexia (all p<0.01). Patients with cachexia obviously acquired poorer physical function (PF), role function (RF), cognitive function (CF), emotional function (EF), social function (SF) and overall QoL than non-cachexia patients (all p<0.01). Cachexia was positively associated with depression (unstandardised coefficient (B)=2.123, p<0.001) and anxiety (B=1.123, p=0.024), and had a negative relationship with PF, CF, EF, SF and overall QoL (all B<0, all p<0.05). Conclusions Cachexia was associated with greater depression and anxiety and poorer QoL in patients with cancer, which emphasised the importance of timely identification and management of cachexia to improve the psychological problems and QoL among patients with cancer.
EEG Source Identification through Phase Space Reconstruction and Complex Networks

Artifact elimination has become an inseparable part while processing electroencephalogram (EEG) in most brain computer interface (BCI) applications. Scientists have tried to introduce effective and efficient methods which can remove artifacts and also reserve desire information pertaining to brain activity. Blind source separation (BSS) methods have been receiving a great deal of attention in recent decades since they are considered routine and standard signal processing tools and are commonly used to eliminate artifacts and noise. Most studies, mainly EEG-related ones, apply BSS methods in preprocessing sections to achieve better results. On the other hand, BSS methods should be followed by a classifier in order to identify artifactual sources and remove them in next steps. Therefore, artifact identification is always a challenging problem while employing BSS methods. Additionally, removing all detected artifactual components leads to loss of information since some desire information related to neural activity leaks to these sources. So, an approach should be employed to suppress the artifacts and reserve neural activity. In this study, a new hybrid method is proposed to automatically separate and identify electroencephalogram (EEG) sources with the aim of classifying and removing artifacts. Automated source identification is still a challenge. Researchers have always made efforts to propose precise, fast and automated source verification methods. Reliable source identification has always been of great importance. This paper addresses blind source separation based on second order blind identification (SOBI) as it is reportedly one of the most effective methods in EEG source separation problems. Then a new method for source verification is introduced which takes advantage of components phase spaces and their dynamics. A new state space called angle space (AS) is introduced and features are extracted based on the angle plot (AP) and Poincare planes. Identified artifactual sources are eliminated using stationary wavelet transform (SWT). Simulated, semi-simulated and real EEG signals are employed to evaluate the proposed method. Different simulations are performed and performance indices are reported. Results show that the proposed method outperforms most recent studies in this subject.
Phase separation of tunable biomolecular condensates predicted by an interacting particle model

Phase separation is emerging as key principle in the spatiotemporal organization of living cells. Given its relevance in the regulation of numerous biological functions, including gene transcription and chromatin architecture, modeling biomolecular condensation is gaining interest. Yet, most models developed so far rely on specific descriptions and/or experimentally inaccessible properties. Here we propose a theoretical model, where phase separation is explained by means of interaction probabilities between particles. With minimum model requirements, particle condensates emerge above a critical interaction probability. We tested the model predictions with single molecule experiments of tunable transcription factor condensates in the nucleus of living cells. Phase separation, condensate sizes, diffusion behavior, and mobility parameters, quantified by data analysis and machine learning, are fully recapitulated by our model. Our combined theoretical and experimental approach provides a general framework to investigate the biophysical parameters controlling phase separation in living cells and in other soft matter-based interacting systems.
Adaptability and evolution of the cell polarization machinery in budding yeast

How can a self-organized cellular function evolve, adapt to perturbations, and acquire new sub-functions? To make progress in answering these basic questions of evolutionary cell biology, we analyze, as a concrete example, the cell polarity machinery of Saccharomyces cerevisiae. This cellular module exhibits an intriguing resilience: it remains operational under genetic perturbations and recovers quickly and reproducibly from the deletion of one of its key components. Using a combination of modeling, conceptual theory, and experiments, we show that multiple, redundant self-organization mechanisms coexist within the protein network underlying cell polarization and are responsible for the module’s resilience and adaptability. Based on our mechanistic understanding of polarity establishment, we hypothesize how scaffold proteins, by introducing new connections in the existing network, can increase the redundancy of mechanisms and thus increase the evolvability of other network components. Moreover, our work suggests how a complex, redundant cellular module could have evolved from a more rudimental ancestral form.
Seroprevalence and Correlates of SARS-CoV-2 Antibodies in Health Care Workers in Chicago

Background: Identifying factors associated with SARS-CoV-2 infection among healthcare workers (HCW)s may help health systems optimize SARS-CoV-2 infection control strategies. Methods: We conducted a cross-sectional analysis of baseline data from the Northwestern HCW SARS-CoV-2 Serology Cohort Study. The Abbott Architect Nucleocapsid IgG assay was used to determine seropositivity. Logistic regression models (unadjusted and adjusted for demographics and self-reported community exposure to COVID-19) were fit to quantify the associations between occupation group, healthcare delivery tasks, and community exposure and seropositive status. Results: 6,510 HCWs, including 1,794 nurses, and 904 non-patient facing administrators participated. The majority were women (79.6%), 74.9% were white, 9.7% were Asian, 7.3% were Hispanic and 3.1% were Black. The crude prevalence rate of seropositivity was 4.8% (95% confidence interval (CI): 4.6%-5.2%). Out-of-hospital exposure to COVID-19 occurred in 9.3% of HCWs and was strongly associated with seropositivity (OR=4.7, 95% CI: 3.5-6.4). When compared to administrators, nursing was the only occupation group with a significantly higher adjusted-odds (OR: 1.9, 95% CI: 1.3-2.9) of seropositivity. Exposure to COVID-19 patients was reported by 37.8% of participants and was associated with higher positivity than those not exposed (OR= 2.2, 95% CI: 1.6-3.0). Being exposed to patients receiving high-flow oxygen therapy, and hemodialysis also remained significantly associated with a 45% and 57% higher odds for seropositive status, respectively. Conclusions: Exposure to COVID-19 patients, and longer duration patient therapies were each associated with higher risk for seropositive status; however, the community burden of COVID-19 remains a significant source of exposure to SARS CoV-2 infection among HCWs in Chicago.
Diversity, phylogeny, and DNA barcoding of brachyuran crabs in mangrove environments created artificially

Globally, mangrove coverings are disappearing at the rate of 1–2% per annum and 35% have been lost in the last 20 years. Changes in climate and human activities are affecting the mangrove habitats significantly. When the mangroves were transplanted artificially 25 years ago in the Vellar estuary, no mangrove-associated crabs were found. We sampled this mangrove ecosystem and intent to estimate the diversity, species abundance, composition and phylogenetic relationships of barchyuran crabs. We also intend to evaluate the efficacy of DNA barcoding technique in precisely identifying species of brachyuran crab associated with mangroves. Mangrove species such as, Avicennia marina, A. officinalis, Rhizophora apiculata, R. mucronata and R. annamalayana, Acanthus ilicifolius and salt marshes; Suaeda maritima and Prosopis juliflora constituted the artificially created mangrove ecosystem. A total of 2844 crabs were collected, representing 35 species belonging to 20 genera within 8 families. The four species of brachyuran crab, that is, Uca lactae, U. triangularis, Selatium brockii, and Neosarmatium asiaticum contribute >70% of total abundances. The present study recovered an estimated 87.5% of crab species. The maximum association index value (97.7%) was observed between Uca lactea and Uca triangularis. Cluster analysis, grouped the sampled stations according to the type of mangrove species present. It was clear that the type of mangrove species influences brachyuran crabs’ structure and species composition. Clustering analysis also clearly distinguished the mangrove stations and salt-marsh station (control) based on the composition of the brachyuran crab species. In general, the abundances of all collected species of crabs, and particularly Neosarmatium asiaticum, prefers vegetative cover composed of multiple species of mangroves. DNA barcoding analysis shows that 40% of the species collected in this study was barcoded for the first time. In near future, the advent of new high-throughput sequencing technologies will dramatically change bio-monitoring applications and surveys. This will make reference datasets such as ours important. Using the array of diversity and species estimator indices we presented useful data on brachyuran crab diversity associated with artificially created mangrove ecosystem, which will be useful for marine policy makers, coastal ecosystem designers and climate researchers.
The Temporal Dynamics of Opportunity Costs: A Normative Account of Cognitive Fatigue and Boredom

Cognitive fatigue and boredom are two phenomenological states widely associated with limitations in cognitive control. In this paper, we present a rational analysis of the temporal structure of controlled behavior, which provides a new framework for providing a formal account of these phenomena. We suggest that in controlling behavior, the brain faces competing behavioral and computational imperatives, and must balance them by tracking their opportunity costs over time. We use this analysis to flesh out previous suggestions that feelings associated with subjective effort, like cognitive fatigue and boredom, are the phenomenological counterparts of these opportunity cost measures, rather then reflecting the depletion of resources as has often been assumed. Specifically, we propose that both fatigue and boredom reflect the competing value of particular options that require foregoing immediate reward but can improve future performance: Fatigue reflects the value of offline computation (internal to the organism) to improve future decisions, while boredom signals the value of exploratory actions (external in the world) to gather information. We demonstrate that these accounts provide a mechanistically explicit and parsimonious account for a wide array of findings related to cognitive control, integrating and reimagining them under a single, formally rigorous framework.
Characterization of SOX2, OCT4 and NANOG in Ovarian Cancer Tumor-Initiating Cells

Identification of tumor initiating cells (TICs) has traditionally relied on expression of surface markers such as CD133, CD44, and CD117 and enzymes such as aldehyde dehydrogenase (ALDH). Unfortunately, these markers are often cell type specific and not reproducible across patient samples. A more reliable indication of TICs may include elevated expression of stem cell transcription factors such as SOX2, OCT4, and NANOG that function to support long-term self-renewal, multipotency, and quiescence. RNA-sequencing studies presented here highlight a potential role for SOX2 in cell cycle progression in cells grown as 3-D spheroids, which are more tumorigenic and contain higher numbers of TICs than their 2-D monolayer cultured counterparts. SOX2, OCT4, and NANOG have not been comprehensively evaluated in ovarian cancer cell lines, although their expression is often associated with tumorigenic cells. We hypothesize that SOX2, OCT4, and NANOG will be enriched in ovarian TICs and will correlate with chemotherapy resistance, tumor initiation, and expression of traditional TIC markers. To investigate this hypothesis, we evaluated SOX2, OCT4, and NANOG in a panel of eight ovarian cancer cell lines grown as a monolayer in standard 2-D culture or as spheroids in TIC-enriching 3-D culture. Our data show that the high-grade serous ovarian cancer (HGSOC) lines CAOV3, CAOV4, OVCAR4, and OVCAR8 had longer doubling-times, greater resistance to chemotherapies, and significantly increased expression of SOX2, OCT4, and NANOG in TIC-enriching 3-D culture conditions. We also found that in vitro chemotherapy treatment enriches for cells with significantly higher expression of SOX2. We further show that the traditional TIC marker, CD117 identifies ovarian cancer cells with enhanced SOX2, OCT4, and NANOG expression. Tumor-initiation studies and analysis of The Cancer Genome Atlas (TCGA) suggest a stronger role for SOX2 in ovarian cancer relapse compared with OCT4 or NANOG. Overall, our study clarifies the expression of SOX2, OCT4, and NANOG in TICs from a variety of ovarian cancer cell lines. Our findings suggest that SOX2 expression is a stronger indicator of ovarian TICs with enhanced tumor-initiation capacity and potential for relapse. Improved identification of ovarian TICs will advance our understanding of TIC biology and facilitate the design of better therapies to eliminate TICs and overcome chemotherapy resistance and disease relapse.
Evidence for conformational change-induced hydrolysis of β-tubulin-GTP

Microtubules, protein polymers of α/β-tubulin dimers, form the structural framework for many essential cellular processes including cell shape formation, intracellular transport, and segregation of chromosomes during cell division. It is known that tubulin-GTP hydrolysis is closely associated with microtubule polymerization dynamics. However, the precise roles of GTP hydrolysis in tubulin polymerization and microtubule depolymerization, and how it is initiated are still not clearly defined. We report here that tubulin-GTP hydrolysis can be triggered by conformational change induced by the depolymerizing kinesin-13 proteins or by the stabilizing chemical agent paclitaxel. We provide biochemical evidence that conformational change precedes tubulin-GTP hydrolysis, confirming this process is mechanically driven and structurally directional. Furthermore, we quantitatively measure the average size of the presumptive stabilizing “GTP cap” at growing microtubule ends. Together, our findings provide the molecular basis for tubulin-GTP hydrolysis and its role in microtubule polymerization and depolymerization.