The impact of light and thioredoxins on the plant thiol-disulfide proteome.

Thiol-based redox regulation is a crucial posttranslational mechanism to acclimate plants to changing light availability. Here, we conducted a biotin switch-based redox proteomics study in Arabidopsis (Arabidopsis thaliana) to systematically investigate dynamics of thiol-redox networks in response to temporal changes in light availability and across genotypes lacking parts of the thioredoxin (Trx) or NADPH-Trx-reductase C (NTRC) systems in the chloroplast. Time-resolved dynamics revealed light led to marked decreases in the oxidation states of many chloroplast proteins with photosynthetic functions during the first 10 min, followed by their partial reoxidation after 2 to 6 h into the photoperiod. This involved f, m, and x-type Trx proteins showing similar light-induced reduction-oxidation dynamics, while NTRC, 2-Cys peroxiredoxins, and Trx y2 showed an opposing pattern, being more oxidized in light than dark. In Arabidopsis trxf1f2, trxm1m2, or ntrc mutants, most proteins showed increased oxidation states in the light compared to wild type, suggesting their light-dependent dynamics were related to NTRC/Trx networks. While NTRC deficiency had a strong influence in all light conditions, deficiencies in f- or m-type Trxs showed differential impacts on the thiol-redox proteome depending on the light environment, being higher in constant or fluctuating light, respectively. The results indicate plant redox proteomes are subject to dynamic changes in reductive and oxidative pathways to cooperatively fine-tune photosynthetic and metabolic processes in the light. The importance of the individual elements of the NTRC/Trx networks mediating these responses depend on the extent of light variability, with NTRC playing a crucial role to balance protein-redox states in rapidly fluctuating light.

Thioredoxins o1 and h2 jointly adjust mitochondrial dihydrolipoamide dehydrogenase-dependent pathways towards changing environments.

Thioredoxins (TRXs) are central to redox regulation, modulating enzyme activities to adapt metabolism to environmental changes. Previous research emphasized mitochondrial and microsomal TRX o1 and h2 influence on mitochondrial metabolism, including photorespiration and the tricarboxylic acid (TCA) cycle. Our study aimed to compare TRX-based regulation circuits towards environmental cues mainly affecting photorespiration. Metabolite snapshots, phenotypes and CO2 assimilation were compared among single and multiple TRX mutants in the wild-type and the glycine decarboxylase T-protein knockdown (gldt1) background. Our analyses provided evidence for additive negative effects of combined TRX o1 and h2 deficiency on growth and photosynthesis. Especially metabolite accumulation patterns suggest a shared regulation mechanism mainly on mitochondrial dihydrolipoamide dehydrogenase (mtLPD1)-dependent pathways. Quantification of pyridine nucleotides, in conjunction with 13C-labelling approaches, and biochemical analysis of recombinant mtLPD1 supported this. It also revealed mtLPD1 inhibition by NADH, pointing at an additional measure to fine-tune it's activity. Collectively, we propose that lack of TRX o1 and h2 perturbs the mitochondrial redox state, which impacts on other pathways through shifts in the NADH/NAD+ ratio via mtLPD1. This regulation module might represent a node for simultaneous adjustments of photorespiration, the TCA cycle and branched chain amino acid degradation under fluctuating environmental conditions.

Correlation of serum homocysteine and cystatin C levels with prognosis in heart failure with preserved ejection fraction patients.

OBJECTIVE: This study investigated the relationship of serum homocysteine (Hcy) and cystatin C (Cys C) levels with the prognosis of patients with heart failure with preserved ejection fraction (HFpEF). METHODS: A total of 178 patients with HFpEF who were admitted to our hospital between December 2019 and November 2020 were included. Patients were grouped based on their serum Hcy and Cys C levels: high Hcy level, normal Hcy level, high Cys C level, and normal Cys C level. Cardiac function, ventricular remodeling indices, and prognosis were compared among patients in these groups. Additionally, the predictive value of serum Hcy and Cys C levels for adverse cardiovascular events in HFpEF patients was analyzed. RESULTS: Patients' mean age in the high Hcy level, normal Hcy level, high Cys C level, and normal Cys C level groups was 69.21 ± 4.17,67.74 ± 4.28,69.95 ± 4.98, and 67.06 ± 4.13 years old, respectively. The high Hcy level group exhibited a lower proportion of class II cardiac function according to the New York Heart Association (NYHA) classification and a higher proportion of class IV cardiac function than the normal Hcy level group, with statistically significant differences. Similarly, the high Cys C level group had a lower proportion of class II cardiac function and a higher proportion of class IV cardiac function compared with the normal Cys C level group, with statistically significant differences. Left ventricular end-diastolic internal diameter (LVEDD), left ventricular end-systolic internal diameter (LVESD), and left ventricular mass index (LVMI) were significantly higher in both the high Hcy level and high Cys C level groups compared with the normal group, with statistically significant differences. The rates of all-cause mortality and class I endpoint events were significantly higher in the high Hcy level and high Cys C level groups than in the normal group. Multifactorial logistic regression analysis demonstrated that adverse cardiovascular events were significantly associated with cardiac function class, LVEDD, LVESD, LVMI, Hcy, and Cys C in patients with HFpEF. The area under the curve (AUC) values for Hcy and Cys C, determined using receiver operating characteristic (ROC) curve analysis, were 0.778 (optimal critical value, 25.38) and 0.681 (optimal critical value, 1.56), respectively, for predicting adverse cardiovascular events. Both Hcy and Cys C serum levels were positively correlated with LVEDD, LVESD, LVMI, and NYHA classification. CONCLUSION: Serum levels of Hcy and Cys C were closely associated with cardiac function, ventricular remodeling indices, and prognosis in patients with HFpEF. These levels may serve as valuable indices for assessing HFpEF patients' health status and prognosis, providing important insights into their potential role as biomarkers for HFpEF management and prognosis.

Design, synthesis and biological evaluation of novel quinazoline-derived EGFR/HER-2 dual-target inhibitors bearing a heterocyclic-containing tail as potential anti-tumor agents.

A series of novel quinazoline-derived EGFR/HER-2 dual-target inhibitors were designed and synthesized by heterocyclic-containing tail approach. The inhibitory activities against four human epidermal growth factor receptor (HER) isozymes (EGFR, HER-2, HER-3 and HER-4) of all new compounds so designed were investigated in vitro. Compound 12k was found to be the most effective and rather selective dual-target inhibitor of EGFR and HER-2 with inhibitory constant (IC50) values of 6.15 and 9.78 nM, respectively, which was more potent than the clinical used agent Lapatinib (IC50 = 8.41 and 9.41 nM). Meanwhile, almost all compounds showed excellent antiproliferative activities against four cancer cell models (A549, NCI-H1975, SK-BR-3 and MCF-7) and low damage to healthy cells. Among them, compound 12k also exhibited the most prominent antitumor activity. Moreover, the hit compound 12k could bind to EGFR and HER-2 stably in molecular docking and dynamics studies. The following wound healing assay revealed that compound 12k could inhibit the migration of SK-BR-3 cells. Further studies found that compound 12k could arrest cell cycle in the G0/G1 phase and induce SK-BR-3 cells apoptosis. Notably, compound 12k could effectively inhibit breast cancer growth with little toxicity in the SK-BR-3 cell xenograft model. Taken together, in vitro and in vivo results disclosed that compound 12k had high drug potential as a dual-target inhibitor of EGFR/HER-2 to inhibit breast cancer growth.

Corrosion Monitoring by Plastic Optic Fiber Sensor Using Bi-Directional Light Transmission.

In this paper, a new sensor is proposed to efficiently gather crucial information on corrosion phenomena and their progression within steel components. Fabricated with plastic optical fibers (POF), the sensor can detect corrosion-induced physical changes in the appearance of monitoring points within the steel material. Additionally, the new sensor incorporates an innovative structure that efficiently utilizes bi-directional optical transmission in the POF, simplifying the installation procedure and reducing the total cost of the POF cables by as much as 50% when monitoring multiple points. Furthermore, an extremely compact dummy sensor with the length of 5 mm and a diameter of 2.2 mm for corrosion-depth detection was introduced, and its functionality was validated through experiments. This paper outlines the concept and fundamental structure of the proposed sensor; analyzes the results of various experiments; and discusses its effectiveness, prospects, and economic advantages.

Experimental Investigation for Monitoring Corrosion Using Plastic Optical Fiber Sensors.

The timely and cost-effective identification of the onset of corrosion and its progress would be critical for effectively maintaining structural integrity. Consequently, a series of fundamental experiments were conducted to capture the corrosion process on a steel plate using a new type of plastic optical fiber (POF) sensor. Electrolytic corrosion experiments were performed on a 5 mm thick steel plate immersed in an aqueous solution. The POF sensor installed on the upper side of the plate and directed downward detected the upward progression of the corrosion zone that formed on the underside of the plate. The results showed that the POF sensors could detect the onset of the upward-progressing corrosion front as it passed the 1 and 2 mm marks related to the thickness of the corroded zone. The POF sensors were designed to optically identify corrosion; therefore, the data obtained by these sensors could be processed using a newly developed graphic application software for smartphones and also identified by the naked eye. This method offered an easy and cost-effective solution for verifying the corrosion state of structural components.

Plant NADPH-dependent thioredoxin reductases are crucial for the metabolism of sink leaves and plant acclimation to elevated CO2.

Plants contain three NADPH-thioredoxin reductases (NTR) located in the cytosol/mitochondria (NTRA/B) and the plastid (NTRC) with important metabolic functions. However, mutants deficient in all NTRs remained to be investigated. Here, we generated and characterised the triple Arabidopsis ntrabc mutant alongside with ntrc single and ntrab double mutants under different environmental conditions. Both ntrc and ntrabc mutants showed reduced growth and substantial metabolic alterations, especially in sink leaves and under high CO2 (HC), as compared to the wild type. However, ntrabc showed higher effective quantum yield of PSII under both constant and fluctuating light conditions, altered redox states of NADH/NAD+ and glutathione (GSH/GSSG) and lower potential quantum yield of PSII in sink leaves in ambient but not high CO2 concentrations, as compared to ntrc, suggesting a functional interaction between chloroplastic and extra-chloroplastic NTRs in photosynthesis regulation depending on leaf development and environmental conditions. Our results unveil a previously unknown role of the NTR system in regulating sink leaf metabolism and plant acclimation to HC, while it is not affecting full plant development, indicating that the lack of the NTR system can be compensated, at least to some extent, by other redox mechanisms.

Deformation prediction of functionally graded materials in laser directional energy deposition using forward-inverse calibration of the inherent strain in multi-scanning directions.

This paper presents the study of the residual deformation of functional gradient materials (FGMs) constructed by laser directed energy deposition (L-DED) and proposes a forward and reverse framework for inherent strain calibration, considering the effect of scan directions. First, the inherent strain and the corresponding residual deformation in the scanning strategies with the 0°, 45°, and 90° directions are calculated from the multi-scale model of the forward process, respectively. Then the inherent strain is calibrated inversely using the pattern search method based on the residual deformation of experiments by L-DED. The final inherent strain calibrated in the direction of 0° can be achieved through the rotation matrix and averaging. Finally, the final calibrated inherent strain is applied to the model of the rotational scanning strategy. The predicted trend of the residual deformation is highly consistent with the experiments in the verification stage. This work can provide a reference for the prediction of the residual deformation of FGMs.

Chiro-optical fields with asymmetric orbital angular momentum and polarization.

In this paper, we proposed a flexible method for generating asymmetric chiro-optical fields. Different from most of the chiro-optical fields superimposed by vortex beams which are rotationally symmetric, the asymmetric chiro-optical field has a locally controllable orbital angular momentum (OAM) and polarization state. By using a helix phase plate (HPP) calculated based on coordinates transformation of the perfect vortex, the OAM controllability of a single chiro-optical field could be achieved. Then, by using the transformation matrix method, several discrete chiro-optical fields with different rotation angles and topological charges were stitched together as a multi-lobed chiro-optical field with asymmetric OAM on each side-lobe. Furthermore, we designed two HPPs that can be loaded into two spatial light modulators to modulate the polarization state of each side-lobe of the asymmetric chiro-optical field independently. The proposed asymmetric chiro-optical field breaks the characteristics of uniform OAM and polarization distribution of conventional chiro-optical fields, which may have potential applications in optical tweezers, communications, and enantiomer-selective sensing.

Staging Liver Fibrosis: Comparison of Native T1 Mapping, T2 Mapping, and T1ρ: An Experimental Study in Rats With Bile Duct Ligation and Carbon Tetrachloride at 11.7 T MRI.

BACKGROUND: T1, T2, and T1ρ might be potential biomarkers for assessing liver fibrosis. However, few studies reported the value of them in different animal models. PURPOSE: To investigate and compare the performances of T1, T2, and T1ρ for noninvasively staging liver fibrosis in bile duct ligation (BDL) or carbon tetrachloride (CCl4 ) model. STUDY TYPE: Prospective animal model. SUBJECTS: Liver fibrosis was induced by BDL or injection of CCl4 in 120 rats. FIELD STRENGTH/SEQUENCE: 11.7 T, T1 mapping with 10 repetition times, T2 mapping with 32 echo times, and T1ρ with 10 spin-lock times. ASSESSMENT: T1, T2, and T1ρ were measured and correlated with liver fibrosis stages, as well as the degree of inflammation, steatosis, iron deposition, and the expression of cytokeratin 19. The discriminative performance of T1, T2, and T1ρ for staging liver fibrosis was compared. STATISTICAL TESTS: One-way analysis of variance (ANOVA), Spearman's correlation analysis, factorial design ANOVA, and receiver operating characteristic curves (P < 0.05 was considered statistically significant). RESULTS: T1, T2, and T1ρ (BDL: rho = 0.73, 0.85, 0.68; CCl4 : rho = 0.80, 0.29, 0.61) were significantly correlated with liver fibrosis stages, while there was no significant difference in T2 among stage F0-F4 in the CCl4 model (P = 0.204). The area under the curves (AUCs) range of T1, T2, and T1ρ for predicting ≥F1, ≥F2, ≥F3, and F4 were 0.76-0.95, 0.89-0.98, and 0.80-0.94 in the CCl4 model. For the CCl4 model, the AUCs range of T1, T2, and T1ρ for predicting ≥F1, ≥F2, ≥F3, and F4 were 0.83-0.95, 0.61-0.74, and 0.73-0.89, respectively. T2 had significantly higher AUC in the BDL model than CCl4 model for diagnosing liver fibrosis. DATA CONCLUSION: The most sensitive and accurate method for staging liver fibrosis appeared to be T1 in our animal models followed by T1ρ. T2 may not be suitable for evaluating liver fibrosis. LEVEL OF EVIDENCE: 1 TECHNICAL EFFICACY STAGE: 2.

3D Measurement Method for Saturated Highlight Characteristics on Surface of Fuel Nozzle.

Saturated highlights on metal surfaces reduce the detection accuracy of fuel nozzles. In this paper, we propose an image inpainting method with a saturated highlight based on the statistics of similar patches used in prior segmentation of the subregion. The sequence image acquisition is based on the shape from focus in the five-axis platform. By our method, the focus measure (FM) operator and the window size are evaluated using the sharpness evaluation curve and calculating time. We observe that the detection accuracy is improved when the highlight area is filled by the highlight-free area within the same segmentation region. There are fewer deviation points in the three-dimensional (3D) point cloud that are extracted from the sequence images. The inlet circle and the outlet circle of the fuel nozzle are both detected by the two-dimensional (2D) Hough Transform (HT) method. Our experiments show that the method yields better results in 3D detection of the key parameters of fuel nozzles with the saturated highlight characteristics.

Modeling and Verification of an Acquisition Strategy for Wheel Loader's Working Trajectories and Resistance.

To overcome the difficulty of collecting the working resistance and working trajectory of a wheel loader, this paper constructs a statics model of the bucket working resistance and a kinematics model of the working trajectory in the shoveling process and analyzes the key parameters of measuring the working resistance and working trajectory. Based on this, a working resistance and working trajectory acquisition strategy is proposed. To verify the effectiveness of the acquisition strategy, the in-service operation data of fine sand and loose soil shoveled by the wheel loader are collected and analyzed. Then, the test-fitted working resistance and working trajectory are obtained, and the working trajectory is input into the RecurDyn-EDEM co-simulation model to obtain the simulation-fitted working resistance. Considering the complex working conditions of the wheel loader, it is difficult to obtain accurate working resistance, and the actual working resistance is also a relative value. Therefore, a strong correlation between the two curves indicates that the acquisition strategy of the wheel loader's working trajectory and working resistance proposed in this paper is feasible.

Multi-Object Detection Method in Construction Machinery Swarm Operations Based on the Improved YOLOv4 Model.

To handle the problem of low detection accuracy and missed detection caused by dense detection objects, overlapping, and occlusions in the scenario of complex construction machinery swarm operations, this paper proposes a multi-object detection method based on the improved YOLOv4 model. Firstly, the K-means algorithm is used to initialize the anchor boxes to improve the learning efficiency of the depth features of construction machinery objects. Then, the pooling operation is replaced with dilated convolution to solve the problem that the pooling layer reduces the resolution of feature maps and causes a high missed detection rate. Finally, focus loss is introduced to optimize the loss function of YOLOv4 to improve the imbalance of positive and negative samples during the model training process. To verify the effectiveness of the above optimizations, the proposed method is verified on the Pytorch platform with a self-build dataset. The experimental results show that the mean average precision(mAP) of the improved YOLOv4 model for multi-object detection of construction machinery can reach 97.03%, which is 2.16% higher than that of the original YOLOv4 detection network. Meanwhile, the detection speed is 31.11 fps, and it is reduced by only 0.59 fps, still meeting the real-time requirements. The research lays a foundation for environment perception of construction machinery swarm operations and promotes the unmanned and intelligent development of construction machinery swarm operations.

An Improved Shape from Focus Method for Measurement of Three-Dimensional Features of Fuel Nozzles.

The precise three-dimensional measurement of fuel nozzles is of great significance to assess the manufacturing accuracy and improve the spray and atomization performance. This paper proposes an improved fast shape from focus (SFF) method for three-dimensional measurement of key features of fuel nozzles. In order to ensure the measurement accuracy and efficiency of the SFF, the dispersion of the measured points from a standard flat plane was used to select the optimal combination of the focus measure operator, window size and sampling step size. In addition, an approximate method for the focus measure interval is proposed to improve the measurement efficiency, which uses the peak region of the central pixel to replace the peak region of other pixels. The results show that the proposed method decreased the average computation time of the focus measure by 79.19% for the cone section and by 38.30% for the swirl slot. Compared with a reference laser scanning microscope, the measurement error in length is within 10 µm and the error in angle is within a maximum 0.15°.

CT radiomics facilitates more accurate diagnosis of COVID-19 pneumonia: compared with CO-RADS.

BACKGROUND: Limited data was available for rapid and accurate detection of COVID-19 using CT-based machine learning model. This study aimed to investigate the value of chest CT radiomics for diagnosing COVID-19 pneumonia compared with clinical model and COVID-19 reporting and data system (CO-RADS), and develop an open-source diagnostic tool with the constructed radiomics model. METHODS: This study enrolled 115 laboratory-confirmed COVID-19 and 435 non-COVID-19 pneumonia patients (training dataset, n = 379; validation dataset, n = 131; testing dataset, n = 40). Key radiomics features extracted from chest CT images were selected to build a radiomics signature using least absolute shrinkage and selection operator (LASSO) regression. Clinical and clinico-radiomics combined models were constructed. The combined model was further validated in the viral pneumonia cohort, and compared with performance of two radiologists using CO-RADS. The diagnostic performance was assessed by receiver operating characteristics curve (ROC) analysis, calibration curve, and decision curve analysis (DCA). RESULTS: Eight radiomics features and 5 clinical variables were selected to construct the combined radiomics model, which outperformed the clinical model in diagnosing COVID-19 pneumonia with an area under the ROC (AUC) of 0.98 and good calibration in the validation cohort. The combined model also performed better in distinguishing COVID-19 from other viral pneumonia with an AUC of 0.93 compared with 0.75 (P = 0.03) for clinical model, and 0.69 (P = 0.008) or 0.82 (P = 0.15) for two trained radiologists using CO-RADS. The sensitivity and specificity of the combined model can be achieved to 0.85 and 0.90. The DCA confirmed the clinical utility of the combined model. An easy-to-use open-source diagnostic tool was developed using the combined model. CONCLUSIONS: The combined radiomics model outperformed clinical model and CO-RADS for diagnosing COVID-19 pneumonia, which can facilitate more rapid and accurate detection.

[Proposal of Living Evidence-based Guideline for Combination of Traditional Chinese and Western Medicine for Treatment of COVID-19].

In order to standardize the clinical diagnosis and treatment decision-making with traditional Chinese medicine for pa-tients of coronavirus disease 2019(COVID-19) and put the latest clinical study evidence into clinical practice, the international trust-worthy traditional Chinese medicine recommendations( TCM Recs) working group started the compilation of Living Evidence-based Guideline for Combination of Traditional Chinese and Western Medicine for Treatment of COVID-19 on the basis of the standards and re-quirements of WHO handbook, GRADE and RIGHT. This proposal mainly introduces the formulation methods and processes of the living guidelines in details, such as the composition of the working group, the collection and identification of clinical issues and out-comes, the production of the living systematic review and the consensus of recommendations. The guidelines will continue to monitor the clinical study evidences of TCM in the prevention and treatment of COVID-19, and conduct regular evidence updating, retrieval and screening. When there is new study evidence, the steering committee will evaluate the possibility of the evidence to change clinical practice or previous recommendations, so as to decide whether the recommendations for the guidelines shall be implemented or upda-ted. The main criteria considered in the guideline updating are as follows:(1) There are new high-quality randomized controlled trial(RCT) evidences for TCM uninvolved in the previous edition of the guidelines;(2) as for the TCM involved in the guidelines, living sys-tematic review shows that new evidence may change the direction or strength of the existing recommendations. The specific implementation of the living evidence-based guidelines will take this proposal as the study basis and framework, in order to ensure the standardization of the formulation process and methods. This will be the first exploration of the methodology for living guidelines in the field of TCM.

NTRC Plays a Crucial Role in Starch Metabolism, Redox Balance, and Tomato Fruit Growth.

NADPH-thioredoxin reductase C (NTRC) forms a separate thiol-reduction cascade in plastids, combining both NADPH-thioredoxin reductase and thioredoxin activities on a single polypeptide. While NTRC is an important regulator of photosynthetic processes in leaves, its function in heterotrophic tissues remains unclear. Here, we focus on the role of NTRC in developing tomato (Solanum lycopersicum) fruits representing heterotrophic storage organs important for agriculture and human diet. We used a fruit-specific promoter to decrease NTRC expression by RNA interference in developing tomato fruits by 60% to 80% compared to the wild type. This led to a decrease in fruit growth, resulting in smaller and lighter fully ripe fruits containing less dry matter and more water. In immature fruits, NTRC downregulation decreased transient starch accumulation, which led to a subsequent decrease in soluble sugars in ripe fruits. The inhibition of starch synthesis was associated with a decrease in the redox-activation state of ADP-Glc pyrophosphorylase and soluble starch synthase, which catalyze the first committed and final polymerizing steps, respectively, of starch biosynthesis. This was accompanied by a decrease in the level of ADP-Glc. NTRC downregulation also led to a strong increase in the reductive states of NAD(H) and NADP(H) redox systems. Metabolite profiling of NTRC-RNA interference lines revealed increased organic and amino acid levels, but reduced sugar levels, implying that NTRC regulates the osmotic balance of developing fruits. These results indicate that NTRC acts as a central hub in regulating carbon metabolism and redox balance in heterotrophic tomato fruits, affecting fruit development as well as final fruit size and quality.

Thioredoxin h2 contributes to the redox regulation of mitochondrial photorespiratory metabolism.

Thioredoxins (TRXs) are important proteins involved in redox regulation of metabolism. In plants, it has been shown that the mitochondrial metabolism is regulated by the mitochondrial TRX system. However, the functional significance of TRX h2, which is found at both cytosol and mitochondria, remains unclear. Arabidopsis plants lacking TRX h2 showed delayed seed germination and reduced respiration alongside impaired stomatal and mesophyll conductance, without impacting photosynthesis under ambient O2 conditions. However, an increase in the stoichiometry of photorespiratory CO2 release was found during O2 -dependent gas exchange measurements in trxh2 mutants. Metabolite profiling of trxh2 leaves revealed alterations in key metabolites of photorespiration and in several metabolites involved in respiration and amino acid metabolism. Decreased abundance of serine hydroxymethyltransferase and glycine decarboxylase (GDC) H and L subunits as well as reduced NADH/NAD+ ratios were also observed in trxh2 mutants. We further demonstrated that the redox status of GDC-L is altered in trxh2 mutants in vivo and that recombinant TRX h2 can deactivate GDC-L in vitro, indicating that this protein is redox regulated by the TRX system. Collectively, our results demonstrate that TRX h2 plays an important role in the redox regulation of mitochondrial photorespiratory metabolism.

Preoperative sarcopenia is a predictor of poor prognosis of esophageal cancer after esophagectomy: a comprehensive systematic review and meta-analysis.

The impact of preoperative sarcopenia on long-term survival of esophageal cancer patients after esophagectomy remains unclear. We conducted an updated meta-analysis focusing on current topic comprehensively. We systematically searched relevant studies investigating the impact of preoperative sarcopenia on survival of patients with surgically treated esophageal cancer in PubMed, Embase, and Web of Science up to July 20, 2018. Data of 3-year and 5-year overall survival (OS) rates as well as hazard ratio (HR) of OS and disease-free survival (DFS) were collected for analysis by using the STATA 12.0 package. Finally, a total of 11 cohort studies consisting of 1520 patients (795 sarcopenic patients and 725 nonsarcopenic patients) were included for analysis. Our meta-analysis showed that patients with sarcopenia had a significantly lower 3-year (51.6% vs. 65.4%, P < 0.001) and 5-year OS rate (41.2% vs. 52.2%, P = 0.018) than those without sarcopenia. Sarcopenia was found to be an independent predictor of poor OS (HR = 1.58; 95% confidence interval (CI) = [1.35, 1.85]; P < 0.001) and DFS (HR = 1.46; 95% CI = [1.12, 1.90]; P = 0.005) in esophageal cancer patients after esophagectomy. No obvious heterogeneities or publication bias were observed during analysis. Therefore, patients with sarcopenia had a significantly worse prognosis than those without after surgical resection of esophageal cancer. Preoperative sarcopenia is an independent unfavorable prognostic factor for esophageal cancer patients after esophagectomy. However, high-quality studies with appropriate adjustments for confounding factors are needed to confirm our conclusions.

Micro-analysis model for material removal mechanisms of bonnet polishing.

There have been many researches concerning the modeling for material removal mechanisms of bonnet polishing (BP) based on the well-known Preston model. However, various parameters involved in the BP process are not formulated and considered in the classical model, such as slurry characteristics, pad properties, bonnet features, and processing conditions. In this paper, a micro-analysis model capturing those parameters is proposed based on the mutual interaction of the slurry, pad, and workpiece among the BP interfaces with the micro-contact theory and the tribology theory. The proposed model is validated by comparison with the experimental data, and good agreement can be obtained. According to the analysis of key parameters, the proposed model is capable of providing some insight into the material removal mechanisms of BP, and even those cannot be explained properly by the classical Preston model.