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PDZ-binding kinase/T-lymphokine-activated killer-cell-originated protein kinase (PBK/TOPK) is a serine-threonine protein kinase. This study aimed to investigate the expression pattern, prognostic significance, and relationship with tumor immune infiltration of PBK/TOPK in breast cancer through bioinformatics analyses and immunohistochemistry (IHC), providing insights for individualized treatment and immunotherapy strategies. PBK/TOPK expression and its correlation with clinicopathological features were analyzed using TIMER, UALCAN, and TCGA databases. Prognostic value was assessed via Kaplan–Meier plotter and bc-GenExMiner. Variants of the PBK/TOPK gene and their prognostic implications were explored using cBioPortal. Enrichment analysis in R identified signaling pathways linked to PBK/TOPK. The relationships between PBK/TOPK, tumor-infiltrating lymphocytes (TILs), and immune cell markers were evaluated using TIMER and TISIDB. IHC experiments validated PBK/TOPK expression in tumor samples and its association with prognosis. Meanwhile, IHC also further confirmed the correlation between PBK/TOPK and CD4 + and CD8 + T cells infiltration, as well as the relationship between T cells and breast cancer prognosis. PBK/TOPK was significantly overexpressed in breast cancer tissues compared to normal tissues and correlated with clinicopathological features, including tumor size and lymph node stage. High expression of PBK/TOPK was associated with poor prognosis. While breast cancer subtypes exhibited different PBK/TOPK gene variants, these variants did not influence prognosis. PBK/TOPK is involved in cell meiosis, cytoskeletal motility, and pathways such as FoxO and p53. It is associated with immune infiltration and is differentially expressed in breast cancer subtypes and correlates with TILs and immune cell markers. IHC confirms that PBK/TOPK expression positively correlates with CD4 +  T and CD8 + T cells infiltration. CD4 + T cells were positively associated with the prognosis of triple-negative breast cancer. PBK/TOPK is overexpressed in breast cancer tissues, and high expression levels are associated with poor patient prognosis. Additionally, PBK/TOPK is linked to immune infiltration in breast cancer, positively correlating with CD4 + and CD8 + T cells infiltration, suggesting a new avenue for immunotherapy research in breast cancer.

Background Neoadjuvant chemotherapy is the recommended treatment for stage II and III triple-negative breast cancer (TNBC). We aimed to study the role of phosphorylated Nrf2 (pNrf2) in the responses to neoadjuvant chemotherapy in TNBC patients. Methods A prospective observational cohort study was performed in stage II and III TNBC patients who were scheduled for neoadjuvant chemotherapy between January 2017 and December 2021. The pre-treatment characteristics, including age, menses, tumor size and stages, and lymph node metastasis, were collected. The pNrf2 expression was determined by immunohistochemistry examination of tumor specimens obtained by pre-treatment core-needle biopsy. Post-treatment responses were evaluated as the clinical outcomes (RECIST) and pathological outcomes (Miller–Payne grading). Patients were assigned into either the low or high Nrf2 expression group. Their clinical characteristics and treatment responses were compared. Multivariate logistic regression analysis was performed to study the association between pNrf2 and pathological outcomes. Results In total, 59 patients were included, with a mean age of 52.5 years old. There were 29 patients in the low pNrf2 group and 30 in the high pNrf2 group, respectively. The pre-treatment characteristics were comparable between the two groups. Compared with the low pNrf2 expression group, the high pNrf2 expression group had poorer clinical and pathological responses ( P  = 0.010 and < 0.001, respectively). Multivariate logistic regression analysis showed that the pNrf2 expression was negatively associated with the pathological response to neoadjuvant chemotherapy (odds ratio 0.033, 95% confidence interval 0.006–0.187). Conclusions In patients with TNBC, the pre-treatment pNrf2 expression was negatively correlated with the response to neoadjuvant chemotherapy.

The quality of visual feature representation has always been a key factor in many computer vision tasks. In the person re-identification (Re-ID) problem, combining global and local features to improve model performance is becoming a popular method, because previous works only used global features alone, which is very limited at extracting discriminative local patterns from the obtained representation. Some existing works try to collect local patterns explicitly slice the global feature into several local pieces in a handcrafted way. By adopting the slicing and duplication operation, models can achieve relatively higher accuracy but we argue that it still does not take full advantage of partial patterns because the rule and strategy local slices are defined. In this paper, we show that by firstly over-segmenting the global region by the proposed multi-branch structure, and then by learning to combine local features from neighbourhood regions using the proposed Collaborative Attention Network (CAN), the final feature representation for Re-ID can be further improved. The experiment results on several widely-used public datasets prove that our method outperforms many existing state-of-the-art methods.

The properties of galaxies are intricately linked to the characteristics of their host dark-matter haloes. We use a suite of controlled simulations of isolated galaxies to quantify how halo spin, concentration, inner density profile, and baryon fraction regulate galaxy sizes, at fixed halo mass of \\(M_{\\rm{vir}}=10^{11} M_\\odot\\). We generate initial conditions of haloes and inhabitant spherical gas distributions in equilibrium, on a parameter grid spanned by these four halo parameters, and evolve the systems with the \\(\\texttt{GIZMO}\\) code and the \\(\\texttt{FIRE-3}\\) physics. The resulting half-mass radii of stars and cold baryons depend systematically on halo structure and baryon content: galaxy size increases with halo spin, decreases with halo concentration, is weakly sensitive to the inner density slope except in highly cuspy haloes, and is strongly suppressed at high baryon fractions. We evaluate the relative importance of the halo parameters on galaxy size using different metrics including the quadratic response-surface method and random-forest regression, and consistently find halo concentration to be the most informative predictor of size. The baryon fraction shows a subtle, non-monotonic impact on size, by modulating how galaxy size depends on halo spin. Our results clarify which secondary parameters of host dark-matter haloes dominate the scatter in galaxy sizes at the massive-dwarf mass scale.

It has long been predicted that the Milky Way (MW) will eventually merge with Andromeda (M31), a view reinforced by \\textit{HST} measurements indicating a small M31 transverse velocity. However, using updated \\textit{Gaia}-based proper motions (PMs) and including the dynamical influence of the Large Magellanic Cloud (LMC) and M33, Sawala et al. reported an MW--M31 merger probability of \\(\\sim\\)50\\% within 10 Gyr, leaving the fate of the Local Group (LG) uncertain. Adopting their semi-analytic framework, we revisit this problem with the latest and most precise \\textit{Gaia}-based PMs for M31 and M33, corrected for systematic offsets in \\textit{Gaia} astrometry. In our fiducial model, the MW--M31 merger probability rises to 90\\%, with a median merger time of \\(6.5_{-1.5}^{+1.3}\\) Gyr, broadly restoring the classical picture. A sensitivity analysis shows that the merger probability depends strongly on the adopted M31 PM through two channels: a direct effect via the radial-tangential balance of the MW-M31 orbit, and a satellite-mediated effect, where the M31 PM fixes the orbital plane and determines how satellite-induced barycentric reflex motions project onto it, either promoting or suppressing a merger. Given this sensitivity, current measurements, while favoring a high merger probability, remain inconclusive, spanning from 64.7\\% to 100\\% across the 2\\(\\sigma\\) PM region. Future PM measurements with uncertainty of \\(\\lesssim2\\,\\upmu\\mathrm{as\\,yr^{-1}}\\) will be required to reach a firm conclusion, i.e., to constrain the probability range within 10\\% at the 2\\(\\sigma\\) level.

PTEN is frequently mutated in human cancers and PTEN mutants promote tumor progression and metastasis. PTEN mutations have been implicated in immune regulation, however, the underlying mechanism is largely unknown. Here, we report that PTENα, the isoform of PTEN, remains active in cancer bearing stop-gained PTEN mutations. Through counteraction of CD8 +  T cell-mediated cytotoxicity, PTENα leads to T cell dysfunction and accelerates immune-resistant cancer progression. Clinical analysis further uncovers that PTENα-active mutations suppress host immune responses and result in poor prognosis in cancer as relative to PTENα-inactive mutations. Furthermore, germline deletion of Ptenα in mice increases cell susceptibility to immune attack through augmenting stress granule formation and limiting synthesis of peroxidases, leading to massive oxidative cell death and severe inflammatory damage. We propose that PTENα protects tumor from T cell killing and thus PTENα is a potential target in antitumor immunotherapy. PTENα is an N-terminally extended isoform of PTEN, a gene frequently mutated in human cancers. Here the authors show that PTENα remains active in PTEN-mutant cancers and is associated with tumor immune escape by promoting tumor cell resistance to T cell cytotoxicity.

Cancer cells subvert immune surveillance through inhibition of T cell effector function. Elucidation of the mechanism of T cell dysfunction is therefore central to cancer immunotherapy. Here, we report that dual specificity phosphatase 2 (DUSP2; also known as phosphatase of activated cells 1, PAC1) acts as an immune checkpoint in T cell antitumor immunity. PAC1 is selectively upregulated in exhausted tumor-infiltrating lymphocytes and is associated with poor prognosis of patients with cancer. PAC1 hi effector T cells lose their proliferative and effector capacities and convert into exhausted T cells. Deletion of PAC1 enhances immune responses and reduces cancer susceptibility in mice. Through activation of EGR1, excessive reactive oxygen species in the tumor microenvironment induce expression of PAC1, which recruits the Mi-2β nucleosome-remodeling and histone-deacetylase complex, eventually leading to chromatin remodeling of effector T cells. Our study demonstrates that PAC1 is an epigenetic immune regulator and highlights the importance of targeting PAC1 in cancer immunotherapy. Yin and colleagues show that the phosphatase PAC1 (DUSP2) acts as a checkpoint in cytotoxic T cells to restrain their antitumor function.

Open-type check dams are widely used to mitigate debris-flow hazards in mountainous areas. However, the regulation function of dams is a non-trivial and still open issue. With the aim to better understand the process regulation of open-type check dam against debris flow, in this study, a series of specially designed flume experiments are conducted as well as contrast tests of closed-type dam. The effects of the debris-flow bulk density, opening form, and dam size are considered. Analysis of the flow patterns, discharge process, peak discharge, and flow duration give an insight into regulating detail. Results reveal that the regulation characteristics depend on the blocking performance of open structure. There are differences in the debris-flow hydrography after passing through an open-type or closed-type dam, and the temporary blocking phenomenon is found to play an important role in regulating the discharge process. Moreover, open-type dams produce a reduction and time lag in the peak discharge, and more effectively regulate the travel time of debris flow downstream than closed-type dam. The reduction ratio of peak discharge for narrow openings is similar to that of closed-type dam and decreases as the relative opening becomes wider. Finally, based on these regulation characteristics, the application of open-type dams for a novel form of debris flow mitigation is discussed from the perspective of balancing interception and regulation of sediment.

Elastic ring squeeze film damper (ERSFD) is widely used for vibration and noise control of industrial rotating machinery. However, the oil film temperature has an impact on the ERSFD rotor system under large unbalanced force and speed, which is not considered in the existing ERSFD rotor system research. In this paper, by coupling energy equation with Reynolds equation and viscosity-temperature equation, an ERSFD model considering oil film temperature is established to investigate the oil film force and temperature distribution. Based on this model, an ERSFD combined support rotor considering oil film temperature is modeled by coupling the dynamic equations of the combined support rotor with the ERSFD reaction force. Then, the influence of oil film temperature on the amplitude frequency response curve and the sudden unbalance response curve of the ERSFD rotor is analyzed. The results reveal that lower temperature decreases the vibration amplitude and shortens the transient process. Finally, the established model and some simulation results are validated by the ERSFD rotor test platform.

CO2 geo-storage is a promising approach in reducing greenhouse gas emissions and controlling global temperature rise. Although numerous studies have reported that offshore saline aquifers have greater storage potential and safety, current suitability evaluation models for CO2 geo-storage primarily focus on onshore saline aquifers, and site-level evaluations for offshore CO2 geo-storage remain unreported. In this study, we propose a framework to evaluate the site-level offshore CO2 geo-storage suitability with a multi-tiered indicator system, which considers three types of factors: engineering geology, storage potential, and socio-economy. Compared to the onshore CO2 geo-storage suitability evaluation models, the proposed indicator system considers the unique conditions of offshore CO2 geo-storage, including water depth, offshore distance, and distance from drilling platforms. The Analytic Hierarchy Process (AHP) and Fuzzy Comprehensive Evaluation (FCE) methods were integrated and applied to the analysis of the Ying–Qiong Basin, South China Sea. The results indicated that the average suitability score in the Yinggehai Basin (0.762) was higher than that in the Qiongdongnan Basin (0.691). This difference was attributed to more extensive fault development in the Qiongdongnan Basin, suggesting that the Yinggehai Basin is more suitable for CO2 geo-storage. In addition, the DF-I reservoir in the Yinggehai Basin and the BD-A reservoir in the Qiongdongnan Basin were selected as the optimal CO2 geo-storage targets for the two sub-basins, with storage potentials of 1.09 × 108 t and 2.40 × 107 t, respectively. This study advances the methodology for assessing site-level potential of CO2 geo-storage in offshore saline aquifers and provides valuable insights for engineering applications and decision-making in future CO2 geo-storage projects in the Ying–Qiong Basin.