Calcineurin is an adaptor required for assembly of the TCR signaling complex.

The serine/threonine phosphatase calcineurin is a component of the T cell receptor (TCR) signalosome, where it promotes T cell activation by dephosphorylating LckS59. Using small interfering RNA (siRNA)-mediated knockdown and CRISPR-Cas9-targeted genetic disruption of the calcineurin A chain α and ß isoforms, we find that calcineurin also functions as an adaptor in TCR-signaled human T cells. Unlike inhibition of its phosphatase activity, in the absence of calcineurin A, TCR signaling results in attenuated actin rearrangement, markedly reduced TCR-Lck microcluster formation and recruitment of the adaptor RhoH, and diminished phosphorylation of critical targets downstream of Lck such as TCRζ and ZAP-70. Reconstitution of deficient T cells with either calcineurin Aα or Aß restores TCR microcluster formation and signaling, as does reconstitution with a phosphatase-inactive Aα chain. These results assign a non-enzymatic adaptor function to calcineurin in the formation and stabilization of a functional TCR signaling complex.

[Anti-inflammatory effect and its mechanism of Saracae Cortex based on zebrafish model and network pharmacology].

This paper aims to explore the anti-inflammatory mechanism of Saracae Cortex by using network pharmacology and molecular docking methods and verify it through the inflammation model of zebrafish. The effective components, potential core targets, and signaling pathways of Saracae Cortex were obtained by using network pharmacology. A lipopolysaccharide(LPS)-induced inflammation model of zebrafish was established to evaluate the anti-inflammatory activity of aqueous extract and 70% ethanol extract of Saracae Cortex with cell apoptosis rate and reactive oxygen species(ROS) production rate as indicators. q PCR was performed to verify the main targets predicted by network pharmacology. The prediction found that there were 121 potential anti-inflammatory targets in Saracae Cortex. Protein-protein interaction(PPI) analysis showed that Saracae Cortex mainly acted on signal transducer and activator of transcription 3(STAT3), vascular endothelial growth factor A( VEGFA), epidermal growth factor( EGF), tumor necrosis factor( TNF),tumor protein p53(TP53), matrix metalloprotein 9(MMP9), c-fos proto-oncogene protein(FOS), estrogen receptor 1(ESR1), cx-c motif chemokine ligand 8(CXCL8), cluster of differentiation 8(CD8), and other targets. Gene Ontology(GO) analysis showed the biological process mainly acted on the inhibition of apoptosis, the positive regulation of gene expression, and the positive regulation of cell proliferation. Kyoto Encyclopedia of Genes and Genomes(KEGG) analysis showed that the mitogen-activated protein kinase(MAPK) signaling pathway, PI3K-Akt signaling pathway, and hypoxia-inducible factor 1(HIF-1) signaling pathway may play a key role in anti-inflammation of Saracae Cortex. Molecular docking verified that five key compounds had a strong binding force with their corresponding core target. Zebrafish animal experiments showed that Saracae Cortex could significantly inhibit ROS formation and reduce cell apoptosis in juvenile fish caused by inflammation and inhibit the further enhancement of inflammatory response in tissue. In addition, compared with the blank group, the transcription levels of nuclear factor kappa-B(NF-κB), TP53, FOS, adaptor protein complex-1(AP-1), and mitogen-activated protein kinases P38(P38) were significantly up-regulated in the model group. Compared with the model group, the m RNA expression of NF-κB, TP53, FOS, AP-1, and P38 was significantly down-regulated in zebrafish tissue treated with aqueous extract and 70% ethanol extract of Saracae Cortex. Saracae Cortex plays an anti-inflammatory role through multiple components and targets, and its anti-inflammatory effect may be related to the inhibition of the MAPK signaling pathway.

Deep Learning-Based Dynamic Region of Interest Autofocus Method for Grayscale Image.

In the field of autofocus for optical systems, although passive focusing methods are widely used due to their cost-effectiveness, fixed focusing windows and evaluation functions in certain scenarios can still lead to focusing failures. Additionally, the lack of datasets limits the extensive research of deep learning methods. In this work, we propose a neural network autofocus method with the capability of dynamically selecting the region of interest (ROI). Our main work is as follows: first, we construct a dataset for automatic focusing of grayscale images; second, we transform the autofocus issue into an ordinal regression problem and propose two focusing strategies: full-stack search and single-frame prediction; and third, we construct a MobileViT network with a linear self-attention mechanism to achieve automatic focusing on dynamic regions of interest. The effectiveness of the proposed focusing method is verified through experiments, and the results show that the focusing MAE of the full-stack search can be as low as 0.094, with a focusing time of 27.8 ms, and the focusing MAE of the single-frame prediction can be as low as 0.142, with a focusing time of 27.5 ms.

The histone methyltransferase KMT2D maintains cellular glucocorticoid-responsiveness by shielding the glucocorticoid receptor from degradation.

Because of their ability to induce lymphocyte apoptosis, glucocorticoids (GC) are widely used to treat hematological malignancies such as lymphomas and multiple myeloma. Their effectiveness is often limited, however, due to the development of glucocorticoid resistance by a variety of molecular mechanisms. Here we performed an unbiased genome-wide CRISPR screen with the human T cell leukemia cell line Jurkat to find previously unidentified genes required for GC-induced apoptosis. One such gene was KMT2D (also known as MLL2 or MLL4), which encodes a histone lysine methyltransferase whose mutations are associated with a variety of cancers, blood malignancies in particular, and are considered markers of poor prognosis. Knockout of KMT2D by CRISPR/Cas9 gene editing in Jurkat and several multiple myeloma cell lines downregulated GR protein expression. Surprisingly, this was not due to a reduction in GR transcripts, but rather to a decrease in the protein's half-life, primarily due to proteasomal degradation. Reconstitution of KMT2D expression restored GR levels. In contrast to the known ability of KMT2D to control gene transcription through covalent histone methylation, KMT2D-mediated upregulation of GR levels did not require its methyltransferase activity. Co-immunoprecipitation and proximity ligation assays found constitutive binding of KMT2D to the GR, which was enhanced in the presence of GC. These observations reveal KMT2D to be essential for stabilization of cellular GR levels, and suggest a possible mechanism by which KMT2D mutations may lead to GC resistance in some malignancies.

Construction of Near-Infrared Probes with Remarkable Large Stokes Shift Based on a Novel Purine Platform for the Visualization of mtG4 Upregulation during Mitochondrial Disorder in Somatic Cells and Human Sperms.

G-quadruplex structures within the nuclear genome (nG4) is an important regulatory factor, while the function of G4 in the mitochondrial genome (mtG4) still needs to be explored, especially in human sperms. To gain a better understanding of the relationship between mtG4 and mitochondrial function, it is crucial to develop excellent probes that can selectively visualize and track mtG4 in both somatic cells and sperms. Herein, based on our previous research on purine frameworks, we attempted for the first time to extend the conjugated structure from the C-8 site of purine skeleton and discovered that the purine derivative modified by the C-8 aldehyde group is an ideal platform for constructing near-infrared probes with extremely large Stokes shift (>220 nm). Compared with the compound substituted with methylpyridine (PAP), the molecule substituted with methylthiazole orange (PATO) showed better G4 recognition ability, including longer emission (∼720 nm), more significant fluorescent enhancement (∼67-fold), lower background, and excellent photostability. PATO exhibited a sensitive response to mtG4 variation in both somatic cells and human sperms. Most importantly, PATO helped us to discover that mtG4 was significantly increased in cells with mitochondrial respiratory chain damage caused by complex I inhibitors (6-OHDA and rotenone), as well as in human sperms that suffer from oxidative stress. Altogether, our study not only provides a novel ideal molecular platform for constructing high-performance probes but also develops an effective tool for studying the relationship between mtG4 and mitochondrial function in both somatic cells and human sperms.

An experimental study on flow behaviour of pharmaceutical powders during suction filling.

Die filling is a crucial step in the pharmaceutical tablet manufacturing process. For industrial-scale production using rotary presses, suction filling is typically employed due to its significant efficiency advantages over gravity filling. Despite its widespread use, our understanding of the suction filling process remains limited. Specifically, there is insufficient comprehension of how filling performance is influenced by factors such as suction velocity, filling velocity, and the properties of the powder materials. Building on our previous research, this study aims to further investigate the effects of powder properties and process parameters (e.g., filling velocity, suction velocity, fill depth) on suction filling behaviour. A systematic experimental investigation was conducted using a model suction filling system, considering both cohesive and free-flowing pharmaceutical powders. The effect of fill depth on suction filling of these powders was examined at different filling and suction velocities. The results demonstrate that two distinctive flow regimes for suction filling can be identified: slow filling and fast filling. These regimes are delineated by a critical filling-to-suction velocity ratio. In the slow filling regime, the filling-to-suction velocity ratio is lower than the critical ratio, meaning that the filling phase is slower than the suction phase. Conversely, the fast filling regime occurs when the filling-to-suction velocity ratio exceeds the critical ratio, implying that the filling phase is faster than the suction phase. This study reveals, for the first time, that when the powder flow pattern during suction filling is dominated by plug flow, full die fill (i.e., the fill ratio equals unity) is achieved in the slow filling regime. However, in the fast filling regime, incomplete die fill is obtained. It is also found that when plug flow prevails during fast filling, the fill ratio has an inverse correlation with the filling-to-suction velocity ratio. This study further reveals that when the plug flow assumption is valid, the filling ratio at various fill-to-suction velocity ratios can be well predicted mathematically. Furthermore, it is also found that once the powder flow pattern differs from the ideal plug flow, which could be induced by the filling conditions and powder cohesion, the fill ratio can be overpredicted.

Research on flexural mechanical properties and mechanism of green ecological coir fiber foamed concrete (CFFC).

To explore the effect and mechanism of coir fiber on the performance of foamed concrete, the flexural performance test, pore characteristics and microstructure test of coir fiber foamed concrete with different content were carried out. First, Image-Pro Plus (image processing software) was used to study the pore morphology, porosity, average pore diameter, and pore roundness of CFFC with various fibers dosage (0, 0.5%, 1.0%, 1.5%, 2.0%, 2.5%) by binarization processing method. Then, a total of eighteen specimens, divided into six groups, were used to investigate the effect of CF dosage on flexural strength, toughness, energy absorption, and failure patterns of FC through a three-point flexural test. Furthermore, the microscopic properties of coir fiber foamed concrete (CFFC) were observed by scanning electron microscope (SEM) and energy dispersive X-ray detector (XRD) to explain the influence mechanism of CF on FC flexural properties. According to the research, CF can affect the pore characteristics of CFFC and improve its flexural performance. When CF content is 1.5-2.0%, the porosity, diameter and roundness of CFFC have lower values of 68.6%, 1.96 mm and 1.29. After the fiber dosage reaches 1.5%, the CFFC failure mode changed to plastic damage, the flexural strength increased from 0.33 to 0.73 MPa, and the toughness energy absorption value was increased from 0.05 to 1.4 J. The optimum dosage of coir fiber is 2.0% for improving the flexural mechanical properties of FC. CF affects the process of hydration reaction of CFFC, but does not change the type of hydration product. However, the flexural performance of FC would decrease with excessive dosage of CF (> 2.0%) due to accelerating the formation of Ca(OH)2. CFFC can solve problems such as brittleness and easy cracking existing in traditional foamed concrete, and it can be used in the field of pavement engineering, foundation backfill and lightweight wall structure with CF dosage of 15-2.0%.

Exploiting tertiary lymphoid structures gene signature to evaluate tumor microenvironment infiltration and immunotherapy response in colorectal cancer.

Background: Tertiary lymphoid structures (TLS) is a particular component of tumor microenvironment (TME). However, its biological mechanisms in colorectal cancer (CRC) have not yet been understood. We desired to reveal the TLS gene signature in CRC and evaluate its role in prognosis and immunotherapy response. Methods: The data was sourced from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) databases. Based on TLS-related genes (TRGs), the TLS related subclusters were identified through unsupervised clustering. The TME between subclusters were evaluated by CIBERSORT and xCell. Subsequently, developing a risk model and conducting external validation. Integrating risk score and clinical characteristics to create a comprehensive nomogram. Further analyses were conducted to screen TLS-related hub genes and explore the relationship between hub genes, TME, and biological processes, using random forest analysis, enrichment and variation analysis, and competing endogenous RNA (ceRNA) network analysis. Multiple immunofluorescence (mIF) and immunohistochemistry (IHC) were employed to characterize the existence of TLS and the expression of hub gene. Results: Two subclusters that enriched or depleted in TLS were identified. The two subclusters had distinct prognoses, clinical characteristics, and tumor immune infiltration. We established a TLS-related prognostic risk model including 14 genes and validated its predictive power in two external datasets. The model's AUC values for 1-, 3-, and 5-year overall survival (OS) were 0.704, 0.737, and 0.746. The low-risk group had a superior survival rate, more abundant infiltration of immune cells, lower tumor immune dysfunction and exclusion (TIDE) score, and exhibited better immunotherapy efficacy. In addition, we selected the top important features within the model: VSIG4, SELL and PRRX1. Enrichment analysis showed that the hub genes significantly affected signaling pathways related to TLS and tumor progression. The ceRNA network: PRRX1-miRNA (hsa-miR-20a-5p, hsa-miR-485-5p) -lncRNA has been discovered. Finally, IHC and mIF results confirmed that the expression level of PRRX1 was markedly elevated in the TLS- CRC group. Conclusion: We conducted a study to thoroughly describe TLS gene signature in CRC. The TLS-related risk model was applicable for prognostic prediction and assessment of immunotherapy efficacy. The TLS-hub gene PRRX1, which had the potential to function as an immunomodulatory factor of TLS, could be a therapeutic target for CRC.

Identifying Frailty in Older Adults Receiving Home Care Assessment Using Machine Learning: Longitudinal Observational Study on the Role of Classifier, Feature Selection, and Sample Size.

BACKGROUND: Machine learning techniques are starting to be used in various health care data sets to identify frail persons who may benefit from interventions. However, evidence about the performance of machine learning techniques compared to conventional regression is mixed. It is also unclear what methodological and database factors are associated with performance. OBJECTIVE: This study aimed to compare the mortality prediction accuracy of various machine learning classifiers for identifying frail older adults in different scenarios. METHODS: We used deidentified data collected from older adults (65 years of age and older) assessed with interRAI-Home Care instrument in New Zealand between January 1, 2012, and December 31, 2016. A total of 138 interRAI assessment items were used to predict 6-month and 12-month mortality, using 3 machine learning classifiers (random forest [RF], extreme gradient boosting [XGBoost], and multilayer perceptron [MLP]) and regularized logistic regression. We conducted a simulation study comparing the performance of machine learning models with logistic regression and interRAI Home Care Frailty Scale and examined the effects of sample sizes, the number of features, and train-test split ratios. RESULTS: A total of 95,042 older adults (median age 82.66 years, IQR 77.92-88.76; n=37,462, 39.42% male) receiving home care were analyzed. The average area under the curve (AUC) and sensitivities of 6-month mortality prediction showed that machine learning classifiers did not outperform regularized logistic regressions. In terms of AUC, regularized logistic regression had better performance than XGBoost, MLP, and RF when the number of features was ≤80 and the sample size ≤16,000; MLP outperformed regularized logistic regression in terms of sensitivities when the number of features was ≥40 and the sample size ≥4000. Conversely, RF and XGBoost demonstrated higher specificities than regularized logistic regression in all scenarios. CONCLUSIONS: The study revealed that machine learning models exhibited significant variation in prediction performance when evaluated using different metrics. Regularized logistic regression was an effective model for identifying frail older adults receiving home care, as indicated by the AUC, particularly when the number of features and sample sizes were not excessively large. Conversely, MLP displayed superior sensitivity, while RF exhibited superior specificity when the number of features and sample sizes were large.

Comparative mitogenome research revealed the phylogenetics and evolution of the superfamily Tenebrionoidea (Coleoptera: Polyphage).

Despite the worldwide distribution and rich diversity of the superfamily Tenebrionoidea, the knowledge of the mitochondrial genomes (mtgenome) characteristics of the superfamily is still very limited, and its phylogenetics and evolution remain unresolved. In the present study, we newly sequenced mtgenomes from 19 species belonging to Tenebrionoidea, and a total of 90 mitochondrial genomes from 16 families of Tenebrionoidea were used for phylogenetic analysis. There exist 37 genes for all 82 species of complete mtgenomes of 16 families investigated, and their characteristics are identical as reported mtgenomes of other Tenebrionoids. The Ka/Ks analysis suggests that all 13 PCGs have undergone a strong purifying selection. The phylogenetic analysis suggests the monophyly of Mordellidae, Meloidae, Oedemeridae, Pyrochroidae, Salpingidae, Scraptiidae, Lagriidae, and Tenebrionidae, and the Mordellidae is close to the Ripiphoridae. The "Tenebrionidae clade" and "Meloidae clade" are monophyletic, and both of them are sister groups. In the "Meloidae clade," Meloidae is close to Anthicidae. In the "Tenebrionidae clade," the family Lagriidae and Tenebrionidae are sister groups. The divergence time analysis suggests that Tenebrionoidea originated in the late Jurassic, Meloidae Mordellidae, Lagriidae, and Tenebrionidae in the Cretaceous, Oedemeridae in Paleogene. The work lays a base for the study of mtgenome, phylogenetics, and evolution of the superfamily Tenebrionoidea.

Unraveling the Intrinsic Origin of the Superior Sodium-Ion Storage Performance of Metal Selenides Anode in Ether-Based Electrolytes.

Metal selenides show outstanding sodium-ion storage performance when matched with an ether-based electrolyte. However, the intrinsic origin of improvement and deterministic interface characteristics have not been systematically elucidated. Herein, employing FeSe2 anode as the model system, the electrochemical kinetics of metal selenides in ether and ester-based electrolytes and associated solid electrolyte interphase (SEI) are investigated in detail. Based on the galvanostatic intermittent titration technique and in situ electrochemical impedance spectroscopy, it is found that the ether-based electrolyte can ensure fast Na+ transfer and low interface impedance. Additionally, the ether-derived thin and smooth double-layer SEI, which is critical in facilitating ion transport, maintaining structural stability, and inhibiting electrolyte overdecomposition, is concretely visualized by transmission electron microscopy, atomic force microscopy, and depth-profiling X-ray photoelectron spectroscopy. This work provides a deep understanding of the optimization mechanism of electrolytes, which can guide available inspiration for the design of practical electrode materials.

Modelling the controlled drug release of push-pull osmotic pump tablets using DEM.

The push-pull osmotic pump tablet is a promising drug delivery approach, offering advantages over traditional dosage forms in achieving consistent and predictable drug release rates. In the current study, the drug release process of push-pull osmotic pump tablets is modelled for the first time using the discrete element method (DEM) incorporated with a microscopic diffusion-induced swelling model. The effects of dosage and formulation design, such as delivery orifice size, drug-to-polymer ratio, tablet surface curvature, friction between particles and cohesion of polymer particles, on the drug release performance are systematically analysed. Numerical results reveal that an enlarged delivery orifice significantly increases both the total drug release and the drug release rate. Moreover, the larger the swellable particle component in the tablet, the higher the drug release rate. Furthermore, the tablet surface curvature is found to affect the drug release profile, i.e. the final drug release percentage increases with the increasing tablet surface curvature. It is also found that the drug release rate could be controlled by adjusting the inter-particle friction and the cohesion of polymer particles in the formulation. This DEM study offers valuable insights into the mechanisms governing drug release in push-pull osmotic pump tablets.

Synergistic N/Mn Codoping Deagglomerate Carbon Coating of LiFePO4/C To Boost Electrochemical Performance.

LiFePO4 is widely used because of its high safety and cycle stability, but its inefficient electronic conductivity combined with sluggish Li+ diffusivity restricts its performance. To overcome this obstacle, applying a layer of conductive carbon onto the surface of LiFePO4 has the greatest improvement in electronic conductivity and Li+ diffusivity. However, the rate performance of carbon-coated LiFePO4 makes it difficult to meet the application requirements. Although nitrogen doping improves electrochemical performance by providing active sites and electronic conductivity, the N-doped carbon coating is prone to agglomeration, which causes a sharp decrease in capacity when the current rate increases. In this work, a synergistic N, Mn codoping strategy is implemented to overcome the aforementioned drawbacks by disrupting the large agglomeration of C-N bonds, improving the uniformity of the surface coating layer to enhance the completeness of the conductive network and increasing the number of Li+ diffusion channels, and thus accelerating the mass transfer rate under high-rate current. Consequently, this strategy effectively improves the rate capability (119 mA h g-1 at 10 C) while maintaining excellent cycling performance (88% capacity retention over 600 cycles at 5 C). This work improves the rate of ion diffusion and the rate capability of micrometer-sized LiFePO4, thus, enabling its wider application.

From Lab to Application: Challenges and Opportunities in Achieving Fast Charging with Polyanionic Cathodes for Sodium-Ion Batteries.

Sodium-ion batteries (SIBs), recognized for balanced energy density and cost-effectiveness, are positioned as a promising complement to lithium-ion batteries (LIBs) and a substitute for lead-acid batteries, particularly in low-speed electric vehicles and large-scale energy storage. Despite their extensive potential, concerns about range anxiety due to lower energy density underscore the importance of fast-charging technologies, which drives the exploration of high-rate electrode materials. Polyanionic cathode materials are emerging as promising candidates in this regard. However, their intrinsic limitation in electronic conductivity poses challenges for synchronized electron and ion transport, hindering their suitability for fast-charging applications. This review provides a comprehensive analysis of sodium ion migration during charging/discharging, highlighting it as a critical rate-limiting step for fast charging. By delving into intrinsic dynamics, key factors that constrain fast-charging characteristics are identified and summarized. Innovative modification routes are then introduced, with a focus on shortening migration paths and increasing diffusion coefficients, providing detailed insights into feasible strategies. Moreover, the discussion extends beyond half cells to full cells, addressing challenges and opportunities in transitioning polyanionic materials from the laboratory to practical applications. This review aims to offer valuable insights into the development of high-rate polyanionic cathodes, acknowledging their pivotal role in advancing fast-charging SIBs.

[Assessment of the lagging effect of vegetation response and loss probability in the Pearl River basin under drought stress]. / å¹²æ—±èƒè¿«ä¸‹ç æ±ŸæµåŸŸæ¤è¢«å“åº”çš„æ»žåŽæ•ˆåº”åŠæŸå¤±æ¦‚çŽ‡è¯„ä¼°.

We quantified the lag time of vegetation response to drought in the Pearl River basin (PRB) based on the standardized precipitation evapotranspiration index (SPEI) and normalized difference vegetation index (NDVI), and constructed a vegetation loss probability model under drought stress based on the Bayesian theory and two-dimensional joint distribution. We further quantitatively evaluated the spatial variations of loss probability of four vegetation types (evergreen broadleaf forest, mixed forest, grassland, and cropland) under different drought intensities. The results showed that the drought risk in eastern West River, the upper reaches of North River and East River, and southern Pearl River Delta was obviously higher than that in other regions during 1982-2020. The response time of vegetation to drought in high-altitude areas in the upper reaches of PRB (mostly<3 month) was generally shorter than that in low altitude areas (>8 month). Drought exacerbated the probability of vegetation loss, with higher vulnerability of mixed forest than the other three vegetation types. The loss probability of vegetation was lower in northwestern PRB than that in central PRB.

Towards Superior Aqueous Zinc-Ion Batteries: The Insights of Artificial Protective Interfaces.

Aqueous zinc ion batteries (AZIBs) with metallic Zn anode have the potential for large-scale energy storage application due to their cost-effectiveness, safety, environmental-friendliness, and ease of preparation. However, the concerns regarding dendrite growth and side reactions on Zn anode surface hamper the commercialization of AZIBs. This review aims to give a comprehensive evaluation of the protective interphase construction and provide guidance to further improve the electrochemical performance of AZIBs. The failure behaviors of the Zn metal anode including dendrite growth, corrosion, and hydrogen evolution are analyzed. Then, the applications and mechanisms of the constructed interphases are introduced, which are classified by the material species. The fabrication methods of the artificial interfaces are summarized and evaluated, including the in-situ strategy and ex-situ strategy. Finally, the characterization means are discussed to give a full view for the study of Zn anode protection. Based on the analysis of this review, a stable and high-performance Zn anode could be designed by carefully choosing applied material, corresponding protective mechanism, and appropriate construction technique. Additionally, this review for Zn anode modification and construction techniques for anode protection in AZIBs may be helpful in other aqueous metal batteries with similar problems.

Tuft cell-derived acetylcholine promotes epithelial chloride secretion and intestinal helminth clearance.

Epithelial cells secrete chloride to regulate water release at mucosal barriers, supporting both homeostatic hydration and the "weep" response that is critical for type 2 immune defense against parasitic worms (helminths). Epithelial tuft cells in the small intestine sense helminths and release cytokines and lipids to activate type 2 immune cells, but whether they regulate epithelial secretion is unknown. Here, we found that tuft cell activation rapidly induced epithelial chloride secretion in the small intestine. This response required tuft cell sensory functions and tuft cell-derived acetylcholine (ACh), which acted directly on neighboring epithelial cells to stimulate chloride secretion, independent of neurons. Maximal tuft cell-induced chloride secretion coincided with immune restriction of helminths, and clearance was delayed in mice lacking tuft cell-derived ACh, despite normal type 2 inflammation. Thus, we have uncovered an epithelium-intrinsic response unit that uses ACh to couple tuft cell sensing to the secretory defenses of neighboring epithelial cells.

Tunneling Proton Grotthuss Transfer Channels by Hydrophilic-Zincophobic Heterointerface Shielding for High-Performance Zn-MnO2 Batteries.

Hollandite-type manganese dioxide (α-MnO2) is recognized as a promising cathode material upon high-performance aqueous zinc-ion batteries (ZIBs) owing to the high theoretical capacities, high working potentials, unique Zn2+/H+ co-insertion chemistry, and environmental friendliness. However, its practical applications limited by Zn2+ accommodation, where the strong coulombic interaction and sluggish kinetics cause significant lattice deformation, fast capacity degradation, insufficient rate capability, and undesired interface degradation. It remains challenging to accurately modulate H+ intercalation while suppressing Zn2+ insertion for better lattice stability and electrochemical kinetics. Herein, proton Grotthuss transfer channels are first tunneled by shielding MnO2 with hydrophilic-zincophobic heterointerface, fulfilling the H+-dominating diffusion with the state-of-the-art ZIBs performance. Local atomic structure and theoretical simulation confirm that surface-engineered α-MnO2 affords to the synergy of Mn electron t2g-eg activation, oxygen vacancy enrichment, selective H+ Grotthuss transfer, and accelerated desolvation kinetics. Consequently, fortified α-MnO2 achieves prominent low current density cycle stability (≈100% capacity retention at 1 C after 400 cycles), remarkable long-lifespan cycling performance (98% capacity retention at 20 C after 12 000 cycles), and ultrafast rate performance (up to 30 C). The study exemplifies a new approach of heterointerface engineering for regulation of H+-dominating Grotthuss transfer and lattice stabilization in α-MnO2 toward reliable ZIBs.

Bacterial Sphingolipids Exacerbate Colitis by Inhibiting ILC3-derived IL-22 Production.

BACKGROUND & AIMS: Gut bacterial sphingolipids, primarily produced by Bacteroidetes, have dual roles as bacterial virulence factors and regulators of the host mucosal immune system, including regulatory T cells and invariant natural killer T cells. Patients with inflammatory bowel disease display altered sphingolipids profiles in fecal samples. However, how bacterial sphingolipids modulate mucosal homeostasis and regulate intestinal inflammation remains unclear. METHODS: We used dextran sodium sulfate (DSS)-induced colitis in mice monocolonized with Bacteroides fragilis strains expressing or lacking sphingolipids to assess the influence of bacterial sphingolipids on intestinal inflammation using transcriptional, protein, and cellular analyses. Colonic explant and organoid were used to study the function of bacterial sphingolipids. Host mucosal immune cells and cytokines were profiled and characterized using flow cytometry, enzyme-linked immunosorbent assay, and Western blot, and cytokine function in vivo was investigated by monoclonal antibody injection. RESULTS: B fragilis sphingolipids exacerbated intestinal inflammation. Mice monocolonized with B fragilis lacking sphingolipids exhibited less severe DSS-induced colitis. This amelioration of colitis was associated with increased production of interleukin (IL)-22 by ILC3. Mice colonized with B fragilis lacking sphingolipids following DSS treatment showed enhanced epithelial STAT3 activity, intestinal cell proliferation, and antimicrobial peptide production. Protection against DSS colitis associated with B fragilis lacking sphingolipids was reversed on IL22 blockade. Furthermore, bacterial sphingolipids restricted epithelial IL18 production following DSS treatment and interfered with IL22 production by a subset of ILC3 cells expressing both IL18R and major histocompatibility complex class II. CONCLUSIONS: B fragilis-derived sphingolipids exacerbate mucosal inflammation by impeding epithelial IL18 expression and concomitantly suppressing the production of IL22 by ILC3 cells.

Research on Vibration Accumulation Self-Powered Downhole Sensor Based on Triboelectric Nanogenerators.

In drilling operations, measuring vibration parameters is crucial for enhancing drilling efficiency and ensuring safety. Nevertheless, the conventional vibration measurement sensor significantly extends the drilling cycle due to its dependence on an external power source. Therefore, we propose a vibration-accumulation-type self-powered sensor in this research, aiming to address these needs. By leveraging vibration accumulation and electromagnetic power generation to accelerate charging, the sensor's output performance is enhanced through a complementary charging mode. The experimental results regarding sensing performance demonstrate that the sensor possesses a measurement range spanning from 0 to 11 Hz, with a linearity of 3.2% and a sensitivity of 1.032. Additionally, it exhibits a maximum average measurement error of less than 4%. The experimental results of output performance measurement indicate that the sensor unit and generator set exhibit a maximum output power of 0.258 µW and 25.5 mW, respectively, and eight LED lights can be lit at the same time. When the sensor unit and power generation unit output together, the maximum output power of the sensor is also 25.5 mW. Furthermore, we conducted tests on the sensor's output signal in conditions of high temperature and humidity, confirming its continued functionality in such environments. This sensor not only achieves self-powered sensing capabilities, addressing the power supply challenges faced by traditional downhole sensors, but also integrates energy accumulation with electromagnetic power generation to enhance its output performance. This innovation enables the sensor to harness downhole vibration energy for powering other micro-power devices, showcasing promising application prospects.