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AbstractTwo strategies are proposed to design new hierarchically reinforced double-square tubes (HRDST). Strategy A: adding triangles from inside to outside in one direction. Strategy B: adding triangles along both the outer and inner quadrilateral directions at the same time. Their crashworthiness analyses are carried out under the conditions of the same wall thickness and the same mass. The results show that the proposed double square tubes, combined with the gradient hierarchical design, can effectively improve the crashworthiness of the structure under both conditions. The improvement of strategy B is more significant than that of strategy A. The energy absorption (EA), specific energy absorption (SEA), and crushing force efficiency (CFE) and initial peak crush force (IPCF) of HRDSTB-3 are improved by 2343.87%, 493.17%, 573.74% and 262.73%, respectively, under the same wall thickness. The EA, SEA, CFE of HRDSTB-3 also increased by 111.23%, 111.23%, and 226.34%, respectively, for the same mass, while the IPCF decreased by 35.27%. The parametric study shows that the effect of wall thickness on structural crashworthiness is significant, but the rate of increase between two adjacent wall thicknesses decreases as the wall thickness increases. The inner and outer edge length ratios (k) also have a substantial effect on structural crashworthiness, with SEA and CFE being 24.42% and 23.47% higher for k = 5/12 compared to k = 8/12 for HRDSTA-3, and 29.24% and 27.55% higher for k = 4/12 compared to k = 8/12 for HRDSTB-3. Finally, comparing HRDSTA-3 and HRDSTB-3 with other square-layered multicellular designs, the results show that the two designs proposed in this paper, combining double square tubes with gradient hierarchies, exhibit better crashworthiness. Compared with MSTL2-2, the SEA of HRDSTA-3 and HRDSTB-3 are 27.98% and 33.01% higher, respectively, and the CFE is 27.86% and 32.96% higher, respectively. [ABSTRACT FROM AUTHOR]

The Arctic is one of the most important regions in the world's oceans for understanding the impacts of a changing climate. Yet, it is also difficult to measure because of extreme weather and ice conditions. In this work, we directly compare four datasets from the Group for High-Resolution Sea Surface Temperature (GHRSST) with a NASA Saildrone deployment along the Alaskan Coast and the Bering Sea and Bering Strait. The four datasets used are the Remote Sensing Systems Microwave Infrared Optimally Interpolated (MWIR) product, the Canadian Meteorological Center (CMC) product, the Daily Optimally Interpolated Product (DOISST), and the Operational Sea Surface Temperature and Ice Analysis (OSTIA) product. Spatial sea surface temperature (SST) gradients were derived for both the Saildrone deployment and GHRSST products, with the GHRSST products collocated with the Saildrone deployment. Overall, statistics indicate that the OSTIA product had a correlation of 0.79 and a root mean square difference of 0.11 °C/km when compared with Saildrone. CMC had the highest correlation of 0.81. Scatter plots indicate that OSTIA had the slope closest to one, thus best reproducing the magnitudes of the Saildrone gradients. Differences increased at latitudes > 65°N where sea ice would have a greater impact. A trend analysis was then performed on the gradient fields. Overall, positive trends in gradients occurred in areas along the coastal regions. A negative trend occurred at approximately 60°N. A major finding of this study is that future work needs to revolve around the impact of changing ice conditions on SST gradients. Another major finding is that a northward shift in the southern ice edge occurred after 2010 with a maxima at approximately 2019. This indicates that the shift of the southern ice edge is not gradual but has dramatically increased over the last decade. Future work needs to revolve around examining the possible causes for this northward shift. [ABSTRACT FROM AUTHOR]

Gradients of smooth functions with nonindependent variables are relevant for exploring complex models and for the optimization of the functions subjected to constraints. In this paper, we investigate new and simple approximations and computations of such gradients by making use of independent, central, and symmetric variables. Such approximations are well suited for applications in which the computations of the gradients are too expansive or impossible. The derived upper bounds of the biases of our approximations do not suffer from the curse of dimensionality for any 2-smooth function, and they theoretically improve the known results. Also, our estimators of such gradients reach the optimal (mean squared error) rates of convergence (i.e., O (N − 1) ) for the same class of functions. Numerical comparisons based on a test case and a high-dimensional PDE model show the efficiency of our approach. [ABSTRACT FROM AUTHOR]

Network neuroscience offers a unique framework to understand the organizational principles of the human brain. Despite recent progress, our understanding of how the brain is modulated by focal lesions remains incomplete. Resection of the temporal lobe is the most effective treatment to control seizures in pharmaco-resistant temporal lobe epilepsy (TLE), making this syndrome a powerful model to study lesional effects on network organization in young and middle-aged adults. Here, we assessed the downstream consequences of a focal lesion and its surgical resection on the brain's structural connectome, and explored how this reorganization relates to clinical variables at the individual patient level. We included adults with pharmaco-resistant TLE (n = 37) who underwent anterior temporal lobectomy between two imaging time points, as well as age- and sex-matched healthy controls who underwent comparable imaging (n = 31). Core to our analysis was the projection of high-dimensional structural connectome data—derived from diffusion MRI tractography from each subject—into lower-dimensional gradients. We then compared connectome gradients in patients relative to controls before surgery, tracked surgically-induced connectome reconfiguration from pre- to postoperative time points, and examined associations to patient-specific clinical and imaging phenotypes. Before surgery, individuals with TLE presented with marked connectome changes in bilateral temporo-parietal regions, reflecting an increased segregation of the ipsilateral anterior temporal lobe from the rest of the brain. Surgery-induced connectome reorganization was localized to this temporo-parietal subnetwork, but primarily involved postoperative integration of contralateral regions with the rest of the brain. Using a partial least-squares analysis, we uncovered a latent clinical imaging signature underlying this pre- to postoperative connectome reorganization, showing that patients who displayed postoperative integration in bilateral fronto-occipital cortices also had greater preoperative ipsilateral hippocampal atrophy, lower seizure frequency and secondarily generalized seizures. Our results bridge the effects of focal brain lesions and their surgical resections with large-scale network reorganization and interindividual clinical variability, thus offering new avenues to examine the fundamental malleability of the human brain. [ABSTRACT FROM AUTHOR]

The human brain exhibits a diverse yet constrained range of activity states. While these states can be faithfully represented in a low-dimensional latent space, our understanding of the constitutive functional anatomy is still evolving. Here we applied dimensionality reduction to task-free and task fMRI data to address whether latent dimensions reflect intrinsic systems and if so, how these systems may interact to generate different activity states. We find that each dimension represents a dynamic activity gradient, including a primary unipolar sensory-association gradient underlying the global signal. The gradients appear stable across individuals and cognitive states, while recapitulating key functional connectivity properties including anticorrelation, modularity, and regional hubness. We then use dynamical systems modeling to show that gradients causally interact via state-specific coupling parameters to create distinct brain activity patterns. Together, these findings indicate that a set of dynamic, intrinsic spatial gradients interact to determine the repertoire of possible brain activity states.

The ecology of macrofauna on the sandy bottom of oceanic islands in the tropics has rarely been studied. The present study was conducted at Isla del Coco, Costa Rica, a tropical oceanic island, to determine how the soft-bottom macrofauna assemblages vary along different levels of ocean exposure and their associated environmental conditions. The macrofauna was collected from five grabs at each of the 27 stations (between 3 and 75 m deep) in April 2010. The broad-scale pattern consists of a gradual increase in the complexity of assemblages (taxonomical or feeding guilds in the sediment) from the inner part to the outside of the bays. The leading determinant of this pattern was the interplay between ocean exposure and sediment variation with depth that produces habitat heterogeneity. The main taxa responsible for differences between ocean exposure zones were the polychaetes Westheidesyllis heterocirrata and Magelona californica, the filter-feeding bivalve Gouldia californica, and the predatory isopod Eurydice caudata. Coarse bottoms had more mobile predators and suspension feeders, whereas passive suspension feeders or subsurface deposit feeders dominated fine sands. The deeper stations were dominated by organisms feeding actively on particles from the water or on the sediment surface. Moreover, more feeding guilds were found in deeper waters. Additionally, at the small-scale view (grabs within each station), macrofauna composition evidences a mosaic pattern, mainly at the inner and middle of the bays, caused by biological or environmental disturbances. [ABSTRACT FROM AUTHOR]

During the scale‐up of biopharmaceutical production processes, insufficiently predictable performance losses may occur alongside gradients and heterogeneities. To overcome such performance losses, tools are required to explain, predict, and ultimately prohibit inconsistencies between laboratory and commercial scale. In this work, we performed CHO fed‐batch cultivations in the single multicompartment bioreactor (SMCB), a new scale‐down reactor system that offers new access to study large‐scale heterogeneities in mammalian cell cultures. At volumetric power inputs of 20.4–1.5 W m−3, large‐scale characteristics like long mixing times and dissolved oxygen (DO) heterogeneities were mimicked in the SMCB. Compared to a reference bioreactor (REFB) set‐up, the conditions in the SMCB provoked an increase in lactate accumulation of up to 87%, an increased glucose uptake, and reduced viable cell concentrations in the stationary phase. All are characteristic for large‐scale performance. The unique possibility to distinguish between the effects of changing power inputs and observed heterogeneities provided new insights into the potential reasons for altered product quality attributes. Apparently, the degree of galactosylation in the evaluated glycan patterns changed primarily due to the different power inputs rather than the provoked heterogeneities. The SMCB system could serve as a potent tool to provide new insights into scale‐up behavior and to predict cell line‐specific drawbacks at an early stage of process development. [ABSTRACT FROM AUTHOR]

Recent work has recognized a gradient-like organization in cortical function, spanning from primary sensory to transmodal cortices. It has been suggested that this axis is aligned with regional differences in neurotransmitter expression. Given the abundance of dopamine D1-receptors (D1DR), and its importance for modulation and neural gain, we tested the hypothesis that D1DR organization is aligned with functional architecture, and that inter-regional relationships in D1DR co-expression modulate functional cross talk. Using the world's largest dopamine D1DR-PET and MRI database (N = 180%, 50% female), we demonstrate that D1DR organization follows a unimodal-transmodal hierarchy, expressing a high spatial correspondence to the principal gradient of functional connectivity. We also demonstrate that individual differences in D1DR density between unimodal and transmodal regions are associated with functional differentiation of the apices in the cortical hierarchy. Finally, we show that spatial co-expression of D1DR primarily modulates couplings within, but not between, functional networks. Together, our results show that D1DR co-expression provides a biomolecular layer to the functional organization of the brain. [ABSTRACT FROM AUTHOR]

Visual hallucinations in Parkinson's disease can be viewed from a systems-level perspective, whereby dysfunctional communication between brain networks responsible for perception predisposes a person to hallucinate. To this end, abnormal functional interactions between higher-order and primary sensory networks have been implicated in the pathophysiology of visual hallucinations in Parkinson's disease, however the precise signatures remain to be determined. Dimensionality reduction techniques offer a novel means for simplifying the interpretation of multidimensional brain imaging data, identifying hierarchical patterns in the data that are driven by both within- and between-functional network changes. Here, we applied two complementary non-linear dimensionality reduction techniques—diffusion-map embedding and t-distributed stochastic neighbour embedding (t-SNE)—to resting state functional MRI data, in order to characterize the altered functional hierarchy associated with susceptibility to visual hallucinations. Our study involved 77 people with Parkinson's disease (31 with hallucinations; 46 without hallucinations) and 19 age-matched healthy control subjects. In patients with visual hallucinations, we found compression of the unimodal-heteromodal gradient consistent with increased functional integration between sensory and higher order networks. This was mirrored in a traditional functional connectivity analysis, which showed increased connectivity between the visual and default mode networks in the hallucinating group. Together, these results suggest a route by which higher-order regions may have excessive influence over earlier sensory processes, as proposed by theoretical models of hallucinations across disorders. By contrast, the t-SNE analysis identified distinct alterations in prefrontal regions, suggesting an additional layer of complexity in the functional brain network abnormalities implicated in hallucinations, which was not apparent in traditional functional connectivity analyses. Together, the results confirm abnormal brain organization associated with the hallucinating phenotype in Parkinson's disease and highlight the utility of applying convergent dimensionality reduction techniques to investigate complex clinical symptoms. In addition, the patterns we describe in Parkinson's disease converge with those seen in other conditions, suggesting that reduced hierarchical differentiation across sensory-perceptual systems may be a common transdiagnostic vulnerability in neuropsychiatric disorders with perceptual disturbances. [ABSTRACT FROM AUTHOR]

Temporal lobe epilepsy, a common drug-resistant epilepsy in adults, is primarily a limbic network disorder associated with predominant unilateral hippocampal pathology. Structural MRI has provided an in vivo window into whole-brain grey matter structural alterations in temporal lobe epilepsy relative to controls, by either mapping (i) atypical inter-hemispheric asymmetry; or (ii) regional atrophy. However, similarities and differences of both atypical asymmetry and regional atrophy measures have not been systematically investigated. Here, we addressed this gap using the multisite ENIGMA-Epilepsy dataset comprising MRI brain morphological measures in 732 temporal lobe epilepsy patients and 1418 healthy controls. We compared spatial distributions of grey matter asymmetry and atrophy in temporal lobe epilepsy, contextualized their topographies relative to spatial gradients in cortical microstructure and functional connectivity calculated using 207 healthy controls obtained from Human Connectome Project and an independent dataset containing 23 temporal lobe epilepsy patients and 53 healthy controls and examined clinical associations using machine learning. We identified a marked divergence in the spatial distribution of atypical inter-hemispheric asymmetry and regional atrophy mapping. The former revealed a temporo-limbic disease signature while the latter showed diffuse and bilateral patterns. Our findings were robust across individual sites and patients. Cortical atrophy was significantly correlated with disease duration and age at seizure onset, while degrees of asymmetry did not show a significant relationship to these clinical variables. Our findings highlight that the mapping of atypical inter-hemispheric asymmetry and regional atrophy tap into two complementary aspects of temporal lobe epilepsy-related pathology, with the former revealing primary substrates in ipsilateral limbic circuits and the latter capturing bilateral disease effects. These findings refine our notion of the neuropathology of temporal lobe epilepsy and may inform future discovery and validation of complementary MRI biomarkers in temporal lobe epilepsy.

The intrinsic heterogeneity of bacterial niches should be retained in in vitro cultures to represent the complex microbial ecology. As a case study, mucin‐containing hydrogels ‐CF‐Mu3Gel ‐ are generated by diffusion‐induced gelation, bioinspired on cystic fibrosis (CF) mucus, and a microbial niche challenging current therapeutic strategies. At breathing frequency, CF‐Mu3Gel exhibits a G′ and G″ equal to 24 and 3.2 Pa, respectively. Notably, CF‐Mu3Gel exhibits structural gradients with a gradual reduction of oxygen tension across its thickness (280–194 µmol L−1). Over the culture period, a steep decline in oxygen concentration occurs just a few millimeters below the air–mucus interface in CF‐Mu3Gel, similar to those of CF airway mucus. Importantly, the distinctive features of CF‐Mu3Gel significantly influence bacterial organization and antimicrobial tolerance in mono‐ and co‐cultures of Staphylococcus aureus and Pseudomonas aeruginosa that standard cultures are unable to emulate. The antimicrobial susceptibility determined in CF‐Mu3Gel corroborates the mismatch on the efficacy of antimicrobial treatment between planktonically cultured bacteria and those in patients. With this example‐based research, new light is shed on the understanding of how the substrate influences microbial behavior, paving the way for improved fundamental microbiology studies and more effective drug testing and development. [ABSTRACT FROM AUTHOR]

Macroecology and biogeography have made significant strides in understanding the patterns and processes underlying biodiversity, yet the problem of underdetermination (the Duhem–Quine thesis) remains an ongoing challenge. Underdetermination arises when multiple explanations are consistent with the observed data, resulting in challenges in theory and model development and testing. Here, we explore the different forms of underdetermination in macroecology and biogeography and their implications for understanding biodiversity patterns. We highlight the gradient ranging from optimistic to pessimistic views in addressing the problem, coupled then with realistic and instrumentalist scientific reasonings, illustrating these issues by evaluating how underdetermination may affect our understanding of the latitudinal diversity gradient. We show how evolution and diversification introduce a new and unexpected source of underdetermination, and that unpacking the underdetermination problem in macroecology and biogeography requires deconstruction methods in a more comprehensive and integrated approach that considers both hierarchical scale and phylogenetic relationships between organisms and trait‐based explanations. [ABSTRACT FROM AUTHOR]

Gene expression plays a critical role in the pathogenesis of Parkinson's disease (PD). How gene expression profiles are correlated with functional‐metabolic architecture remains obscure. We enrolled 34 PD patients and 25 age‐and‐sex‐matched healthy controls for simultaneous 18F‐FDG‐PET/functional MRI scanning during resting state. We investigated the functional gradients and the ratio of standard uptake value. Principal component analysis was used to further combine the functional gradients and glucose metabolism into functional‐metabolic architecture. Using partial least squares (PLS) regression, we introduced the transcriptomic data from the Allen Institute of Brain Sciences to identify gene expression patterns underlying the affected functional‐metabolic architecture in PD. Between‐group comparisons revealed significantly higher gradient variation in the visual, somatomotor, dorsal attention, frontoparietal, default mode, and subcortical network (pFDR <.048) in PD. Increased FDG‐uptake was found in the somatomotor and ventral attention network while decreased FDG‐uptake was found in the visual network (pFDR <.008). Spatial correlation analysis showed consistently affected patterns of functional gradients and metabolism (p = 2.47 × 10−8). PLS analysis and gene ontological analyses further revealed that genes were mainly enriched for metabolic, catabolic, cellular response to ions, and regulation of DNA transcription and RNA biosynthesis. In conclusion, our study provided genetic pathological mechanism to explain imaging‐defined brain functional‐metabolic architecture of PD. [ABSTRACT FROM AUTHOR]

Abstract Multiphasic scaffolds with tailored gradient features hold significant promise for tissue regeneration applications. Herein, this work reports the transformation of two‐dimensional (2D) layered fiber mats into three‐dimensional (3D) multiphasic scaffolds using a ‘solids‐of‐revolution’ inspired gas‐foaming expansion technology. These scaffolds feature precise control over fiber alignment, pore size, and regional structure. Manipulating nanofiber mat layers and Pluronic F127 concentrations allows further customization of pore size and fiber alignment within different scaffold regions. The cellular response to multiphasic scaffolds demonstrates that the number of cells migrated and proliferated onto the scaffolds is mainly dependent on the pore size rather than fiber alignment. In vivo subcutaneous implantation of multiphasic scaffolds to rats reveals substantial cell infiltration, neo tissue formation, collagen deposition, and new vessel formation within scaffolds, greatly surpassing the capabilities of traditional nanofiber mats. Histological examination indicates the importance of optimizing pore size and fiber alignment for the promotion of cell infiltration and tissue regeneration. Overall, these scaffolds have potential applications in tissue modeling, studying tissue‐tissue interactions, interface tissue engineering, and high‐throughput screening for optimized tissue regeneration.

The Arctic is one of the most important regions in the world’s oceans for understanding the impacts of a changing climate. Yet, it is also difficult to measure because of extreme weather and ice conditions. In this work, we directly compare four datasets from the Group for High-Resolution Sea Surface Temperature (GHRSST) with a NASA Saildrone deployment along the Alaskan Coast and the Bering Sea and Bering Strait. The four datasets used are the Remote Sensing Systems Microwave Infrared Optimally Interpolated (MWIR) product, the Canadian Meteorological Center (CMC) product, the Daily Optimally Interpolated Product (DOISST), and the Operational Sea Surface Temperature and Ice Analysis (OSTIA) product. Spatial sea surface temperature (SST) gradients were derived for both the Saildrone deployment and GHRSST products, with the GHRSST products collocated with the Saildrone deployment. Overall, statistics indicate that the OSTIA product had a correlation of 0.79 and a root mean square difference of 0.11 °C/km when compared with Saildrone. CMC had the highest correlation of 0.81. Scatter plots indicate that OSTIA had the slope closest to one, thus best reproducing the magnitudes of the Saildrone gradients. Differences increased at latitudes > 65°N where sea ice would have a greater impact. A trend analysis was then performed on the gradient fields. Overall, positive trends in gradients occurred in areas along the coastal regions. A negative trend occurred at approximately 60°N. A major finding of this study is that future work needs to revolve around the impact of changing ice conditions on SST gradients. Another major finding is that a northward shift in the southern ice edge occurred after 2010 with a maxima at approximately 2019. This indicates that the shift of the southern ice edge is not gradual but has dramatically increased over the last decade. Future work needs to revolve around examining the possible causes for this northward shift.

Gradients of smooth functions with nonindependent variables are relevant for exploring complex models and for the optimization of the functions subjected to constraints. In this paper, we investigate new and simple approximations and computations of such gradients by making use of independent, central, and symmetric variables. Such approximations are well suited for applications in which the computations of the gradients are too expansive or impossible. The derived upper bounds of the biases of our approximations do not suffer from the curse of dimensionality for any 2-smooth function, and they theoretically improve the known results. Also, our estimators of such gradients reach the optimal (mean squared error) rates of convergence (i.e., O(N−1)) for the same class of functions. Numerical comparisons based on a test case and a high-dimensional PDE model show the efficiency of our approach.

Australia-wide consensus was reached on seven core concepts of physiology. The "movement of substances" core concept with the descriptor "the movement of substances (ions or molecules) is a fundamental process that occurs at all levels of organization in the organism" was unpacked by a team of three Australian physiology educators from the Delphi Task Force into hierarchical levels. There were 10 themes and 23 subthemes arranged in a hierarchy, some 3 levels deep. Using a 5-point Likert scale, the unpacked core concept was then rated for level of importance for students to understand (ranging from 1 = Essential to 5 = Not Important) and level of difficulty for students (ranging from 1 = Very Difficult to 5 = Not Difficult) by the 23 physiology educators from different Australian universities, all with a broad range of teaching and curriculum experience. Survey data were analyzed using a one-way ANOVA to compare between and within concept themes. The main themes all were rated on average as important. There was a wide range of difficulty ratings and more variation for this concept compared with the other core concepts. This may in part be due to the physical forces such as gravity, electrochemistry, resistance, and thermodynamics that underpin this concept, which in themselves are inherently complex. Separation of concepts into subthemes can help prioritize learning activities and time spent on difficult concepts. Embedding of core concepts across curricula will allow commonality and consistency between programs of study and inform learning outcomes, assessment, and teaching and learning activities. NEW & NOTEWORTHY This article unpacks the core concept of the "movement of substances" within the body, with the aim to produce a resource that will help guide the teaching of physiology at tertiary education institutes in Australia. The concept introduces fundamental knowledge of the factors that drive substance movement and then applies them in physiological contexts. [ABSTRACT FROM AUTHOR]

Conducting a quantitative assessment of water yield in mountainous areas is crucial for the management, development, and sustainable utilization of water resources. The Hengduan Mountains Region (HDMR) is a significant water-supporting area characterized by complex topography and climate changes. To analyze the spatial and temporal variations of water yield in the HDMR from 2001 to 2020, we employed the InVEST model and examined the influencing factors in conjunction with the elevation gradient. Our results indicate that: (1) The water yield in the Hengduan Mountains decreases from southeast to northwest, with the southwestern and eastern regions having high water yield values, and the high-altitude areas in the northwestern part having low water yield values. (2) The water yield in the Hengduan Mountains exhibits a decreasing trend followed by an increasing trend from 2001 to 2020, with the lowest level in 2011 and higher levels in 2004, 2018, and 2020. (3) Pixel-based trend analysis demonstrates a decreasing trend in water yield in the central and western parts of the study area, while the eastern part shows an increasing trend. (4) The climatic components, particularly precipitation, predominantly influence the spatial and temporal variations of water yield in the Transverse Mountain region. In most areas, evapotranspiration and land surface temperature have a negative impact on water yield. (5) Water yield tends to decrease and then increase on the altitudinal gradient, with precipitation and actual evapotranspiration being the factors directly affecting water yield, and land surface temperature and the proportion of forested areas having a significant indirect effect on water yield. Our study provides a scientific basis for water resources management and sustainable development in the Hengduan Mountains. [ABSTRACT FROM AUTHOR]

The experimental study of learning and plasticity has always been driven by an implicit question: how can physiological changes be adaptive and improve performance? For example, in Hebbian plasticity only synapses from presynaptic neurons that were active are changed, avoiding useless changes. Similarly, in dopamine‐gated learning synapse changes depend on reward or lack thereof and do not change when everything is predictable. Within machine learning we can make the question of which changes are adaptive concrete: performance improves when changes correlate with the gradient of an objective function quantifying performance. This result is general for any system that improves through small changes. As such, physiology has always implicitly been seeking mechanisms that allow the brain to approximate gradients. Coming from this perspective we review the existing literature on plasticity‐related mechanisms, and we show how these mechanisms relate to gradient estimation. We argue that gradients are a unifying idea to explain the many facets of neuronal plasticity. [ABSTRACT FROM AUTHOR]

For decades, 3D bioprinting has offered a revolutionising approach to combine living cells and biomaterials to engineer complex, yet functional constructs. However, traditional 3D bioprinting platforms fall short of the ability to pattern complex gradients of biomaterials, cells, and ultimately bio-physical properties to drive tissue formation and regeneration. Recently, 3D microfluidic-assisted bioprinting (3DMB) has risen as a new hybrid approach for the fabrication of physiologically relevant tissues, adopting a microfluidic chip as functional printhead to achieve hierarchical patterning of bioinks and precise control over the microscale architecture of printed constructs, enabling the creation of multi-layered tissues. This review explores recent advancements in graded biomaterial patterning using microfluidic-assisted spinning and novel 3D bioprinting technologies. The physiological hierarchical arrangement of human tissues and the crucial role of biomaterials in achieving ordered assembly is hereby discussed. Lastly, the integration of microfluidic-assisted techniques with new bioprinting platforms is highlighted, examining the latest advancements in tissue regeneration and disease modelling.

In recent years, multi-lingual character segmentation and recognition has attracted the wide range of researchers. However, the variations in the structures of characters in different languages, writing styles of different people and font sizes challenges that need further enhancement. Towards such objective, in this paper, we have proposed a novel multi-lingual handwritten character recognition framework for three different languages such as Bangla, Kannada and Telugu. At segmentation phase, this framework performs both word and character segmentation with the help of an Adaptive Projection Profiling (APP) and Edge Density Filter (EDF) respectively. Further at the recognition phase, we propose to use gradient based feature descriptors to extract a Composite Feature Vector (CFV) from handwritten character images, which are then fed to Support Vector Machine (SVM) algorithm for recognition. At experimental evaluation, we have simulated the proposed model over three different language scripts. The experimental results show that the proposed model outperforms the conventional method with an average improvement in the recognition accuracy of 3% for both cross validation and test simulations. [ABSTRACT FROM AUTHOR]

Spatial patterns of body size are associated with environmental factors like temperature, seasonality, precipitation, resources, and altitude, among the most relevant. Latitudinal size patterns have been extensively studied. Studies on altitudinal gradients of body size, however, are relatively few. Besides, it is still unclear whether there is variation in the relationship between environmental factors and body size of species, or correlations within different altitudes. China provides a good opportunity to assess the altitudinal gradients of body size, because the entire terrain of China changes from high altitude in the west to low altitude in the east, with three natural terrain stages (low: less than 660 m.a.s.l.; medium: 660–2600 m.a.s.l.; and high: more than 2600 m.a.s.l.). Similarly, lizards are distributed across a wide altitudinal range (from −154.31 m to ~6000 m above sea level). We examined 211 lizard species in China and assessed the altitudinal gradients of Chinese lizard body sizes at assemblage and interspecific levels. Piecewise structural equation models (pSEM) were used to investigate the direct and indirect relationships between body size and environmental factors within different terrains (low, medium, and high altitudes). Overall, we found that body size in Chinese lizards decreases with increasing altitude. However, there were variations in the altitudinal gradients and drivers within the three terrain stages. Altitude has both direct (medium and low stages) and indirect (high stages) effects in shaping lizard size. We established that body size increased with increasing altitudes in the low and medium terrain stages. Seasonality had different effects on body size in medium (positively) and low (negatively) stages. However, among the three terrain stages, temperature was consistently negatively correlated with lizard size. Overall, we identified complex patterns and drivers of altitudinal gradients of body size within the three terrain stages, probably due to the different environmental conditions across altitudes. [ABSTRACT FROM AUTHOR]

We analyze the data-dependent capacity of neural networks and assess anomalies in inputs from the perspective of networks during inference. The notion of data-dependent capacity allows for analyzing the knowledge base of a model populated by learned features from training data. We define purview as the additional capacity necessary to characterize inference samples that differ from the training data. To probe the purview of a network, we utilize gradients to measure the amount of change required for the model to characterize the given inputs more accurately. To eliminate the dependency on ground-truth labels in generating gradients, we introduce confounding labels that are formulated by combining multiple categorical labels. We demonstrate that our gradient-based approach can effectively differentiate inputs that cannot be accurately represented with learned features. We utilize our approach in applications of detecting anomalous inputs, including out-of-distribution, adversarial, and corrupted samples. Our approach requires no hyperparameter tuning or additional data processing and outperforms state-of-the-art methods by up to 2.7%, 19.8%, and 35.6% of AUROC scores, respectively.

We combined domestic ground-based and satellite magnetic measurements to create a regional three-dimensional surface Spline (3DSS) gradient model of the main geomagnetic field over the Chinese continent. To improve the precision of the model, we considered the data gap between the ground and satellite data. We compared and analyzed the results of the Taylor polynomial, surface Spline, and CHAOS-6 (the CHAMP, Ørsted and SAC-C model of Earth’s magnetic field) gradient models. Results showed that the gradients in the south−north and east−west directions of the four models were consistent. The 3DSS model was able to express not only gradients at different altitudes, but also average gradients inside the research area. The two Spline models were able to capture more information on gradient anomalies than were the fitted models. Strong local anomalies were observed in northern Xinjiang, Beijing, and the junction area between Jiangsu and Zhejiang, and the total intensity F decreased whereas the altitude increased. The gradient decreased by 21.69% in the south−north direction and increased by 11.78% in the east−west direction. In addition, the altitude gradient turned from negative to positive while the altitude increased. The Spline model and the two fitted models differed mainly in the field sources they expressed and the modeling theory.

The cerebral cortex is characterized as the integration of distinct functional principles that correspond to basic primary functions, such as vision and movement, and domain‐general functions, such as attention and cognition. Diffusion embedding approach is a novel tool to describe transitions between different functional principles, and has been successively applied to investigate pathological conditions in between‐group designs. What still lacking and urgently needed is the efficacy of this method to differentiate within‐subject circumstances. In this study, we applied the diffusion embedding to eyes closed (EC) and eyes on (EO) resting‐state conditions from 145 participants. We found significantly lower within‐network dispersion of visual network (VN) (p = 7.3 × 10−4) as well as sensorimotor network (SMN) (p = 1 × 10−5) and between‐network dispersion of VN (p = 2.3 × 10−4) under EC than EO, while frontoparietal network (p = 9.2 × 10−4) showed significantly higher between‐network dispersion during EC than EO. Test–retest reliability analysis further displayed fair reliability (intraclass correlation coefficient [ICC] < 0.4) of the network dispersions (mean ICC = 0.116 ± 0.143 [standard deviation]) except for the within‐network dispersion of SMN under EO (ICC = 0.407). And the reliability under EO was higher but not significantly higher than reliability under EC. Our study demonstrated that the diffusion embedding approach that shows fair reliability is capable of distinguishing EC and EO resting‐state conditions, such that this method could be generalized to other within‐subject designs. [ABSTRACT FROM AUTHOR]

Designing components for thermo-mechanical loads is a challenging process. While mechanical loads like forces or pressure demand a stiff and thick-walled design, thermal loads create temperature gradients, resulting in thermo-mechanical stress from the structure's temperature proportional and, therefore, uneven expansion. In contrast to a pure mechanical load case, an initial design before optimization can already include stress levels beyond the limit of the material. Therefore, common optimization approaches for a preliminary design use exemplary systems with low-temperature gradients, so thermal stresses do not exceed the limit. From there, energy density is used to calculate the topology optimizations sensitivity and therefore decide which elements to remove and which to keep. This paper describes a novel approach for reducing thermo-mechanical stress by following the stress corresponding temperature gradients from the heat source to the sink to calculate a new sensitivity that helps to grow cooling channels. The optimization is exemplarily shown on a piston for internal combustion engines. While handling delta temperatures of 600K, results show a reduction in thermo-mechanical stress while reducing the component's mass. Because the approach reduces critical stress in a component, it allows the initial design (before the topology optimization) to have stress levels way above yield strength. [ABSTRACT FROM AUTHOR]

The isolation of single homologs of polyethylene glycol by preparative reversed-phase chromatography is investigated. A thermodynamic model developed accurately previously describes the retention times of individual homologs as function of their size, temperature, and mobile phase composition under linear, diluted conditions. The model is extended to predict limiting retention times for linear gradient operation in preparative applications. Isocratic and gradient-based separations are studied under strongly overloaded conditions. Baseline separation of homologs up to 3000 g/mol is demonstrated. Quantitative production of pure single homologs up to molar weights of 1000 g/mol was performed using an automated setup. [ABSTRACT FROM AUTHOR]

Planar cell polarity (PCP), the coordinated orientation of structures such as cilia, mammalian hairs or insect bristles, depends on at least two molecular systems. We have argued that these two systems use similar mechanisms; each depending on a supracellular gradient of concentration that spans a field of cells. In a linked paper, we studied the Dachsous/Fat system. We found a graded distribution of Dachsous in vivo in a segment of the pupal epidermis in the abdomen of Drosophila. Here we report a similar study of the key molecule for the Starry Night/Frizzled or ‘core’ system. We measure the distribution of the receptor Frizzled on the cell membranes of all cells of one segment in the living pupal abdomen of Drosophila. We find a supracellular gradient that falls about 17% in concentration from the front to the rear of the segment. We present some evidence that the gradient then resets in the most anterior cells of the next segment back. We find an intracellular asymmetry in all the cells, the posterior membrane of each cell carrying about 22% more Frizzled than the anterior membrane. These direct molecular measurements add to earlier evidence that the two systems of PCP act independently.

The default-mode network (DMN) is a distributed functional brain system integral for social and higher-order cognition in humans with implications in a myriad of neuropsychological disorders. In this study, we compared the functional architecture of the DMN between humans and marmosets to assess their similarities and differences using joint gradients. This approach permits simultaneous large-scale mapping of functional systems across the cortex of humans and marmosets, revealing evidence of putative homologies between them. In doing so, we find that the DMN architecture of the marmoset exhibits differences along its anterolateral-posterior axis. Specifically, the anterolateral node of the DMN (dorsolateral prefrontal cortex) displayed weak connections and inconsistent connection topographies as compared to its posterior DMN-nodes (posterior cingulate and posterior parietal cortices). We also present evidence that the marmoset medial prefrontal cortex and temporal lobe areas correspond to other macroscopical distributed functional systems that are not part of the DMN. Given the importance of the marmoset as a pre-clinical primate model for higher-order cognitive functioning and the DMN's relevance to cognition, our results suggest that the marmoset may lack the capacity to integrate neural information to subserve cortical dynamics that are necessary for supporting diverse cognitive demands.

Understanding cortical topographic organization and how it supports complex perceptual and cognitive processes is a fundamental question in neuroscience. Previous work has characterized functional gradients that demonstrate large-scale principles of cortical organization. How these gradients are modulated by rich ecological stimuli remains unknown. Here, we utilize naturalistic stimuli via movie-fMRI to assess macroscale functional organization. We identify principal movie gradients that delineate separate hierarchies anchored in sensorimotor, visual, and auditory/language areas. At the opposite/heteromodal end of these perception-to-cognition axes, we find a more central role for the frontoparietal network along with the default network. Even across different movie stimuli, movie gradients demonstrated good reliability, suggesting that these hierarchies reflect a brain state common across different naturalistic conditions. The relative position of brain areas within movie gradients showed stronger and more numerous correlations with cognitive behavioral scores compared to resting state gradients. Together, these findings provide an ecologically valid representation of the principles underlying cortical organization while the brain is active and engaged in multimodal, dynamic perceptual and cognitive processing.

Coastal upwelling regions are one of the most dynamic areas of the world's oceans. The California and Baja California Coasts are impacted by both coastal upwelling and the California Current, leading to frontal activity that is captured by gradients in both Sea Surface Temperature (SST) and Sea Surface Salinity (SSS). Satellite data are a great source of spatial data to study fronts. However, biases near coastal areas and coarse resolutions can impair its usefulness in upwelling areas. In this work gradients in SST from NASA Multi-Scale Ultra-High Resolution (MUR) and in two SSS products derived from the Soil Moisture Active Passive (SMAP) NASA mission are compared directly with gradients derived from the Saildrone uncrewed vehicles to validate the gradients as well as to assess their ability to detect known frontal features. The three remotely sensed data sets (MURSST/JPL, SMAP SSS/RSS, SMAP SSS) were co-located with the Saildrone data prior to the calculation of the gradients. Wavelet analysis is used to determine how well the satellite derived SST and SSS products are reproducing the Saildrone derived gradients. Overall results indicate the remote sensing products are reproducing features of known areas of coastal upwelling. Differences between the SST and SSS gradients are mainly associated with the limitations of the microwave derived SSS coverage near land and its reduced spatial resolution. The results are promising for using remote sensing data sets to monitor frontal structure along the California Coast and the application to long term changes in coastal upwelling and dynamics. [ABSTRACT FROM AUTHOR]

In magnetic resonance imaging (MRI), spatial field gradients are applied along each axis to encode the location of the nuclear spin in the frequency domain. During recent years, the development of new gradient technologies has been focused on the generation of stronger and faster gradient fields for imaging with higher spatial and temporal resolution. This benefits imaging methods, such as brain diffusion and functional MRI, and enables human imaging at ultra‐high field MRI. In addition to improving gradient performance, new technologies have been presented to minimize peripheral nerve stimulation and gradient‐related acoustic noise, both generated by the rapid switching of strong gradient fields. This review will provide a general background on the gradient system and update on the state‐of‐the‐art gradient technology. Evidence Level: 5 Technical Efficacy: Stage 1 [ABSTRACT FROM AUTHOR]

Gradient-based analyses have contributed to the description of cerebellar functional neuroanatomy. More recently, functional gradients of the cerebellum have been used as a multi-purpose tool for neuroimaging research. Here, we provide an overview of the many practical applications of cerebellar functional gradient analyses. These practical applications include examination of intra-cerebellar and cerebellar-extracerebellar organization; transformation of functional gradients into parcellations with discrete borders; projection of functional gradients calculated within cerebellar structures to other extracerebellar structures; interpretation of cerebellar neuroimaging findings using qualitative and quantitative methods; detection of differences in patient populations; and other more complex practical applications of cerebellar gradient-based analyses. This review may serve as an introduction and catalog of options for neuroscientists who wish to design and analyze imaging studies using functional gradients of the cerebellum. [ABSTRACT FROM AUTHOR]

In this paper, the problem of estimating the dominant image orientation (DIO) is experimentally investigated using the characteristics of the scattering ellipse of the gradient field components. According to these characteristics, the angle of rotation, the parameters of the shape of the Weibull distribution characterizing the blurring of the image, as well as the assessment of the sharpness of the DIO angle determination, are estimated. The results of an experimental study of the properties of DIO in various situations, such as the implementation of rotations of texture and other types of images by various methods, the presence of distorting noise, etc. are given. Using the Photoshop software system, the results of applying the previously proposed approach to assessing the quality of image rotation algorithms called the "backlash method", are studied. [ABSTRACT FROM AUTHOR]

Galactic cosmic ray (GCR) solar diurnal variation data recorded by shielded ion chambers at Cheltenham/Fredericksburg (CH-IC) and Yakutsk (Yak-IC) are corrected for diurnal temperature variation in upper atmosphere and used to calculate the ratio α of GCR free paths normal (λ ⊥) and parallel (λ||) to mean interplanetary magnetic field (IMF) B for 1936–2006; α is an important parameter in theories for GCR modulations in heliosphere including anisotropies. Also, neutron monitor (NM) data at low latitudes (Huancayo / Haleakala) are analyzed for 1953–2006; they are not affected by temperature variation in upper atmosphere. Calculations assume negligible symmetric latitude GCR density gradient (Gθs) based on observational evidence. Results support Ahluwalia and Modzelewska (2020) inference for global network of NMs and Nagoya vertical muon telescope (NagV-MT) that α depends on polarity of B at Earth orbit. GCR modulation theories quote α values much smaller than those computed by us. Flat heliosphere current sheet (HCS) and Master equations derived by Ahluwalia and Dorman (1997) are used for computing α and study its correlation with solar activity for positive (p) and negative (n) polarity intervals of B at 1 AU; B points outward/ inward from the Sun during p/n interval in northern hemisphere, IMF polarity changes sign near sunspot number (SSN) maximum. The results challenge validity of the conceptual understanding of GCR modulation processes in the heliosphere, pointing to a need for an acceptable theory to explain empirical results reported in this paper. We propose two Ulysses-like spacecrafts be put in a fast scan mode, making complimentary observations in solar north and south hemispheres for at least a complete solar cycle to obtain more precise information about temporal variations of GCR latitude gradients with solar activity and its dependence on GCR rigidity, facilitating a physically meaningful computation of α. [ABSTRACT FROM AUTHOR]

Abstract Knee osteoarthritis is the most common joint disease. It causes pain and suffering for affected patients and is the source of major economic costs for healthcare systems. Despite ongoing research, there is a lack of knowledge regarding disease mechanisms, biomarkers, and possible cures. Current treatments do not fulfill patients’ long-term needs, and it often requires invasive surgical procedures with subsequent long periods of rehabilitation. Researchers and companies worldwide are working to find a suitable cell source to engineer or regenerate a functional and healthy articular cartilage tissue to implant in the damaged area. Potential cell sources to accomplish this goal include embryonic stem cells, mesenchymal stem cells, or induced pluripotent stem cells. The differentiation of stem cells into different tissue types is complex, and a suitable concentration range of specific growth factors is vital. The cellular microenvironment during early embryonic development provides crucial information regarding concentrations of signaling molecules and morphogen gradients as these are essential inducers for tissue development. Thus, morphogen gradients implemented in developmental protocols aimed to engineer functional cartilage tissue can potentially generate cells comparable to those within native cartilage. In this review, we have summarized the problems with current treatments, potential cell sources for cell therapy, reviewed the progress of new treatments within the regenerative cartilage field, and highlighted the importance of cell quality, characterization assays, and chemically defined protocols.

Conducting a quantitative assessment of water yield in mountainous areas is crucial for the management, development, and sustainable utilization of water resources. The Hengduan Mountains Region (HDMR) is a significant water-supporting area characterized by complex topography and climate changes. To analyze the spatial and temporal variations of water yield in the HDMR from 2001 to 2020, we employed the InVEST model and examined the influencing factors in conjunction with the elevation gradient. Our results indicate that: (1) The water yield in the Hengduan Mountains decreases from southeast to northwest, with the southwestern and eastern regions having high water yield values, and the high-altitude areas in the northwestern part having low water yield values. (2) The water yield in the Hengduan Mountains exhibits a decreasing trend followed by an increasing trend from 2001 to 2020, with the lowest level in 2011 and higher levels in 2004, 2018, and 2020. (3) Pixel-based trend analysis demonstrates a decreasing trend in water yield in the central and western parts of the study area, while the eastern part shows an increasing trend. (4) The climatic components, particularly precipitation, predominantly influence the spatial and temporal variations of water yield in the Transverse Mountain region. In most areas, evapotranspiration and land surface temperature have a negative impact on water yield. (5) Water yield tends to decrease and then increase on the altitudinal gradient, with precipitation and actual evapotranspiration being the factors directly affecting water yield, and land surface temperature and the proportion of forested areas having a significant indirect effect on water yield. Our study provides a scientific basis for water resources management and sustainable development in the Hengduan Mountains.

The formation of identical twins from a single egg has fascinated developmental biologists for a very long time. Previous work had shown that Xenopus blastulae bisected along the dorsal-ventral (D-V) midline (i.e., the sagittal plane) could generate twins but at very low frequencies. Here, we have improved this method by using an eyelash knife and changing saline solutions, reaching frequencies of twinning of 50% or more. This allowed mechanistic analysis of the twinning process. We unexpectedly observed that the epidermis of the resulting twins was asymmetrically pigmented at the tailbud stage of regenerating tadpoles. This pigment was entirely of maternal (oocyte) origin. Bisecting the embryo generated a large wound, which closed from all directions within 60 minutes, bringing cells normally fated to become Spemann organizer in direct contact with predicted ventral-most cells. Lineage-tracing analyses at the four-cell stage showed that in regenerating embryos midline tissues originated from the dorsal half, while the epidermis was entirely of ventral origin. Labeling of D-V segments at the 16-cell stage showed that the more pigmented epidermis originated from the ventral-most cells, while the less-pigmented epidermis arose from the adjoining ventral segment. This suggested a displacement of the organizer by 90°. Studies with the marker Chordin and phospho-Smad1/5/8 showed that in half embryos a new D-V gradient is intercalated at the site of the missing half. The displacement of self-organizing morphogen gradients uncovered here may help us understand not only twin formation in amphibians, but also rare cases of polyembryony.

The hippocampus is a uniquely infolded allocortical structure in the medial temporal lobe that consists of the microstructurally and functionally distinct subregions: subiculum, cornu ammonis, and dentate gyrus. The hippocampus is a remarkably plastic region that is implicated in learning and memory. At the same time it has been shown that hippocampal subregion volumes are heritable, and that genetic expression varies along a posterior to anterior axis. Here, we studied how a heritable, stable, hippocampal organisation may support its flexible function in healthy adults. Leveraging the twin set-up of the Human Connectome Project with multimodal neuroimaging, we observed that the functional connectivity between hippocampus and cortex was heritable and that microstructure of the hippocampus genetically correlated with cortical microstructure. Moreover, both functional and microstructural organisation could be consistently captured by anterior-to-posterior and medial-to-lateral axes across individuals. However, heritability of functional, relative to microstructural, organisation was found reduced, suggesting individual variation in functional organisation may be explained by experience-driven factors. Last, we demonstrate that structure and function couple along an inherited macroscale organisation, suggesting an interplay of stability and plasticity within the hippocampus. Our study provides new insights on the heritability of the hippocampal of the structure and function within the hippocampal organisation.

The human brain exhibits a diverse yet constrained range of activity states. While these states can be faithfully represented in a low-dimensional latent space, our understanding of the constitutive functional anatomy is still evolving. Here we applied dimensionality reduction to task-free and task fMRI data to address whether latent dimensions reflect intrinsic systems and if so, how these systems may interact to generate different activity states. We find that each dimension represents a dynamic activity gradient, including a primary unipolar sensory-association gradient underlying the global signal. The gradients appear stable across individuals and cognitive states, while recapitulating key functional connectivity properties including anticorrelation, modularity, and regional hubness. We then use dynamical systems modeling to show that gradients causally interact via state-specific coupling parameters to create distinct brain activity patterns. Together, these findings indicate that a set of dynamic, intrinsic spatial gradients interact to determine the repertoire of possible brain activity states.

Previous papers have shown the impact of partial convergence of discretized PDEs on the accuracy of tangent and adjoint linearizations. A series of papers suggested linearization of the fixed-point iteration used in the solution process as a means of computing the sensitivities rather than linearizing the discretized PDE, as the lack of convergence of the nonlinear problem indicates that the discretized form of the governing equations has not been satisfied. These works showed that the accuracy of an approximate linearization depends in part on the convergence of the nonlinear system. This work shows an error analysis of the impact of the approximate linearization and the convergence of the nonlinear problem for both the tangent and adjoint modes and provides a series of results for an exact Newton solver, an inexact Newton solver, and a low-storage explicit Runge-Kutta scheme to confirm the error analyses. [ABSTRACT FROM AUTHOR]