Prediction of early neurologic deterioration in patients with perforating artery territory infarction using machine learning: a retrospective study.

Background: Early neurological deterioration (END) is a frequent complication in patients with perforating artery territory infarction (PAI), leading to poorer outcomes. Therefore, we aimed to apply machine learning (ML) algorithms to predict the occurrence of END in PAI and investigate related risk factors. Methods: This retrospective study analyzed a cohort of PAI patients, excluding those with severe stenosis of the parent artery. We included demographic characteristics, clinical features, laboratory data, and imaging variables. Recursive feature elimination with cross-validation (RFECV) was performed to identify critical features. Seven ML algorithms, namely logistic regression, random forest, adaptive boosting, gradient boosting decision tree, histogram-based gradient boosting, extreme gradient boosting, and category boosting, were developed to predict END in PAI patients using these critical features. We compared the accuracy of these models in predicting outcomes. Additionally, SHapley Additive exPlanations (SHAP) values were introduced to interpret the optimal model and assess the significance of input features. Results: The study enrolled 1,020 PAI patients with a mean age of 60.46 (range 49.11-71.81) years. Of these, 30.39% were women, and 129 (12.65%) experienced END. RFECV selected 13 critical features, including blood urea nitrogen (BUN), total cholesterol (TC), low-density-lipoprotein cholesterol (LDL-C), apolipoprotein B (apoB), atrial fibrillation, loading dual antiplatelet therapy (DAPT), single antiplatelet therapy (SAPT), argatroban, the basal ganglia, the thalamus, the posterior choroidal arteries, maximal axial infarct diameter (measured at < 15 mm), and stroke subtype. The gradient-boosting decision tree had the highest area under the curve (0.914) among the seven ML algorithms. The SHAP analysis identified apoB as the most significant variable for END. Conclusion: Our results suggest that ML algorithms, especially the gradient-boosting decision tree, are effective in predicting the occurrence of END in PAI patients.

Construction and validation of an immune infiltration-related risk model for predicting prognosis and immunotherapy response in low grade glioma.

BACKGROUND: Low grade glioma (LGG) is considered a heterogeneous tumor with highly variable survival and limited efficacy of immunotherapy. To identify high-risk subsets and apply immunotherapy effectively in LGG, the status and function of immune infiltration in the glioma microenvironment must be explored. METHODS: Four independent glioma cohorts comprising 1,853 patients were enrolled for bioinformatics analysis. We used ConsensusClusterPlus to cluster patients into four different immune subtypes based on immune infiltration. The immune-infiltration signature (IIS) was constructed by LASSO regression analysis. Somatic mutation and copy number variation (CNV) analyses were performed to explore genomic and transcriptomic traits in the high- and low- risk groups. The correlation between response to programmed cell death 1 (PD-1) blockade and the IIS risk score was confirmed in an in vivo glioma model. RESULTS: Patients were clustered into four different immune subtypes based on immune infiltration, and the high immune infiltration subtype was associated with worse survival in LGG. The high immune infiltration subtype had stronger inflammatory response, immune response and immune cell chemotaxis. The IIS, consisting of EMP3, IQGAP2, METTL7B, SLC1A6 and TNFRSF11B, could predict LGG malignant progression, which was validated with internal clinical samples. M2 macrophage infiltration positively correlated with the IIS risk score. The high-risk group had significantly more somatic mutations and CNVs. The IIS risk score was related to immunomodulatory molecules and could predict immunotherapy clinical benefit. In vivo, immunotherapy-sensitive glioma model exhibited higher IIS risk score and more infiltration of immune cells, especially M2 macrophages. The IIS risk score was decreased in an immunotherapy-sensitive glioma model after anti-PD1 immunotherapy. CONCLUSION: Different immune subtypes of LGG had unique immune cell infiltration characteristics, and the high immune infiltration subtype was associated with immunosuppressive signaling pathways. A novel IIS prognostic model based on immune infiltration status was constructed for immunophenotypic classification, risk stratification, prognostication and immunotherapy response prediction in LGG.

Association between morphologic features of intracranial distal arteries and brain atrophy indexes in cerebral small vessel disease: a voxel-based morphometry study.

Background: Brain atrophy represents a final common pathway for pathological processes in patients with cerebral small vessel disease (CSVD) and is now recognized as a strong independent predictor of clinical status and progression. The mechanism underlying brain atrophy in patients with CSVD is not yet fully comprehended. This study aims to investigate the association of morphologic features of intracranial distal arteries (A2, M2, P2 and more distal) with different brain structures [gray matter volume (GMV), white matter volume (WMV), and cerebrospinal fluid volume (CSFV)]. Furthermore, we also examined whether a correlation existed between these cerebrovascular characteristics and GMV in different brain regions. Method: A total of 39 participants were eventually enrolled. The morphologic features of intracranial distal arteries based on TOF-MRA were extracted and quantified using the intracranial artery feature extraction technique (iCafe). The brain 3D-T1 images were segmented into gray matter (GM), white matter (WM), and cerebrospinal fluid (CSF) using the "Segment" tool in CAT12 for the voxel-based morphometry (VBM) analysis. Univariable and multivariable linear regression models were used to investigate the relationship between these cerebrovascular features and different brain structures. Partial correlation analysis with a one-tailed method was used to evaluate the relationship between these cerebrovascular features and GMV in different brain regions. Results: Our findings indicate that both distal artery length and density were positively correlated with GM fraction in CSVD patients, regardless of whether univariable or multivariable linear regression analyses were performed. In addition, distal artery length (ß = -0.428, p = 0.007) and density (ß = -0.337, p = 0.036) were also found to be negative associated with CSF fraction, although this relationship disappeared after adjusting for potential confounders. Additional adjustment for the effect of WMHs volume did not change these results. In subgroup anasysis, we found that participants in the highest distal artery length tertile had significantly higher GM fraction and lower CSF fraction level than participants in the lowest distal artery length tertile. In partial correlation analysis, we also found that these cerebrovascular characteristics associated with regional GMV, especially subcortical nuclear. Conclusion: The morphologic features of intracranial distal arteries, including artery length, density and average tortuosity, measured from 3D-TOF MRA, are associated with generalized or focal atrophy indexes of CSVD.

Learning-based near-optimal tracking control for industrial processes with slow and fast modes.

This paper devotes to solving the optimal tracking control (OTC) problem of singular perturbation systems in industrial processes under the framework of reinforcement learning (RL) technology. The encountered challenges include the different time scales in system operations and an unknown slow process. The immeasurability of slow process states especially increases the difficulty of finding the optimal tracking controller. To overcome these challenges, a novel off-policy ridge RL method is developed after decomposing the singular perturbed systems using the singular perturbation (SP) theory and replacing unmeasured states using important mathematical manipulations. Theoretical analysis of approximate equivalence of the sum of solutions of subproblems to the solution of the OTC problem is presented. Finally, a mixed separation thickening process (MSTP) and a numerical example are used to verify the effectiveness.

Genome-wide analysis of WD40 protein family and functional characterization of BvWD40-82 in sugar beet.

Sugar beet is one of the most important sugar crops in the world. It contributes greatly to the global sugar production, but salt stress negatively affects the crop yield. WD40 proteins play important roles in plant growth and response to abiotic stresses through their involvement in a variety of biological processes, such as signal transduction, histone modification, ubiquitination, and RNA processing. The WD40 protein family has been well-studied in Arabidopsis thaliana, rice and other plants, but the systematic analysis of the sugar beet WD40 proteins has not been reported. In this study, a total of 177 BvWD40 proteins were identified from the sugar beet genome, and their evolutionary characteristics, protein structure, gene structure, protein interaction network and gene ontology were systematically analyzed to understand their evolution and function. Meanwhile, the expression patterns of BvWD40s under salt stress were characterized, and a BvWD40-82 gene was hypothesized as a salt-tolerant candidate gene. Its function was further characterized using molecular and genetic methods. The result showed that BvWD40-82 enhanced salt stress tolerance in transgenic Arabidopsis seedlings by increasing the contents of osmolytes and antioxidant enzyme activities, maintaining intracellular ion homeostasis and increasing the expression of genes related to SOS and ABA pathways. The result has laid a foundation for further mechanistic study of the BvWD40 genes in sugar beet tolerance to salt stress, and it may inform biotechnological applications in improving crop stress resilience.

Effect of prophylactic antiviral intervention on T cell immunity in hepatitis B virus-infected pregnant women.

BACKGROUND: Antiviral intervention in hepatitis B virus (HBV)-infected pregnant women can effectively reduce mother-to-child transmission. However, the immunological characteristics of pregnant women with chronic HBV infection and the effects of antiviral intervention during pregnancy on maternal immune response remain unknown. We aimed to investigate these effects by comparing mothers who received antiviral intervention during pregnancy with those who did not. METHODS: Pregnant women positive for hepatitis B surface antigen and hepatitis B e-antigen (HBsAg+ HBeAg+) were enrolled at delivery, including 34 received prophylactic antiviral intervention during pregnancy (AVI mothers) and 15 did not (NAVI mothers). T lymphocyte phenotypes and functions were analysed using flow cytometry. RESULTS: At delivery, maternal regulatory T cell (Treg) frequency in AVI mothers was significantly higher than that in NAVI mothers (P < 0.002), and CD4+ T cells in AVI mothers displayed a decreased ability to secrete IFN-γ (P = 0.005) and IL-21 (P = 0.043), but an increased ability to secrete IL-10 and IL-4 (P = 0.040 and P = 0.036), which represented a higher Treg frequency, enhanced Th2 response and suppressed Th1 response. Treg frequency among AVI mothers was correlated negatively with serum HBsAg and HBeAg levels. After delivery, the ability of CD4+ T cells or CD8+ T cells to secrete IFN-γ or IL-10 was similar and no significant difference in Treg frequency was found between the two groups. CONCLUSIONS: Prophylactic antiviral intervention during pregnancy has an effect on T cell immunity in pregnant women, which was characterised by increased maternal Treg frequency, enhanced Th2 response and suppressed Th1 response at delivery.

A novel inflammation-related signature for predicting prognosis and characterizing the tumor microenvironment in colorectal cancer.

Inflammation is a critical component of tumor progression, and it modifies the tumor microenvironment by various mechanisms. Here, we explore the effect of the inflammatory response on the tumor microenvironment in colorectal cancer (CRC). A prognostic signature consisting of inflammation-related genes (IRGs) was constructed and verified based on the inflammatory response by bioinformatics analysis. IRG risk model was identified as an independent prognostic factor in CRC, and was related to biological processes of extracellular matrix, cell adhesion and angiogenesis. The IRG risk score predicted the clinical benefit of ipilimumab. Weighted correlation network analysis identified TIMP1 as the hub gene of the inflammatory response in the IRG risk model. Coculture experiments with macrophages and CRC cells revealed that TIMP1 promoted macrophage migration, inhibited the expression of M1 markers (CD11C and CD80), and promoted the expression of M2 markers (ARG1 and CD163). TIMP1 promoted the expression of ICAM1 and CCL2 by activating the ERK1/2 signaling pathway to promote macrophage migration and M2-like polarization. These IRGs in the risk model regulated stromal and immune components in the tumor microenvironment and could serve as potential therapeutic targets in CRC. TIMP1 promoted macrophage migration and meditated macrophage M2 polarization by activating ERK1/2/CLAM1 and CCL2.

Data-Driven H∞ Optimal Output Feedback Control for Linear Discrete-Time Systems Based on Off-Policy Q-Learning.

This article develops two novel output feedback (OPFB) Q -learning algorithms, on-policy Q -learning and off-policy Q -learning, to solve H∞ static OPFB control problem of linear discrete-time (DT) systems. The primary contribution of the proposed algorithms lies in a newly developed OPFB control algorithm form for completely unknown systems. Under the premise of satisfying disturbance attenuation conditions, the conditions for the existence of the optimal OPFB solution are given. The convergence of the proposed Q -learning methods, and the difference and equivalence of two algorithms are rigorously proven. Moreover, considering the effects brought by probing noise for the persistence of excitation (PE), the proposed off-policy Q -learning method has the advantage of being immune to probing noise and avoiding biasedness of solution. Simulation results are presented to verify the effectiveness of the proposed approaches.

Reinforcement learning based proportional-integral-derivative controllers design for consensus of multi-agent systems.

This paper develops a novel Proportional-Integral-Derivative (PID) tuning method for multi-agent systems with a reinforced self-learning capability for achieving the optimal consensus of all agents. Unlike the traditional model-based and data-driven PID tuning methods, the developed PID self-learning method updates the controller parameters by actively interacting with unknown environment, with the outcomes of guaranteed consensus and performance optimization of agents. Firstly, the PID control-based consensus problem of multi-agent systems is formulated. Then, finding the PID gains is converted into solving a nonzero-sum game problem, thus an off-policy Q-learning algorithm with the critic-only structure is proposed to update the PID gains using only data, without the knowledge of dynamics of agents. Finally, simulations are given to verify the effectiveness of the proposed method.

A Retrospective Study of Trifluridine/Tipiracil with Fruquintinib in Patients with Chemorefractory Metastatic Colorectal Cancer.

INTRODUCTION: Trifluridine/tipiracil (TAS-102) and fruquintinib are novel antitumor agents for patients with refractory metastatic colorectal cancer (mCRC). We conducted a retrospective study to explore the clinical efficacy and drug toxicities of combination therapy with TAS-102 and fruquintinib in real-life clinical practice. METHODS: Between March 2021 and February 2023, patients at two different centers with mCRC who failed two or more lines of prior therapy and received TAS-102 in combination with fruquintinib were recruited. RESULTS: In total, 32 mCRC patients were included in the analysis. The objective response rate (ORR) and the disease control rate (DCR) were 9.4% and 75%. The median progression-free survival (PFS) and overall survival (OS) were 6.3 (95% CI: 5.3-7.3) and 13.5 (95% CI: 9.5-17.5) months, respectively. Patients without liver metastasis or peritoneal metastasis obtained better median PFS (7.1 m vs. 5.6 m, p = 0.03 and 6.3 m vs. 3.4 m, p = 0.04), and OS (15.2 m vs. 10.4 m, p = 0.01 and 13.6 m vs. 7.1 m, p = 0.03), respectively. Other clinicopathological features, including age, tumor site, KRAS status, dosage of fruquintinib, and treatment line, did not affect the clinical efficacy of TAS-102 combined with fruquintinib. The most common grade three-four toxicities were neutropenia (46.9%), anemia (21.9%), diarrhea (15.6%), nausea (12.5%), and hand-foot syndrome rash (12.5%). CONCLUSIONS: Our results suggest that TAS-102 combined with fruquintinib has promising clinical efficacy and manageable safety for refractory mCRC patients in a real-world clinical setting. Further prospective trials are warranted to confirm our results.

Comparative Ubiquitination Proteomics Revealed the Salt Tolerance Mechanism in Sugar Beet Monomeric Additional Line M14.

Post-translational modifications (PTMs) are important molecular processes that regulate organismal responses to different stresses. Ubiquitination modification is not only involved in human health but also plays crucial roles in plant growth, development, and responses to environmental stresses. In this study, we investigated the ubiquitination proteome changes in the salt-tolerant sugar beet monomeric additional line M14 under salt stress treatments. Based on the expression of the key genes of the ubiquitination system and the ubiquitination-modified proteins before and after salt stress, 30 min of 200 mM NaCl treatment and 6 h of 400 mM NaCl treatment were selected as time points. Through label-free proteomics, 4711 and 3607 proteins were identified in plants treated with 200 mM NaCl and 400 mM NaCl, respectively. Among them, 611 and 380 proteins were ubiquitinated, with 1085 and 625 ubiquitination sites, in the two salt stress conditions, respectively. A quantitative analysis revealed that 70 ubiquitinated proteins increased and 47 ubiquitinated proteins decreased. At the total protein level, 42 were induced and 20 were repressed with 200 mM NaCl, while 28 were induced and 27 were repressed with 400 mM NaCl. Gene ontology, KEGG pathway, protein interaction, and PTM crosstalk analyses were performed using the differentially ubiquitinated proteins. The differentially ubiquitinated proteins were mainly involved in cellular transcription and translation processes, signal transduction, metabolic pathways, and the ubiquitin/26S proteasome pathway. The uncovered ubiquitinated proteins constitute an important resource of the plant stress ubiquitinome, and they provide a theoretical basis for the marker-based molecular breeding of crops for enhanced stress tolerance.

Quantitative redox proteomics revealed molecular mechanisms of salt tolerance in the roots of sugar beet monomeric addition line M14.

BACKGROUND: Salt stress is often associated with excessive production of reactive oxygen species (ROS). Oxidative stress caused by the accumulation of ROS is a major factor that negatively affects crop growth and yield. Root is the primary organ that senses and transmits the salt stress signal to the whole plant. How oxidative stress affect redox sensitive proteins in the roots is not known. RESULTS: In this study, the redox proteome of sugar beet M14 roots under salt stress was investigated. Using iTRAQ reporters, we determined that salt stress caused significant changes in the abundance of many proteins (2305 at 20 min salt stress and 2663 at 10 min salt stress). Using iodoTMT reporters, a total of 95 redox proteins were determined to be responsive to salt stress after normalizing again total protein level changes. Notably, most of the differential redox proteins were involved in metabolism, ROS homeostasis, and stress and defense, while a small number play a role in transport, biosynthesis, signal transduction, transcription and photosynthesis. Transcription levels of 14 genes encoding the identified redox proteins were analyzed using qRT-PCR. All the genes were induced by salt stress at the transcriptional level. CONCLUSIONS: Based on the redox proteomics results, we construct a map of the regulatory network of M14 root redox proteins in response to salt stress. This study further refines the molecular mechanism of salt resistance at the level of protein redox regulation.

Neural network-based adaptive event-triggered sliding mode control for singular systems with an adaptive event-triggering communication scheme.

This paper studies the event-triggered sliding mode control problem for singular systems subject to the unknown nonlinear function and the exogenous disturbance. For saving the communication resources, a new adaptive event-triggering communication scheme (AETCS) is designed, which scheme uses the information on the nonlinear function part. Secondly, for the error system, we provide a novel integral sliding surface, which makes it beneficial to construct a new augmented delay system model by utilizing a delay system method. Furthermore, the sliding mode control (SMC) method for the error system is applied to compensate the unknown nonlinearity by using its estimate and match the exogenous disturbance by its upper bound. According to the Lyapunov function theory, stability criteria are got on the basis of LMIs. Moreover, two novel event-triggered adaptive sliding mode controllers based on RBF neural network are designed such that reachability conditions are obtained, and the asymptotic stability of singular systems with the H∞ performance is guaranteed. The RBF neural networks way is exploited to evaluate the unknown nonlinear function, which can eliminate the strict assumption of nonlinear function in some existing results. Finally, the proposed method is validated by two examples.

Adaptive Interleaved Reinforcement Learning: Robust Stability of Affine Nonlinear Systems With Unknown Uncertainty.

This article investigates adaptive robust controller design for discrete-time (DT) affine nonlinear systems using an adaptive dynamic programming. A novel adaptive interleaved reinforcement learning algorithm is developed for finding a robust controller of DT affine nonlinear systems subject to matched or unmatched uncertainties. To this end, the robust control problem is converted into the optimal control problem for nominal systems by selecting an appropriate utility function. The performance evaluation and control policy update combined with neural networks approximation are alternately implemented at each time step for solving a simplified Hamilton-Jacobi-Bellman (HJB) equation such that the uniformly ultimately bounded (UUB) stability of DT affine nonlinear systems can be guaranteed, allowing for all realization of unknown bounded uncertainties. The rigorously theoretical proofs of convergence of the proposed interleaved RL algorithm and UUB stability of uncertain systems are provided. Simulation results are given to verify the effectiveness of the proposed method.

Polymorphonuclear neutrophils promote endothelial apoptosis by enhancing adhesion upon stimulation by intermittent hypoxia.

PURPOSE: This study explored the interactive effects between polymorphonuclear neutrophils (PMNs) and vascular endothelial cells under intermittent hypoxia (IH) and investigated the mechanisms underlying these effects. METHODS: Endothelial cells were co-cultured with PMNs isolated from rats exposed to normoxia or IH. The PMN apoptotic rate was determined using flow cytometry. Expression of apoptosis-related proteins in the endothelial cells were evaluated using Western blotting, and the levels of intercellular adhesion molecules in the co-culture supernatants were measured using enzyme-linked immunosorbent assay. RESULTS: The PMN apoptotic rate in the IH-exposed rat group was significantly lower than that of the normoxia control group. There was a positive relationship between the PMN apoptotic rate and IH exposure time. In endothelial cells co-cultured with PMNs isolated from IH-exposed rats, a significant increase in the protein expression levels of Bax, Bcl-2, and caspase-3 and a significant decrease in the Bcl-2/Bax ratio were observed. Furthermore, the intercellular cell adhesion molecule-1(ICAM-1) and E-select element (E-S) levels were elevated significantly in the co-cultured supernatants of endothelial cells and PMNs from IH-exposed rats compared to that from controls. The above IH-induced alterations were partially restored by tempol pretreatment. CONCLUSIONS: The apoptotic rate was low in PMNs from IH-exposed rats, which consequently increased the apoptotic signals in endothelial cells in vitro. This may be associated with the increased levels of intercellular adhesion molecules. Further, tempol partially attenuates the PMN-mediated pro-apoptotic effects on endothelial cells under IH.

Functional Characterization of Sugar Beet M14 Antioxidant Enzymes in Plant Salt Stress Tolerance.

Salt stress can cause cellular dehydration, which induces oxidative stress by increasing the production of reactive oxygen species (ROS) in plants. They may play signaling roles and cause structural damages to the cells. To overcome the negative impacts, the plant ROS scavenging system plays a vital role in maintaining the cellular redox homeostasis. The special sugar beet apomictic monosomic additional M14 line (BvM14) showed strong salt stress tolerance. Comparative proteomics revealed that six antioxidant enzymes (glycolate oxidase (GOX), peroxiredoxin (PrxR), thioredoxin (Trx), ascorbate peroxidase (APX), monodehydroascorbate reductase (MDHAR), and dehydroascorbate reductase3 (DHAR3)) in BvM14 were responsive to salt stress. In this work, the full-length cDNAs of genes encoding these enzymes in the redox system were cloned from the BvM14. Ectopic expression of the six genes reduced the oxidative damage of transgenic plants by regulating the contents of hydrogen peroxide (H2O2), malondialdehyde (MDA), ascorbic acid (AsA), and glutathione (GSH), and thus enhanced the tolerance of transgenic plants to salt stress. This work has charecterized the roles that the antioxidant enzymes play in the BvM14 response to salt stress and provided useful genetic resources for engineering and marker-based breeding of crops that are sensitive to salt stress.

Effect of curcumin on lung epithelial injury and ferroptosis induced by cigarette smoke.

Cigarette smoke (CS)-caused ferroptosis was involved in the pathogenesis of COPD, but the role of ferroptosis in lung epithelial injury and inflammation is not clear. Rats were treated with CS or CUR and BEAS-2B cells were exposed to CS extract (CSE), ferrostatin-1 (Fer-1), deferoxamine (DFO), or CUR to detect reactive oxygen species (ROS) accumulation, lipid peroxidation, iron overload, and ferroptosis-related protein, which were the characteristic changes of ferroptosis. Compared with the control group, CSE-treated BEAS-2B cells had more cell death, higher cytotoxicity, and lower cell viability. The infiltration of inflammatory cell around the bronchi in the CS group of rats was more than that in the normal group. Meanwhile, CSE/CS elevated the levels of interleukin-6 and tumor necrosis factor-α in BEAS-2B cells and bronchoalveolar lavage fluid of rats. Besides, accumulative ROS and depleted glutathione was observed in vitro. In BEAS-2B cells and lung tissues of rats, CSE/CS increased malondialdehyde and iron; down-regulated solute carrier family 7, glutathione peroxidase 4, and ferritin heavy chain levels; and up-regulated transferrin receptor level. These changes were rescued by pretreatment of Fer-1 or DFO in vitro, and mitigated by CUR in vitro and in vivo. Collectively, this study reveals that ferroptosis was involved in lung epithelial cell injury and inflammation induced by CS, and CUR may alleviate CS-induced injury, inflammation, and ferroptosis of lung epithelial cell.

Cys-SH based quantitative redox proteomics of salt induced response in sugar beet monosomic addition line M14.

BACKGROUND: Salt stress is a major abiotic stress that limits plant growth, development and productivity. Studying the molecular mechanisms of salt stress tolerance may help to enhance crop productivity. Sugar beet monosomic addition line M14 exhibits tolerance to salt stress. RESULTS: In this work, the changes in the BvM14 proteome and redox proteome induced by salt stress were analyzed using a multiplex iodoTMTRAQ double labeling quantitative proteomics approach. A total of 80 proteins were differentially expressed under salt stress. Interestingly, A total of 48 redoxed peptides were identified for 42 potential redox-regulated proteins showed differential redox change under salt stress. A large proportion of the redox proteins were involved in photosynthesis, ROS homeostasis and other pathways. For example, ribulose bisphosphate carboxylase/oxygenase activase changed in its redox state after salt treatments. In addition, three redox proteins involved in regulation of ROS homeostasis were also changed in redox states. Transcription levels of eighteen differential proteins and redox proteins were profiled. (The proteomics data generated in this study have been submitted to the ProteomeXchange and can be accessed via username: reviewer_pxd027550@ebi.ac.uk, password: q9YNM1Pe and proteomeXchange# PXD027550.) CONCLUSIONS: The results showed involvement of protein redox modifications in BvM14 salt stress response and revealed the short-term salt responsive mechanisms. The knowledge may inform marker-based breeding effort of sugar beet and other crops for stress resilience and high yield.

Auxiliary Structures-Assisted Radiotherapy Improvement for Advanced Left Breast Cancer.

BACKGROUND: To improve the quality of plan for the radiation treatment of advanced left breast cancer by introducing the auxiliary structures (ASs) which are used to spare the regions with no intact delineated structures adjacent to the target volume. METHODS: CT data from 20 patients with left-sided advanced breast cancer were selected. An AS designated as A1 was created to spare the regions of the aorta, pulmonary artery, superior vena ava, and contralateral tissue of the upper chest and neck, and another, designated as A2, was created in the regions of the cardia and fundus of the stomach, left liver lobe, and splenic flexure of the colon. IMRT and VMAT plans were created for cases with and without the use of the AS dose constraints in plan optimization. Dosimetric parameters of the target and organs at risk (OARs) were compared between the separated groups. RESULTS: With the use of AS dose constraints, both the IMRT and VMAT plans were clinically acceptable and deliverable, even showing a slight improvement in dose distribution of both the target and OARs compared with the AS-unused plans. The ASs significantly realized the dose sparing for the regions and brought a better conformity index (p < 0.05) and homogeneity index (p < 0.05) in VMAT plans. In addition, the volume receiving at least 20 Gy (V20) for the heart (p < 0.05), V40 for the left lung (p < 0.05), and V40 for the axillary-lateral thoracic vessel juncture region (p < 0.05) were all lower in VMAT plans. CONCLUSION: The use of the defined AS dose constraints in plan optimization was effective in sparing the indicated regions, improving the target dose distribution, and sparing OARs for advanced left breast cancer radiotherapy, especially those that utilize VMAT plans.

Corrigendum to "Potential Factors for Psychological Symptoms at Three Months in Patients with Young Ischemic Stroke".

[This corrects the article DOI: 10.1155/2021/5545078.].