Cell Packing Research Articles

Histological analysis of retinal development and remodeling in the brown anole lizard (Anolis sagrei).

The fovea, a pit in the retina, is crucial for high-acuity vision in humans and is found in the eyes of other vertebrates, including certain primates, birds, lizards, and fish. Despite its importance for vision, our understanding of the mechanisms involved in fovea development remains limited. Widely used ocular research models lack a foveated retina, and studies on fovea development are mostly limited to histological and molecular studies in primates. As a first step toward elucidating fovea development in nonprimate vertebrates, we present a detailed histological atlas of retina and fovea development in the bifoveated Anolis sagrei lizard, a novel reptile model for fovea research. We test the hypothesis that retinal remodeling, leading to fovea formation and photoreceptor cell packing, is related to asymmetric changes in eye shape. Our findings show that anole retina development follows the typical spatiotemporal patterning observed in most vertebrates: retinal neurogenesis starts in the central retina, progresses through the temporal retina, and finishes in the nasal retina. However, the areas destined to become the central or temporal fovea differentiate earlier than the rest of the retina. We observe dynamic changes in retinal thickness during ocular elongation and retraction-thinning during elongation and thickening during retraction. Additionally, a transient localized thickening of the ganglion cell layer occurs in the temporal fovea region just before pit formation. Our data indicate that anole retina development is similar to that of humans, including the onset and progression of retinal neurogenesis, followed by changes in ocular shape and retinal remodeling leading to pit formation. We propose that anoles are an excellent model system for fovea development research.

Experimental Investigation of Temperature Homogeneity and Peak Temperature in a Battery Pack of Cylindrical Li-ion Cells Under Free and Forced Convection

Electrical vehicles (EVs) are emerging as a suitable replacement for conventional IC engine-based automobiles because of their environmental friendliness. An EV is powered by a rechargeable battery pack usually made of Lithium-ion batteries and these batteries generate heat during their operation cycle due to exothermic reactions and ohmic effect. Thermal management of batteries is important for their safe operation and optimum lifespan. In this paper, a comparative analysis of temperature homogeneity, peak temperature and average temperature of battery pack is presented between free and forced convection-based Battery Thermal Management System (BTMS). Cells that are at higher temperature than average temperature of battery pack are more liable to fail earlier as compared to other cells of pack. Present research focuses on finding such critical cells in a battery pack consisting of twelve lithium-ion batteries. The battery pack is discharged at three different rates: 1C, 2C and 3C, and temperature of each cell is measured at regular intervals during the discharge process. The experimental results from present study revealed that free convection is better at maintaining temperature homogeneity, but peak temperatures were above 50 ̊C. Forced convection based BTMS was able to keep peak temperatures below 50˚C at 1C discharge rate but temperature homogeneity was not maintained within ideal limits of 5˚C. At higher discharge rates, the performance of both free convection and forced convection based BTMS is not within acceptable limits. Critical cells were identified to get better insight into limitations of conventional cooling systems so that better layout of battery module and better alternative methods of battery pack cooling can be developed.

Evaluating the impact of ambient temperature on energy consumption rate of electric two-wheeler using real-world driving data

Electric two-wheelers are gaining popularity due to environmental benefits, extensive operating temperature, and low running costs. However, various environmental factors significantly affect their energy consumption rate and overall performance, with ambient temperature being the critical one. This study investigates the impact of ambient temperature on energy consumption rate and performance of electric two-wheelers by utilizing real-world driving data. An experimental setup consists of drive cycle source, speed control unit, motor control unit, battery pack, and motor with varying ambient temperatures ranging from 15 °C to 40 °C. The experimental setup utilized various sensors to collect parameters such as speed, temperature, current, voltage, state of charge, state of health, and driving range. The result shows that the optimal operating temperature for electric two-wheelers is between 20 °C and 30 °C, where energy efficiency and driving range are maximized. At 15 °C, the driving range decreases to 112.41 km, approximately 2 % lower than at moderate ambient temperature, while at 40 °C, the driving range increases by 2 %, reaching 114.68 km. The study also reveals that an extreme ambient temperature reduces the battery's useable capacity, negatively impacting power output and driving range. Additionally, the battery pack's cell temperature rises by 2.2 °C above the ambient temperature in both low and high conditions.

Transfer Learning from Synthetic Data for SOH Estimation

Public data on battery cell and battery pack aging, especially accessible from outside the automotive industry, is scarce. Scaling up from cell to pack level is not straightforward, as it requires an understanding of the underlying inhomogeneities and degradation patterns. Within the automotive industry, comprehensive time-series data on battery pack or battery electric vehicle aging is also limited due to high costs and data privacy concerns related to customer fleet data. Moreover, it is nearly impossible to capture the vast array of possible aging trajectories in controlled experiments. Such datasets, however, are essential for diagnosis and forecast of battery pack aging in the field, as well as for developing data-driven methods for state estimation.In this work, we introduce a fast, publicly available, battery pack aging data simulation toolbox based on pristine half-cell potential measurements at various C-rates. This toolbox enables the generation of constant-current charging events at different C-rates and can simulate any conceivable aging path. The modular framework allows users to adjust individual cell parameters, including state of charge (SOC), state of health (SOH), and degradation modes.Utilizing pristine half-cell potential measurements from a modern automotive lithium-ion battery, we create an initial cell model. This model, founded on the ‘alawa-toolbox [1], is validated with experimental data from a laboratory dataset. As Figure 1 illustrates, we construct a battery pack model by serially and parallelly connecting multiple cell models, incorporating intermediate resistances. This pack model reflects the configuration of a physical battery pack and permits modifications to SOC, SOH, degradation modes, and lead resistances.We collect time-series data from partial charging events of development vehicles at various aging states and use this data to calibrate our model by minimizing the discrepancy between simulated and measured voltage curves. Our model allows users to simulate and analyze the evolution of battery pack asymmetries, creating a digital twin to monitor aging impacts and identify the "weakest" cell for early damage detection and intervention.Giving every user the opportunity to generate big data from our toolbox expedites the development of data-driven SOH estimation or open-circuit voltage (OCV) reconstruction models. Future research will explore the use of synthetic data to develop state estimation algorithms applicable to various chemistries and configurations, including the analysis and validation against real customer fleet data, their battery pack aging and asymmetry patterns.Our work represents a significant advancement in facilitating access to battery and battery electric vehicle aging data, thereby reducing barriers in this research field. We anticipate that our contribution will hasten the development of data-driven methods at the battery pack level.[1] M. Dubarry, C. Truchot, B. Y. Liaw, Synthesize battery degradation modes via a diagnostic and prognostic model, Journal of Power Sources 219 (2012) 204-216, https://doi.org/10.1016/j.jpowsour.2012.07.016. Figure 1

Quantifying Volume Change in Porous Electrodes Via the Multi-Species, Multi-Reaction Model

Automotive manufacturers are working to improve individual cell and overall pack design by increasing their performance, durability, and range, while reducing cost; and active material volume change1–7 is one of the more complex aspects that needs to be considered during this process. As the time from initial design to manufacture of electric vehicles is decreased, design work that used to rely solely on testing needs to be supplemented or replaced by virtual methods. As electrochemical engineers drive battery and system design using model-based methods8, the need for coupled electrochemical/mechanical9 models that take into account the active material change utilizing physics based or semi-empirical approaches is necessary. In this study, we illustrated the applicability of a mechano-electrochemical coupled modeling method considering the multi-species, multi-reaction model as popularized by Verbrugge10,11 and Baker. To do this, validation tests were conducted using a computer-controlled press apparatus that can control the press displacement and press force with precision. The coupled MSMR volume change model was developed and its applicability to graphite and NMC cells was illustrated. The increased accuracy of the model considering the coupled MSMR volume change approach shows in the importance of accounting for individual gallery volume change behavior on cell level predictions.

Graphene functionalized nano-encapsulated composite phase change material based nanofluid for battery cooling: An experimental investigation

The graphene-nano encapsulated composite phase change material (GnePCM) based nanofluid holds great potential as a coolant for batteries in electric vehicles. The current work focuses on the synthesis and study of the cooling performance of GnePCM-based nanofluid. Few layered graphene (FLG) was synthesized via the liquid phase exfoliation method. Mini-emulsion polymerization was adopted to encapsulate composite PCM (octadecane: paraffin wax) within polystyrene shell and distribute these nanoballs across the graphene flakes of FLG to obtain GnePCM. Differential Scanning Calorimetry (DSC) was used to optimize the composition of composite PCM based on the melting range and latent heat. GnePCM was characterized by Scanning Electron Microscope (SEM), Transmission Electron Microscopy (TEM), DSC, Fourier Transform Infrared (FTIR) spectroscopy, and Raman Spectroscopy. Nanofluid was made by mixing GnePCM slurry with the base fluid (ethylene glycol − water mixture) and its thermo-physical properties were estimated. The analysis of thermal conductivity and specific heat capacity showed a 14.7 % and 56 % increase for the nanofluid compared to the base fluid. The optimal concentration of nanofluid for maximum stability was 10 % v/v based on zeta potential measurements. The heat transfer studies and pressure drop studies were conducted on a set of 10 cylindrical heaters, mimicking a 18,650 battery cell pack. The nanofluid could potentially achieve a maximum reduction of 5 °C in average surface temperatures of the cells as compared to the base fluid. The enhanced cooling efficiency of nanofluid could be related to the increased thermal conductivity and heat capacity of GnePCM, as well as the absorption of latent heat during its melting process. Enhancement in heat transfer parameters was found to be more prominent at lower flow rates for the nanofluids. The results reveal that the flow rate and power input play a significant role in the cooling performance of the nanofluid. Due to the increased viscosity of the nanofluid, a slight increase in the pressure drop and pumping power was observed at higher flow rates, as compared to base fluid.

Planar polarized force propagation integrates cell behavior with tissue shaping during convergent extension.

Convergent extension (CE) is an evolutionarily conserved developmental process that elongates tissues and organs via collective cell movements known as cell intercalation. Here, we sought to understand the mechanisms connecting cell behaviors and tissue shaping. We focus on an often-overlooked aspect of cell intercalation, the resolution of 4-cell vertices. Our data reveal that imbalanced cellular forces are involved in a timely vertex resolution, which, in turn, enables the propagation of such cellular forces, facilitating the propagation of tissue-scale CE. Conversely, delayed vertex resolution leads to a subtle but significant change in tissue-wide cell packing and exerts a profound impact by blocking force propagation, resulting in CE propagation defects. Our findings propose a collaborative nature of local cell intercalations in propagating tissue-wide CE. It unveils a multiscale biomechanical synergy underpinning the cellular mechanisms that orchestrate tissue morphogenesis during CE.

Signatures of Structural Disorder in the Developing Drosophila Germband Epithelium

Epithelial cells generate functional tissues in developing embryos through collective movements and shape changes. In some morphogenetic events, a tissue dramatically reorganizes its internal structure—often generating high degrees of structural disorder—to accomplish changes in tissue shape. However, the origins of structural disorder in epithelia and what roles it might play in morphogenesis are poorly understood. We study this question in the germband epithelium, which undergoes dramatic changes in internal structure as cell rearrangements drive elongation of the embryo body axis. Using two order parameters that quantify volumetric and shear disorder, we show that structural disorder increases during body axis elongation and is strongly linked with specific developmental processes. Both disorder metrics begin to increase around the onset of axis elongation, but then plateau at values that are maintained throughout the process. Notably, the disorder plateau values for volumetric disorder are similar to those for random cell packings, suggesting this may reflect a limit on tissue behavior. In mutant embryos with disrupted external stresses from the ventral furrow, both disorder metrics reach wild-type maximum disorder values with a delay, correlating with delays in cell rearrangements. In contrast, in mutants with disrupted internal stresses and cell rearrangements, volumetric disorder is reduced compared to wild type, and shear disorder depends on specific external stress patterns. Together, these findings demonstrate that internal and external stresses both contribute to epithelial tissue disorder and suggest that the maximum values of disorder in a developing tissue reflect physical or biological limits on morphogenesis. Published by the American Physical Society 2024

Modeling Reversible Volume Change in Automotive Battery Cells with Porous Silicon Oxide-Graphite Composite Anodes

Automotive battery manufacturers are working to improve the individual cell and overall pack design by increasing durability, performance, and range, while reducing cost, and active material volume change is a key aspect that needs to be considered during this design process. Recently, silicon oxide-graphite composite anodes are being explored to increase total anode capacity while maintaining a tolerable amount of cell level reversible volume expansion due to the relatively lower reversible volume change of the silicon oxide compared to pure battery grade or metallurgical grade silicon. To predict the blended anode response and contribution to the overall cell volume change, we integrated the mechanical behavior of the individual active materials with the multi-species, multi-reaction model to predict the state-of-lithiation of the active materials in the cell at a given potential. The resulting simulations illustrate the tradeoff in volume change between the silicon oxide and the graphite during cell operation. This type of modeling approach will allow designers to virtually consider the impact of cell level and pack level design changes on overall system mechanical performance for automotive and grid storage applications, namely that relatively small addition of silicon containing materials can drive a significant increase in the volume change at the cell level, as demonstrated by the 5 wt% addition of silicon oxide accounting for half of the overall volume change in the cell.

Diverse morphology and motility induced emergent order in bacterial collectives.

Microbial communities exhibit complex behaviors driven by species interactions and individual characteristics. In this study, we delve into the dynamics of a mixed bacterial population comprising two distinct species with different morphology and motility aspects. Employing agent-based modeling and computer simulations, we analyze the impacts of size ratios and packing fractions on dispersal patterns, aggregate formation, clustering, and spatial ordering. Notably, we find that motility and anisotropy of elongated bacteria significantly influence the distribution and spatial organization of nonmotile spherical species. Passive spherical cells display a superdiffusive behavior, particularly at larger size ratios in the ballistic regime. As the size ratio increases, clustering of passive cells is observed, accompanied by enhanced alignment and closer packing of active cells in the presence of higher passive cell area fractions. In addition, we identify the pivotal role of passive cell area fraction in influencing the response of active cells toward nematicity, with its dependence on size ratio. These findings shed light on the significance of morphology and motility in shaping the collective behavior of microbial communities, providing valuable insights into complex microbial behaviors with implications for ecology, biotechnology, and bioengineering.

Quantifying Volume Change in Porous Electrodes via the Multi-Species, Multi-Reaction Model

Automotive manufacturers are working to improve individual cell and overall pack design by increasing their performance, durability, and range, while reducing cost; and active material volume change is one of the more complex aspects that needs to be considered during this process. As the time from initial design to manufacture of electric vehicles is decreased, design work that used to rely solely on testing needs to be supplemented or replaced by virtual methods. As electrochemical engineers drive battery and system design using model-based methods, the need for coupled electrochemical/mechanical models that take into account the active material change utilizing physics based or semi-empirical approaches is necessary[1-9]. In this study[10], we illustrated the applicability of a mechano-electrochemical coupled modeling method considering the multi-species, multi-reaction model as popularized by Verbrugge[11-16] and Baker. To do this, validation tests were conducted using a computer-controlled press apparatus that can control the press displacement and press force with precision. The coupled MSMR volume change model was developed and its applicability to graphite and NMC cells was illustrated. The increased accuracy of the model considering the coupled MSMR volume change approach shows in the importance of accounting for individual gallery volume change behavior on cell level predictions. References T. R. Garrick, K. Kanneganti, X. Huang and J. W. Weidner, J Electrochem Soc, 161, E3297 (2014).T. R. Garrick, Y. Dai, K. Higa, V. Srinivasan and J. W. Weidner, Ecs Transactions, 72, 11 (2016).T. R. Garrick, K. Higa, S.-L. Wu, Y. Dai, X. Huang, V. Srinivasan and J. W. Weidner, J Electrochem Soc, 164, E3592 (2017).T. R. Garrick, X. Huang, V. Srinivasan and J. W. Weidner, J Electrochem Soc, 164, E3552 (2017).D. J. Pereira, J. W. Weidner and T. R. Garrick, J Electrochem Soc, 166, A1251 (2019).D. J. Pereira, M. A. Fernandez, K. C. Streng, X. X. Hou, X. Gao, J. W. Weidner and T. R. Garrick, J Electrochem Soc, 167, 080515 (2020).T. R. Garrick, J. Gao, X. Yang and B. Koch, J Electrochem. Soc., 168 (1) 010530 (2021)D. J. Pereira, A. M. Aleman, J. W. Weidner and T. R. Garrick, J Electrochem Soc, 169, 020577 (2022).T. R. Garrick, Y. Miao, E. Macciomei, M. Fernandez and J. W. Weidner, J Electrochem Soc, 170, 100513 (2023).T. R. Garrick, M. A. Fernandez, M. Verbrugge, C. Labaza, R. Mollah, B. J. Koch, M. Jones, J. Gao, X. Gao and N. Irish, J. Electrochem. Soc., 170 060548 (2023)M. Verbrugge, D. Baker and X. Xiao, J Electrochem Soc, 163, A262 (2016).M. Verbrugge, D. Baker, B. Koch, X. Xiao and W. Gu, J Electrochem Soc, 164, E3243 (2017).D. R. Baker and M. W. Verbrugge, J Electrochem Soc, 165, A3952 (2018).D. R. Baker and M. W. Verbrugge, J Electrochem Soc, 167, 013504 (2019).D. R. Baker, M. W. Verbrugge and W. Gu, J Electrochem Soc, 166, A521 (2019).M. W. Verbrugge, X. Xiao and D. R. Baker, J Electrochem Soc, 167, 080523 (2020).

Investigating the Formation of Different (NH4)2[M(H2O)5(NH3CH2CH2COO)]2[V10O28]·nH2O (M = CoII, NiII, ZnII, n = 4; M = CdII, MnII, n = 2) Crystallohydrates

Three hybrid compounds based on decavanadates, i.e., (NH4)2[Co(H2O)5(β-HAla)]2[V10O28]·4H2O (1), (NH4)2[Ni(H2O)5(β-HAla)]2[V10O28]·4H2O (2), and (NH4)2[Cd(H2O)5(β-HAla)]2[V10O28]·2H2O (3), (where β-Hala = zwitterionic form of β-alanine) were prepared by reactions in mildly acidic conditions (pH ~ 4) at room temperature. These compounds crystallise in two structure types, both crystallising in monoclinic P21/n space group but with dissimilar cell packing, i.e., as tetrahydrates (1 and 2) and as a dihydrate (3). An influence of crystal radii and spin state of the central atom in [M(H2O)5(β-HAla)]2+ complex cations on the crystal packing leading to the formation of different crystallohydrate forms was investigated together with previously prepared (NH4)2[Zn(H2O)5(β-HAla)]2[V10O28]·4H2O (4) and (NH4)2[Mn(H2O)5(β-HAla)]2[V10O28]·2H2O (5) and spin states of [M(H2O)5(β-HAla)]2+ (M = Co2+, Ni2+, and Mn2+) cations in solution were confirmed by 1H-NMR paramagnetic effects. FT-IR and FT-Raman spectra for 1–5 are in agreement with the X-ray structure analysis results.

Mechanisms for the evolution of cell-to-cell variations and their impacts on fast-charging performance within a lithium-ion battery pack

Cell-to-cell variations (CtCV) compromise the electrochemical performance of battery packs, yet the evolutional mechanism and quantitative impacts of CtCV on the pack’s fast-charging performance remain unexplored. This knowledge gap is vital for the proliferation of electric vehicles. This study underlies the relationship between CtCV and charging performance by assessing the pack’s charge speed, final electric quantity, and temperature consistency. Cell variations and pack status are depicted using 2D parameter diagrams, and an mPnS configured pack model is built upon a decomposed electrode cell model. Variations in three single electric parameters, i.e., capacity (Q), electric quantity (E), and internal resistance (R), and their dual interactions, i.e., E-Q and R-Q, are analyzed carefully. The results indicate that Q variations predominantly affect the final electric quantity of the pack, while R variations impact the charge speed most. With incremental variances in cell parameters, the pack’s fast-charging capability first declines linearly and then deteriorates sharply as variations intensify. This research elucidates the correlations between pack charging capabilities and cell variations, providing essential insights for optimizing cell sorting and assembly, battery management design, and charging protocol development for battery packs.

Flexibility, toughness, and load bearing of 3D-printed chiral kerf composite structures

Chiral kerf structures are formed by arranging chiral and coiled unit cells which allows for multi-dimensional and multi-scale shape configurations under mechanical loadings. In this study, we investigate how the mechanical properties of materials and microstructural topologies interact to control the flexibility, toughness, and load bearing of 3D-printed chiral kerf structures. We explore chiral kerf structures with two different kerf patterns, i.e., square and hexagon, and three coiling densities. We consider three materials, namely brittle Polylactic Acid (PLA), compliant thermoplastic polyurethane (TPU), and a ductile composite made by alternating PLA and TPU, referred to as a programmable composite. The chiral kerf structures undergo two deformation mechanisms when subjected to mechanical loadings. The first one results from reconfigurations of kerf cells such as uncoiling, rotation of cells, and cell packing, and the second mechanism arises from nonlinear and inelastic material responses. The use of brittle material limits cell reconfigurations before material failure, reducing the overall flexibility and toughness of kerf structures. While the compliant material enables full cell reconfigurations, it results in low load bearing. The use of PLA:TPU composite allows for cell reconfigurations and inelastic material response, enhancing flexibility and toughness while maintaining a relatively high load bearing. We demonstrate that stress distribution in kerf structures can be controlled by using multiple materials or coil densities. This strategy can delay failure and improve the toughness and load-bearing capabilities of kerf structures.

Modeling Rate Dependent Volume Change in Porous Electrodes in Lithium-Ion Batteries

Automotive manufacturers are working to improve individual cell, module, and overall pack design by increasing the performance, range, and durability, while reducing cost. One key piece to consider during the design process is the active material volume change, its linkage to the particle, electrode, and cell level volume changes, and the interplay with structural components in the rechargeable energy storage system. As the time from initial design to manufacture of electric vehicles decreases, design work needs to move to the virtual domain; therefore, a need for coupled electrochemical-mechanical models that take into account the active material volume change and the rate dependence of this volume change need to be considered. In this study, we illustrated the applicability of a coupled electrochemical-mechanical battery model considering multiple representative particles to capture experimentally measured rate dependent reversible volume change at the cell level through the use of an electrochemical-mechanical battery model that couples the particle, electrode, and cell level volume changes. By employing this coupled approach, the importance of considering multiple active material particle sizes representative of the distribution is demonstrated. The non-uniformity in utilization between two different size particles as well as the significant spatial non-uniformity in the radial direction of the larger particles is the primary driver of the rate dependent characteristics of the volume change at the electrode and cell level.

Surgical Outcome and Microbial Colonization of Standardized Smear Locations after Pancreatic Head Resection (Pylorus-Preserving Pancreatoduodenectomy, PPPD) for Chronic Pancreatitis and Pancreatic Head Carcinoma.

Introduction: Patients with chronic pancreatitis (CP) as well as with pancreatic head carcinoma (CA) undergo the surgical intervention named "pylorus-preserving pancreatoduodenectomy according to Traverso-Longmire (PPPD)", which allowed a comparative analysis of the postoperative courses. The hypothesis was that patients with CA would have worse general as well as immune status than patients with CP due to the severity of the tumor disease and that this would be reflected in the more disadvantageous early postoperative outcome after PPPD. Methods: With the aim of eliciting the influence of the different diagnoses, the surgical outcome of all consecutive patients who underwent surgery at the Dept. of General, Abdominal, Vascular and Transplant Surgery at the University Hospital at Magdeburg between 2002 and 2015 (inclusion criterion) was recorded and comparatively evaluated. Early postoperative outcome was characterized by general and specific complication rate indicating morbidity, mortality, and microbial colonization rate, in particular surgical site infection (SSI, according to CDC criteria). In addition, microbiological findings of swabs and cultures from all compartments as well as preoperative and perioperative parameters from patient records were retrospectively documented and used for statistical comparison in this systematic retrospective unicenter observational study (design). Results: In total, 192 cases with CA (68.1%) and 90 cases with CP (31.9%) met the inclusion criteria of this study. Surprisingly, there were similar specific complication rates of 45.3% (CA) vs. 45.6% (CP; p = 0.97) and in-hospital mortality, which differed only slightly at 3.65% (CA) vs. 3.3% (CP; p = 0.591); the overall complication rate tended to be higher for CA at 23.4% vs. 14.4% (CP; p = 0.082). Overall, potentially pathogenic germs were detected in 28.9% of all patients in CP compared to 32.8% in CA (p = 0.509), and the rate of SSI was 29.7% (CA) and 24.4% (CP; p = 0.361). In multivariate analysis, CA was found to be a significant risk factor for the development of SSI (OR: 2.025; p = 0.048); the underlying disease had otherwise no significant effect on early postoperative outcome. Significant risk factors in the multivariate analysis were also male sex for SSI and microbial colonization, and intraoperatively transfused red cell packs for mortality, general and specific complications, and surgical revisions. Conclusions: Based on these results, a partly significant, partly trending negative influence of the underlying disease CA, compared to CP, on the early postoperative outcome was found, especially with regard to SSI after PPPD. This influence is corroborated by the international literature.

Experimental evolution of multicellularity via cuboidal cell packing in fission yeast

Abstract The evolution of multicellularity represents a major transition in life’s history, enabling the rise of complex organisms. Multicellular groups can evolve through multiple developmental modes, but a common step is the formation of permanent cell–cell attachments after division. The characteristics of the multicellular morphology that emerges have profound consequences for the subsequent evolution of a nascent multicellular lineage, but little prior work has investigated these dynamics directly. Here, we examine a widespread yet understudied emergent multicellular morphology: cuboidal packing. Extinct and extant multicellular organisms across the tree of life have evolved to form groups in which spherical cells divide but remain attached, forming approximately cubic subunits. To experimentally investigate the evolution of cuboidal cell packing, we used settling selection to favor the evolution of simple multicellularity in unicellular, spherical Schizosaccharomyces pombe yeast. Multicellular clusters with cuboidal organization rapidly evolved, displacing the unicellular ancestor. These clusters displayed key hallmarks of an evolutionary transition in individuality: groups possess an emergent life cycle driven by physical fracture, group size is heritable, and they respond to group-level selection via multicellular adaptation. In 2 out of 5 lineages, group formation was driven by mutations in the ace2 gene, preventing daughter cell separation after division. Remarkably, ace2 mutations also underlie the transition to multicellularity in Saccharomyces cerevisiae and Candida glabrata, lineages that last shared a common ancestor >300 million years ago. Our results provide insight into the evolution of cuboidal cell packing, an understudied multicellular morphology, and highlight the deeply convergent potential for a transition to multicellular individuality within fungi.

Modeling and Simulation of a Gas-Exhaust Design for Battery Thermal Runaway Propagation in a LiFePO4 Module

The release of flammable gases during battery thermal runaway poses a risk of combustion and explosion, endangering personnel safety. The convective and diffusive properties of the gas make it challenging to accurately measure gas state, complicating the assessment of the battery pack exhaust design. In this paper, a thermal resistance network model is established, which is used to calculate the battery thermal runaway propagation. Gas accumulation after thermal runaway venting of a LiFeO4 module is studied using ANSYS Fluent under different venting schemes. The results show that the scheme of battery inversion and simultaneous exhaust from the side and bottom of the module is optimal. The methods and results presented can guide the design of LiFeO4 cell pack runners.

Excitable dynamics driven by mechanical feedback in biological tissues

Pulsatory activity patterns, driven by mechanochemical feedback, are prevalent in many biological systems. However, the role of cellular mechanics and geometry in the propagation of pulsatory signals remains poorly understood. Here we present a theoretical framework to elucidate the mechanical origin and regulation of pulsatile activity patterns within excitable multicellular tissues. We show that a simple mechanical feedback at the level of individual cells – activation of contractility upon stretch and subsequent inactivation upon turnover of active elements – is sufficient to explain the emergence of quiescent states, long-range wave propagation, and traveling activity pulse at the tissue-level. We find that the transition between a propagating pulse and a wave is driven by the competition between timescales associated with cellular mechanical response and geometrical disorder in the tissue. This sheds light on the fundamental role of cell packing geometry on tissue excitability and spatial propagation of activity patterns.

Optimizing interleukin-6 and 8 expression, clarification and purification in plant cell packs and plants for application in advanced therapy medicinal products and cellular agriculture

Healthcare and nutrition are facing a paradigm shift in light of advanced therapy medicinal products (ATMPs) and cellular agriculture options respectively. Both options heavily rely on some sort of animal cell culture, e.g. autologous stem cells. These cultures require various growth factors, such as interleukin-6 and 8 (IL-6/8), in a pure, safe and sustainable form that can be provided in a scalable manner. Plants seem well suited for this task because purification of small proteins can be readily achieved by membrane separation, human/animal pathogens do not replicate in plants and production can be scaled up using in-door farming or agricultural practices. Here, we illustrate this capacity by first optimizing the codon usage of IL-6/8 for translation in Nicotiana spp., as well as testing the effect of untranslated regions and product targeting to different sub-cellular compartments on expression in a high-throughput plant cell pack (PCP) assay. In the chloroplast, IL-6 accumulated up to 6.9±3.8 (SD, n=2) and 14.4±7.4 mg kg−1 (SD, n=5) were observed in case of IL-8. When transferring IL-8 expression into whole plants, accumulation was 12.3±1.5 mg kg−1 (SD, n=3). After extraction and clarification, IL-8 was purified using a two-stage process consisting of an ultrafiltration/diafiltration step with 100 kDa and 10 kDa cut off membranes followed by an IMAC polishing step. The purity, yield and recovery were 97.8%, 6.6 mg kg−1 and 38%, respectively. We evaluated the ability of the proposed purification process to remove endotoxins to ensure the compatibility of plant-made growth factors with cell culture.