An Amino Acids and Dipeptide Injection Inhibits the TNF-α/HMGB1 Inflammatory Signaling Pathway to Reduce Pyroptosis and M1 Microglial Polarization in POCD Mice: the Gut to the Brain.

Peripheral surgery-induced neural inflammation is a key pathogenic mechanism of postoperative cognitive dysfunction (POCD). However, the mechanism underlying neuroinflammation and associated neural injury remains elusive. Surgery itself can lead to gut damage, and the occurrence of POCD is accompanied by high levels of TNF-α in the serum and blood‒brain barrier (BBB) damage. Reductions in stress, inflammation and protein loss have been emphasized as strategies for enhanced recovery after surgery (ERAS). We designed an amino acids and dipeptide (AAD) formula for injection that could provide intestinal protection during surgery. Through the intraoperative infusion of AAD based on the ERAS concept, we aimed to explore the effect of AAD injection on POCD and its underlying mechanism from the gut to the brain. Here, we observed that AAD injection ameliorated neural injury in POCD, in addition to restoring the function of the intestinal barrier and BBB. We also found that TNF-α levels decreased in the ileum, blood and hippocampus. Intestinal barrier protectors and TNF-α inhibitors also alleviated neural damage. AAD injection treatment decreased HMGB1 production, pyroptosis, and M1 microglial polarization and increased M2 polarization. In vitro, AAD injection protected the impaired gut barrier and decreased TNF-α production, alleviating damage to the BBB by stimulating cytokine transport in the body. HMGB1 and Caspase-1 inhibitors decreased pyroptosis and M1 microglial polarization and increased M2 polarization to protect TNF-α-stimulated microglia in vitro. Collectively, these findings suggest that the gut barrier-TNF-α-BBB-HMGB1-Caspase-1 inflammasome-pyroptosis-M1 microglia pathway is a novel mechanism of POCD related to the gut-brain axis and that intraoperative AAD infusion is a potential treatment for POCD.

Photoactivated Formation of an Extravascular Dynamic Hydrogel as an Intelligent Blood Flow Regulator to Reprogram the Immunogenic Landscape.

Long-term tumor starvation may be a potential strategy to elevate the antitumor immune response by depriving nutrients. However, combining long-term starvation therapy with immunotherapy often yields limited efficacy due to the blockage of immune cell migration pathways. Herein, an intelligent blood flow regulator (BFR) is first established through photoactivated in situ formation of the extravascular dynamic hydrogel to compress blood vessels, which can induce long-term tumor starvation to elicit metabolic stress in tumor cells without affecting immune cell migration pathways. By leveraging methacrylate-modified nanophotosensitizers (HMMAN) and biodegradable gelatin methacrylate (GelMA), the developed extravascular hydrogel dynamically regulates blood flow via enzymatic degradation. Additionally, aPD-L1 loaded into HMMAN continuously blocks immune checkpoints. Systematic in vivo experiments demonstrate that the combination of immune checkpoint blockade (ICB) and BFR-induced metabolic stress (BIMS) significantly delays the progression of Lewis lung and breast cancers by reshaping the tumor immunogenic landscape and enhancing antitumor immune responses.

The Promising Potential of Gallium Based Liquid Metals for Energy Storage.

Energy storage devices play a crucial role in various applications, such as powering electronics, power backup for homes and businesses, and support for the integration of renewable energy sources into electrical grid applications. Electrode materials for energy storage devices are preferred to have a flexible nature, conductive, better capacity, and low-toxicity. Currently, using Gallium based liquid metal alloys, such as Eutectic Gallium-Indium (EGaIn), Eutectic Gallium-Tin (EGaSn), and Eutectic Gallium-Indium-Tin (EGaInSn), as electrode materials play very important role in energy storage devices. These liquid metals have some interesting properties with a self-healing nature, high mechanical stability, compatibility with various materials, fluidity, low young's modulus, high electrical and thermal conductivity. Those properties have made it suitable to be used in various energy storage devices. In this mini review, we have concisely described the advantages and challenges of using liquid metal as electrode materials for various energy storage devices.

Ceria nanoparticles: biomedical applications and toxicity. / 二氧化铈纳米颗粒：生物医学应用和毒性.

Ceria nanoparticles (CeO2 NPs) have become popular materials in biomedical and industrial fields due to their potential applications in anti-oxidation, cancer therapy, photocatalytic degradation of pollutants, sensors, etc. Many methods, including gas phase, solid phase, liquid phase, and the newly proposed green synthesis method, have been reported for the synthesis of CeO2 NPs. Due to the wide application of CeO2 NPs, concerns about their adverse impacts on human health have been raised. This review covers recent studies on the biomedical applications of CeO2 NPs, including their use in the treatment of various diseases (e.|g., Alzheimer's disease, ischemic stroke, retinal damage, chronic inflammation, and cancer). CeO2 NP toxicity is discussed in terms of the different systems of the human body (e.|g., cytotoxicity, genotoxicity, respiratory toxicity, neurotoxicity, and hepatotoxicity). This comprehensive review covers both fundamental discoveries and exploratory progress in CeO2 NP research that may lead to practical developments in the future.

Association of urinary bisphenol A levels with heart failure risk in U.S. adults from the NHANES (2003-2016).

Introduction: Although heart failure (HF) has been linked to bisphenol A (BPA), few studies have investigated the cut-off values for the effects of urinary BPA levels on heart failure risk. The association between urinary BPA levels and HF prognosis has not been investigated. Methods: This study included 11,849 adults over 20 years old using information from the National Health and Nutrition Examination Survey (NHANES), which was conducted from 2003 to 2016. The relationship between urinary BPA levels and the risk of HF was determined via a multivariable logistic regression model, and restricted cubic spline (RCS) methods were used to determine the cut-off for the effect of BPA levels on HF risk. Based on the available NT-proBNP concentration data from the NHANES (2003-2004), multivariable linear regression was applied to determine the linear association between the NT-proBNP concentration and urinary BPA concentration. Results: The results revealed a positive correlation between a urinary BPA concentration in the fourth quartile and the occurrence of heart failure [OR 1.49, 95% CI (1.09, 2.04), p = 0.012]. A one-unit increase (1 ng/mg creatinine) in the ln-transformed BPA concentration was linked to a 15% increase in the incidence of HF [OR 1.15, 95% CI (1.03, 1.29), p = 0.014]. The cut-off urinary BPA concentration for HF risk was 1.51 ng/mg creatinine. There was a positive correlation between urinary BPA and NT-proBNP concentrations [ß = 0.093, 95% CI (0.014, 0.171), p = 0.02] in males, but there was no linear association [ß = 0.040, 95% CI (-0.033, 0.113), p = 0.283] in females. Discussion: Increased urinary BPA levels are linked to an increased risk of heart failure and poor prognosis. There is a significant increase in the risk of heart failure if the urinary concentration of BPA exceeds 1.51 ng/mg creatinine.

A machine learning-based approach to predict energy layer for each field in spot-scanning proton arc therapy for lung cancer: A feasibility study.

BACKGROUND: Determining the optimal energy layer (EL) for each field, under considering both dose constraints and delivery efficiency, is crucial to promoting the development of proton arc therapy (PAT) technology. PURPOSE: This study aimed to explore the feasibility and potential clinical benefits of utilizing machine learning (ML) technique to automatically select EL for each field in PAT plans of lung cancer. METHODS: Proton Bragg peak position (BPP) was employed to characterize EL. The ground truth BPPs for each field were determined using the modified ELO-SPAT framework. Features in geometric, water-equivalent thicknesses (WET) and beamlet were defined and extracted. By analyzing the relationship between the extracted features and ground truth, a polynomial regression model with L2-norm regularization (Ridge regression) was constructed and trained. The performance of the regression model was reported as an error between the predictions and the ground truth. Besides, the predictions were used to make PAT plans (PAT_PRED). These plans were compared with those using the ground truth BPPs (PAT_TRUTH) and the mid-WET of the target volumes (PAT_MID) in terms of relative biological effectiveness-weighted dose (RWD) distributions. One hundred ten patients with lung cancer, a total of 7920 samples, were enrolled retrospectively, with 5940 cases randomly selected as the training set and the remaining 1980 cases as the testing set. Nine patients (648 samples) were collected additionally to evaluate the regression model in terms of plan quality and robustness. RESULTS: With regard to the prediction errors, the root mean squared errors and mean absolute errors between the ML-predicted and ground truth BPPs for the testing set were 9.165 and 6.572 mm, respectively, indicating differences of approximately two to three ELs. As for plan quality, the PAT_TRUTH and PAT_PRED plans performed similarly in terms of plan robustness, target coverage and organs at risk (OARs) protection, with differences smaller than 0.5 Gy(RBE). This trend was also observed for dose conformity and uniformity. The PAT_MID plans produced the lowest robustness index and lowest doses to OARs, along with the highest heterogeneity index, indicating better protection for OARs, improved plan robustness, but compromised dose homogeneity. Additionally, for relatively small tumor sizes, the PAT_MID plan demonstrated a notably poor dose conformity index. CONCLUSIONS: Within this cohort under investigation, our study demonstrated the feasibility of using ML technique to predict ELs for each field, offering a fast (within 2 s) and memory-efficient reduced way to select ELs for PAT plan.

Polyaniline/Tungsten Trioxide Organic-Inorganic Hybrid Anode for Aqueous Proton Batteries.

Aqueous proton batteries have received increasing attention due to their outstanding rate performance, stability and high capacity. However, the selection of anode materials in strongly acidic electrolytes poses a challenge in achieving high-performance aqueous proton batteries. This study optimized the proton reaction kinetics of layered metal oxide WO3 by introducing interlayer structural water and coating polyaniline (PANI) on its surface to prepare organic-inorganic hybrid material (WO3 ⋅ 2H2O@PANI). We constructed an aqueous proton battery with WO3 ⋅ 2H2O@PANI anode and MnO2@GF cathode. After 1500 cycles at a current density of 10 A g-1, the capacity retention rate can still reach 80.2 %. These results can inspire the development of new aqueous proton batteries.

Atorvastatin-induced intracerebral hemorrhage is inhibited by berberine in zebrafish.

Intracerebral hemorrhage (ICH), for which there are currently no effective preventive or treatment methods, has a very high fatality rate. Statins, such as atorvastatin (ATV), are the first-line drugs for regulating blood lipids and treating hyperlipidemia-related cardiovascular diseases. However, ATV-associated ICH has been reported, although its incidence is rare. In this study, we aimed to investigate the protective action and mechanisms of berberine (BBR) against ATV-induced brain hemorrhage. We established an ICH model in zebrafish induced by ATV (2 µM) and demonstrated the effects of BBR (10, 50, and 100 µM) on ICH via protecting the vascular network using hemocyte staining and three transgenic zebrafish. BBR was found to reduce brain inflammation and locomotion injury in ICH-zebrafish. Mechanism research showed that ATV increased the levels of VE-cadherin and occludin proteins but disturbed their localization at the cell membrane by abnormal phosphorylation, which decreased the number of intercellular junctions between vascular endothelial cells (VECs), disrupting the integrity of vascular walls. BBR reversed the effects of ATV by promoting autophagic degradation of phosphorylated VE-cadherin and occludin in ATV-induced VECs examined by co-immunoprecipitation (co-IP). These findings provide crucial insights into understanding the BBR mechanisms involved in the maintenance of vascular integrity and in mitigating adverse reactions to ATV.

Frequency-encoded eye tracking smart contact lens for human-machine interaction.

Eye tracking techniques enable high-efficient, natural, and effortless human-machine interaction by detecting users' eye movements and decoding their attention and intentions. Here, a miniature, imperceptible, and biocompatible smart contact lens is proposed for in situ eye tracking and wireless eye-machine interaction. Employing the frequency encoding strategy, the chip-free and battery-free lens successes in detecting eye movement and closure. Using a time-sequential eye tracking algorithm, the lens has a great angular accuracy of <0.5°, which is even less than the vision range of central fovea. Multiple eye-machine interaction applications, such as eye-drawing, Gluttonous Snake game, web interaction, pan-tilt-zoom camera control, and robot vehicle control, are demonstrated on the eye movement model and in vivo rabbit. Furthermore, comprehensive biocompatibility tests are implemented, demonstrating low cytotoxicity and low eye irritation. Thus, the contact lens is expected to enrich approaches of eye tracking techniques and promote the development of human-machine interaction technology.

The mediating effect of internet addiction and the moderating effect of physical activity on the relationship between alexithymia and depression.

There is a certain relationship between alexithymia and depression, but further investigation is needed to explore their underlying mechanisms. The aims of this study was to explore the mediating role of internet addiction between alexithymia and depression and the moderating role of physical activity. A total of 594 valid responses were included in the analysis, with a mean age of 18.72 years (SD = 1.09). The sample comprised 250 males (42.09%) and 344 females (57.91%). These responses were utilized for descriptive analysis, correlation analysis, regression analysis, and the development of mediation and moderation models. Alexithymia showed positive correlations with depression and internet addiction, and physical activity was negatively correlated with internet addiction and depression. Internet addiction partially mediated the relationship between alexithymia and depression, while physical activity weakened the association between internet addiction and depression, acting as a moderator. Our findings suggest that excessive Internet engagement may mediate the relationship between alexithymia and depression as an emotional regulatory coping strategy, and that physical activity attenuates the predictive effect of Internet addiction on depression.

Nanocellulose-mediated bilayer hydrogel actuators with thermo-responsive, shape memory and self-sensing performances.

Inspired by creatures, abundant stimulus-responsive hydrogel actuators with diverse functionalities have been manufactured for applications in soft robotics. However, constructing a shape memory and self-sensing bilayer hydrogel actuator with high mechanical strength and strong interfacial bonding still remains a challenge. Herein, a novel bilayer hydrogel with a stimulus-responsive TEMPO-oxidized cellulose nanofibers/poly(N-isopropylacrylamide) (TOCN/PNIPAM) layer and a non-responsive TOCN/polyacrylamide (TOCN/PAM) layer is proposed as a thermosensitive actuator. TOCNs as a nano-reinforced phase provide a high mechanical strength and endow the hydrogel actuator with a strong interfacial bonding. Due to the incorporation of TOCNs, the TOCN/PNIPAM hydrogel exhibits a high compressive strength (~89.2 kPa), elongation at break (~170.7 %) and tensile strength (~24.0 kPa). The prepared PNIPAM/TOCN/PAM hydrogel actuator performs the roles of an encapsulation, jack, temperature-controlled fluid valve and temperature-control manipulator. The incorporation of Fe3+ further endows the bilayer hydrogel actuator with a synergistic performance of shape memory and temperature-driven, which can be used as a temperature-responsive switch to detect ambient temperature. The PNIPAM/TOCN/PAM-Fe3+ conductive hydrogel can be assembled into a flexible sensor and generate sensing signals when driven by temperature changes to achieve real-time feedback. This research may lead to new insights into the design and manufacturing of intelligent flexible soft robots.

Pyroptosis-mediator GSDMD promotes Parkinson's disease pathology via microglial activation and dopaminergic neuronal death.

GSDMD-mediated pyroptosis occurs in the nigrostriatal pathway in Parkinson's disease animals, yet the role of GSDMD in neuroinflammation and death of dopaminergic neurons in Parkinson's disease remains elusive. Here, our in vivo and in vitro studies demonstrated that GSDMD, as a pyroptosis executor, contributed to glial reaction and death of dopaminergic neurons across different Parkinson's disease models. The ablation of the Gsdmd attenuated Parkinson's disease damage by reducing dopaminergic neuronal death, microglial activation, and detrimental transformation. Disulfiram, an inhibitor blocking GSDMD pore formation, efficiently curtailed pyroptosis, thereby lessening the pathology of Parkinson's disease. Additionally, a modification in GSDMD was identified in the blood of Parkinson's disease patients in contrast to healthy subjects. Therefore, the detected alteration in GSDMD within the blood of Parkinson's disease patients and the protective impact of disulfiram could be promising for the diagnostic and therapeutic approaches against Parkinson's disease.

A novel bioprospecting strategy via 13C-based high-throughput probing of active methylotrophs inhabiting oil reservoir surface soil.

Methane-oxidizing bacteria (MOB) have long been considered as a microbial indicator for oil and gas prospecting. However, due to the phylogenetically narrow breath of ecophysiologically distinct MOB, classic culture-dependent approaches could not discriminate MOB population at fine resolution, and accurately reflect the abundance of active MOB in the soil above oil and gas reservoirs. Here, we presented a novel microbial anomaly detection (MAD) strategy to quantitatively identify specific indicator methylotrophs in the surface soils for bioprospecting oil and gas reservoirs by using a combination of 13C-DNA stable isotope probing (SIP), high-throughput sequencing (HTS), quantitative PCR (qPCR) and geostatistical analysis. The Chunguang oilfield of the Junggar Basin was selected as a model system in western China, and type I methanotrophic Methylobacter was most active in the topsoil above the productive oil wells, while type II methanotrophic Methylosinus predominated in the dry well soils, exhibiting clear differences between non- and oil reservoir soils. Similar results were observed by quantification of Methylobacter pmoA genes as a specific bioindicator for the prediction of unknown reservoirs by grid sampling. A microbial anomaly distribution map based on geostatistical analysis further showed that the anomalous zones were highly consistent with petroleum, geological and seismic data, and validated by subsequent drilling. Over seven years, a total of 24 wells have been designed and drilled into the targeted anomaly, and the success rate via the MAD prospecting strategy was 83 %. Our results suggested that molecular techniques are powerful tools for oil and gas prospecting. This study indicates that the exploration efficiency could be significantly improved by integrating multi-disciplinary information in geophysics and geomicrobiology while reducing the drilling risk to a greater extent.

Kernel Bayesian nonlinear matrix factorization based on variational inference for human-virus protein-protein interaction prediction.

Identification of potential human-virus protein-protein interactions (PPIs) contributes to the understanding of the mechanisms of viral infection and to the development of antiviral drugs. Existing computational models often have more hyperparameters that need to be adjusted manually, which limits their computational efficiency and generalization ability. Based on this, this study proposes a kernel Bayesian logistic matrix decomposition model with automatic rank determination, VKBNMF, for the prediction of human-virus PPIs. VKBNMF introduces auxiliary information into the logistic matrix decomposition and sets the prior probabilities of the latent variables to build a Bayesian framework for automatic parameter search. In addition, we construct the variational inference framework of VKBNMF to ensure the solution efficiency. The experimental results show that for the scenarios of paired PPIs, VKBNMF achieves an average AUPR of 0.9101, 0.9316, 0.8727, and 0.9517 on the four benchmark datasets, respectively, and for the scenarios of new human (viral) proteins, VKBNMF still achieves a higher hit rate. The case study also further demonstrated that VKBNMF can be used as an effective tool for the prediction of human-virus PPIs.

Armoring the cathode with starch gel enables Shuttle-Free Zinc-Iodine batteries.

Zinc-iodine batteries (ZIBs) have been recognized as a promising energy storage device due to their high energy density, low cost and environmental friendliness. However, the development of ZIBs is hindered by the shuttle effect of polyiodides which results in capacity degradation and poor cycling performance. Inspired by the ability of starch to form inclusion compounds with iodine, we propose to use a starch gel on the cathode to suppress the shuttle of polyiodides. Herein, porous carbon is utilized as a host for iodine species and provides an excellent conductive network, while starch gel is used as another host to suppress polyiodides shuttle, resulting in improved battery performance. The test results demonstrate that the conversion between I-/I2/I3- in the cathode and the effective inclusion role of starch suppress the shuttle of polyiodides during the charging process. Meanwhile, based on the electrochemical tests and theoretical DFT calculations, it is found that starch has a stronger ability to adsorb polyiodides compared to carbon materials, which enables effective confinement of polyiodides. The ZIBs used the cathode with starch gel exhibit high coulombic efficiency (>95 % at 0.2 A/g) and low self-discharge (86.8 % after resting for 24 h). This strategy is characterized by its simplicity, low cost and high applicability, making it significant for the advancement of high-performance ZIBs.

Orosomucoid 2 upregulation mediates liver injury-induced colorectal cancer liver metastasis by promoting EMT and cell migration.

The relationship between drug-induced liver injury and liver metastasis of colorectal cancer and the underlying mechanisms are not well understood. In this study, we used carbon tetrachloride to construct a classic mouse liver injury model and injected CT26 colorectal cancer cells into the mouse spleen to simulate the natural route of colorectal cancer liver metastasis. Liver injury significantly increased the number of colorectal cancer liver metastases. Transcriptome sequencing and data-independent acquisition protein quantification identified proteins that were significantly differentially expressed in injured livers, and orosomucoid (ORM) 2 was identified as a target protein for tumor liver metastasis. In vitro experiments showed that exogenous ORM2 protein increased the expression of EMT markers such as Twist, Zeb1, Vim, Snail1 and Snail2 and chemokine ligands to promote CT26 cell migration. In addition, liver-specific overexpression of the ORM2 protein in the mouse model significantly promoted tumor cell liver metastasis without inducing liver injury. Our results indicate that drug-induced liver injury can promote colorectal cancer liver metastasis and that ORM2 can promote cell migration by inducing EMT in tumor cells.

Hydrogen Spillover Phenomenon at the Interface of Metal-Supported Electrocatalysts for Hydrogen Evolution.

ConspectusHydrogen spillover, as a well-known phenomenon for thermal hydrogenation, generally involves the migration of active hydrogen on the surface of metal-supported catalysts. For thermocatalytic hydrogenation, hydrogen spillover generally takes place from metals with superiority for dissociating hydrogen molecules to supports with strong hydrogen adsorption under a H2 environment with high pressures. The former can bring high hydrogen chemical potential to largely reduce the kinetic barrier of the migration of active hydrogen species from metals to supports. At the same time, the latter can make H* migration thermodynamically spontaneous. For these reasons, hydrogen spillover is a common interfacial phenomenon occurring on metal-supported catalysts during thermocatalysis. Recently, this phenomenon has been observed for the exceptionally enhanced electrocatalytic performance for hydrogen evolution and other electrocatalytic organic synthesis. Different from hydrogen spillover for thermocatalysis under high H2 pressure, hydrogen spillover for electrocatalysis involves the migration of active hydrogen species (H*) from metals with strong hydrogen adsorption to supports with weak hydrogen adsorption, thereby suffering from a thermodynamically unfavorable process accompanied by a high kinetic barrier. Thus, the occurrence of hydrogen spillover at the electrocatalytic interface is not easy, and successful cases are rare. Understanding the underlying nature of hydrogen spillover at the electrocatalytic interface of metal-supported catalysts is critical to the rational design of advanced electrocatalysts.In this Account, we provide in-depth insights into recent advances in hydrogen spillover at the electrocatalytic interface for a significantly enhanced hydrogen evolution performance. Electron accumulation at the metal-support interface induces severe interfacial H* trapping and is recognized as the main factor in the failed hydrogen spillover. Given this, we developed two novel strategies to promote the occurrence of hydrogen spillover at the electrocatalytic interface. These strategies include (i) the introduction of ligand environments to enrich the local hydrogen coverage on metals and lower the barrier for interfacial hydrogen spillover and (ii) the minimization of work function difference between metals and supports (ΔΦ) to relieve electron accumulation and lower the kinetic barrier for hydrogen spillover. Also, we summarize the previously reported strategy of shortening the metal-support interface distance to lower the kinetic barrier for interfacial hydrogen spillover. Afterward, some criteria and methodologies are proposed to identify the hydrogen spillover phenomenon at the electrocatalytic interface. Finally, the remaining challenges and future perspectives are also discussed. Based on this Account, we aim to provide new insights into electrocatalysis, particularly the targeted control of hydrogen spillover at the electrocatalytic interface, and then to offer guidelines for the rational design of advanced electrocatalysts.

SS-31 inhibits mtDNA-cGAS-STING signaling to improve POCD by activating mitophagy in aged mice.

BACKGROUND: Neuroinflammation is crucial in the development of postoperative cognitive dysfunction (POCD), and microglial activation is an active participant in this process. SS-31, a mitochondrion-targeted antioxidant, is widely regarded as a potential drug for neurodegenerative diseases and inflammatory diseases. In this study, we sought to explore whether SS-31 plays a neuroprotective role and the underlying mechanism. METHODS: Internal fixation of tibial fracture was performed in 18-month-old mice to induce surgery-associated neurocognitive dysfunction. LPS was administrated to BV2 cells to induce neuroinflammation. Neurobehavioral deficits, hippocampal injury, protein expression, mitophagy level and cell state were evaluated after treatment with SS-31, PHB2 siRNA and an STING agonist. RESULTS: Our study revealed that SS-31 interacted with PHB2 to activate mitophagy and improve neural damage in surgically aged mice, which was attributed to the reduced cGAS-STING pathway and M1 microglial polarization by decreased release of mitochondrial DNA (mtDNA) but not nuclear DNA (nDNA). In vitro, knockdown of PHB2 and an STING agonist abolished the protective effect of SS-31. CONCLUSIONS: SS-31 conferred neuroprotection against POCD by promoting PHB2-mediated mitophagy activation to inhibit mtDNA release, which in turn suppressed the cGAS-STING pathway and M1 microglial polarization.

Nanodosimetric quantity-weighted dose optimization for carbon-ion treatment planning.

Dose verification of treatment plans is an essential step in radiotherapy workflows. In this work, we propose a novel method of treatment planning based on nanodosimetric quantity-weighted dose (NQWD), which could realize biological representation using pure physical quantities for biological-oriented carbon ion-beam treatment plans and their direct verification. The relationship between nanodosimetric quantities and relative biological effectiveness (RBE) was studied with the linear least-squares method for carbon-ion radiation fields. Next, under the framework of the matRad treatment planning platform, NQWD was optimized using the existing RBE-weighted dose (RWD) optimization algorithm. The schemes of NQWD-based treatment planning were compared with the RWD treatment plans in term of the microdosimetric kinetic model (MKM). The results showed that the nanodosimetric quantity F3 - 10 had a good correlation with the radiobiological effect reflected by the relationship between RBE and F3 - 10. Moreover, the NQWD-based treatment plans reproduced the RWD plans generally. Therefore, F3 - 10 could be adopted as a radiation quality descriptor for carbon-ion treatment planning. The novel method proposed herein not only might be helpful for rapid physical verification of biological-oriented ion-beam treatment plans with the development of experimental nanodosimetry, but also makes the direct comparison of ion-beam treatment plans in different institutions possible. Thus, our proposed method might be potentially developed to be a new strategy for carbon-ion treatment planning and improve patient safety for carbon-ion radiotherapy.