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Although the functions of tyrosine phosphatases in T‐cell biology have been extensively studied, our knowledge on the contribution of serine/threonine phosphatases in T cells remains poor. Protein phosphatase 2A (PP2A) is one of the most abundantly expressed serine/threonine phosphatases. It is important in thymocyte development and CD4+ T‐cell differentiation. Utilizing a genetic model in which its catalytic subunit alpha isoform (PP2A Cα) is deleted in T cells, we investigated its contribution to CD8+ T‐cell homeostasis and effector functions. Our results demonstrate that T‐cell intrinsic PP2A Cα is critically required for CD8+ T‐cell homeostasis in secondary lymphoid organs and intestinal mucosal site. Importantly, PP2A Cα–deficient CD8+ T cells exhibit reduced proliferation and survival. CD8+ T‐cell antibacterial response is strictly dependent on PP2A Cα. Expression of Bcl2 transgene rescues CD8+ T‐cell homeostasis in spleens, but not in intestinal mucosal site, nor does it restore defective antibacterial responses. Finally, proteomics and phosphoproteomics analyses reveal potential targets dependent on PP2A Cα, including mTORC1 and AKT. Thus, PP2A Cα is a key modulator of CD8+ T‐cell homeostasis and effector functions. [ABSTRACT FROM AUTHOR]

Abstract\nPLAIN LANGUAGE SUMMARYThis study aimed to explore the critical role of FUNDC1 on epithelial cells in model of asthma. Patients with asthma and normal healthy volunteers were obtained from our hospital. The serum of FUNDC1 mRNA expression was down-regulated in patients with asthma. Meanwhile, the serum of FUNDC1 mRNA expression was positive correlation with IgE and anti-HDM IgE protein. FUNDC1 expression in lung tissue of mice model was decreased in mice model of asthma. Sh-FUNDC1 enhanced asthma in mice model of asthma. FUNDC1 up-regulation reduced IL-4, IL-5, IL-10 and IL-13 activity levels in vitro model of asthma.FUNDC1 down-regulation promoted IL-4, IL-5, IL-10 and IL-13 activity levels in vitro model of asthma. FUNDC1 reduced ferroptosis of epithelial cells in model of asthma through the inhibition of mitochondrial damage. FUNDC1 induced FBXL2 and AR protein expression in model of asthma. FUNDC1 interlinked with FBXL2 is modified by SUMO1 at K136. FBXL2, ASN-205, GLN-204, ARG-235, and GLN-237 form hydrogen bonds with FUNDC1's ASP-15, ASP-16, GLU-25, and ARG-29, with lengths of 2.3, 3.1, 2.9, 2.3, and 2.9 Å, respectively. The induction of FBXL2 reduced the effects of Sh-FUNDC1 on asthma in mice model of asthma. The inhibition of AR reduced the effects of Sh-FUNDC1 on asthma in mice model of asthma Overall, FUNDC1 prevents ferroptosis of airway epithelial cells of asthma through FBXL2/AR/GPX4 signaling pathway of SUMO1 at K136. FUNDC1 might benefit the treatment of asthma or other pulmonary disease.FUNDC1 prevents ferroptosis of airway epithelial cells of asthma through FBXL2/AR/GPX4 signaling pathway of SUMO1 at K136. FUNDC1 might benefit the treatment of asthma or other pulmonary disease. [ABSTRACT FROM AUTHOR]

Introduction: Baseline olfactory impairment, poor performance on cognitive test, and medial temporal lobe atrophy are considered biomarkers for predicting future cognitive decline in dementia-free older adults. However, the combined effect of these predictors has not been fully investigated. Methods: A group of 110 participants without dementia were continuously recruited into this study, and underwent olfactory, cognitive tests and MRI scanning at baseline and 5-year follow-up. Olfactory function was assessed using the University of Pennsylvania Smell Identification Test (UPSIT). Participants were divided into the cognitive decliners and non-decliners. Results: Among 87 participants who completed the 5-year follow-up, cognitive decline was present in 32 cases and 55 remained stable. Compared with non-decliners, cognitive decliners presented lower scores on both the UPSIT and the Montreal Cognitive Assessment (MoCA), and smaller hippocampal volume at baseline (all P <.001). The logistic regression analysis revealed that lower scores on UPSIT and MoCA, and smaller hippocampal volume were strongly associated with subsequent cognitive decline, respectively (all P <.001). For the prediction of cognitive decline, lower score on UPSIT performed the sensitivity of 63.6% and specificity of 81.2%, lower score on MoCA with the sensitivity of 74.5% and specificity of 65.6%, smaller hippocampal volume with the sensitivity of 70.9% and specificity of 78.1%, respectively. Combining three predictors resulted in the sensitivity of 83.6% and specificity of 93.7%. Conclusions: The combination of olfactory test, cognitive test with structural MRI may enhance the predictive ability for future cognitive decline for dementia-free older adults. [ABSTRACT FROM AUTHOR]

The introduction of fractional vegetation cover could improve the accuracy of soil moisture inversion model to some extent, but most studies estimated fractional vegetation cover based on normalized difference vegetation index NDVI, and without in-depth study on the impact of vegetation coverage based on other vegetation indices on the model. Therefore, taking the winter wheat planting area in Xiping County, Zhumadian City, Henan Province as the experimental area, based on the UAV platform with high resolution and strong mobility, the multi-spectral and TIR imaging apparatus were equipped to carry out the soil moisture inversion research of winter wheat covered surface, and to explore the changes of model accuracy after introducing differed fractional vegetation cover parameters, so as to make up for the limitations of soil moisture monitoring caused by the low resolution and poor timeliness of satellite remote sensing images. The two drought indices of temperature vegetation dryness index TVDI and perpendicular drought index PDI were combined with the parameters of fractional vegetation cover estimated through seven vegetation indices, respectively, and seven soil moisture inversion models were constructed based on the random forest algorithm, and the spatial distribution of soil moisture in the experimental area was analyzed according to the inversion results of the optimal model. At the same Lime, the soil moisture inversion model TP model, which could integrateed TVDI and PDI indices and without introducing fractional vegetation cover, was built as the control group. The results showed that the R² of the TP model was 0.606, 0.670, the root mean square error RMSE was 0.045, 0.041 for the depths of 0 to 10 cm and >10 to 20 cm respectively. The accuracy of the seven models introducing fractional vegetation cover was improved to some extent compared with that of the TP model. Among them, the R² of the optimal model TPOSAVI was improved by 0.143, 0.158, the RMSE was reduced by 0.7 percentage points, 0.8 percentage points respectively, compared with the TP model. It showed that the introduction of fractional vegetation cover based on the drought indices could improve the accuracy of model inversion and different fractional vegetation cover had different effects on the accuracy of the model. [ABSTRACT FROM AUTHOR]

Multi‐modal brain image registration has been widely applied to functional localisation, neurosurgery and computational anatomy. The existing registration methods based on the dense deformation fields involve too many parameters, which is not conducive to the exploration of correct spatial correspondence between the float and reference images. Meanwhile, the unidirectional registration may involve the deformation folding, which will result in the change of topology during registration. To address these issues, this work has presented an unsupervised image registration method using the free form deformation (FFD) and the symmetry constraint‐based generative adversarial networks (FSGAN). The FSGAN utilises the principle component analysis network‐based structural representations of the reference and float images as the inputs and uses the generator to learn the FFD model parameters, thereby producing two deformation fields. Meanwhile, the FSGAN uses two discriminators to decide whether the bilateral registration have been realised simultaneously. Besides, the symmetry constraint is utilised to construct the loss function, thereby avoiding the deformation folding. Experiments on BrainWeb, high grade gliomas, IXI and LPBA40 show that compared with state‐of‐the‐art methods, the FSGAN provides superior performance in terms of visual comparisons and such quantitative indexes as dice value, target registration error and computational efficiency. [ABSTRACT FROM AUTHOR]

Designing cost‐effective alkaline water‐splitting electrocatalysts is essential for large‐scale hydrogen production. However, nonprecious catalysts face challenges in achieving high activity and durability at a large current density. An effective strategy for designing high‐performance electrocatalysts is regulating the active electronic states near the Fermi‐level, which can improve the intrinsic activity and increase the number of active sites. As a proof‐of‐concept, it proposes a one‐step self‐assembly approach to fabricate a novel metallic heterostructure based on nickel phosphide and cobalt sulfide (Ni2P@Co9S8) composite. The charge transfer between active Ni sites of Ni2P and Co─Co bonds of Co9S8 efficiently enhances the active electronic states of Ni sites, and consequently, Ni2P@Co9S8 exhibits remarkably low overpotentials of 188 and 253 mV to reach the current density of 100 mA cm−2 for the hydrogen evolution reaction and oxygen evolution reaction, respectively. This leads to the Ni2P@Co9S8 incorporated water electrolyzer possessing an ultralow cell voltage of 1.66 V@100 mA cm−2 with ≈100% retention over 100 h, surpassing the commercial Pt/C║RuO2 catalyst (1.9 V@100 mA cm−2). This work provides a promising methodology to boost the activity of overall water splitting with ultralow overpotentials at large current density by shedding light on the charge self‐regulation of metallic heterostructure. [ABSTRACT FROM AUTHOR]