Miracle-dz/UniFAR-FTUs huggingface dataset:
Disturbance increases functional diversity but decreases phylogenetic diversity of an arboreal tropical ant community

Tropical rainforest canopies host a highly diverse arthropod fauna, which contribute to ecosystem function through their functional (FD) and phylogenetic diversity (PD). While a lot of previous research has documented the severe negative impacts of disturbance on the FD and PD of ground invertebrate communities, our understanding of arboreal counterparts is limited. Here, we studied the effects of forest disturbance on an ecologically important invertebrate group, the ants, in a lowland rainforest in New Guinea. We exhaustively sampled 4000 m2 area of a primary and a secondary forest for canopy ants. We report > 2800 occurrences of 128 ant species in 852 trees, one of the most comprehensive arboreal collections to date. To test how ant PD and FD differ between the two forests, we constructed the ant species-level community phylogeny and measured 10 functional traits. Furthermore, we assessed by data exclusion the influence of species which were not nesting in individual trees (visitors) or only nesting (nesters), and of non-native species on FD and PD values. We expected that disturbance would decrease FD and PD in tree dwelling ants. We hypothesized that traits in primary forests would be more overdispersed due to the greater availability of ecological niches, while secondary forests would have stronger trait clustering due to a a stronger habitat filtering caused by more extreme microclimate. Primary forests had higher species richness and PD than secondary forest. Surprisingly, we found higher FD in secondary forest. This pattern was robust even if we decoupled functional and phylogenetic signals or if non-native ant species were excluded from the data. Visitors did not contribute strongly to FD, but they increased PD. Community trait means further corroborate the functional distinctiveness of arboreal ants among secondary and primary forest, with almost all traits being impacted by disturbance and forest succession. We conclude that the most plausible explanation is increased competition among closely related ant species in the secondary forest, which drives trait divergence. In the primary forest, abiotic habitat filters leads to more similar morphology and thus lower FD of phylogenetically more diverse ant assemblages.
PhenoCellPy: A Python package for biological cell behavior modeling

PhysiCell, a mechanistic center-based agent-based modeling framework, describes sequences of cell behaviors in a very elegant way with its phenotype submodel. However, its phenotypes are not usable in other frameworks, and the creation of a new phenotype is not straight forward. PhenoCellPy is an open-source Python package that implements PhysiCell’s phenotypes and their methods in a general way, that is easily extended and embedded into other python-based models. PhenoCellPy defines methods for modeling sequences of cell behaviors and states (e.g., the cell cycle, or the Phases of cellular necrosis). PhenoCellPy defines Python classes for the Cell Volume (which it subdivides between the cytoplasm and nucleus) and its evolution, the state of the cell and the behaviors the cell displays in each state (called the Phase), and the sequence of behaviors (called the Phenotype). PhenoCellPy’s can extend existing modeling frameworks as an embedded model. It integrates with the frameworks by defining the cell states (phases), signaling when a state change occurs, if division occurs, and by receiving information from the framework (e.g., how much interferon the cell is exposed to). PhenoCellPy can function with any python-based modeling framework that supports Python 3, NumPy and SciPy.
Stochastic characterization of navigation strategies in an automated variant of the Barnes maze

Animals can use a repertoire of strategies to navigate in an environment, and it remains an intriguing question how these strategies are selected based on the nature and familiarity of environments. To investigate this question, we developed a fully automated variant of the Barnes maze, characterized by 24 vestibules distributed along the periphery of a circular arena, and monitored the trajectories of mice over 15 days as they learned to navigate from a random start vestibule to a goal vestibule. We show that the patterns of vestibule visits can be reproduced by the combination of three stochastic processes reminiscent of random, serial and spatial strategies. The processes randomly selected vestibules based on either uniform (random) or biased (serial and spatial) probability distributions; closely matched experimental data across a range of statistical distributions characterizing the length, distribution, step size, direction, and stereotypy of vestibule sequences; and revealed a shift from random to spatial and serial strategies over time, with a strategy switch occurring approximately every 6 vestibule visits. Our study provides a novel apparatus and analysis toolset for tracking the repertoire of navigation strategies and demonstrates that a set of stochastic processes can largely account for exploration patterns in the Barnes maze.
Event-Induced Modulation of Aperiodic Background EEG: Attention-Dependent and Age-Related Shifts in E:I balance, and Their Consequences for Behavior

The broadband shape of the EEG spectrum, summarized using a 1/fx function, is thought to reflect the balance between excitation and inhibition in cortical regions (E:I balance). This balance is an important characteristic of neural circuits and could inform studies of aging, as older adults show a relative inhibitory activity deficit. Thus far, no studies have leveraged the event-related temporal dynamics of 1/fx activity to better understand the phases of information processing, especially in the context of aging. Here, for the first time, we examined variations of this activity during the foreperiod of a cued flanker task in younger (YA) and older adults (OA), with picture cues varying in task relevance, relative novelty, and valence. We report a biphasic change in the spectral exponent (corresponding to negative slopes in log-log space) after cue presentation, independent of cue-elicited ERPs, with an initial period of increased negativity (indicating cortical inhibition, similar in YA and OA) followed by decreased negativity (indicating cortical excitation, especially in OA). The decrease in the exponent negativity was associated with lower performance and greater congruency costs in the flanker task. Finally, more novel cues reduced the shift towards excitation in OA, partly restoring their E:I balance, and diminishing congruency costs. These findings demonstrate that the broadband shape of the EEG spectrum varies dynamically in a manner that is predictive of subsequent behavior. They also expand our understanding of how neural communication shapes cognition in YA and OA and have implications for neuroscientific models of cognitive processing and age-related cognitive decline.
Comparative gene expression analysis of differentiated terminal and lateral haustoria of the obligate root parasitic plant Phelipanche ramosa (Orobanchaceae)

Branched broomrape (Phelipanche ramosa, Orobanchaceae) is the most important parasitic weed of oilseed and vegetable crops in Europe. Deciphering the parasite’s basic biology and genetics underpinning adaptations to parasitism are essential for effective weed management. Here, we compared the gene expression profiles of differentiated terminal haustoria, formed immediately after the germination of P. ramosa with those of the parasite’s adventitious roots and lateral haustoria, which develop on the latter as it grows. Principal component analysis and functional annotation of differentially expressed genes indicate a greater transcriptional similarity between adventitious roots and lateral haustoria compared to terminal haustoria. Genes involved in hydrogen peroxide catabolic processes and mucilage metabolic processes were more abundant in lateral haustoria compared to adventitious roots, indicating that secondary host attachment involves secretion of adhesive compounds, cell wall modification, and a termination of the developmental program associated with root growth. In terminal haustoria, phytohormonal signaling pathways for post-germination growth and meristem development were the most prominent expression profile difference to lateral haustoria. Besides this, wide similarity of expressed genes between lateral and terminal haustoria suggest overlapping pathways underlying haustorium differentiation and a conserved functional relevance of both haustoria types at maturity. Together, our study provides first insights into the transcriptional landscapes of the primary organs securing P.ramosa’s nutritional success. However, more research is needed to investigate whether the parasite’s various haustorium types differ in their sensitivities to environmental stimuli and whether transcriptional divergence in terminal and lateral haustoria of P. ramosa reflect differences regarding their developmental origin.
Honeybee flight dynamics and pair separation in windy conditions near the hive entrance

Animals and living organisms are continuously adapting to changes in their environment. How do animals, especially those that are critical to their ecosystem, respond to rapidly changing conditions in their environment? Here, we report on the three-dimensional trajectories of flying honeybees under calm and windy conditions in front of the hive entrance. We also investigate the pitch and yaw in our experiments. We find that the mean velocities, accelerations and angular velocities of honeybees increase with increasing wind speeds. We observed that pair separation between honeybees is highly controlled and independent of wind speeds. Our results on the coordination used by honeybees may have potential applications for coordinated flight of unmanned aerial vehicles.
Recursive self-embedded vocal motifs in wild orangutans

Recursive procedures that allow placing a vocal signal inside another of similar kind provide a neuro-computational blueprint for syntax and phonology in spoken language and human song. There are, however, no known vocal sequences among nonhuman primates arranged in self-embedded patterns that evince vocal recursion or potential insipient or evolutionary transitional forms thereof, suggesting a neuro-cognitive transformation exclusive to humans. Here, we uncover that wild flanged male orangutan long calls feature rhythmically isochronous call sequences nested within isochronous call sequences, consistent with two hierarchical strata. Remarkably, three temporally and acoustically distinct call rhythms in the lower stratum were not related to the overarching rhythm at the higher stratum by any low multiples, which suggests that these recursive structures were neither the result of parallel non-hierarchical procedures or anatomical artifacts of bodily constrains or resonances. Findings represent a case of temporally recursive hominid vocal combinatorics in the absence syntax, semantics, phonology or music. Second-order combinatorics, ‘sequences within sequences’, involving hierarchically organized and cyclically structured vocal sounds in ancient hominids may have preluded the evolution of recursion in modern language-able humans.
Efficient Fisher Information Computation and Policy Search in Sampled Stochastic Chemical Reaction Networks through Deep Learning

Markov jump processes constitute the central class of Chemical Reaction Network models used to account for the intrinsic stochasticity observed in the dynamics of molecular species abundance throughout Molecular Biology. These models are specified in a parametric form, and their identification requires the use of inference procedures, and in particular the estimation of the Fisher Information. Here, a fast and accurate computation method is introduced in the case of partial observations at discrete time points, based on the use of a Mixture Density Network. We also demonstrate how this Neural Network can be used to perform fast policy search. The efficiency of these approaches is illustrated on a set of examples, and is compared to that of the current state-of-the-art.
Paired yeast one-hybrid assays to detect DNA-binding cooperativity and antagonism across transcription factors

Cooperativity and antagonism between transcription factors (TFs) can drastically modify their binding to regulatory DNA elements. While mapping these relationships between TFs is important for understanding their context-specific functions, existing approaches either rely on DNA binding motif predictions, interrogate one TF at a time, or study individual TFs in parallel. Here, we introduce paired yeast one-hybrid (pY1H) assays to detect cooperativity and antagonism across hundreds of TF-pairs at DNA regions of interest. We provide evidence that a wide variety of TFs are subject to modulation by other TFs in a DNA sequence-specific manner. We also demonstrate that TF-TF relationships are often affected by alternative isoform usage, and identify cooperativity and antagonism between human TFs and viral proteins. pY1H assays provide a broadly applicable framework to study how different functional relationships affect protein occupancy at regulatory DNA regions.
Exact confidence intervals for population growth rate, longevity and generation time

By quantifying key life history parameters in populations, such as growth rate, longevity, and generation time, researchers and administrators can obtain valuable insights into its dynamics. Although point estimates of demographic parameters have been available since the inception of demography as a scientific discipline, the construction of confidence intervals has typically relied on approximations through series expansions or computationally intensive techniques. This study introduces the first mathematical expression for calculating confidence intervals for the aforementioned life history traits when individuals are unidentifiable and data are presented as a life table. The key finding is the accurate estimation of the confidence interval for r, the instantaneous growth rate, which is tested using Monte Carlo simulations with four arbitrary discrete distributions. In comparison to the bootstrap method, the proposed interval construction method proves more efficient, particularly for experiments with a total offspring size below 400. We discuss handling cases where data are organized in extended life tables or as a matrix of vital rates.
Development of an integrated cardiac rehabilitation program to improve the adaptation level of patients after acute myocardial infarction

Background Individual’s adaptation following acute myocardial infarction (AMI) and low attendance of whole-course cardiac rehabilitation (CR) are significant issues. For optimal health post AMI, an integrated CR program aiming at individual’s adaptive behaviors is imperative for improving the CR efficiency and patients’ outcomes. This study aims to develop theory-guided interventions to increase CR attendance and adaptation level of patients post-AMI. Methods This study was conducted in a tertiary hospital from July 2021 to September 2022 in Shanghai China. Guided by the theory of adaptation to chronic illness (ACI theory), the study followed the Intervention mapping (IM) framework to develop the interventions for CR program. Four phases included: (1) needs assessment of patients and facilitators using a cross-sectional study and semi-structured, in-depth interviews, (2) identification of implementation outcomes and performance objectives, (3) selection of theoretical methods to explain the mechanism of patients’ adaptive behaviors and to use for behavior change, and (4) development of implementation protocol from the results of the previous phases. Results A total of 226 AMI patient-caregivers paired samples were eligible for the data analysis, 30 AMI patients participated in the qualitative inquiry, 16 experts in the CR field evaluated the implementation protocol, and 8 AMI patients commented on the practical interventions. Following the IM framework, an integrated cardiac rehabilitation program using mHealth strategies was developed for AMI patients to facilitate CR attendance and completion, to improve their adaptation level and health outcomes. Conclusion Using the IM framework and ACI theory, an integrated CR program was developed to help guide the behavior change and improve adaptation among AMI patients. The preliminary findings suggest that further intervention in enhancing the combination of three-stage CR is required. A feasibility study will be conducted to assess the acceptability and effectiveness of this generated CR intervention.
Differential gene expression patterns between the head and thorax of Gynaephora aureata are associated with high-altitude adaptation

Grassland caterpillars (Lepidoptera: Erebidae: Gynaephora) are important pests in alpine meadows of the Qinghai-Tibetan Plateau (QTP). These pests have morphological, behavioral, and genetic adaptations for survival in high-altitude environments. However, mechanisms underlying high-altitude adaptation in QTP Gynaephora species remain largely unknown. Here, we performed a comparative analysis of the head and thorax transcriptomes of G. aureata to explore the genetic basis of high-altitude adaptation. We detected 8,736 significantly differentially expressed genes (sDEGs) between the head and thorax, including genes related to carbohydrate metabolism, lipid metabolism, epidermal proteins, and detoxification. These sDEGs were significantly enriched in 312 Gene Ontology terms and 16 KEGG pathways. We identified 73 pigment-associated genes, including 8 rhodopsin-associated genes, 19 ommochrome-associated genes, 1 pteridine-associated gene, 37 melanin-associated genes, and 12 heme-associated genes. These pigment-associated genes were related to the formation of the red head and black thorax of G. aureata. A key gene, yellow-h, in the melanin pathway was significantly upregulated in the thorax, suggesting that it is related to the formation of the black body and contributed to the adaptation of G. aureata to low temperatures and high ultraviolet radiation in the QTP. Another key gene, cardinal, in the ommochrome pathway was significantly upregulated in the head and may be related to red warning color formation. We also identified 107 olfactory-related genes in G. aureata, including genes encoding 29 odorant-binding proteins, 16 chemosensory proteins, 22 odorant receptor proteins, 14 ionotropic receptors, 12 gustatory receptors, 12 odorant degrading enzymes, and 2 sensory neuron membrane proteins. Diversification of olfactory-related genes may be associated with the feeding habits of G. aureata, including larvae dispersal and searching for plant resources available in the QTP. These results provide new insights into high-altitude adaptation of Gynaephora in the QTP and may contribute to the development of new control strategies for these pests.
The predictive role of impulsivity and perceived social support in psychiatric symptoms of women with methamphetamine use disorder

Background Currently, few studies have examined the mental states of Women methamphetamine patients, and the influence of impulsivity and perceived social support on substance misuse-induced mental disorders is unclear. We want to examine the mental state of women with methamphetamine use disorder and compare it to the Chinese norm value of healthy women. Investigate the connection between impulsivity, perceived social support and mental state of women with methamphetamine use disorder. Method Two hundred thirty women subjects with a history of methamphetamine usage were recruited. The Chinese version of the SCL-90-R, (SCL-90) was used to evaluate psychological health problems, while the Multidimensional Scale of Perceived Social Support (MSPSS) and Barratt Impulsiveness Seale-11 (BIS-11) were utilized to evaluate perceived social support and impulsivity, respectively. The t-test, Pearson correlation analysis, multivariable linear regression, stepwise regression models, moderating effect analysis were used to analyze the statistics. Results There was a noticeable difference between the Chinese norm and all participants’ SCL-90 ratings, especially for Somatization (t = 24.34, p < 0.001), Anxiety (t = 22.23, p < 0.001), Phobic anxiety (t = 26.47, p < 0.001), and Psychoticism (t = 24.27, p < 0.001). In addition, perceived social support levels and impulsivity levels are independently predictive of SCL-90 scores. Lastly, the impact of Impulsivity on SCL-90 can be modulated by perceived social support. Conclusion According to this study, women with methamphetamine use disorder have worse mental health conditions compared to healthy subjects. Furthermore, certain psychological symptoms associated with methamphetamine use in women can be aggravated by impulsivity, while perceived social support acts as a protective factor for methamphetamine-related psychiatric symptoms. Specifically, perceived social support weakens the impact of impulsivity on psychiatric symptoms in women with methamphetamine use disorder.
Overlapped tobacco shred image segmentation and area computation using an improved Mask RCNN network and COT algorithm

Introduction The classification of the four tobacco shred varieties, tobacco silk, cut stem, expanded tobacco silk, and reconstituted tobacco shred, and the subsequent determination of tobacco shred components, are the primary tasks involved in calculating the tobacco shred blending ratio. The identification accuracy and subsequent component area calculation error directly affect the composition determination and quality of the tobacco shred. However, tiny tobacco shreds have complex physical and morphological characteristics; in particular, there is substantial similarity between the expanded tobacco silk and tobacco silk varieties, and this complicates their classification. There must be a certain amount of overlap and stacking in the distribution of tobacco shreds on the actual tobacco quality inspection line. There are 24 types of overlap alone, not to mention the stacking phenomenon. Self-winding does not make it easier to distinguish such varieties from the overlapped types, posing significant difficulties for machine vision-based tobacco shred classification and component area calculation tasks. Methods This study focuses on two significant challenges associated with identifying various types of overlapping tobacco shreds and acquiring overlapping regions to calculate overlapping areas. It develops a new segmentation model for tobacco shred images based on an improved Mask region-based convolutional neural network (RCNN). Mask RCNN is used as the segmentation network’s mainframe. Convolutional network and feature pyramid network (FPN) in the backbone are replaced with Densenet121 and U-FPN, respectively. The size and aspect ratios of anchors parameters in region proposal network (RPN) are optimized. An algorithm for the area calculation of the overlapped tobacco shred region (COT) is also proposed, which is applied to overlapped tobacco shred mask images to obtain overlapped regions and calculate the overlapped area. Results The experimental results showed that the final segmentation accuracy and recall rates are 89.1% and 73.2%, respectively. The average area detection rate of 24 overlapped tobacco shred samples increases from 81.2% to 90%, achieving high segmentation accuracy and overlapped area calculation accuracy. Discussion This study provides a new implementation method for the type identification and component area calculation of overlapped tobacco shreds and a new approach for other similar overlapped image segmentation tasks.