Diabetes, glycemic profile and risk of vitiligo: A Mendelian randomization study.

BACKGROUD: Previous observational studies have shown that vitiligo usually co-manifests with a variety of dysglycemic diseases, such as Type 1 diabetes mellitus (T1DM) and Type 2 diabetes mellitus (T2DM). Mendelian randomization (MR) analysis was performed to further evaluate the causal association between fasting plasma glucose, glycosylated hemoglobin (HbA1c), T1DM, T2DM and vitiligo. MATERIALS AND METHODS: We used aggregated genome-wide association data from the Integrative Epidemiology Unit (IEU) online database of European adults vitiligo; HbA1c data were from IEU. Fasting blood glucose data were obtained from the European Bioinformatics Institute (EBI). T1DM and T2DM data were from FinnGen. We used bidirectional two-sample and multivariate MR analyses to test whether dysglycemic measures (fasting blood glucose, HbA1c), diabetes-related measures (T1DM, T2DM) are causatively associated with vitiligo. Inverse variance weighting (IVW) method was used as the main test method, MR-Egger, Weighted mode and Weighted median were used as supplementary methods. RESULTS: We found no statistically significant evidence to support a causal association between dysglycemic traits and vitiligo, but in the correlation analysis of diabetic traits, our data supported a positive causal association between T1DM and vitiligo (p = 0.018). In the follow-up multivariate MR analysis, our results still supported this conclusion (p = 0.016), and suggested that HbA1c was not a mediator of T1DM affecting the pathogenesis of vitiligo. No reverse causality was found in any of the reverse MR Analyses of dysglycemic traits and diabetic traits. CONCLUSIONS: Our findings support that T1DM is a risk factor for the development of vitiligo, and this conclusion may explain why the co-presentation of T1DM and vitiligo is often seen in observational studies. Clinical use of measures related to T1DM may be a new idea for the prevention or treatment of vitiligo.

A robust methodology for PEC performance analysis of photoanodes using machine learning and analytical data.

Machine learning (ML) is increasingly applied across various fields, including chemistry, for molecular design and optimizing reaction parameters. Yet, applying ML to experimental data is challenging due to the limited number of synthesized samples, which restricts its broader application in device development. In energy harvesting, photoanodes are crucial for solar-driven water splitting, generating hydrogen and oxygen. We explored electrodes like hematite and bismuth vanadate for photocatalytic uses, noting varied photoelectrochemical performances despite similar preparations. To understand this variability, we applied a data-driven ML approach, predicting photocurrent values and identifying key performance influencers even with limited experimental data in the research development of inorganic devices. We have utilized multiple machine learning algorithms to predict the target value in the calculation process, where the contributions of the dominant descriptors were unknown. We introduced a novel methodology, incorporating clustering to manage multicollinearity from correlated analytical data and Shapley analysis for clear interpretation of contributions to performance prediction. This method was validated on hematite and bismuth vanadate, showing superior predictability and factor identification, and then extended to tungsten oxide and bismuth vanadate heterojunction photoanodes. Despite their complexity, our approach achieved determination coefficients (R2) with a prediction accuracy over 0.85, successfully pinpointing performance-determining factors, demonstrating the robustness of the new scheme in advancing photodevice research.

Exploring causal correlations of inflammatory biomarkers in idiopathic normal-pressure hydrocephalus: insights from bidirectional Mendelian randomization analysis.

Background and objective: Neuroinflammatory processes have been identified as playing a crucial role in the pathophysiology of various neurodegenerative diseases, including idiopathic normal-pressure hydrocephalus (iNPH). iNPH, defined as a common disease of cognitive impairment in older adults, poses major challenges for therapeutic interventions owing to the stringent methodological requirements of relevant studies, clinical heterogeneity, unclear etiology, and uncertain diagnostic criteria. This study aims to assess the relationship between circulating inflammatory biomarkers and iNPH risk using bidirectional two-sample Mendelian randomization (MR) combined with meta-analysis. Methods: In our bidirectional MR study, genetic data from a genome-wide association study (GWAS) involving 1,456 iNPH cases and 409,726 controls of European ancestry were employed. Single-nucleotide polymorphisms (SNPs) associated with exposures served as instrumental variables for estimating the causal relationships between iNPH and 132 types of circulating inflammatory biomarkers from corresponding GWAS data. Causal associations were primarily examined using the inverse variance-weighted method, supplemented by MR-Egger, weighted median, simple mode, and weighted mode analyses. In the results, heterogeneity was assessed using the Cochran Q test. Horizontal pleiotropy was evaluated through the MR-Egger intercept test and the MR pleiotropy residual sum and outliers test. Sensitivity analysis was conducted through leave-one-out analysis. Reverse MR analyses were performed to mitigate bias from reverse causality. Meta-analyses of identical inflammatory biomarkers from both data sources strengthened the findings. Results: Results indicated a genetically predicted association between Interleukin-16 (IL-16) [OR: 1.228, 95% CI: 1.049-1.439, p = 0.011], TNF-related apoptosis ligand (TRAIL) [OR: 1.111, 95% CI: 1.019-1.210, p = 0.017] and Urokinase-type plasminogen activator (uPA) [OR: 1.303, 95% CI: 1.025-1.658, p = 0.031] and the risk of iNPH. Additionally, changes in human Glial cell line-derived neurotrophic factor (hGDNF) [OR: 1.044, 95% CI: 1.006-1.084, p = 0.023], Matrix metalloproteinase-1 (MMP-1) [OR: 1.058, 95% CI: 1.020, 1.098, p = 0.003] and Interleukin-12p70 (IL-12p70) [OR: 0.897, 95% CI: 0.946-0.997, p = 0.037] levels were identified as possible consequences of iNPH. Conclusion: Our MR study of inflammatory biomarkers and iNPH, indicated that IL-16, TRAIL, and uPA contribute to iNPH pathogenesis. Furthermore, iNPH may influence the expression of hGDNF, MMP-1, and IL-12p70. Therefore, targeting specific inflammatory biomarkers could be promising strategy for future iNPH treatment and prevention.

OsNLP3 enhances grain weight and reduces grain chalkiness in rice.

Grain weight, a key determinant of yield in rice (Oryza sativa L.), is governed primarily by genetic factors, whereas grain chalkiness, a detriment to grain quality, is intertwined with environmental factors such as mineral nutrients. Nitrogen (N) is recognized for its impact on grain chalkiness, yet the underlying molecular mechanisms remain elusive. This study revealed the pivotal role of rice NODULE INCEPTION-LIKE PROTEIN 3 (OsNLP3) in simultaneously regulating grain weight and grain chalkiness. Our investigation showed that the loss of OsNLP3 leads to a reduction in both grain weight and dimension, in contrast to the enhancement observed with OsNLP3 overexpression. OsNLP3 directly suppresses the expression of OsCEP6.1 and OsNF-YA8, which were identified as negative regulators associated with grain weight. Consequently, two novel regulatory modules, OsNLP3-OsCEP6.1 and OsNLP3-OsNF-YA8, were identified as key players in grain weight regulation. Notably, the OsNLP3-OsNF-YA8 module not only augments grain weight but also mitigates grain chalkiness in response to N. This research clarifies the molecular mechanisms orchestrating grain weight through the OsNLP3-OsCEP6.1 and OsNLP3-OsNF-YA8 modules, underscoring the pivotal role of the OsNLP3-OsNF-YA8 module in alleviating grain chalkiness. These findings offer potential targets for concurrently enhancing rice yield and quality.

Promising roles of combined therapy based on immune response and iron metabolism in systemic lupus erythematosus.

Systemic lupus erythematosus (SLE) is an intricate autoimmune disease with diverse manifestations. Immunometabolism reprogramming contributes to the progression of SLE by regulating the phenotype and function of immune cells. Dysregulated iron metabolism is implicated in SLE pathogenesis, affecting both systemic and immune cell-specific iron homeostasis. This review explores the systemic and cellular iron handling and regulation. Additionally, the advancements regarding iron metabolism in SLE with a focus on the distinct subsets of immune cells are highlighted. By gaining insight into the interplay between iron dysregulation and immune dysfunction, the potential therapeutic avenues may be unveiled. However, challenges remain in elucidating cell-specific iron metabolic reprogramming and its contribution to SLE pathogenesis needs further research for personalized therapeutic interventions and biomarker discovery. This review provides an in-depth understanding of immune cell-specific regulatory mechanisms of iron metabolism and new insights in current challenges as well as possible clinical applications.

Subtraction Descriptors in Machine Learning for Optimizing the Cocatalyst Effect of Cobalt Phosphate on Hematite Photoanodes.

In the quest for sustainable energy solutions, the optimization of the photoelectrochemical (PEC) performance of hematite photoanodes through cocatalysts represents a promising avenue. This study introduces a novel machine learning approach, leveraging subtraction descriptors, to isolate and quantify the specific effects of cobalt phosphate (Co-Pi) as a cocatalyst on hematite's PEC performance. By integrating data from various analytical techniques, including photoelectrochemical impedance spectroscopy and ultraviolet-visible spectroscopy, with advanced machine learning models, we successfully predicted the PEC performance enhancement attributed to Co-Pi. The Gaussian process regression (GPR) model emerged as the most effective, revealing the critical influence of the interfacial resistance, bulk resistance, and interfacial capacitance on the PEC performance. These findings underscore the potential of cocatalysts in improving charge separation and extending charge carrier lifetimes, thereby boosting the efficiency of photocatalytic reactions. This study not only advances our understanding of the cocatalyst effect in photocatalytic systems but also demonstrates the power of machine learning in modifying complex materials and guiding the development of optimized photocatalytic materials. The implications of this research extend beyond hematite photoanodes, offering a generalizable framework for enhancing the photoelectrochemical properties of a wide range of material modifications such as cocatalyst deposition, doping, and passivation.

Selenium nanoparticles enhance mucosal immunity against Mycobacterium bovis infection.

Selenium nanoparticles (SeNPs) enhance the immune response as adjuvants, increasing the efficacy of viral vaccines, including those for COVID-19. However, the efficiency of mucosal SeNPs in boosting vaccine-induced protective immunity against tuberculosis remains unclear. Therefore, this study aims to investigate whether the combination of SeNPs with the AH antigen (Ag85A-HspX) can boost respiratory mucosal immunity and thereby enhance the protective effects against tuberculosis. We synthesized SeNPs and assessed their impact on the immune response and protection against Mycobacterium bovis (M. bovis) as a mucosal adjuvant in mice, administered intranasally at a dose of 20 µg. SeNPs outperformed polyinosinic-polycytidylic acid (Poly IC) in stimulating the maturation of bone marrow-derived dendritic cells (BMDCs), which enhanced antigen presentation. SeNPs significantly activated and proliferated tissue-resident memory T cells (TRMs) and effector CD4+ T cells in the lungs. The vaccines elicited specific antibody responses in the respiratory tract and stimulated systemic Th1 and Th17 immune responses. Immunization with AH and SeNPs led to higher levels of mucosal secretory IgA in bronchoalveolar lavage fluid (BALF) and secretory IL-17 in splenocytes. Moreover, SeNPs immunized mice showed reduced M. bovis infection loads and inflammatory lesions in the lungs post-challenge. Notably, immunization with AH and SeNPs significantly reduced bacterial load in the lungs, achieving the lowest levels compared to all other tested groups. This study calls for pre-clinical investigation of AHB-SeNPs as an anti-bovine tuberculosis vaccine and for exploring its human vaccine potential, which is anticipated to aid in the development of innovative vaccines or adjuvants.

Crucial Roles of RSAD2/viperin in Immunomodulation, Mitochondrial Metabolism and Autoimmune Diseases.

Autoimmune diseases are typically characterized by aberrant activation of immune system that leads to excessive inflammatory reactions and tissue damage. Nevertheless, precise targeted and efficient therapies are limited. Thus, studies into novel therapeutic targets for the management of autoimmune diseases are urgently needed. Radical S-adenosyl methionine domain-containing 2 (RSAD2) is an interferon-stimulated gene (ISG) renowned for the antiviral properties of the protein it encodes, named viperin. An increasing number of studies have underscored the new roles of RSAD2/viperin in immunomodulation and mitochondrial metabolism. Previous studies have shown that there is a complex interplay between RSAD2/vipeirn and mitochondria and that binding of the iron-sulfur (Fe-S) cluster is necessary for the involvement of viperin in mitochondrial metabolism. Viperin influences the proliferation and development of immune cells as well as inflammation via different signaling pathways. However, the function of RSAD2/viperin varies in different studies and a comprehensive overview of this emerging theme is lacking. This review will describe the characteristics of RSAD2/viperin, decipher its function in immunometabolic processes, and clarify the crosstalk between RSAD2/viperin and mitochondria. Furthermore, we emphasize the crucial roles of RSAD2 in autoimmune diseases and its potential application value.

Frequency tuning and automatic frequency tracking of shunted piezoelectric transducers.

Piezoelectric ultrasonic transducers, vital in medical devices and aerospace, often face challenges like resonant frequency shifts and impedance variations affecting their operational efficiency. This paper introduces a shunted piezoelectric transducer which could tune itself by digitally programmable inductance. A transformer and inductance-capacitance matching network ensures enhanced compatibility and impedance management. Proposing a fuzzy PI-based phase control method achieves resonant frequency tracking, synchronizing operational frequency with the transducer. In contrast to traditional methods, our approach enables faster and more precise fine-tuning, detecting and rectifying real-world deviations for optimal performance. A comprehensive experimental validation, based on fundamental knowledge analysis, confirms the feasibility and superiority of our proposed method, and the commonly encountered issues of resonance frequency deviation and impedance variation in high-power piezoelectric transducer applications can be effectively mitigated.

One-Stone-for-Two-Birds Strategy for VSe2 to Enable High Capacity and Long-Life Zinc Storage.

Based on a specific zinc storage mechanism and excellent electronic conductivity, transition metal dichalcogenides, represented by vanadium diselenide, are widely used in aqueous zinc-ion battery (AZIB) energy storage systems. However, most vanadium diselenide cathode materials are presently limited by low specific capacity and poor cycling life. Herein, a simple hydrothermal process has been proposed for obtaining a vanadium diselenide cathode for an AZIB. The interaction of defects and crystal planes enhances zinc storage capacity and reduces the migration energy barrier. Moreover, abundant lamellar structure greatly increases reaction sites and alleviates volume expansion during the electrochemical process. Thus, the as-obtained vanadium diselenide AZIB exhibits an excellent reversible specific capacity of 377 mAh g-1 at 1 A g-1, and ultralong cycle stability of 291 mAh g-1 after 3200 cycles, with a nearly negligible capacity loss. This one-stone-for-two-birds strategy would be expected to be applied to large-scale synthesis of a high-performance zinc-ion battery cathode in the future.

Bio-Inspired Electrodes with Rational Spatiotemporal Management for Lithium-Ion Batteries.

Lithium-ion batteries (LIBs) are currently the predominant energy storage power source. However, the urgent issues of enhancing electrochemical performance, prolonging lifetime, preventing thermal runaway-caused fires, and intelligent application are obstacles to their applications. Herein, bio-inspired electrodes owning spatiotemporal management of self-healing, fast ion transport, fire-extinguishing, thermoresponsive switching, recycling, and flexibility are overviewed comprehensively, showing great promising potentials in practical application due to the significantly enhanced durability and thermal safety of LIBs. Taking advantage of the self-healing core-shell structures, binders, capsules, or liquid metal alloys, these electrodes can maintain the mechanical integrity during the lithiation-delithiation cycling. After the incorporation of fire-extinguishing binders, current collectors, or capsules, flame retardants can be released spatiotemporally during thermal runaway to ensure safety. Thermoresponsive switching electrodes are also constructed though adding thermally responsive components, which can rapidly switch LIB off under abnormal conditions and resume their functions quickly when normal operating conditions return. Finally, the challenges of bio-inspired electrode designs are presented to optimize the spatiotemporal management of LIBs. It is anticipated that the proposed electrodes with spatiotemporal management will not only promote industrial application, but also strengthen the fundamental research of bionics in energy storage.

NAP-seq reveals multiple classes of structured noncoding RNAs with regulatory functions.

Up to 80% of the human genome produces "dark matter" RNAs, most of which are noncapped RNAs (napRNAs) that frequently act as noncoding RNAs (ncRNAs) to modulate gene expression. Here, by developing a method, NAP-seq, to globally profile the full-length sequences of napRNAs with various terminal modifications at single-nucleotide resolution, we reveal diverse classes of structured ncRNAs. We discover stably expressed linear intron RNAs (sliRNAs), a class of snoRNA-intron RNAs (snotrons), a class of RNAs embedded in miRNA spacers (misRNAs) and thousands of previously uncharacterized structured napRNAs in humans and mice. These napRNAs undergo dynamic changes in response to various stimuli and differentiation stages. Importantly, we show that a structured napRNA regulates myoblast differentiation and a napRNA DINAP interacts with dyskerin pseudouridine synthase 1 (DKC1) to promote cell proliferation by maintaining DKC1 protein stability. Our approach establishes a paradigm for discovering various classes of ncRNAs with regulatory functions.

Spatiotemporal variation of 6PPD and 6PPDQ in dust and soil from e-waste recycling areas.

N-(1,3-dimethylbutyl)-N'-phenyl-p-phenylenediamine (6PPD) and its derivative 6PPDQ have been detected in various environmental media, with harmful consequences for both ecosystems and biological health. However, the distribution of 6PPD and 6PPDQ in areas around e-waste recycling areas is currently unknown. We collected soil and dust samples from areas around a traditional e-waste recycling zone, an emerging recycling park, and a reference area. Higher levels of 6PPD were found in dust from residential areas around the traditional e-waste recycling zone compared to the reference area (median: 108.99 versus 33.57 ng/g, P < 0.01). Lower levels of 6PPDQ were detected in dust samples from around the emerging e-waste recycling parks compared to traditional e-waste recycling zones (median: 15.40 versus 46.37 ng/g, P < 0.05). The median concentrations of 6PPD and 6PPDQ were higher in the dust samples than in the soil samples (P < 0.001). The concentrations of 6PPD and 6PPDQ in the dust and soil varied seasonally, with the highest total concentrations occurring in the winter. Results from a multiple linear regression analysis indicate that 6PPDQ is negatively correlated with temperature and positively correlated with 6PPD, O3, and radiation. This study confirms that e-waste is a potential contributor to 6PPD and 6PPDQ. In residential areas, 6PPD and 6PPDQ are more likely to accumulate in dust than in soil. The emerging e-waste recycling parks have greatly improved the local 6PPDQ pollution situation. Further studies are necessary to understand the distribution of newly found substances in various settings.

Salmonella manipulates macrophage migration via SteC-mediated myosin light chain activation to penetrate the gut-vascular barrier.

The intestinal pathogen Salmonella enterica rapidly enters the bloodstream after the invasion of intestinal epithelial cells, but how Salmonella breaks through the gut-vascular barrier is largely unknown. Here, we report that Salmonella enters the bloodstream through intestinal CX3CR1+ macrophages during early infection. Mechanistically, Salmonella induces the migration/invasion properties of macrophages in a manner dependent on host cell actin and on the pathogen effector SteC. SteC recruits host myosin light chain protein Myl12a and phosphorylates its Ser19 and Thr20 residues. Myl12a phosphorylation results in actin rearrangement, and enhanced migration and invasion of macrophages. SteC is able to utilize a wide range of NTPs other than ATP to phosphorylate Myl12a. We further solved the crystal structure of SteC, which suggests an atypical dimerization-mediated catalytic mechanism. Finally, in vivo data show that SteC-mediated cytoskeleton manipulation is crucial for Salmonella breaching the gut vascular barrier and spreading to target organs.

Challenges and opportunities in inflammatory bowel disease: from current therapeutic strategies to organoid-based models.

BACKGROUND: Inflammatory bowel disease (IBD) is an increasingly prevalent global health concern that has garnered substantial attention. However, the underlying mechanisms are still unclear and the current treatments have significant limitations. Intestinal organoids provide an in vitro model to explore the pathogenesis, test the therapeutic effects, and develop regenerative treatments as well as offer the potential to transform drug discovery of IBD. METHODS: To advance our understanding of the whole story of IBD spanning from the pathogenesis to the current therapeutic strategies and latest advancements, a comprehensive search of major databases including PubMed, Scopus, and Web of Science was conducted to retrieve original articles and reviews related to IBD, organoids, pathogenesis and therapy. RESULTS: This review deciphers the etiopathogenesis and the current therapeutic approaches in the treatment of IBD. Notably, critical aspects of intestinal organoids in IBD, such as their potential applications, viability, cell renewal ability, and barrier functionality are highlighted. We also discuss the advances, limitations, and prospects of intestinal organoids for precision medicine. CONCLUSION: The latest strides made in research about intestinal organoids help elucidate intricate aspects of IBD pathogenesis, and pave the prospective avenues for novel therapeutic interventions.

Dietary factors and the risk of atopic dermatitis: a Mendelian randomisation study.

Previous studies have revealed an association between dietary factors and atopic dermatitis (AD). To explore whether there was a causal relationship between diet and AD, we performed Mendelian randomisation (MR) analysis. The dataset of twenty-one dietary factors was obtained from UK Biobank. The dataset for AD was obtained from the publicly available FinnGen consortium. The main research method was the inverse-variance weighting method, which was supplemented by MR‒Egger, weighted median and weighted mode. In addition, sensitivity analysis was performed to ensure the accuracy of the results. The study revealed that beef intake (OR = 0·351; 95 % CI 0·145, 0·847; P = 0·020) and white bread intake (OR = 0·141; 95 % CI 0·030, 0·656; P = 0·012) may be protective factors against AD. There were no causal relationships between AD and any other dietary intake factors. Sensitivity analysis showed that our results were reliable, and no heterogeneity or pleiotropy was found. Therefore, we believe that beef intake may be associated with a reduced risk of AD. Although white bread was significant in the IVW analysis, there was large uncertainty in the results given the wide 95 % CI. Other factors were not associated with AD in this study.

Tailoring the catalytic sites by regulating photogenerated electron/hole pairs separation spatially for simultaneous selective oxidation of benzyl alcohol and hydrogen evolution.

Photocatalytic selective oxidation of alcohols into aldehydes and H2 is a green strategy for obtaining both value-added chemicals and clean energy. Herein, a dual-purpose ZnIn2S4@CdS photocatalyst was designed and constructed for efficient catalyzing benzyl alcohol (BA) into benzaldehyde (BAD) with coupled H2 evolution. To address the deep-rooted problems of pure CdS, such as high recombination of photogenerated carriers and severe photo-corrosion, while also preserving its superiority in H2 production, ZnIn2S4 with a suitable band structure and adequate oxidizing capability was chosen to match CdS by constructing a coupled reaction. As designed, the photoexcited holes (electrons) in the CdS (ZnIn2S4) were spatially separated and transferred to the ZnIn2S4 (CdS) by electrostatic pull from the built-in electric field, leading to expected BAD production (12.1 mmol g-1 h-1) at the ZnIn2S4 site and H2 generation (12.2 mmol g-1 h-1) at the CdS site. This composite photocatalyst also exhibited high photostability due to the reasonable hole transfer from CdS to ZnIn2S4. The experimental results suggest that the photocatalytic transform of BA into BAD on ZnIn2S4@CdS is via a carbon-centered radical mechanism. This work may extend the design of advanced photocatalysts for more chemicals by replacing H2 evolution with N2 fixation or CO2 reduction in the coupled reactions.

Neuromyelitis optica spectrum disorder mimicking stroke: A case report and literature review.

Hemiparesis is a frequently observed manifestation of stroke but exceptionally rare in the context of neuromyelitis optica spectrum disorder (NMOSD). In this case, a 68-year-old woman initially presented with acute right-sided weakness, leading to suspicion of ischemic stroke. However, her symptoms worsened despite treatment with aspirin and statins. Subsequent spinal MRI and aquaporin 4 antibody testing confirmed the diagnosis of NMOSD. The administration of methylprednisolone and immunoglobulin resulted in improved clinical outcomes. This case serves as an illustrative example of the diverse manifestations encountered in NMOSD and underscores the significance of considering this potential etiology in elderly patients to facilitate prompt diagnosis and therapeutic intervention.

Supramolecular Responsive Chitosan Microcarriers for Cell Detachment Triggered by Adamantane.

Supramolecular responsive microcarriers based on chitosan microspheres were prepared and applied for nonenzymatic cell detachment. Briefly, chitosan microspheres (CSMs) were first prepared by an emulsion crosslinking approach, the surface of which was then modified with ß-cyclodextrin (ß-CD) by chemical grafting. Subsequently, gelatin was attached onto the surface of the CSMs via the host-guest interaction between ß-CD groups and aromatic residues in gelatin. The resultant microspheres were denoted CSM-g-CD-Gel. Due to their superior biocompatibility and gelatin niches, CSM-g-CD-Gel microspheres can be used as effective microcarriers for cell attachment and expansion. L-02, a human fetal hepatocyte line, was used to evaluate cell attachment and expansion with these microcarriers. After incubation for 48 h, the cells attached and expanded to cover the entire surface of microcarriers. Moreover, with the addition of adamantane (AD), cells can be detached from the microcarriers together with gelatin because of the competitive binding between ß-CD and AD. Overall, these supramolecular responsive microcarriers could effectively support cell expansion and achieve nonenzymatic cell detachment and may be potentially reusable with a new cycle of gelatin attachment and detachment.

Lithium-ion battery multi-scale modeling coupled with simplified electrochemical model and kinetic Monte Carlo model.

The multi-scale modeling of lithium-ion battery (LIB) is difficult and necessary due to its complexity. However, it is difficult to capture the aging behavior of batteries, and the coupling mechanism between multiple scales is still incomplete. In this paper, a simplified electrochemical model (SEM) and a kinetic Monte Carlo (KMC)-based solid electrolyte interphase (SEI) film growth model are used to study the multi-scale characteristics of LIBs. The single-particle SEM (SP-SEM) is described for macro scale, and a simple and self-consistent multi-particle SEM (MP-SEM) is developed. Then, the KMC-based SEI model is established for micro-scale molecular evolution. And, the two models are coupled to construct the full-cycle multi-scale model. After modeling, validation is performed by using a commercial 18650-type LIB. Finally, the effect of parameters on the SEI model is studied, including qualitative trend analysis and quantitative sensitivity analysis. The growth of SEI film with different particle sizes is studied by MP-SEM coupling simulation.