An Insulin-Modified pH-Responsive Nanopipette Based on Ion Current Rectification.

The properties of nanopipettes largely rely on the materials introduced onto their inner walls, which allow for a vast extension of their sensing capabilities. The challenge of simultaneously enhancing the sensitivity and selectivity of nanopipettes for pH sensing remains, hindering their practical applications. Herein, we report insulin-modified nanopipettes with excellent pH response performances, which were prepared by introducing insulin onto their inner walls via a two-step reaction involving silanization and amidation. The pH response intensity based on ion current rectification was significantly enhanced by approximately 4.29 times when utilizing insulin-modified nanopipettes compared with bare ones, demonstrating a linear response within the pH range of 2.50 to 7.80. In addition, insulin-modified nanopipettes featured good reversibility and selectivity. The modification processes were monitored using the I-V curves, and the relevant mechanisms were discussed. The effects of solution pH and insulin concentration on the modification results were investigated to achieve optimal insulin introduction. This study showed that the pH response behavior of nanopipettes can be greatly improved by introducing versatile molecules onto the inner walls, thereby contributing to the development and utilization of pH-responsive nanopipettes.

PRMT6-mediated ADMA promotes p62 phase separation to form a negative feedback loop in ferroptosis.

Purpose: Due to intrinsic defensive response, ferroptosis-activating targeted therapy fails to achieve satisfactory clinical benefits. Though p62-Keap1-Nrf2 axis is activated to form a negative feedback loop during ferroptosis induction, how p62 is activated remains largely unknown. Methods: MTS assay was applied to measure cell growth. Lipid ROS was detected with C11-BODIPY reagent by flow cytometer. Quantitative real-time PCR (qPCR) and western blotting were performed to determine mRNA and protein level. Immunofluorescence (IF) was performed to examine the distribution of proteins. Fluorescence recovery after photobleaching (FRAP) was adopted to evaluate p62 phase separation. Immunoprecipitation (IP), co-IP and Proximal ligation assay (PLA) were performed to detected protein posttranslational modifications and protein-protein interactions. Tumor xenograft model was employed to inspect in vivo growth of pancreatic cancer cells. Results: Upon ferroptosis induction, Nuclear Factor E2 Related Factor 2 (Nrf2) protein and its downstream genes such as HMOX1 and NQO1 were upregulated. Knockdown of p62 significantly reversed Nrf2 upregulation and Keap1 decrease after ferroptosis induction. Knockdown of either p62 or Nrf2 remarkably sensitized ferroptosis induction. Due to augmented p62 phase separation, formation of p62 bodies were increased to recruit Keap1 after ferroptosis induction. Protein arginine methyltransferase 6 (PRMT6) mediated asymmetric dimethylarginine (ADMA) of p62 to increase its oligomerization, promoting p62 phase separation and p62 body formation. Knockdown of p62 or PRMT6 notably sensitized pancreatic cancer cells to ferroptosis both in vitro and in vivo through suppressing Nrf2 signaling. Conclusion: During ferroptosis induction, PRMT6 mediated p62 ADMA to promote its phase separation, sequestering Keap1 to activate Nrf2 signaling and inhibit ferroptosis. Therefore, targeting PRMT6-mediated p62 ADMA could be a new option to sensitize ferroptosis for cancer treatment.

Quantifying Chemical Reactions and Interfacial Properties at Buried Polymer/Polymer Interfaces.

Maleic anhydride (MAH)-modified polymers are used as tie layers for binding dissimilar polymers in multilayer polymer films. The MAH chemistry which promotes adhesion is well characterized in the bulk; however, only recently has the interfacial chemistry been studied. Sum frequency generation vibrational spectroscopy (SFG) is an interfacial spectroscopy technique which provides detailed information on interfacial chemical reactions, species, and molecular orientations and has been essential for characterizing the MAH chemistry in both nylon and ethyl vinyl alcohol copolymer (EVOH) model systems and coextruded multilayer films. Here, we further characterize the interfacial chemistry between MAH-modified polyethylene tie layers and both EVOH and nylon by investigating the model systems over a range of MAH concentrations. We can detect the interfacial chemical reaction products between MAH and the barrier layer at MAH concentrations of ≥0.022 wt % for nylon and ≥0.077 wt % for EVOH. Additionally, from the concentration-dependent reaction reactant/product SFG peak positions and the product imide or ester/acid C═O group tilt angles extracted from the polarization-dependent SFG spectra, we quantitatively observe concentration-dependent changes to both the interfacial chemistry and interfacial structure. The interfacial chemistry and molecular orientation as a function of MAH concentration are well correlated with the adhesion strength, providing important quantitative information for the future design of MAH-modified tie layers for a variety of important applications.

Terpene synthases GhTPS6 and GhTPS47 participate in resistance to Verticillium dahliae in upland cotton.

Terpene synthases (TPSs) are enzymes responsible for catalyzing the production of diverse terpenes, the largest class of secondary metabolites in plants. Here, we identified 107 TPS gene loci encompassing 92 full-length TPS genes in upland cotton (Gossypium hirsutum L.). Phylogenetic analysis showed they were divided into six subfamilies. Segmental duplication and tandem duplication events contributed greatly to the expansion of TPS gene family, particularly the TPS-a and TPS-b subfamilies. Expression profile analysis screened out that GhTPSs may mediate the interaction between cotton and Verticillium dahliae. Three-dimensional structures and subcellular localizations of the two selected GhTPSs, GhTPS6 and GhTPS47, which belong to the TPS-a subfamily, demonstrated similarity in protein structures and nucleus and cytoplasm localization. Virus-induced gene silencing (VIGS) of the two GhTPSs yielded plants characterized by increased wilting and chlorosis, more severe vascular browning, and higher disease index than control plants. Additionally, knockdown of GhTPS6 and GhTPS47 led to the down-regulation of cotton terpene synthesis following V. dahliae infection, indicating that these two genes may positively regulate resistance to V. dahliae through the modulation of disease-resistant terpene biosynthesis. Overall, our study represents a comprehensive analysis of the G. hirsutum TPS gene family, revealing their potential roles in defense responses against Verticillium wilt.

Recognition of small water bodies under complex terrain based on SAR and optical image fusion algorithm.

Understanding the spatial and temporal distribution of small water bodies is essential for managing water resources, crafting conservation policies, and preserving watershed ecosystems and biodiversity. However, existing studies often rely on a single remote sensing data source (optical or microwave), focusing on large-scale, flat areas and lacking comprehensive monitoring of small water bodies in complex terrain. Therefore, considering the complementary advantages of multisource remote sensing (multispectral and SAR), this paper proposes a multispectral and SAR fusion algorithm, named Multispectral and SAR Fusion algorithm (MASF), to better capture the remote sensing characteristics of small water bodies in complex areas. Based on this, a dataset containing spectral, texture, and geometric features is constructed, and multi-scale segmentation and random forest algorithms are applied for identification of small water bodies in complex terrain. The results demonstrate that the proposed fusion algorithm MASF exhibits minimal spectral distortion (SAM < 3.5, ERGAS <21, RMSE <0.01) and robust spatial feature enhancement (PSNR >40, SSIM >0.999, CC > 0.99). The Overall Accuracy (OA) and Kappa coefficients for both experimental areas surpassed 0.9. For rivers and reservoirs, both Producer's Accuracy (PA) and User's Accuracy (UA) exceeded 0.9. The UA for agricultural ponds exceeded 0.8. Comparative analysis with three other types of water-related data products shows that the freshwater identification results in this study have certain advantages in local small water bodies. Our research holds significant implications for the utilization of water resources in mountainous areas, prevention and control of floods and floods, as well as the development of aquaculture industry.

Wafer-Scale Patterning Integration of Chiral 3D Perovskite Single Crystals toward High-Performance Full-Stokes Polarimeter.

Chiral three-dimensional (3D) perovskites exhibit exceptional optoelectronic characteristics and inherent chiroptical activity, which may overcome the limitations of low-dimensional chiral optoelectronic devices and achieve superior performance. The integrated chip of high-performance arbitrary polarized light detection is one of the aims of chiral optoelectronic devices and may be achieved by chiral 3D perovskites. Herein, we first fabricate the wafer-scale integrated full-Stokes polarimeter by the synergy of unprecedented chiral 3D perovskites (R/S-PyEA)Pb2Br6 and one-step capillary-bridge assembly technology. Compared with the chiral low-dimensional perovskites, chiral 3D perovskites present smaller exciton binding energies of 57.3 meV and excellent circular dichroism (CD) absorption properties, yielding excellent circularly polarized light (CPL) photodetectors with an ultrahigh responsivity of 86.7 A W-1, an unprecedented detectivity exceeding 4.84 × 1013 Jones, a high anisotropy factor of 0.42, and high-fidelity CPL imaging with 256 pixels. Moreover, the anisotropic crystal structure also enables chiral 3D perovskites to have a large linear-polarization response with a polarized ratio of 1.52. The combination of linear-polarization and circular-polarization discrimination capabilities guarantees the achievement of a full-Stokes polarimeter. Our study provides new research insights for the large-scale patterning wafer integration of high-performance chiroptical devices.

Molecular behavior of silicone adhesive at buried polymer interface studied by molecular dynamics simulation and sum frequency generation vibrational spectroscopy.

Silicones have excellent material properties and are used extensively in many applications, ranging from adhesives and lubricants to electrical insulation. To ensure strong adhesion of silicone adhesives to a wide variety of substrates, silane-based adhesion promotors are typically blended into the silicone adhesive formulation. However, little is known at the molecular level about the true silane adhesion promotion mechanism, which limits the ability to develop even more effective adhesion promoters. To understand the adhesion promotion mechanism of silane molecules at the molecular level, this study has used sum frequency generation vibrational spectroscopy (SFG) to determine the behavior of (3-glycidoxypropyl)trimethoxy silane (γ-GPS) at the buried interface between poly(ethylene terephthalate) (PET) and a bulk silicone adhesive. To complement and extend the SFG results, atomistic molecular dynamics (MD) simulations were applied to investigate molecular behavior and interfacial interaction of γ-GPS at the silicone/PET interface. Free energy computations were used to study the γ-GPS interaction in the sample system and determine the γ-GPS interfacial segregation mechanism. Both experiments and simulations consistently show that γ-GPS molecules prefer to segregate at the interface between PET and PDMS. The methoxy groups on γ-GPS molecules orient toward the PDMS polymer phase. The consistent picture of interfacial structure emerging from both simulation and experiment provides enhanced insight on how γ-GPS behaves in the silicone - PET system and illustrates why γ-GPS could improve the adhesion of silicone adhesive, leading to further understanding of silicone adhesion mechanisms useful in the design of silicone adhesives with improved performance.

D-dimer levels predict the treatment efficacy and prognosis of esophageal squamous cell carcinoma treated with PD-1/PD-L1 inhibitors.

OBJECTIVES: This study aimed to explore the value of D-dimer levels in predicting the treatment efficacy and prognosis of advanced esophageal squamous cell carcinoma (ESCC) treated with programmed cell death protein-1/programmed death-ligand 1 (PD-1/PD-L1) inhibitors. METHODS: The study retrospectively analyzed 233 ESCC patients who received PD-1/PD-L1 inhibitors. The optimal cut-off values for platelets, fibrinogen, and D-dimer were calculated based on maximally selected rank statistics for patients' overall survival. Univariate and multivariate analyses of progression-free survival and overall survival were conducted by Cox proportional hazards regression model. Subgroup analyses of D-dimer levels in different fibrinogen levels were performed by log-rank test. RESULTS: The multivariate Cox regression analyses demonstrated that ESCC patients with D-dimer levels > 236 ng/mL exhibited both poorer progression-free survival (P = 0.004) and overall survival (P < 0.0001) compared to those with low D-dimer levels. The subgroup analyses further indicated that in the group of low fibrinogen levels, the higher D-dimer levels of ESCC patients exhibited significantly shorter progression-free survival (P = 0.0021) and overall survival (P < 0.0001). CONCLUSIONS: The study revealed that the D-dimer levels possess predictive value for the treatment efficacy and prognosis of ESCC patients treated with PD-1/PD-L1 inhibitors.

Coinfecting phages impede each other's entry into the cell.

The developmental choice made by temperate phages, between cell death (lysis) and viral dormancy (lysogeny), is influenced by the relative abundance of viruses and hosts in the environment. The paradigm for this abundance-driven decision is phage lambda of E. coli, whose propensity to lysogenize increases with the number of viruses coinfecting the same bacterium. It is believed that lambda uses this number to infer whether phages or bacteria outnumber each other. However, this interpretation is premised on an accurate mapping between the extracellular phage-to-bacteria ratio and the intracellular multiplicity of infection (MOI). Here, we show this premise to be faulty. By simultaneously labeling phage capsids and genomes, we find that, while the number of phages landing on each cell reliably samples the population ratio, the number of phages entering the cell does not. Single-cell infections, performed in a microfluidic device and interpreted using a stochastic model, reveal that the probability and rate of phage entry decrease with the number of adsorbed phages. This decrease reflects an MOI-dependent perturbation to host physiology caused by phage attachment, as evidenced by compromised membrane integrity and loss of membrane potential. The dependence of entry dynamics on the surrounding medium results in a strong impact on the infection outcome, while the protracted entry of coinfecting phages increases the heterogeneity in infection outcome at a given MOI. Our findings in lambda, and similar results we obtained for phages T5 and P1, demonstrate the previously unappreciated role played by entry dynamics in determining the outcome of bacteriophage infection.

Giant magneto-photoluminescence at ultralow field in organic microcrystal arrays for on-chip optical magnetometer.

Optical detection of magnetic field is appealing for integrated photonics; however, the light-matter interaction is usually weak at low field. Here we observe that the photoluminescence (PL) decreases by > 40% at 10 mT in rubrene microcrystals (RMCs) prepared by a capillary-bridge assembly method. The giant magneto-PL (MPL) relies on the singlet-triplet conversion involving triplet-triplet pairs, through the processes of singlet fission (SF) and triplet fusion (TF) during radiative decay. Importantly, the size of RMCs is critical for maximizing MPL as it influences on the photophysical processes of spin state conversion. The SF/TF process is quantified by measuring the prompt/delayed PL with time-resolved spectroscopies, which shows that the geminate SF/TF associated with triplet-triplet pairs are responsible for the giant MPL. Furthermore, the RMC-based magnetometer is constructed on an optical chip, which takes advantages of remarkable low-field sensitivity over a broad range of frequencies, representing a prototype of emerging opto-spintronic molecular devices.

Self-Supervised Image Denoising of Third Harmonic Generation Microscopic Images of Human Glioma Tissue by Transformer-based Blind Spot (TBS) Network.

Third harmonic generation (THG) microscopy shows great potential for instant pathology of brain tumor tissue during surgery. However, due to the maximal permitted exposure of laser intensity and inherent noise of the imaging system, the noise level of THG images is relatively high, which affects subsequent feature extraction analysis. Denoising THG images is challenging for modern deep-learning based methods because of the rich morphologies contained and the difficulty in obtaining the noise-free counterparts. To address this, in this work, we propose an unsupervised deep-learning network for denoising of THG images which combines a self-supervised blind spot method and a U-shape Transformer using a dynamic sparse attention mechanism. The experimental results on THG images of human glioma tissue show that our approach exhibits superior denoising performance qualitatively and quantitatively compared with previous methods. Our model achieves an improvement of 2.47-9.50 dB in SNR and 0.37-7.40 dB in CNR, compared to six recent state-of-the-art unsupervised learning models including Neighbor2Neighbor, Blind2Unblind, Self2Self+, ZS-N2N, Noise2Info and SDAP. To achieve an objective evaluation of our model, we also validate our model on public datasets including natural and microscopic images, and our model shows a better denoising performance than several recent unsupervised models such as Neighbor2Neighbor, Blind2Unblind and ZS-N2N. In addition, our model is nearly instant in denoising a THG image, which has the potential for real-time applications of THG microscopy.

KMTLabeler: An Interactive Knowledge-Assisted Labeling Tool for Medical Text Classification.

The process of labeling medical text plays a crucial role in medical research. Nonetheless, creating accurately labeled medical texts of high quality is often a time-consuming task that requires specialized domain knowledge. Traditional methods for generating labeled data typically rely on rigid rule-based approaches, which may not adapt well to new tasks. While recent machine learning (ML) methodologies have mitigated the manual labeling efforts, configuring models to align with specific research requirements can be challenging for labelers without technical expertise. Moreover, automated labeling techniques, such as transfer learning, face difficulties in in directly incorporating expert input, whereas semi-automated methods, like data programming, allow knowledge integration through rules or knowledge bases but may lack continuous result refinement throughout the entire labeling process. In this study, we present a collaborative human-ML teaming workflow that seamlessly integrates visual cluster analysis and active learning to assist domain experts in labeling medical text with high efficiency. Additionally, we introduce an innovative neural network model called the embedding network, which incorporates expert insights to generate task-specific embeddings for medical texts. We integrate the workflow and embedding network into a visual analytics tool named KMTLabeler, equipped with coordinated multi-level views and interactions. Two illustrative case studies, along with a controlled user study, provide substantial evidence of the effectiveness of KMTLabeler in creating an efficient labeling environment for medical text classification.

A single crystal study of Kagome metals U2Mn3Ge and U2Fe3Ge.

Single crystals of U2Mn3Ge and U2Fe3Ge with a Kagome lattice structure were synthesized using a high-temperature self-flux crystal growth method. The physical properties of these crystals were characterized through measurements of resistivity, magnetism, and specific heat. U2Fe3Ge exhibits ferromagnetic ground state and anomalous Hall effect, and U2Mn3Ge demonstrates a complex magnetic structure. Both compounds exhibit large Sommerfeld coefficient, indicating coexistence of heavy Fermion behaviour with magnetism. Our results suggest that this U2TM3Ge (TM = Mn, Fe, Co) family is a promising platform to investigate the interplay of magnetism, Kondo physics and the Kagome lattice.

Integrating water quality data with a Bayesian network model to improve spatial and temporal phosphorus attribution: Application to the Maumee River Basin.

Surface water nutrient pollution, the primary cause of eutrophication, remains a major environmental concern in Western Lake Erie despite intergovernmental efforts to regulate nutrient sources. The Maumee River Basin has been the largest nutrient contributor. The two primary nutrient sources are inorganic fertilizer and livestock manure applied to croplands, which are later carried to the streams via runoff and soil erosion. Prior studies of nutrient source attribution have focused on large watersheds or counties at annual time scales. Source attribution at finer spatiotemporal scales, which enables more effective nutrient management, remains a substantial challenge. This study aims to address this challenge by developing a generalizable Bayesian network model for phosphorus source attribution at the subwatershed scale (12-digit Hydrologic Unit Code). Since phosphorus release is uncertain, we combine excess phosphorus derived from manure and fertilizer application and crop uptake data, flow information simulated by the SWAT model, and in-stream water quality measurements using Approximate Bayesian Computation to derive a posterior that attributes phosphorus contributions to subwatersheds. Our results show significant variability in subwatershed-scale phosphorus release that is lost in coarse-scale attribution. Phosphorus contributions attributed to the subwatersheds are on average lower than the excess phosphorus estimated by the nutrient balance approach currently adopted by environmental agencies. Fertilizer contributes more soluble reactive phosphorus than manure, while manure contributes most of the unreactive phosphorus. While developed for the specific context of Maumee River Basin, our lightweight and generalizable model framework could be adapted to other regions and pollutants and could help inform targeted environmental regulation and enforcement.

Research Progress on CARM1 and its Relationship with Colorectal Cancer.

Coactivator-associated arginine methyltransferase 1 (CARM1) is significant as a key member of the PRMT family, crucial for regulating arginine methylation, and its association with colorectal cancer underscores its potential as a therapeutic target. Consequently, CARM1 inhibitors have emerged as potential therapeutic agents in cancer treatment and valuable chemical tools for cancer research. Despite steady progress in CARM1 inhibitor research, challenges persist in discovering effective, isoform-selective, cell-permeable, and in vivo-active CARM1 inhibitors for colorectal cancer. This review summarizes the research progress on CARM1 and its relationship with colorectal cancer, aiming to provide a theoretical basis for the radiotherapy of colorectal cancer.

GhCLCc-1, a Chloride Channel Gene from Upland Cotton, Positively Regulates Salt Tolerance by Modulating the Accumulation of Chloride Ions.

The ionic toxicity induced by salinization has adverse effects on the growth and development of crops. However, researches on ionic toxicity and salt tolerance in plants have focused primarily on cations such as sodium ions (Na+), with very limited studies on chloride ions (Cl-). Here, we cloned the homologous genes of Arabidopsis thaliana AtCLCc, GhCLCc-1A/D, from upland cotton (Gossypium hirsutum), which were significantly induced by NaCl or KCl treatments. Subcellular localization showed that GhCLCc-1A/D were both localized to the tonoplast. Complementation of Arabidopsis atclcc mutant with GhCLCc-1 rescued its salt-sensitive phenotype. In addition, the silencing of the GhCLCc-1 gene led to an increased accumulation of Cl- in the roots, stems, and leaves of cotton seedlings under salt treatments, resulting in compromised salt tolerance. And ectopic expression of the GhCLCc-1 gene in Arabidopsis reduced the accumulation of Cl- in transgenic lines under salt treatments, thereby enhancing salt tolerance. These findings elucidate that GhCLCc-1 positively regulates salt tolerance by modulating Cl- accumulation and could be a potential target gene for improving salt tolerance in plants.

Vibration-Dependent Dual-Phosphorescent Cu4 Nanocluster with Remarkable Piezochromic Behavior.

The dual emission (DE) characteristics of atomically precise copper nanoclusters (Cu NCs) are of significant theoretical and practical interest. Despite this, the underlying mechanism driving DE in Cu NCs remains elusive, primarily due to the complexities of excited state processes. Herein, a novel [Cu4(PPh3)4(C≡C-p-NH2C6H4)3]PF6 (Cu4) NC, shielded by alkynyl and exhibiting DE, was synthesized. Hydrostatic pressure was applied to Cu4, for the first time, to investigate the mechanism of DE. With increasing pressure, the higher-energy emission peak of Cu4 gradually disappeared, leaving the lower-energy emission peak as the dominant emission. Additionally, the Cu4 crystal exhibited notable piezochromism transitioning from cyan to orange. Angle-dispersive synchrotron X-ray diffraction results revealed that the reduced inter-cluster distances under pressure brought the peripheral ligands closer, leading to the formation of new C-H⋅⋅⋅N and N-H⋅⋅⋅N hydrogen bonds in Cu4. It is proposed that these strengthened hydrogen bond interactions limit the ligands' vibration, resulting in the vanishing of the higher-energy peak. In situ high-pressure Raman and vibrationally resolved emission spectra demonstrated that the benzene ring C=C stretching vibration is the structural source of the DE in Cu4.

High intestinal carriage of Clostridium perfringens in healthy individuals and ICU patients in Hangzhou, China.

Clostridium perfringens has emerged as a growing public health concern due to its ability to cause various infections and its increasing resistance to antibiotics. To assess its current epidemiology in clinical settings, we conducted a survey involving 426 healthy individuals and 273 ICU inpatients at a provincial hospital in China. Our findings revealed a high prevalence of C. perfringens in healthy individuals (45.77%, 95% CI: 41.0%-50.6%) and ICU patients (12.82%, 95% CI: 9.1%-17.4%). The identified 220 C. perfringens isolates displayed substantial resistance to erythromycin (57.9%), clindamycin (50.7%), and tetracycline (32.0%), primarily attributed to the presence of erm(Q) (54.4%), lnu(P) (13.8%), tetB(P) (83.6%), and tetA(P) (66.7%). Notably, C. perfringens isolates from this particular hospital demonstrated a high degree of sequence type diversity and phylogenic variation, suggesting that the potential risk of infection primarily arises from the bacteria's gut colonization rather than clonal transmissions within the clinical environment. This study provides an updated analysis of the current epidemiology of C. perfringens in healthy individuals and ICU patients in China and emphasizes the need to optimize intervention strategies against its public health threat. IMPORTANCE: Clostridium perfringens is a bacterium of growing public health concern due to its ability to cause infections and its increasing resistance to antibiotics. Understanding its epidemiology in clinical settings is essential for intervention strategies. This study surveyed healthy individuals and ICU inpatients in a provincial hospital in China. It found a high prevalence of C. perfringens, indicating infection risk. The isolates also showed significant antibiotic resistance. Importantly, the study revealed diverse sequence types and phylogenetic variation, suggesting infection risk from intestinal colonization rather than clonal transmission in hospitals. This analysis emphasizes the need to optimize intervention strategies against this public health threat.

Long-Term Accumulation of T Cytotoxic 1, T Cytotoxic 17, and T Cytotoxic 17/1 Cells in the Brain Contributes to Microglia-Mediated Chronic Neuroinflammation After Ischemic Stroke.

Post-stroke neuroinflammation affects the damage and recovery of neurological functions. T cells including CD8+ T cells were present in the ipsilateral hemisphere in the subacute and late phases of ischemic stroke. However, the potential roles of CD8+ T cell subsets in the progression of neuroinflammation have not been characterized. In the current mouse transient middle cerebral artery occlusion model, we investigated the existence of CD8+ T cell subsets in the ipsilateral hemisphere in the subacute and late phases of stroke. We found that ipsilateral CD8+ T cells were present on post-stroke day 3 and increased on post-stroke day 30. The day-3 ipsilateral CD8+ T cells predominantly produced interferon-γ (IFN-γ), while the day-30 ipsilateral CD8+ T cells co-expressed IFN-γ and interleukin-17A (IL-17A). In addition, evaluation of cytokines and transcription factors of the day-30 ipsilateral CD8+ T cells revealed the presence of T cytotoxic 1 (Tc1), T cytotoxic 17 (Tc17), and T cytotoxic 17/1 (Tc17/1) cells. Furthermore, based on the expression of a series of chemokine/cytokine receptors, viable ipsilateral Tc1, Tc17, and Tc17.1 cells were identified and enriched from the day-30 ipsilateral CD8+ T cells, respectively. Co-culture of microglia with ipsilateral Tc1, Tc17, or Tc17.1 cells indicated that the three CD8+ T cell subsets up-regulated the expression of pro-inflammatory mediators by microglia, with Tc17.1 cells being the most potent cell in doing so. Collectively, this study sheds light on the contributions of Tc1, Tc17, and Tc17.1 cells to long-term neuroinflammation after ischemic stroke.