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Incidence of intracerebral hemorrhage (ICH) and brain iron accumulation increases with age. Excess iron accumulation in brain tissues post‐ICH induces oxidative stress and neuronal damage. However, the mechanisms underlying iron deregulation in ICH, especially in the aged ICH model have not been well elucidated. Ferroportin1 (Fpn) is the only identified nonheme iron exporter in mammals to date. In our study, we reported that Fpn was significantly upregulated in perihematomal brain tissues of both aged ICH patients and mouse model. Fpn deficiency induced by injecting an adeno‐associated virus (AAV) overexpressing cre recombinase into aged Fpn‐floxed mice significantly worsened the symptoms post‐ICH, including hematoma volume, cell apoptosis, iron accumulation, and neurologic dysfunction. Meanwhile, aged mice pretreated with a virus overexpressing Fpn showed significant improvement of these symptoms. Additionally, based on prediction of website tools, expression level of potential miRNAs in ICH tissues and results of luciferase reporter assays, miR‐124 was identified to regulate Fpn expression post‐ICH. Higher serum miR‐124 levels were correlated with poor neurologic scores of aged ICH patients. Administration of miR‐124 antagomir enhanced Fpn expression and attenuated iron accumulation in aged mice model. Both apoptosis and ferroptosis, but not necroptosis, were regulated by miR‐124/Fpn signaling manipulation. Our study demonstrated the critical role of miR‐124/Fpn signaling in iron metabolism and neuronal death post‐ICH in aged murine model. Thus, Fpn upregulation or miR‐124 inhibition might be promising therapeutic approachs for this disease. Brain iron accumulation following ICH induced secondary brain injury and neuronal death. However, the mechanisms underlying iron deregulation in aged ICH model is poorly understood. miR‐124/Fpn signaling was downregulated in aged ICH model mice and patients as a protection mechanism. Higher serum miR‐124 levels were correlated with poor neurologic scores of aged patients. Targeting miR‐124/Fpn signaling could reduce the iron accumulation post‐ICH in aged murine model, thus ameliorated hematoma volume, cell apoptosis and neurologic dysfunction through inhibiting apoptosis and ferroptosis.

Accurate identification of photovoltaic (PV) model parameters is crucial for the study of factors affecting PV power generation efficiency. This study addresses this challenge by introducing the enhanced RIME algorithm (ERIME). ERIME achieves a fine balance between exploration and exploitation by combining a modified soft‐rime search strategy and a shared information mutation mechanism, thus ensuring population diversity. To assess the efficacy of ERIME, the recognized CEC2022 test function suite is adopted to evaluate its search performance. Furthermore, to validate the versatility of ERIME in parameter identification of PV model, we tested the proposed method on several PV models, including single diode model (SDM), double diode model (DDM), triple diode model (TDM), and multiple PV module models (PVM). An in‐depth statistical analysis of the results and a comparative study with the popular existing research methods highlight the superiority of ERIME. Specifically, ERIME improves the best value metrics of SDM, DDM, and TDM by 6.63E−06, 2.28E−05, and 1.36E−04, respectively, compared to RIME and reduces the standard deviation by 2.02E−03,1.75E−03, and 1.54E−03, respectively, compared to MVO. Comprehensive results show that the proposed method has better robustness and convergence accuracy than the state‐of‐the‐art algorithm.

Successful infection of the host requires secretion of effector proteins to evade or suppress plant immunity. Secretion of effectors in root-infecting fungal pathogens, however, remains unexplored. We previously reported that Verticillium dahliae, a root-infecting phytopathogenic fungus, develops a penetration peg from a hyphopodium to infect cotton roots. In this study, we report that a septin ring, requiring VdSep5, partitions the hyphopodium and the invasive hypha and form the specialized fungus-host interface. The mutant strain, VdΔnoxb, in which NADPH oxidase B (VdNoxB) is deleted, impaired formation of the septin ring at the hyphal neck, indicating that NADPH oxidases regulate septin ring organization. Using GFP tagging and live cell imaging, we observed that several signal peptide containing secreted proteins showed ring signal accumulation/secretion at the penetration interface surrounding the hyphal neck. Targeted mutation for VdSep5 reduced the delivery rate of secretory proteins to the penetration interface. Blocking the secretory pathway by disrupting the vesicular trafficking factors, VdSec22 and VdSyn8, or the exocyst subunit, VdExo70, also arrested delivery of the secreted proteins inside the hyphopodium. Reduced virulence was observed when cotton roots were infected with VdΔsep5, VdΔsec22, VdΔsyn8 and VdΔexo70 mutants compared to infection with the isogenic wild-type V592. Taken together, our data demonstrate that the hyphal neck is an important site for protein secretion during plant root infection, and that the multiple secretory routes are involved in the secretion.

Accurate modeling and parameter identification of photovoltaic (PV) cells is a difficult task due to the nonlinear characteristics of PV cells. The goal of this paper is to propose a multi strategy sine–cosine algorithm (SCA), named enhanced sine–cosine algorithm (ESCA), to evaluate nondirectly measurable parameters of PV cells. The ESCA introduces the concept of population average position to increase the population exploration ability, and at the same time introduces the personal destination agent mutation mechanism and competitive selection mechanism into SCA to provide more search directions for ESCA while ensuring the search accuracy and diversity maintenance. To prove that the proposed ESCA is the best choice for extracting nondirectly measurable parameters of PV cells, ESCA is evaluated by the single‐diode model, the double‐diode model, the three‐diode model, and the photovoltaic module model (PVM), and compared with eight existing popular methods. Experimental results show that ESCA outperforms similar methods in terms of diversity maintenance, high efficiency, and stability. In particular, the proposed ESCA method is less than the SCA by 0.081, 0.144, and 0.578 in the standard deviation statistics metrics of the three PVM models (PV‐PWP201, STM6‐40/36, and STP6‐120/36), respectively. Therefore, the proposed ESCA is an accurate and reliable method for parameter identification of PV cells. Figure 6. The flowchart of enhanced sine–cosine algorithm.

In this article, a modified version of the Sine Cosine algorithm (MSCA) is proposed to solve the optimization problem. Based on the Sine Cosine algorithm (SCA), the position update formula of SCA is redefined to increase the convergence speed, then the Levy random walk mutation strategy is adopted to improve the population diversity. In order to verify the performance of MSCA, 24 well-known classical benchmark problems and IEEE CEC2017 test suites were introduced, and by comparing MSCA with several popular methods, it is demonstrated that MSCA has good convergence and robustness. Finally, MSCA is used to address six complex engineering design problems, demonstrating the engineering utility of the algorithm.

In this paper, we investigate the complexity growth of the tensionless limit of string in the neutral BTZ black hole horizon in massive gravity. When the string approaches the horizon, we observe a novel phenomenon for the Nambu–Goto action growth that produces significant difference from tensile string geometry. The string’s tension is then suggested to partially contribute to the growth of the action. We also argue a potential proposal that reconstructs the complexity from the renormalization group (RG) flow.

Scorpion venom heat-resistant peptide (SVHRP) is a component purified from Buthus martensii Karsch scorpion venom. Our previous studies found SVHRP could enhance neurogenesis and inhibit microglia-mediated neuroinflammation in vivo. Here, we use the transgenic CL4176, CL2006, and CL2355 strains of Caenorhabditis elegans which express the human Aβ1-42 to investigate the effects and the possible mechanisms of SVHRP mediated protection against Aβ toxicity in vivo. The results showed that SVHRP-fed worms displayed remarkably decreased paralysis, less abundant toxic Aβ oligomers, reduced Aβ plaque deposition with respect to untreated animals. SVHRP also suppressed neuronal Aβ expression-induced defects in chemotaxis behavior and attenuated levels of ROS in the transgenic C. elegans. Taken together, these results suggest SVHRP could protect against Aβ-induced toxicity in C. elegans. Further studies need to be conducted in murine models and humans to analyze the effectiveness of the peptide.

Filtering based state of charge (SOC) estimation with an equivalent circuit model is commonly extended to Lithium-ion (Li-ion) batteries for electric vehicle (EV) or similar energy storage applications. During the last several decades, different implementations of online parameter identification such as Kalman filters have been presented in literature. However, if the system is a moving EV during rapid acceleration or regenerative braking or when using heating or air conditioning, most of the existing works suffer from poor prediction of state and state estimation error covariance, leading to the problem of accuracy degeneracy of the algorithm. On this account, this paper presents a particle filter-based hybrid filtering method particularly for SOC estimation of Li-ion cells in EVs. A sampling importance resampling particle filter is used in combination with a standard Kalman filter and an unscented Kalman filter as a proposal distribution for the particle filter to be made much faster and more accurate. Test results show that the error on the state estimate is less than 0.8% despite additive current measurement noise with 0.05 A deviation.

Key Clinical Message Splenic tissue outside the normal anatomical site can be collectively referred to as ectopic spleen. Clinically, the commonest causes of ectopic spleen include accessory spleen, splenic tissue implantation, and splenogonadal fusion (SGF). Accessory spleen is mostly caused by congenital dysplasia, is mostly located near the spleen, and may be supplied by the splenic artery. Splenic implantation is mostly caused by autologous spleen tissue transplantation caused by trauma or surgery. SGF is the abnormal fusion of the spleen with the gonad or with the mesonephric derivatives. As a rare developmental malformation, it is difficult to make a correct diagnosis preoperatively, and easily misdiagnosed as a testicular tumor cause lifelong harm to patients. An 18‐year‐old male student who developed left testicular pain without obvious cause that radiated to the perineum 4 months prior to presentation. He was diagnosed with cryptorchidism 12 years ago and underwent orchiopexy without intraoperative frozen section examination. An ultrasound was performed, identifying hypoechoic nodules in the left testis, suggestive of seminoma. During surgery, the testicular tumor revealed a dark red tissue and the diagnosis of a pathological ectopic splenic tissue was made. Because the clinical manifestations of SGF are not specific, misdiagnosis and unnecessary orchiectomy may occur. If a complete preoperative examination which includes biopsy or intraoperative frozen section is performed, unnecessary orchiectomy can be effectively avoided and bilateral fertility can be preserved.

Anoikis is a form of programmed cell death or programmed cell death(PCD) for short. Studies suggest that anoikis involves in the decisive steps of tumor progression and cancer cell metastasis and spread, but what part it plays in bladder cancer remains unclear. We sought to screen for anoikis-correlated long non-coding RNA (lncRNA) so that we can build a risk model to understand its ability to predict bladder cancer prognosis and the immune landscape. We screened seven anoikis-related lncRNAs (arlncRNAs) from The Cancer Genome Atlas (TCGA) and designed a risk model. It was validated through ROC curves and clinicopathological correlation analysis, and demonstrated to be an independent factor of prognosis prediction by uni- and multi-COX regression. In the meantime, Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis, immune infiltration, and half-maximal inhibitory concentration prediction (IC50) were implemented with the model. Moreover, we divided bladder cancer patients into three subtypes by consensus clustering analysis to further study the differences in prognosis, immune infiltration level, immune checkpoints, and drug susceptibility. We designed a risk model of seven arlncRNAs, and proved its accuracy using ROC curves. COX regression indicated that the model might be an independent prediction factor of bladder cancer prognosis. KEGG enrichment analysis showed it was enriched in tumors and immune-related pathways among the people at high risk. Immune correlation analysis and drug susceptibility results indicated that it had higher immune infiltration and might have a better immunotherapy efficacy for high-risk groups. Of the three subtypes classified by consensus clustering analysis, cluster 3 revealed a positive prognosis, and cluster 2 showed the highest level of immune infiltration and was sensitive to most chemistries. This is helpful for us to discover more precise immunotherapy for bladder cancer patients. In a nutshell, we found seven arlncRNAs and built a risk model that can identify different bladder cancer subtypes and predict the prognosis of bladder cancer patients. Immune-related and drug sensitivity researches demonstrate it can provide individual therapeutic schedule with greater precision for bladder cancer patients.