Multiple Processes Research Articles

Accelerated Development of AAV Purification Process Using a High-Throughput and Automated Crossflow System

Adeno-associated viruses (AAV) are currently predominant viral transfer tools for gene therapy, and efforts are being made to design faster and more efficient methods and technologies for their manufacturing. The early selection of high-performing filters is essential for developing an ultrafiltration and diafiltration (UF/DF) process, especially when feed material is scarce, and timelines are short. However, few methods and technologies exist to enable process optimization with multiple variations in a single run. In this study, we explored the potential of Ambr® Crossflow for high-throughput, automated screening of different membrane materials, pore sizes and different process conditions for the UF/DF step of AAV8. The best overall performance was obtained with a 100 kDa PES flat sheet cassette. The UF/DF process was further transferred to a larger scale to the Sartoflow® Smart Tangential Flow Filtration (TFF) system using a 100 kDa PES Sartocon® Slice 200 cassette and compared to a 100 kDa PES hollow fiber. Virus recovery, permeate flux and total protein removal values of the flat sheet cassette were similar to those achieved in small-scale devices, and higher than those of the hollow fiber, thus demonstrating similar performance at a larger process scale. The high-throughput, automated method described herein allowed to screen multiple materials and process parameters of a UF/DF process in a time- and resource-efficient way, making it a useful tool to accelerate early-stage downstream process development of AAV.

Comprehensive transcriptomic meta-analysis unveils new responsive genes to methyl jasmonate and ethylene in Catharanthusroseus

In Catharanthus roseus, vital plant hormones, namely methyl jasmonate (MeJA) and ethylene, serve as abiotic triggers, playing a crucial role in stimulating the production of specific secondary compounds with anticancer properties. Understanding how plants react to various stresses, stimuli, and the pathways involved in biosynthesis holds significant promise. The application of stressors like ethylene and MeJA induces the plant's defense mechanisms, leading to increased secondary metabolite production. To delve into the essential transcriptomic processes linked to hormonal responses, this study employed an integrated approach combining RNA-Seq data meta-analysis and system biology methodologies. Furthermore, the validity of the meta-analysis findings was confirmed using RT-qPCR. Within the meta-analysis, 903 genes exhibited differential expression (DEGs) when comparing normal conditions to those of the treatment. Subsequent analysis, encompassing gene ontology, KEGG, TF, and motifs, revealed that these DEGs were actively engaged in multiple biological processes, particularly in responding to various stresses and stimuli. Additionally, these genes were notably enriched in diverse biosynthetic pathways, including those related to TIAs, housing valuable medicinal compounds found in this plant. Furthermore, by conducting co-expression network analysis, we identified hub genes within modules associated with stress response and the production of TIAs. Most genes linked to the biosynthesis pathway of TIAs clustered within three specific modules. Noteworthy hub genes, including Helicase ATP-binding domain, hbdA, and ALP1 genes within the blue, turquoise, and green module networks, are presumed to play a role in the TIAs pathway. These identified candidate genes hold potential for forthcoming genetic and metabolic engineering initiatives aimed at augmenting the production of secondary metabolites and medicinal compounds within C. roseus.

Research of ordinal model fusion based apple grading

Near infrared spectrum has been applied for the rapid non-destructive prediction and classification of the internal soluble solids content (SSC) of apples, due to its rapid, non-destructive and non-polluting nature. However, current apple grading methods do not make full use of the orderliness relationship existing in the apple grading labels. Therefore, ordinal model is introduced in the issue of apples grading based on the internal SSC. In details, the orderliness in the classification model is considered and ordinal regression is combined with apple classification model to establish ordered partition neural network and ordinal regression extreme learning machine, respectively. Meanwhile, to address the problems of poor applicability of single prediction model and the grading uncertainty associated with compulsory segmentation of grading boundaries, a Gaussian mass function generating method is proposed based on the distance between the predicted ordinal class labels and the real grading boundaries, and the multiple models can be fused through the Dempster combination rule, making a fuller description of the uncertainty problem on ordinal class labels prediction, providing a research basis for online non destructive testing grading of apples. Finally, the multiple model fusion process is fully demonstrated by simulation examples, the grading accuracy of Yantai Red Fuji apples is also improved than single ordinal model.

Trophic cascades within and across ecosystems: The role of anti-predatory defences, predator type and detritus quality.

Species in one ecosystem can indirectly affect multiple biodiversity components and ecosystem functions of adjacent ecosystems. The magnitude of these cross-ecosystem effects depends on the attributes of the organisms involved in the interactions, including traits of the predator, prey and basal resource. However, it is unclear how predators with cross-ecosystem habitat interact with predators with single-ecosystem habitat to affect their shared ecosystem. Also, unknown is how such complex top-down effects may be mediated by the anti-predatory traits of prey and quality of the basal resource. We used the aquatic invertebrate food webs in tank bromeliads as a model system to investigate these questions. We manipulated the presence of a strictly aquatic predator (damselfly larvae) and a predator with both terrestrial and aquatic habitats (spider), and examined effects on survival of prey (detritivores grouped by anti-predator defence), detrital decomposition (of two plant species differing in litter quality), nitrogen flux and host plant growth. To evaluate the direct and indirect effects each predator type on multiple detritivore groups and ultimately on multiple ecosystem processes, we used piecewise structural equation models. For each response variable, we isolated the contribution of different detritivore groups to overall effects by comparing alternate model formulations. Alone, damselfly larvae and spiders each directly decreased survival of detritivores and caused multiple indirect negative effects on detritus decomposition, nutrient cycling and host plant growth. However, when predators co-occurred, the spider caused a negative non-consumptive effect on the damselfly larva, diminishing the net direct and indirect top-down effects on the aquatic detritivore community and ecosystem functioning. Both detritivore traits and detritus quality modulated the strength and mechanism of these trophic cascades. Predator interference was mediated by undefended or partially defended detritivores as detritivores with anti-predatory defences evaded consumption by damselfly larvae but not spiders. Predators and detritivores affected ecosystem decomposition and nutrient cycling only in the presence of high-quality detritus, as the low-quality detritus was consumed more by microbes than invertebrates. The complex responses of this system to predators from both recipient and adjacent ecosystems highlight the critical role of maintaining biodiversity components across multiple ecosystems.

Performance of explicit and IMEX MRI multirate methods on complex reactive flow problems within modern parallel adaptive structured grid frameworks

Large-scale multiphysics simulations are computationally challenging due to the coupling of multiple processes with widely disparate time scales. The advent of exascale computing systems exacerbates these challenges since these systems enable ever-increasing size and complexity. In recent years, there has been renewed interest in developing multirate methods as a means to handle the large range of time scales, as these methods may afford greater accuracy and efficiency than more traditional approaches of using implicit-explicit (IMEX) and low-order operator splitting schemes. However, to date there have been few performance studies that compare different classes of multirate integrators on complex application problems. In this work, we study the performance of several newly developed multirate infinitesimal (MRI) methods, implemented in the SUNDIALS solver package, on two reacting flow model problems built on structured mesh frameworks. The first model revisits prior work on a compressible reacting flow problem with complex chemistry that is implemented using BoxLib but where we now include comparisons between a new explicit MRI scheme with the multirate spectral deferred correction (SDC) methods in the original paper. The second problem uses the same complex chemistry as the first problem, combined with a simplified flow model, but runs at a large spatial scale where explicit methods become infeasible due to stability constraints. Two recently developed IMEX MRI multirate methods are tested. These methods rely on advanced features of the AMReX framework on which the model is built, such as multilevel grids and multilevel preconditioners. The results from these two problems show that MRI multirate methods can offer significant performance benefits on complex multiphysics application problems and that these methods may be combined with advanced spatial discretization to compound the advantages of both.

Proteomic analysis of multiple organ dysfunction induced by rhabdomyolysis

Rhabdomyolysis (RM) leads to dysfunction in the core organs of kidney, lung and heart, which is an important reason for the high mortality and disability rate of this disease. However, there is a lack of systematic research on the characteristics of rhabdomyolysis-induced injury in various organs and the underlying pathogenetic mechanisms, and especially the interaction between organs. We established a rhabdomyolysis model, observed the structural and functional changes in kidney, heart, and lung. It is observed that rhabdomyolysis results in significant damage in kidney, lung and heart of rats, among which the pathological damage of kidney and lung was significant, and of heart was relatively light. Meanwhile, we analyzed the differentially expressed proteins (DEPs) in the kidney, heart and lung between the RM group and the sham group based on liquid chromatography-tandem mass spectrometry (LC-MS/MS). In our study, Serpina3n was significantly up-regulated in the kidney, heart and lung. Serpina3n is a secreted protein and specifically inhibits a variety of proteases and participates in multiple physiological processes such as complement activation, inflammatory responses, apoptosis pathways, and extracellular matrix metabolism. It is inferred that Serpina3n may play an important role in multiple organ damage caused by rhabdomyolysis and could be used as a potential biomarker. This study comprehensively describes the functional and structural changes of kidney, heart and lung in rats after rhabdomyolysis, analyzes the DEPs of kidney, heart and lung, and determines the key role of Serpina3n in multiple organ injury caused by rhabdomyolysis. SignificanceThis study comprehensively describes the functional and structural changes of kidney, heart and lung in rats after rhabdomyolysis, analyzes the DEPs of kidney, heart and lung, and determines the key role of Serpina3n in multiple organ injury caused by rhabdomyolysis.

From Cognitive Agents to Cognitive Systems: Theoretical, Methodological, and Empirical Developments of van Gelder's (1998) "Dynamical Hypothesis".

Over two decades have passed since the publication of van Gelder's (1998) "dynamical hypothesis." In that paper, van Gelder proposed that cognitive agents were not digital computers-per the representational computational approach-but dynamical systems. The evolution of the dynamical hypothesis was driven by parallel advances in three areas. Theoretically, a deeper understanding of genetics, biology, neuroscience, and cognitive science inspired questions about how systems within each domain dynamically interact and extend their effects across spatiotemporal scales. Methodologically, more sophisticated and domain-general tools allowed researchers to discover, model, and quantify system dynamics, structure, and patterns across multiple scales to generate a more comprehensive system-level understanding of behaviors. Empirically, we can analyze a system's behavior while preserving its natural dynamics, revealing evidence that the reductionist approach leads to an incomplete understanding of the components and the overall system. Researchers have traditionally reduced a complex system into its component processes and assumed that the parts can be recombined to explain the whole. These three advances fundamentally altered our understanding of a "cognitive agent:" How their behaviors are driven by long-range coordination across multiple processes, how the interdependent and nested structure of interacting variables produces behaviors that are greater than the sum of its parts, and how environmental constraints shape adaptive yet stable behavioral patterns.

Facilitation against herbivory more important than resource‐based niche differences for plant coexistence in a field experiment

Abstract Theory suggests that eutrophication impacts plant community biodiversity by constraining niche differences and increasing competitive inequalities among species, leading to the exclusion of weaker competitors. However, explicit tests of nutrient effects on the strength and direction of inter‐ and intraspecific plant–plant interactions that dictate coexistence are lacking, especially in complex field settings where multiple processes can simultaneously affect plant growth and reproduction. We conducted a field experiment in southeastern Vancouver Island, Canada, using four annual grassland plant species to test how species interactions responded to eutrophication and the covariation of herbivore pressure and neighbour species light‐ and moisture‐use. We found that focal species reproduction was limited by nutrient availability and herbivory, such that the nature of species interactions was context‐dependent. Competitive interactions failed to predict species persistence under these conditions. Instead, facilitation was critical—phytometers grown without neighbours consistently failed to produce seed under herbivore pressure meaning that fecundity significantly increased with neighbour density. Synthesis. Our work demonstrates the importance of species interactions in plant community responses to eutrophication but emphasizes that ‘indirect’ drivers of plant performance may influence or overwhelm nutrient effects on plant–plant competition. The widespread occurrence of mortality overcome primarily by facilitation highlights the importance of positive density dependence. Overall, our results suggest that knowledge of resource niche overlap may be insufficient to explain plant community responses to eutrophication. This highlights the necessity of considering the broader environmental context when leveraging ecological theory to understand global change effects in empirical settings.

Peripheral administration of lipidized NPAF and NPFF analogs does not influence central food intake regulation but induces anxiety-like behavior

RF-amide peptides influence multiple physiological processes, including the regulation of appetite, stress responses, behavior, and reproductive and endocrine functions. In this study, we examined the roles of neuropeptide FF receptors (NPFFR1 and NPFFR2) by generating several lipidized analogs of neuropeptide AF (NPAF) and 1DMe, a stable analog of neuropeptide FF (NPFF). These analogs were administered peripherally for the first time to investigate their effects on food intake and other potential physiological outcomes. Lipidized NPAF and 1DMe analogs exhibited enhanced stability and increased pharmacokinetics. These analogs demonstrated preserved high affinity for NPFFR2 in the nanomolar range, while the binding affinity for NPFFR1 was tens of nanomoles. They activated the ERK and Akt signaling pathways in cells overexpressing the NPFFR1 and NPFFR2 receptors.Acute food intake in fasted mice decreased after the peripheral administration of oct-NPAF or oct-1DMe. However, this effect was not as pronounced as that observed after the injection of palm11-PrRP31, a potent anorexigenic compound used as a comparator that binds to GPR10 and the NPFFR2 receptor with high affinity. Neither oct-1DMe nor oct-NPAF decreased food intake or body weight in mice with diet-induced obesity during long-term treatment. In mice treated with oct-1DMe, we observed decreased activity in the central zone during the open field test and decreased activity in the open arms of the elevated plus maze. Furthermore, we observed a decrease in plasma noradrenaline levels and an increase in plasma corticosterone levels, as well as an increase in Crh expression in the hypothalamus. Moreover, neuronal activity in the hypothalamus was increased after treatment with oct-1DMe.In this study, we report that oct-1DMe did not have any long-term effects on the central regulation of food intake; however, it caused anxiety-like behavior.

Controlled synthesis of graphene-based hybrids on hydration-dehydration treated bio-shell-derived catalysts

Graphene-based hybrids such as carbon nanotube/graphene nanosheet (CNT/GNS), carbon nanofiber/graphene nanosheet (CNF/GNS), and CNF-CNT/GNS have attracted extensive attention in energy-related applications due to their excellent properties. The selective synthesis of GNS-based hybrids usually relies on the precise design of metal catalysts and multiple tedious processes. Here, a facile one-step synthesis of GNS-based hybrids was successfully performed by chemical vapor deposition (CVD) on waste bio-shell derived catalysts without the addition of extra metal components, and GNS-based hybrids were selectively synthesized through the hydration and dehydration (H-D) treatment of catalysts. When eggshells were calcined at high temperature, the obtained E-CaO catalyst only synthesized GNSs. After E-CaO was treated by the H-D method, the obtained E-CaO-H-1 catalyst grew CNF/GNS. E-CaO-H-2 catalyst was further prepared by the H-D treatment of E-CaO-H-1, which produced CNF-CNT/GNS. Multiple characterizations of catalysts demonstrated that the high-temperature calcination of eggshells led to the aggregation of CaO and incorporation of Fe into CaO lattices, and thus only GNSs were synthesized on CaO. However, after the H-D treatment of E-CaO, the Fe element was released from CaO lattices and the surface area of CaO enhanced with the decrease of particle size, leading to the dispersion of Fe oxides on the CaO surface, and Fe particles were subsequently formed during the CVD synthesis, which synthesized CNFs on GNS. Further, with the size reduction of Fe particles after the second H-D treatment of the catalyst, smaller Fe particles facilitated the CNT growth, leading to the production of CNF-CNT/GNS. Similarly, the catalysts formed by calcination of other bio-shells (oyster shells, shrimp shells, and crab shells) only synthesized GNSs, whereas these catalysts after H-D treatment produced CNF-CNT/GNS with enhanced carbon yields. This study offers a new method for utilizing the metal species in waste bio-shells for the facile production of structurally tunable GNS-based hybrid materials.

Thirty years of longitudinal talent development research: a systematic review and meta-aggregation

ABSTRACT Talent pathways are longitudinal and multidimensional in nature offering developmental environments for athletes that incorporate multiple processes at multiple timepoints. Recent reviews have unilaterally targeted static talent areas (i.e. talent detection and identification). This review aimed to identify quantitative and qualitative studies with longitudinal designs, within an elite athlete population, that considered development and selection literature collectively. Taking a novel pragmatic approach achieved pluralism in a strive to greatly advance our methodological understanding to acquire knowledge of more effective talent development in sport. This review followed the Preferred Reporting Items for Systematic Review and used a Meta-aggregation methodology. A search of talent development and selection literature identified 41 quantitative and 3 qualitative longitudinal studies. Overall, ten (quantitative) studies investigated interactions between multidimensional selection (i.e. measures of performance) and development characteristics; performance variables changed non-linearly alongside talent development characteristics. No longitudinal mixed-method research studies were found. For practitioners, multiple performance measures need to be considered alongside development characteristics to better assess talent. For researchers, the design of this review models an epistemological and ontological congruent approach that can be used to facilitate the design of future mixed-method and longitudinal research; capturing the dynamic and multifaceted individual differences of talent development.

Evolutionary relationships, hybridization and diversification under domestication of the locoto chile (Capsicum pubescens) and its wild relatives.

Patterns of genetic variation in crops are the result of multiple processes that have occurred during their domestication and improvement, and are influenced by their wild progenitors that often remain understudied. The locoto chile, Capsicum pubescens, is a crop grown mainly in mid-highlands of South-Central America. This species is not known from the wild and exists only as a cultigen. The evolutionary affinities and exact origin of C. pubescens have still not been elucidated, with hypotheses suggesting its genetic relatedness and origin to two wild putative ancestral Capsicum species from the Central Andes, C.eximium and C. cardenasii. In the current study, RAD-sequencing was applied to obtain genome-wide data for 48 individuals of C. pubescens and its wild allies representing different geographical areas. Bayesian, Maximum Likelihood and coalescent-based analytical approaches were used to reconstruct population genetic patterns and phylogenetic relationships of the studied species. The results revealed that C. pubescens forms a well-defined monotypic lineage closely related to wild C. cardenasii and C. eximium, and also to C. eshbaughii. The primary lineages associated with the diversification under domestication of C. pubescens were also identified. Although direct ancestor-descendant relationship could not be inferred within this group of taxa, hybridization events were detected between C. pubescens and both C.cardenasii and C. eximium. Therefore, although hybrid origin of C. pubescens could not be inferred, gene flow involving its wild siblings was shown to be an important factor contributing to its contemporary genetic diversity. The data allowed for the inference of the center of origin of C. pubescens in central-western Bolivia highlands and for better understanding of the dynamics of its gene pool. The results of this study are essential for germplasm conservation and breeding purposes, and provide excellent basis for further research of the locoto chile and its wild relatives.

Insights into the complementation potential of the extreme acidophile's orthologue in replacing Escherichia coli hfq gene-particularly in bacterial resistance to environmental stress.

Acidithiobacillus caldus is a typical extreme acidophile widely used in the biohydrometallurgical industry, which often experiences extreme environmental stress in its natural habitat. Hfq, an RNA-binding protein, typically functions as a global regulator involved in various cellular physiological processes. Yet, the biological functions of Hfq derived from such extreme acidophile have not been extensively investigated. In this study, the recombinant strain Δhfq/Achfq, constructed by CRISPR/Cas9-mediated chromosome integration, fully or partially restored the phenotypic defects caused by hfq deletion in Escherichia coli, including impaired growth performance, abnormal cell morphology, impaired swarming motility, decreased stress resistance, decreased intracellular ATP and free amino acid levels, and attenuated biofilm formation. Particularly noteworthy, the intracellular ATP level and biofilm production of the recombinant strain were increased by 12.2% and 7.0%, respectively, compared to the Δhfq mutant. Transcriptomic analysis revealed that even under heterologous expression, AcHfq exerted global regulatory effects on multiple cellular processes, including metabolism, environmental signal processing, and motility. Finally, we established a potential working model to illustrate the regulatory mechanism of AcHfq in bacterial resistance to environmental stress.

Stress evolution in enamel coating/Ni-based alloy systems during isothermal oxidation

This paper utilizes a coupled chemomechanical model that integrates chemical reactions, diffusion, and mechanical deformation to describe the high-temperature interfacial reactions and stress evolution within an enamel coating/Ni-based super-alloy system. Through finite element simulation, we conduct a comprehensive analysis of multiple reactions and processes at the interface. Experimental characterization of the concentration distribution of various elements is employed to verify the accuracy of the proposed chemomechanical model. Additionally, the simulation reveals that the interface region experiences compressive circumferential stress, which can potentially lead to interfacial failure due to buckling. On the other hand, the enamel coating undergoes tensile circumferential stress, resulting in the formation of vertical surface cracks. These findings hold practical implications for the development of advanced coatings with enhanced durability and performance. Future research can further optimize coating design and enhance the reliability of high-temperature applications based on these results.

Kinome-Wide Virtual Screening by Multi-Task Deep Learning.

Deep learning is a machine learning technique to model high-level abstractions in data by utilizing a graph composed of multiple processing layers that experience various linear and non-linear transformations. This technique has been shown to perform well for applications in drug discovery, utilizing structural features of small molecules to predict activity. Here, we report a large-scale study to predict the activity of small molecules across the human kinome-a major family of drug targets, particularly in anti-cancer agents. While small-molecule kinase inhibitors exhibit impressive clinical efficacy in several different diseases, resistance often arises through adaptive kinome reprogramming or subpopulation diversity. Polypharmacology and combination therapies offer potential therapeutic strategies for patients with resistant diseases. Their development would benefit from a more comprehensive and dense knowledge of small-molecule inhibition across the human kinome. Leveraging over 650,000 bioactivity annotations for more than 300,000 small molecules, we evaluated multiple machine learning methods to predict the small-molecule inhibition of 342 kinases across the human kinome. Our results demonstrated that multi-task deep neural networks outperformed classical single-task methods, offering the potential for conducting large-scale virtual screening, predicting activity profiles, and bridging the gaps in the available data.

Accounting and Finance: Complementarity and Divergence

Abstract Penman (2023. Accounting for Uncertainty. Accounting, Economics, and Law: A Convivium) develops a conceptual framework which reconciles accounting and finance in view to provide information for financial investment. His framework is based upon resolution of uncertainty over expectations as a convenient basis for accrual accounting. In this context, accrual accounting can be interpreted as a convenient instrument to protect the corporate capacity to generate future earnings on which the expected financial value is based upon. However, in order to fulfil this control function, accounting applies an additive process (simple return), while financial valuation imposes a multiplicative process (compound return) over the invested financial capital. This divergence between accounting and finance enables disentangling business profit – as determined by accounting – from money interest and ownership rent, paving the way to a theory of the business firm based upon its accounting structure, and enabling measures of financial performance consistent with this divergence.

SRNA molecules participate in hyperosmotic stress response regulation in Sphingomonas melonis TY.

Drought and salinity are ubiquitous environmental factors that pose hyperosmotic threats to microorganisms and impair their efficiency in performing environmental functions. However, bacteria have developed various responses and regulatory systems to cope with these abiotic challenges. Posttranscriptional regulation plays vital roles in regulating gene expression and cellular homeostasis, as hyperosmotic stress conditions can lead to the induction of specific small RNA molecules (sRNAs) that participate in stress response regulation. Here, we report a candidate functional sRNA landscape of Sphingomonas melonis TY under hyperosmotic stress, and 18 sRNAs were found with a clear response to hyperosmotic stress. These findings will help in the comprehensive analysis of sRNA regulation in Sphingomonas species. Weighted correlation network analysis revealed a 263 nucleotide sRNA, SNC251, which was transcribed from its own promoter and showed the most significant correlation with hyperosmotic response factors. Deletion of snc251 affected biofilm formation and multiple cellular processes, including ribosome-related pathways, aromatic compound degradation, and the nicotine degradation capacity of S. melonis TY, while overexpression of SNC251 facilitated biofilm formation by TY under hyperosmotic stress. Two genes involved in the TonB system were further verified to be activated by SNC251, which also indicated that SNC251 is a trans-acting sRNA. Briefly, this research reports a landscape of sRNAs participating in the hyperosmotic stress response in S. melonis and reveals a novel sRNA, SNC251, which contributes to the S. melonis TY biofilm formation and thus enhances its hyperosmotic stress response ability.IMPORTANCESphingomonas species play a vital role in plant defense and pollutant degradation and survive extensively under drought or salinity. Previous studies have focused on the transcriptional and translational responses of Sphingomonas under hyperosmotic stress, but the posttranscriptional regulation of small RNA molecules (sRNAs) is also crucial for quickly modulating cellular processes to adapt dynamically to osmotic environments. In addition, the current knowledge of sRNAs in Sphingomonas is extremely scarce. This research revealed a novel sRNA landscape of Sphingomonas melonis and will greatly enhance our understanding of sRNAs' acting mechanisms in the hyperosmotic stress response.

State-dependent alteration of respiration in a rat model of Parkinson's disease

Parkinson's disease (PD) is the second most frequent neurodegenerative disorder. Besides major deficits in motor coordination, patients may also display sensory and cognitive impairments, which are often overlooked despite being inherently part of the PD symptomatology. Amongst those symptoms, respiration, a key mechanism involved in the regulation of multiple physiological and neuronal processes, appears to be altered. Importantly, breathing patterns are highly correlated with the animal's behavioral states. This raises the question of the potential impact of behavioral state on respiration deficits in PD. To answer this question, we first characterized the respiratory parameters in a neurotoxin-induced rat model of PD (6-OHDA) across three different vigilance states: sleep, quiet waking and exploration. We noted a significantly higher respiratory frequency in 6-OHDA rats during quiet waking compared to Sham rats. A higher respiratory amplitude was also observed in 6-OHDA rats during both quiet waking and exploration. No effect of the treatment was noted during sleep. Given the relation between respiration and olfaction and the presence of olfactory deficits in PD patients, we then investigated the odor-evoked sniffing response in PD rats, using an odor habituation/cross-habituation paradigm. No substantial differences were observed in olfactory abilities between the two groups, as assessed through sniffing frequency. These results corroborate the hypothesis that respiratory impairments in 6-OHDA rats are vigilance-dependent. Our results also shed light on the importance of considering the behavioral state as an impacting factor when analyzing respiration.

An extension of PARAFAC to analyze multi-group three-way data

This paper introduces a novel methodology for analyzing three-way array data with a multi-group structure. Three-way arrays are commonly observed in various domains, including image analysis, chemometrics, and real-world applications. In this paper, we use a practical case study of process modeling in additive manufacturing, where batches are structured according to multiple groups. Vast volumes of data for multiple variables and process stages are recorded by sensors installed on the production line for each batch. For these three-way arrays, the link between the final product and the observations creates a grouping structure in the observations. This grouping may hamper gaining insight into the process if only some of the groups dominate the controlled variability of the products. In this study, we develop an extension of the PARAFAC model that takes into account the grouping structure of three-way data sets. With this extension, it is possible to estimate a model that is representative of all the groups simultaneously by finding their common structure. The proposed model has been applied to three simulation data sets and a real manufacturing case study. The capability to find the common structure of the groups is compared to PARAFAC and the insights into the importance of variables delivered by the models are discussed.

PH-Responsive Carrier-Free Polyphenol Nanoparticles Assembled by Oxidative Polymerization with Enhanced Stability and Antioxidant Activity for Improved Bioaccessibility.

Encapsulation of plant polyphenols with micro-/nano-carriers for enhanced bioavailability has been well documented, but the preparation of these carriers and subsequent loading of polyphenols is a multiple process, which is generally complicated with potentially unexpected negative effects on the bioactivity of the polyphenols. Here, we reported a convenient method to assemble carrier-free polyphenol nanoparticles (NPs) based on oxidative coupling polymerization. The effectiveness was assessed with five different polyphenols including pyrocatechol (PY), catechin (CA), epigallocatechin gallate (EGCG), tannic acid (TA), and proanthocyanidin (PC). The structural characteristics of these assembled nanoparticles (PY NPs, CA NPs, EG NPs, TA NPs, and PC NPs) were systematically analyzed with dynamic light scattering (DLS), transmission electron microscopy (TEM), UV-visible spectroscopy, and Fourier transform infrared spectroscopy (FTIR). All NPs were colloidally stable with varying NaCl concentrations from 0 to 300 mM, were acid-resistant and alkali-intolerant, and were suitable for oral administration. An array of antioxidant assays further confirmed the superior antioxidant capabilities of NPs over Trolox and polyphenol monomers, indicating that the oxidative polymerization of polyphenols did not compromise the polyphenol activity of NPs. The in vitro simulated digestion studies validated that these responsive NPs were actually gastrointestinal pH-responsive and applicable to the gastrointestinal physiological environment. The bioaccessibility assessments by using a static in vitro digestion model revealed that better results were achieved with NPs than polyphenol monomers, with TA NPs showing about 1.5-fold higher bioaccessibility than other polyphenol nanoparticles. The present study with five polyphenols demonstrated that the oxidative polymerization of polyphenols provides an effective platform to assemble various carrier-free NPs with enhanced antioxidant activity, favorable stability, and improved bioaccessibility, which could be used promisingly as a functional food ingredient in food matrices or as oral drug delivery candidates for helping to manage human health or treating various gastrointestinal disorders in both the pharmaceutical and nutritional fields.