Miracle-dz/UniFAR-FTUs huggingface dataset:
Dynamic Modeling of CHO Cell Metabolism Using the Hybrid Cybernetic Approach With a Novel Elementary Mode Analysis Strategy

Chinese hamster ovary (CHO) cell culture has a major importance on the production of biopharmaceuticals, including recombinant therapeutic proteins such as monoclonal antibodies (MAb). Mathematical modeling of biological systems can successfully assess metabolism complexity while providing logical and systematic methods for relevant genetic target and culture parameter identification toward cell growth and productivity improvements. Most modeling approaches on CHO cells have been performed under stationary constraints, and only a few dynamic models have been presented on simplified reaction sets, due to substantial overparameterization problems. The hybrid cybernetic modeling (HCM) approach has been recently used to describe the dynamic behavior by incorporating regulation between different metabolic states by elementary mode participation control, with sets of equations evaluated by objective functions. However, as metabolic networks evaluated are constructed toward a genomic scale, and cell compartmentalization is considered, identification of the active set becomes more difficult as EM number exponentially grows. Thus, the development of robust approaches for EM active set selection and analysis with smaller computational requirements is required to impulse the use of cybernetic modeling on larger up to genome-scale networks. In this report, a novel elementary mode selection strategy, based on a polar representation of the convex solution space is presented and coupled to a cybernetic approach to model the dynamic physiologic and metabolic behavior of CHO-S cell cultures. The proposed Polar Space Yield Analysis (PSYA) was compared to other reported elementary mode selection approaches derived from Common Metabolic Objective Analysis (CMOA) used in Flux Balance Analysis (FBA), Yield Space Analysis (YSA), and Lumped Yield Space Analysis (LYSA). For this purpose, exponential growth phase dynamic metabolic models were calculated using kinetic rate equations based on previously modeled growth parameters. Finally, complete culture dynamic metabolic flux models were constructed using the HCM approach with selected elementary mode sets. The yield space elementary mode- and the polar space elementary mode- hybrid cybernetic models presented the best fits and performances. Also, a flux reaction perturbation prediction approach based on the polar yield solution space resulted useful for metabolic network flux distribution capability analysis and identification of potential genetic modifications targets.
Effect of Auditory Predictability on the Human Peripheral Auditory System

Auditory perception is facilitated by prior knowledge about the statistics of the acoustic environment. Predictions about upcoming auditory stimuli are processed at various stages along the human auditory pathway, including the cortex and midbrain. Whether such auditory predictions are processed also at hierarchically lower stages—in the peripheral auditory system—is unclear. To address this question, we assessed outer hair cell (OHC) activity in response to isochronous tone sequences and varied the predictability and behavioral relevance of the individual tones (by manipulating tone-to-tone probabilities and the human participants’ task, respectively). We found that predictability alters the amplitude of distortion-product otoacoustic emissions (DPOAEs, a measure of OHC activity) in a manner that depends on the behavioral relevance of the tones. Simultaneously recorded cortical responses showed a significant effect of both predictability and behavioral relevance of the tones, indicating that their experimental manipulations were effective in central auditory processing stages. Our results provide evidence for a top-down effect on the processing of auditory predictability in the human peripheral auditory system, in line with previous studies showing peripheral effects of auditory attention.
Editorial: Spiking Neural Network Learning, Benchmarking, Programming and Executing

Department of Precision Instrument, Center for Brain Inspired Computing Research, Tsinghua University, Beijing, China, 2 Beijing Innovation Center for Future Chips, Tsinghua University, Beijing, China, Department of Electrical and Computer Engineering, University of California, Santa Barbara, Santa Barbara, CA, United States, Huawei Technologies, Shenzhen, China, Department of Cognitive Science, University of California, Irvine, Irvine, CA, United States, Department of Electrical Engineering, National University of Singapore, Singapore, Singapore
Comparative Transcriptome Analysis Reveals New lncRNAs Responding to Salt Stress in Sweet Sorghum

Long non-coding RNAs (lncRNAs) can enhance plant stress resistance by regulating the expression of functional genes. Sweet sorghum is a salt-tolerant energy crop. However, little is known about how lncRNAs in sweet sorghum respond to salt stress. In this study, we identified 126 and 133 differentially expressed lncRNAs in the salt-tolerant M-81E and the salt-sensitive Roma strains, respectively. Salt stress induced three new lncRNAs in M-81E and inhibited two new lncRNAs in Roma. These lncRNAs included lncRNA13472, lncRNA11310, lncRNA2846, lncRNA26929, and lncRNA14798, which potentially function as competitive endogenous RNAs (ceRNAs) that influence plant responses to salt stress by regulating the expression of target genes related to ion transport, protein modification, transcriptional regulation, and material synthesis and transport. Additionally, M-81E had a more complex ceRNA network than Roma. This study provides new information regarding lncRNAs and the complex regulatory network underlying salt-stress responses in sweet sorghum.
The Reciprocal Relationship Between Handwriting Fluency and Spelling Accuracy in Chinese: A Longitudinal Study

Mastering transcription skills is an important goal in the development of children's written language abilities, and handwriting fluency and spelling accuracy are crucial indicators of transcription ability. The current study was a two-year longitudinal study to investigate the reciprocal relationship of handwriting fluency and spelling accuracy. Participants included 123 students living in mainland China, who were tracked from third to fifth grade, and were administered a comprehensive battery of tests including assessments for non-verbal intelligence, phonological awareness, rapid automatized naming, and copying and dictation of Chinese characters. The results showed that: (1) previous handwriting fluency predicted subsequent spelling accuracy; and (2) previous spelling accuracy predicted subsequent handwriting fluency. These findings indicated there is a bidirectional relationship between handwriting fluency and spelling accuracy in Chinese. This implies spelling accuracy should not be unilaterally emphasized when teaching children new vocabulary, but attention should also be given to the cultivation of handwriting fluency in daily pedagogical practice.
White Matter Microstructure Predicts Focal and Broad Functional Brain Dedifferentiation in Normal Aging

Abstract Ventral visual cortex exhibits highly organized and selective patterns of functional activity associated with visual processing. However, this specialization decreases in normal aging, with functional responses to different visual stimuli becoming more similar with age, a phenomenon termed “dedifferentiation. ” The current study tested the hypothesis that age-related degradation of the inferior longitudinal fasciculus (ILF), a white matter pathway involved in visual perception, could account for dedifferentiation of both localized and distributed brain activity in ventral visual cortex. Participants included 281 adults, ages 20–89 years, from the Dallas Lifespan Brain Study who underwent diffusion-weighted imaging to measure white matter diffusivity, as well as fMRI to measure functional selectivity to viewing photographs from different categories (e.g., faces, houses). In general, decreased ILF anisotropy significantly predicted both focal and broad functional dedifferentiation. Specifically, there was a localized effect of structure on function, such that decreased anisotropy in a smaller mid-fusiform region of ILF predicted less selective (i.e., more dedifferentiated) response to viewing faces in a proximal face-responsive region of fusiform. On the other hand, the whole ILF predicted less selective response across broader ventral visual cortex for viewing animate (e.g., human faces, animals) versus inanimate (e.g., houses, chairs) images. This structure–function relationship became weaker with age and was no longer significant after the age of 70 years. These findings indicate that decreased white matter anisotropy is associated with maladaptive differences in proximal brain function and is an important variable to consider when interpreting age differences in functional selectivity.
A Systematic Review of Water and Gender Interlinkages: Assessing the Intersection With Health

Background: Significant developmental challenges in low-resource settings limit access to sustainable water, sanitation, and hygiene (WASH). However, in addition to reducing human agency and dignity, gendered WASH inequities can also increase disease burden among women and girls. In this systematic review, a range of challenges experienced by women relating to inadequate WASH resources are described and their intersection with health are explored. We further assess the effectiveness of interventions in alleviating inequalities related to the Sustainable Development Goals (SDGs) three (health), five (gender), and six (water). Methods: We searched the MEDLINE database to identify research articles related to water (i.e., WASH), gender, and sustainability. An analysis of both observational and interventional studies was undertaken. For each study, content analysis was performed to identify the relevant WASH, gender, and health related outcomes, and the main conclusions of the study. Results: Key themes from our search included that women and girls face barriers toward accessing basic sanitation and hygiene resources, including a lack of secure and private sanitation and of Menstrual Hygiene Management (MHM) resources. In total, 71% of identified studies reported a health outcome, suggesting an intersection of water and gender with health. Half of the research studies that included a health component reflected on the relationship between WASH, gender, and infantile diseases, including under-5 mortality, waterborne parasites, and stunting. In addition, we found that women and girls, as a result of their role as water purveyors, were at risk of exposure to contaminated water and of sustaining musculoskeletal trauma. A limited number of studies directly compared gender differences in accessing WASH resources, and an even smaller fraction (N = 5, 8.5%) reported sex-disaggregated outcomes. Educational, infrastructural, and programmatic interventions showed promise in reducing WASH and health outcomes. Indeed, infrastructural WASH interventions can be successful if long-term maintenance is ensured. Conclusions: Significant WASH inequities in women and girls further manifest as health burdens, providing strong evidence that the water-gender-nexus intersects with health. Thus, addressing gender and water inequities holds the potential to alleviate disease burden and have a significant impact on achieving the SDGs, including SDG three, five, and six.
Comparative Analyses of Mitochondrial Genomes Provide Evolutionary Insights Into Nematode-Trapping Fungi

Predatory fungi in Orbiliaceae (Ascomycota) have evolved a diversity of trapping devices that enable them to trap and kill nematodes, other small animals, and protozoans. These trapping devices include adhesive hyphae, adhesive knobs, adhesive networks, constricting rings, and non-constricting rings. Their diversity and practical importance have attracted significant attention from biologists, making them excellent model organisms for studying adaptative evolution and as biological control agents against parasitic nematodes. The putative origins and evolutionary relationships among these carnivorous fungi have been investigated using nuclear protein-encoding genes, but their patterns of mitogenome relationships and divergences remain unknown. Here we analyze and compare the mitogenomes of 12 fungal strains belonging to eight species, including six species representing all four types of nematode trapping devices and two from related but non-predatory fungi. All 12 analyzed mitogenomes were of circular DNA molecules, with lengths ranging from 146,101 bp to 280,699 bp. Gene synteny analysis revealed several gene rearrangements and intron transfers among the mitogenomes. In addition, the number of protein coding genes (PCGs), GC content, AT skew, and GC skew varied among these mitogenomes. The increased number and total size of introns were the main contributors to the length differences among the mitogenomes. Phylogenetic analyses of the protein-coding genes indicated that mitochondrial and nuclear genomes evolved at different rates, and signals of positive selection were found in several genes involved in energy metabolism. Our study provides novel insights into the evolution of nematode-trapping fungi and shall facilitate further investigations of this ecologically and agriculturally important group of fungi.
Characterization and Classification of Electrophysiological Signals Represented as Visibility Graphs Using the Maxclique Graph

Detection, characterization and classification of patterns within time series from electrophysiological signals have been a challenge for neuroscientists due to their complexity and variability. Here, we aimed to use graph theory to characterize and classify waveforms within biological signals using maxcliques as a feature for a deep learning method. We implemented a compact and easy to visualize algorithm and interface in Python. This software uses time series as input. We applied the maxclique graph operator in order to obtain further graph parameters. We extracted features of the time series by processing all graph parameters through K-means, one of the simplest unsupervised machine learning algorithms. As proof of principle, we analyzed integrated electrical activity of XII nerve to identify waveforms. Our results show that the use of maxcliques allows identification of two distinct types of waveforms that match expert classification. We propose that our method can be a useful tool to characterize and classify other electrophysiological signals in a short time and objectively. Reducing the classification time improves efficiency for further analysis in order to compare between treatments or conditions, e.g., pharmacological trials, injuries, or neurodegenerative diseases.
ThreadScan

The concurrent memory reclamation problem is that of devising a way for a deallocating thread to verify that no other concurrent threads hold references to a memory block being deallocated. To date, in the absence of automatic garbage collection, there is no satisfactory solution to this problem; existing tracking methods like hazard pointers, reference counters, or epoch-based techniques like RCU are either prohibitively expensive or require significant programming expertise to the extent that implementing them efficiently can be worthy of a publication. None of the existing techniques are automatic or even semi-automated. In this article, we take a new approach to concurrent memory reclamation. Instead of manually tracking access to memory locations as done in techniques like hazard pointers, or restricting shared accesses to specific epoch boundaries as in RCU, our algorithm, called ThreadScan, leverages operating system signaling to automatically detect which memory locations are being accessed by concurrent threads. Initial empirical evidence shows that ThreadScan scales surprisingly well and requires negligible programming effort beyond the standard use of Malloc and Free.
Comprehensive Evolutionary Analysis of Lamprey TNFR-Associated Factors (TRAFs) and Receptor-Interacting Protein Kinase (RIPKs) and Insights Into the Functional Characterization of TRAF3/6 and RIPK1

TNFR-associated factors (TRAFs) and receptor-interacting protein kinases (RIPKs) are important immunological linker molecules in mammals and play important roles in the TNFα, TLR and IFN signaling pathways. However, the evolutionary origins of these genes in vertebrates have not previously been described in lampreys. In this study, we searched the genomes of Lampetra japonicum, Lethenteron reissneri, and Petromyzon marinus for genes encoding trafs and ripks and performed homologous sequence alignment, phylogenetic tree, functional domain, conserved motif, gene structure, and synteny analyses to determine their evolutionary relationships. The distribution of the lamprey traf and ripk families and the immune response of the gene families in lampreys stimulated by different pathogens were also demonstrated, suggesting a role of structural changes in expression and functional diversification. Additionally, the dual luciferase reporter gene assay showed that the addition of exogenous immunomodulator (TNFα or IFN) to the overexpression of LjLRIPK1a or LjTRAF3/6 significantly downregulated NF-κB or ISRE activation. LjRIPK1a can significantly enhance caspase-8 activity, and overexpression of LjRIPK1a or LjTRAF3a/6 in HEK293T cells results in cell apoptosis. In summary, this study makes an important contribution to the understanding of the traf and ripk gene families in different vertebrates. Our results also provide new evidence for the evolution of vertebrate TRAFs and RIPKs and their impacts on immune regulation.
Biomimetic Models to Investigate Membrane Biophysics Affecting Lipid–Protein Interaction

Biological membranes are highly dynamic in their ability to orchestrate vital mechanisms including cellular protection, organelle compartmentalization, cellular biomechanics, nutrient transport, molecular/enzymatic recognition, and membrane fusion. Controlling lipid composition of different membranes allows cells to regulate their membrane characteristics, thus modifying their physical properties to permit specific protein interactions and drive structural function (membrane deformation facilitates vesicle budding and fusion) and signal transduction. Yet, how lipids control protein structure and function is still poorly understood and needs systematic investigation. In this review, we explore different in vitro membrane models and summarize our current understanding of the interplay between membrane biophysical properties and lipid–protein interaction, taken as example few proteins involved in muscular activity (dystrophin), digestion and Legionella pneumophila effector protein DrrA. The monolayer model with its movable barriers aims to mimic any membrane deformation while surface pressure modulation imitates lipid packing and membrane curvature changes. It is frequently used to investigate peripheral protein binding to the lipid headgroups. Examples of how lipid lateral pressure modifies protein interaction and organization within the membrane are presented using various biophysical techniques. Interestingly, the shear elasticity and surface viscosity of the monolayer will increase upon specific protein(s) binding, supporting the importance of such mechanical link for membrane stability. The lipid bilayer models such as vesicles are not only used to investigate direct protein binding based on the lipid nature, but more importantly to assess how local membrane curvature (vesicles with different size) influence the binding properties of a protein. Also, supported lipid bilayer model has been used widely to characterize diffusion law of lipids within the bilayer and/or protein/biomolecule binding and diffusion on the membrane. These membrane models continue to elucidate important advances regarding the dynamic properties harmonizing lipid–protein interaction.
Re-imaging the intentional stance

The commonly used paradigm to investigate Dennet's ‘intentional stance’ compares neural activation when participants compete with a human versus a computer. This paradigm confounds whether the opponent is natural or artificial and whether it is intentional or an automaton. This functional magnetic resonance imaging study is, to our knowledge, the first to investigate the intentional stance by orthogonally varying perceptions of the opponents' intentionality (responding actively or passively according to a script) and embodiment (human or a computer). The mere perception of the opponent (whether human or computer) as intentional activated the mentalizing network: the temporoparietal junction (TPJ) bilaterally, right temporal pole, anterior paracingulate cortex (aPCC) and the precuneus. Interacting with humans versus computers induced activations in a more circumscribed right lateralized subnetwork within the mentalizing network, consisting of the TPJ and the aPCC, possibly reflective of the tendency to spontaneously attribute intentionality to humans. The interaction between intentionality (active versus passive) and opponent (human versus computer) recruited the left frontal pole, possibly in response to violations of the default intentional stance towards humans and computers. Employing an orthogonal design is important to adequately capture Dennett's conception of the intentional stance as a mentalizing strategy that can apply equally well to humans and other intentional agents.
Morphological diversification has led to inter-specific variation in elastic wing deformation during flight in scarab beetles

Insect wing shapes and the internal wing-vein arrangement are remarkably diverse. Although the wings lack intrinsic musculature to adjust shape actively, they elastically deform due to aerodynamic and inertial loads during flapping. In turn, the deformations alter the shape of the wing profile affecting the aerodynamic force. To determine how changes in wing-vein arrangement affect elastic wing deformation during free flight, we compared elastic wing deformations between free-flying rose chafers (Protaetia cuprea) and dung beetles (Scarabaeus puncticollis), complementing the comparison with wing static bending measurements. The broader relevance of the results to scarab beetle divergence was examined in a geometric morphometric (GM) analysis of wing-vein arrangement in 20 species differing in phylogeny and ecology. Despite rose chafers and dung beetles demonstrating similar flapping kinematics and wing size, the rose chafer wings undergo greater elastic deformation during flapping. GM analyses corrected for phylogenetic relatedness revealed that the two beetles represent extremes in wing morphology among the scarab subfamilies. Most of the differences occur at the distal leading edge and the proximal trailing edge of the wing, diversifying the flexibility of these regions, thereby changing the pattern of elastic wing deformation during flapping. Changes to local wing compliance seem to be associated with the diversification of scarab beetles to different food sources, perhaps as an adaptation to meet the demands of diverse flight styles.