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Abstract TP53 mutation (TP53 mut) occurs in 10–20% of diffuse large B-cell lymphoma (DLBCL) cases and serves as an unfavorable biomarker of DLBCL progression. It confers resistance to immunochemotherapy, high-dose chemotherapy, autologous stem cell transplantation, and anti-CD19 chimeric antigen receptor T-cell therapy. Therapeutic targeting of TP53 mut remains a significant challenge in DLBCL treatment. Here we assessed TP53 mut in 667 patients with newly diagnosed DLBCL, including 576 patients treated with immunochemotherapy rituximab, cyclophosphamide, doxorubicin, vincristine, and prednisone (R-CHOP) and 91 patients with decitabine plus R-CHOP (DR-CHOP, NCT02951728 and NCT04025593). TP53 mut independently predicted an inferior prognosis in R-CHOP-treated DLBCL, although this could be mitigated by DR-CHOP treatment. In TP53 mut patients, multiple viral regulation pathways were repressed, resulting in the inhibition of immune modulation, as revealed by gene set enrichment analysis. TP53 mut DLBCL exhibited increased methyltransferase SUV39H1 expression and H3K9 trimethylation (H3K9me3), contributing to repression of endogenous retroviruses (ERVs) and immunosuppressive tumor microenvironment. In TP53 mut DLBCL cell lines, decitabine down-regulated SUV39H1, inhibited H3K9me3 occupancy on ERVs, and triggered ERV expression, thereby unleashing interferons program and CD4+T/CD8+T cell activation. Molecular silencing of SUV39H1 significantly abrogated decitabine-induced H3K9me3 inhibition and ERV expression. In TP53 mut patient-derived xenograft models and TP53 mut patients, the anti-tumor effect was improved upon the use of combined treatment of decitabine and doxorubicin via SUV39H1-H3K9me3-ERVs axis. Collectively, our findings highlight an ERV regulatory circuitry in TP53 mut DLBCL and the crucial roles ERVs for epigenetically reprogramming tumor microenvironment for treating TP53 mut-driven cancers.

Actuators play a crucial role in modern distributed electric grids and renewable energy network architectures, implementing control actions based on sensor data to ensure optimal system performance and stability. This paper addresses the economic dispatch (ED) problem of distributed DC microgrids with renewable energy. In these systems, numerous sensors and actuators are integral for monitoring and controlling various parameters to ensure optimal performance. A new event-triggered distributed optimization algorithm in the discrete time domain is employed to ensure the minimum production cost of the power grid. This algorithm leverages data from sensors to make real-time adjustments through actuators, ensuring the maximum energy utilization rate of renewable generators (RGs) and the minimum cost of conventional generators (CGs). It realizes the optimal synergy between conventional energy and renewable energy. Compared to the continuous sampling optimization algorithm, the event-triggered control (ETC) optimization algorithm reduces the frequency of communication and current sampling, thus improving communication efficiency and extending the system’s lifetime. The use of actuators in this context is crucial for implementing these adjustments effectively. Additionally, the convergence and stability of the DC microgrid are proven by the designed Lyapunov function. Finally, the effectiveness of the proposed optimization algorithm is validated through simulations of the DC microgrid.

On 22 May 2021, an earthquake (98.3° E and 34.59° N) struck Maduo town in Qinghai province, occurring along a relatively obscure secondary fault within the block. We utilized 105 archived Sentinel-1A/B acquisitions to investigate the coseismic deformation and the evolution of postseismic displacements in both the temporal and spatial domains, as well as the associated dynamic mechanisms of the 2021 Maduo earthquake. The interference fringes and coseismic deformation revealed that the primary feature of this event was the rupture along a left-lateral strike-slip fault. The released seismic moment was close to 1.88 × 1020 N·m, which is equivalent to an Mw 7.45 event. Simultaneously, the maximum coseismic slip reached approximately 4 m along the fault plane. The evolution of postseismic displacements in both the temporal and spatial domains over 450 days following the mainshock was further analyzed to explore the underlying physical mechanisms. Generally, the patterns of coseismic slip and afterslip were similar, although the postseismic displacements decayed rapidly over time. The modeled afterslip downdip of the coseismic rupture (at depths of 15–40 km) effectively explains the postseismic deformation, with a released moment estimated at 4.57 × 1019 N·m (corresponding to Mw 7.04). Additionally, we found that regions with high coseismic slip tend to exhibit weak seismicity, and that afterslip and aftershocks are likely driven by each other. Finally, we estimated the Coulomb Failure Stress changes (ΔCFS) triggered by both coseismic rupture and aseismic slip resulting from this event. The co- and postseismic ΔCFS show similar patterns, but the magnitude of the postseismic ΔCFS is much lower (≤0.01 MPa). We found that ΔCFS notably increased on the Yushu segment of the Garze-Yushu-Xianshuihe Fault (GYXF), as well as the Maqin–Maqu and Tuosuo Lake sections of the East Kunlun Fault (EKF). Therefore, we infer that these fault segments may have a higher potential seismic risk and should be carefully monitored in the future.

To optimize energy structure and efficiently utilize renewable energy sources, it is necessary to establish a new electrical power–gas mutual transformation virtual power plant that has low-carbon benefits. To promote the economic and low-carbon operation of a virtual power plant and reduce uncertainty regarding the use of new energy, a multi-timescale (day-ahead to intraday) optimal scheduling model is proposed. First, a basic model of a new interconnected power–gas virtual power plant (power-to-gas demand response virtual power plant, PD-VPP) was established with P2G and comprehensive demand response as the main body. Second, in response to the high volatility of new energy, a day-ahead to intraday multi-timescale collaborative operation optimization model is proposed. In the day-ahead optimization period, the next day’s internal electricity price is formulated, and the price-based demand response load is regulated in advance so as to ensure profit maximization for the virtual power plant. Based on the results of day-ahead modeling, intraday optimization was performed on the output of each distributed unit, considering the cost of the carbon emission reductions to achieve low-carbon economic dispatch with minimal operating costs. Finally, several operation scenarios are established for a simulation case analysis. The validity of the proposed model was verified via comparison.

Gravity wave (GW) momentum flux spectra help to uncover the mechanisms through which GWs influence momentum transfer in the atmosphere and provide crucial insights into accurately characterizing atmospheric wave processes. This study examines the momentum flux spectra of GWs in the troposphere (2–14 km) and stratosphere (18–28 km) over Koror Island (7.2°N, 134.3°W) using radiosonde data from 2013–2018. Utilizing hodograph analysis and spectral methods, the characteristics of momentum flux spectra are discussed. Given that the zonal momentum flux spectra of low-level atmospheric GWs generally follow a Gaussian distribution, Gaussian fitting was applied to the spectral structures. This fitting further explores the seasonal variations of the zonal momentum flux spectra and the average spectral parameters for each month. Additionally, the GW energy is analyzed using SABER (Sounding of the Atmosphere using Broadband Emission Radiometry) satellite data and compared with the results of the momentum flux spectra from radiosonde data, revealing the close negative correlation between wave energy and wave momentum for stratospheric GW changing with time. The findings indicate that the Gaussian peak shifts more eastward in both the troposphere and stratosphere, primarily due to the absorption of eastward-propagating GWs by the winter tropospheric westerly jet and critical layer filtering. The full width at half maximum (FWHM) in the stratosphere is larger than in the troposphere, especially in June and July, as the spectrum broadens due to propagation effects, filtering, and interactions among waves. The central phase speed in the stratosphere exceeds that in the troposphere, reflecting the influences of Doppler effects and background wind absorption. The momentum flux in the stratosphere is lower than in the troposphere, which is attributed to jet absorption, partial reflection, or the dissipation of GWs.

Accurate prediction of protein-ligand complex structures is a crucial step in structure-based drug design. Traditional molecular docking methods exhibit limitations in terms of accuracy and sampling space, while relying on machine-learning approaches may lead to invalid conformations. In this study, we propose a novel strategy that combines molecular docking and machine learning methods. Firstly, the protein-ligand binding poses are predicted using a deep learning model. Subsequently, position-restricted docking on predicted binding poses is performed using Uni-Dock, generating physically constrained and valid binding poses. Finally, the binding poses are re-scored and ranked using machine learning scoring functions. This strategy harnesses the predictive power of machine learning and the physical constraints advantage of molecular docking. Evaluation experiments on multiple datasets demonstrate that, compared to using molecular docking or machine learning methods alone, our proposed strategy can significantly improve the success rate and accuracy of protein-ligand complex structure predictions.

The effects of key parameters on locked mode induced disruption (LMiD) are investigated in EAST experiments. The experimental data for locked mode are collected from 2015 to 2022 when the externally applied resonant magnetic perturbation is successfully employed in EAST. In this dataset, ∼42% of the total shots are LMiD, while the remaining 58% are LM without disruption. To better analyze the LMiD, an intuitive physical process is proposed. The LMiD process can be divided into two stages, the evolution of magnetic islands and the loss of plasma stored energy. The LMiD can also be related to the evolution of the other 8 physical quantities. On the basis of this physical process analysis, the time scale and the influencing factors for LMiD are investigated using statistical analysis. It is found that the density (ne), the distance from the magnetic island outer boundary to the plasma last closed surface (dedge), the loop-voltage (Vloop), and the plasma core electron temperature (Te), which are consistent with the intuitive physical model, are key parameters to LMiD. In addition, other potentially important parameters, the relevant reasons, and statistical analysis on the parameter intervals where rapid disruption with greater harmfulness occurred have also been investigated.

Abstract Predatory protists are widely recognized as critical biotic forces driving soil microbial communities, but their top‐down controls on ammonia‐oxidizing microorganisms (AOMs), the major players in nitrification, are largely unresolved. Here, we investigated the communities of predatory protists and their associations with AOMs using high‐throughput sequencing and network analysis in soil aggregates following various long‐term organic substitutions. We found that organic substitutions increased while soil aggregation decreased the alpha diversity of predatory protists. Predatory protistan communities were significantly associated with AOMs. Variosea, an important group of Amoebozoa, were the keystone predatory protists associated with the AOMs. Collectively, our findings highlight the importance of predatory protists, especially Variosea, in regulating the communities of AOMs in an acidic Ultsisol, with implications for managing nitrification by predatory protists in agricultural soils.

Objective This study explored the potential molecular mechanisms of ursolic acid (UA) in bladder cancer treatment using network pharmacology and molecular docking. Methods The Traditional Chinese Medicine Systems Pharmacology and UniProt databases were used to screen potential targets of UA. Relevant bladder cancer target genes were extracted using the GeneCards database. All data were pooled and intercrossed to obtain common target genes of UA and bladder cancer. Gene Ontology functional annotation and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses were performed. Molecular docking was conducted to verify the possible binding conformation between UA and bladder cancer cells. Then, in vitro experiments were performed to further validate the predicted results. Results UA exerts anti-tumor effects on bladder cancer through multiple targets and pathways. Molecular docking indicated that UA undergoes stable binding with the proteins encoded by the top six core genes ( STAT3, VEGFA, CASP3, TP53, IL1B, and CCND1 ). The in vitro experiments verified that UA can induce bladder cancer cell apoptosis by regulating the PI3K/Akt signaling pathway. Conclusions Our study illustrated the potential mechanism of UA in bladder cancer based on network pharmacology and molecular docking. The results will provide scientific references for follow-up studies and clinical treatment.

Chronic interstitial fibrosis presents a significant challenge to the long-term survival of transplanted kidneys. Our research has shown that reduced expression of acyl-coenzyme A oxidase 1 (ACOX1), which is the rate-limiting enzyme in the peroxisomal fatty acid β-oxidation pathway, contributes to the development of fibrosis in renal allografts. ACOX1 deficiency leads to lipid accumulation and excessive oxidation of polyunsaturated fatty acids (PUFAs), which mediate epithelial–mesenchymal transition (EMT) and extracellular matrix (ECM) reorganization respectively, thus causing fibrosis in renal allografts. Furthermore, activation of Toll-like receptor 4 (TLR4)-nuclear factor kappa-B (NF-κB) signaling induced ACOX1 downregulation in a DNA methyltransferase 1 (DNMT1)-dependent manner. Overconsumption of PUFA resulted in endoplasmic reticulum (ER) stress, which played a vital role in facilitating ECM reorganization. Supplementation with PUFAs contributed to delayed fibrosis in a rat model of renal transplantation. The study provides a novel therapeutic approach that can delay chronic interstitial fibrosis in renal allografts by targeting the disorder of lipid metabolism.

ObjectiveTo assess the effect of B cell depletion therapy (BCDT) on circulating T follicular helper (cTfh) and circulating T helper 17 (cTh17) cells and its relation to clinical improvement in patients with myasthenia gravis (MG).Methods28 anti-AchR positive MG patients treated with ofatumumab and 28 healthy controls (HCs) were included. Frequencies of cTfh and cTh17 cells were monitored by flow cytometry at baseline and 4, and 12 weeks after the initial dose ofatumumab. Serum cytokines associated with cTfh and cTh17, including IL-6, IL-21, and IL-17, were also analyzed.ResultsThe frequency of cTfh and cTh17 significantly increased in MG patients compared with HCs. Additionally, elevated levels of both T-cell subsets correlated with MG severity. During the follow-up, cTfh and cTh17 return to normal after BCDT. Furthermore, the decrease in cTfh and cTh17 was associated with MG scores improvement over time. Notably, cTfh- and cTh17-related cytokines, including IL-6, IL-21, and IL-17, exhibited a marked decrease following ofatumumab therapy.ConclusionsAbnormal expansion of cTfh and cTh17 cells may be key features in the immunopathology of MG. Their levels returned to normal after BCDT, which was closely correlated with clinical amelioration. This result suggests that these two T-cell subsets may be targets for BCDT treatment of MG.

BackgroundMost of gastrointestinal stromal tumors (GISTs) are driven by mutations in the KIT/PDGFRA genes and can benefit from TKIs treatment. However, a small subset of GIST (10%-15%) are called “wild-type” GISTs due to the lack of these mutations. Theoretically, they would not benefit from TKIs treatment and may even develop resistance. Therefore, this unexpected response may challenge inherent perceptions. Herein, we present a case of giant wild-type GIST exhibiting an unexpected response to imatinib(IM), followed by laparoscopic surgical resection. Subsequently, potential underlying mechanisms are discussed.Case descriptionThis case describes a 57-year-old man who presented with abdominal pain for two weeks. CT revealed a massive lesion near the splenic hilum along the greater curvature of the stomach, concurrently involving the splenic hilar vessels and surrounding lymph nodes. Ultrasound-guided fine needle aspiration biopsy confirmed it is a mesenchymal spindle cell tumor,GIST. Due to the enormous volume and local invasion, neoadjuvant chemotherapy was initially considered. After 6 months of IM 400 mg/d, CT imaging revealed marked changes in tumor heterogeneity and a significant reduction in volume. Subsequently, laparoscopic surgical resection was performed. Postoperative pathological examination, immunohistochemistry, and genetic testing collectively confirmed it is a wild-type GIST.The patient recovered well and was discharged on the 6th day after surgery, with continued oral IM(400 mg/d) after discharge. No recurrence was observed during follow-up until the publication of this report.ConclusionThis unexpected response suggests that wild-type GISTs may benefit from TKIs treatment, and the potential mechanisms warrant further investigation. Additionally, true wild-type GIST may not be discerned due to current limitations of Next-Generation Sequencing(NGS). Therefore, for advanced/high-risk GIST, additional genetic analysis can be performed after negative NGS results.

Triple-negative breast cancer (TNBC) is one of the major clinical problems to be solved urgently, because of its high malignancy, poor targeted therapy effect and easy occurrence of drug resistance and metastasis. Here, methyltransferase DNMT1 was identified as a key factor mediating PTX resistance for TNBC. Decitabine (DEC), an inhibitor of DNMT1, can inhibit the proliferation and metastasis of TNBC cells and reverse PTX resistance. In this study, we reported a new delivery system (DEC/PTX NPs@αPD-L1) co-loaded with DEC and PTX modified by anti-PD-L1 monoclonal antibody (αPD-L1), which can overcome drug resistance and metastasis through multi-mode synergistic effect. αPD-L1 increases the enrichment of nanoparticles in tumor tissue through active targeting effect, and blocks PD-L1 on the surface of TNBC cells, thereby activating anti-tumor immune while enhancing internalization of nanoparticles by tumor cells. Inside tumor cells, DEC inhibits EMT process and cancer stem cells to overcome PTX resistance and metastasis. PTX can not only exerts direct tumor killing effect, but also inhibit Treg cells from remodeling immune microenvironment, and induces efficient immunogenic death in cooperation with DEC. This delivery system, realizing tumor-specific synchronized chemoimmunotherapy, represents a promising therapeutic platform for TNBC.