Profiling of RNA editing events in plant organellar transcriptomes with high-throughput sequencing.

RNA editing is a crucial post-transcriptional modification process in plant organellar RNA metabolism. rRNA removal-based total RNA-seq is one of the most common methods to study this event. However, the lack of commercial kits to remove rRNAs limits the usage of this method, especially for non-model plant species. DSN-seq is a transcriptome sequencing method utilizing duplex-specific nuclease (DSN) to degrade highly abundant cDNA species especially those from rRNAs while keeping the robustness of transcript levels of the majority of other mRNAs, and has not been applied to study RNA editing in plants before. In this study, we evaluated the capability of DSN-seq to reduce rRNA content and profile organellar RNA editing events in plants, as well we used commercial Ribo-off-seq and standard mRNA-seq as comparisons. Our results demonstrated that DSN-seq efficiently reduced rRNA content and enriched organellar transcriptomes in rice. With high sensitivity to RNA editing events, DSN-seq and Ribo-off-seq provided a more complete and accurate RNA editing profile of rice, which was further validated by Sanger sequencing. Furthermore, DSN-seq also demonstrated efficient organellar transcriptome enrichment and high sensitivity for profiling RNA editing events in Arabidopsis thaliana. Our study highlights the capability of rRNA removal-based total RNA-seq for profiling RNA editing events in plant organellar transcriptomes and also suggests DSN-seq as a widely accessible RNA editing profiling method for various plant species.

Machine learning-based decision support model for selecting intra-arterial therapies for unresectable hepatocellular carcinoma: A national real-world evidence-based study.

IMPORTANCE: Intra-arterial therapies(IATs) are promising options for unresectable hepatocellular carcinoma(HCC). Stratifying the prognostic risk before administering IAT is important for clinical decision-making and for designing future clinical trials. OBJECTIVE: To develop and validate a machine learning(ML)-based decision support model(MLDSM) for recommending IAT modalities for unresectable HCC. DESIGN, SETTING, AND PARTICIPANTS: Between October 2014 and October 2022, a total of 2,959 patients with HCC who underwent initial IATs were enroled retrospectively from 13 tertiary hospitals. These patients were divided into the training cohort (n = 1700), validation cohort (n = 428), and test cohort (n = 200). MAIN OUTCOMES AND MEASURES: Thirty-two clinical variables were input, and five supervised ML algorithms, including eXtreme Gradient Boosting (XGBoost), Categorical Gradient Boosting (CatBoost), Gradient Boosting Decision Tree (GBDT), Light Gradient Boosting Machine (LGBM) and Random Forest (RF), were compared using the areas under the receiver operating characteristic curve (AUC) with the DeLong test. RESULTS: A total of 1856 patients were assigned to the IAT alone Group(I-A), and 1103 patients were assigned to the IAT combination Group(I-C). The 12-month death rates were 31.9% (352/1103) in the I-A group and 50.4% (936/1856) in the I-C group. For the test cohort, in the I-C group, the CatBoost model achieved the best discrimination when 30 variables were input, with an AUC of 0.776 (95% confidence intervals [CI], 0.833-0.868). In the I-A group, the LGBM model achieved the best discrimination when 24 variables were input, with an AUC of 0.776 (95% CI, 0.833-0.868). According to the decision trees, BCLC grade, local therapy, and diameter as top three variables were used to guide clinical decisions between IAT modalities. CONCLUSIONS AND RELEVANCE: The MLDSM can accurately stratify prognostic risk for HCC patients who received IATs, thus helping physicians to make decisions about IAT and providing guidance for surveillance strategies in clinical practice.

Improvement of the Thermoelectric Properties of p-Type Mg3Sb2 by Mg-Site Double Substitution.

A P-type Mg3Sb2-based Zintl phase compound has been considered a promising candidate for thermoelectric applications. Alloying, which introduces a high concentration of point defects, is particularly effective in scattering phonons and reducing lattice thermal conductivity. Herein, alloying in p-type Mg2.995Na0.005Sb2 via the introduction of elements like Yb, Eu, Ca, and Ba was realized, and the room-temperature lattice thermal conductivity has been effectively reduced to ∼1.1 W m-1 K-1. To further intensify the phonon scattering, two groups of elements (Eu and Cd, and Yb and Cd) were chosen for heavy alloying at the Mg site, and the lattice thermal conductivity of Mg1.49Eu0.5Cd1Na0.01Sb2 was further reduced to ∼0.45 W m-1 K-1. Eventually, a peak zT as high as ∼1.0 was achieved at 773 K, and the compound outperforms the previously reported p-type Mg3Sb2 compounds.

Development and evaluation of machine learning models for predicting large-for-gestational-age newborns in women exposed to radiation prior to pregnancy.

INTRODUCTION: The correlation between radiation exposure before pregnancy and abnormal birth weight has been previously proven. However, for large-for-gestational-age (LGA) babies in women exposed to radiation before becoming pregnant, there is no prediction model yet. MATERIAL AND METHODS: The data were collected from the National Free Preconception Health Examination Project in China. A sum of 455 neonates (42 SGA births and 423 non-LGA births) were included. A training set (n = 319) and a test set (n = 136) were created from the dataset at random. To develop prediction models for LGA neonates, conventional logistic regression (LR) method and six machine learning methods were used in this study. Recursive feature elimination approach was performed by choosing 10 features which made a big contribution to the prediction models. And the Shapley Additive Explanation model was applied to interpret the most important characteristics that affected forecast outputs. RESULTS: The random forest (RF) model had the highest average area under the receiver-operating-characteristic curve (AUC) for predicting LGA in the test set (0.843, 95% confidence interval [CI]: 0.714-0.974). Except for the logistic regression model (AUC: 0.603, 95%CI: 0.440-0.767), other models' AUCs displayed well. Thereinto, the RF algorithm's final prediction model using 10 characteristics achieved an average AUC of 0.821 (95% CI: 0.693-0.949). CONCLUSION: The prediction model based on machine learning might be a promising tool for the prenatal prediction of LGA births in women with radiation exposure before pregnancy.

Swimming ability of Schizothoracinae fishes in Yarlung Zangbo River of China.

The Yarlung Zangbo River is a river with abundant hydropower resources but fragile biodiversity in China. As an important benchmark for both research and ecological management, there is still a lack of knowledge about the swimming ability of fishes in the Yarlung Zangbo River. The induced flow velocity (Uind), critical swimming speed (Ucrit), and burst swimming speed (Uburst) of five Schizothoracinae species were tested in this study. Relative swimming ability related to body length and body shape was calculated. The results indicated that the average absolute swimming speeds (Uind-a, Ucrit-a, and Uburst-a) of all the experimental fish were 10.20 ± 0.01, 57.58 ± 3.28, and 69.54 ± 2.94 cm/s, respectively, and the corresponding relative Uind, Ucrit, and Uburst related to body length (Uind-l, Ucrit-l, Uburst-l) were 1.15 ± 0.07, 5.04 ± 0.26, and 7.23 ± 0.28 BL/s, respectively. Moreover, relative Uind, Ucrit, and Uburst related to body shape (Uind-s, Ucrit-s, and Uburst-s) were 0.80 ± 0.13, 2.49 ± 0.51, and 4.32 ± 0.57 cm-2/s, respectively. No significantly differences in relative swimming speeds existed among five species. Only Oxygymnocypris stewartii was significantly weaker in Uburst-s than Schizothorax o'connori. The body shape showed a stronger relationship with swimming speed than the body length did. Schizothoracinae fish in the Yarlung Zangbo River basin are less sensitive to the water flow and performed weaker Ucrit and Uburst compared to those in the Yangtze River basin, indicating that Schizothoracinae fish in the Yarlung Zangbo River may be more susceptible to threats from environmental changes. The paper enriched the research on the swimming ability of Schizothoracinae fishes and provided efficient data for the fish conservation in the Yarlung Zangbo River.

Exploring the Association between Low-dose Aspirin Intake and Hyperuricemia in Individuals over 40: A Cross-Sectional Study using NHANES Data (2011-2018).

BACKGROUND Long-term aspirin treatment was recommended for secondary prevention of cardiovascular and cerebrovascular disease. However, some studies reveal low-dose aspirin (LDA) can raise serum uric acid (SUA) levels. Thus, the purpose of this study was to analyze whether LDA intake is associated with hyperuricemia. MATERIAL AND METHODS Data was collected from the National Health and Nutrition Examination Survey (NHANES) between 2011 and 2018. All participants over 40 years old and who selected "preventive aspirin use" were included in the study. Logistic regression analyses were used to evaluate the relationship between LDA intake and hyperuricemia. The stratified analysis was based on race and estimated glomerular filtration rate (eGFR). RESULTS A total of 3540 participants were included in the study. Of them, 805 (22.7%) took LDA, and 190 (31.6%) had hyperuricemia. There was no significant association between hyperuricemia and LDA intake (OR=1.22, 95% CI: 0.97-1.54) after adjusting for confounding factors. However, further subgroup analysis by age showed a significant association between LDA intake and hyperuricemia (OR=3.44, 95% CI: 1.88-6.27) among those 40 to 50 years of age. After adjusting for confounding factors, the relationship was still significant (OR=2.28, 95% CI: 1.10-4.73); we also found that race (Hispanic American, OR=1.84, 95% CI: 1.11-3.06) and eGFR under 60 mL/min/1.73 m² (OR=1.94, 95% CI: 1.04-3.62) may play important roles in the development of hyperuricemia. CONCLUSIONS LDA does not increase the hyperuricemia risk in people over 40 years. However, those aged between 40 and 50 years, Hispanic American, and with impaired renal function should have careful evaluation during LDA treatment.

Genome-Wide Identification, Expansion Mechanism and Expression Profiling Analysis of GLABROUS1 Enhancer-Binding Protein (GeBP) Gene Family in Gramineae Crops.

The GLABROUS1 enhancer-binding protein (GeBP) gene family encodes a typical transcription factor containing a noncanonical Leucine (Leu-)-zipper motif that plays an essential role in regulating plant growth and development, as well as responding to various stresses. However, limited information on the GeBP gene family is available in the case of the Gramineae crops. Here, 125 GeBP genes from nine Gramineae crops species were phylogenetically classified into four clades using bioinformatics analysis. Evolutionary analyses showed that whole genome duplication (WGD) and segmental duplication play important roles in the expansion of the GeBP gene family. The various gene structures and protein motifs revealed that the GeBP genes play diverse functions in plants. In addition, the expression profile analysis of the GeBP genes showed that 13 genes expressed in all tested organs and stages of development in rice, with especially high levels of expression in the leaf, palea, and lemma. Furthermore, the hormone- and metal-induced expression patterns showed that the expression levels of most genes were affected by various biotic stresses, implying that the GeBP genes had an important function in response to various biotic stresses. Furthermore, we confirmed that OsGeBP11 and OsGeBP12 were localized to the nucleus through transient expression in the rice protoplast, indicating that GeBPs function as transcription factors to regulate the expression of downstream genes. This study provides a comprehensive understanding of the origin and evolutionary history of the GeBP genes family in Gramineae, and will be helpful in a further functional characterization of the GeBP genes.

Long noncoding RNA CDKN2B-AS1 interacts with transcription factor BCL11A to regulate progression of cerebral infarction through mediating MAP4K1 transcription.

The effective therapeutic approach of cerebral infarction is limited because of its underlying complexity. Recently, multiple long noncoding RNAs (lncRNAs) have been identified in the pathogenesis of cerebral infarction. Here, the current study aims to explore the interaction among lncRNA cyclin-dependent kinase inhibitor-2B-antisense RNA 1 (CDKN2B-AS1), transcription factor B-cell lymphoma/leukemia 11A (BCL11A), and MAPKK kinase kinase 1 (MAP4K1) and further investigate whether they affect cerebral infarction progression. The expression of CDKN2B-AS1, BCL11A, and MAP4K1 was altered in lymphocytes extracted from patients with cerebral infarction. In order to identify their roles in regulatory T (Treg) cells, the proliferation and apoptosis of the CD4+CD25+ Treg cells were examined, and levels of IL-4, IL-10, and TGF-ß were determined. Also, the RNA crosstalk among CDKN2B-AS1, BCL11A, and MAP4K1 was validated. Finally, we established a rat model of middle cerebral arterial occlusion to evaluate the neurologic impairment and cerebral infarction volume. The results revealed that lymphocytes in patients with cerebral infarction presented with the up-regulated expression of CDKN2B-AS1. Moreover, BCL11A could specifically bind to CDKN2B-AS1 and MAP4K1 promoter so as to inhibit MAP4K1. Moreover, it was observed that down-regulated CDKN2B-AS1 inhibited CD4+CD25+ Treg-cell proliferation, reduced levels of IL-4, IL-10, and TGF-ß and cerebral infarction volume, and elevated MAP4K1 expression. Collectively, our study provides evidence that CDKN2B-AS1 silencing could increase MAP4K1 expression to inhibit the CD4+CD25+ Treg-cell proliferation by reducing enrichment of transcription factor BCL11A, thereby protecting against cerebral infarction progression, highlighting a promising therapeutic strategy for treating cerebral infarction.-Lei, J.-J., Li, H.-Q., Mo, Z.-H., Liu, K.-J., Zhu, L.-J., Li, C.-Y., Chen, W.-L., Zhang, L. Long noncoding RNA CDKN2B-AS1 interacts with transcription factor BCL11A to regulate progression of cerebral infarction through mediating MAP4K1 transcription.

Assessment of prevalence and risk factors of helicobacter pylori infection in an oilfield Community in Hebei, China.

BACKGROUND: Only a paucity of large-scale perspective and cross-sectional studies on H. pylori infection in China have been published. The purpose of this study was to investigate the prevalence and risk factors for H. pylori infection among residents of Jidong community located in Hebei Province of China. METHODS: A perspective, cross-sectional study was conducted in Jidong community. Questionnaires and 13C-urea breath test were performed, and 10-ml blood samples were obtained for laboratory tests. RESULTS: Four thousand seven hundred ninety-six subjects were enrolled in this study, and 2506 (52.25%) were H. pylori positive. There was no difference in prevalence between both sexes (P = 0.5974). Age (P = 0.004) and education level (P = 0.0128) were significantly associated with H. pylori infection, and there were statistical trends in the prevalence across five age subgroups (χ2 test for trend = 23.5; P < 0.001) and education levels (χ2 test for trend = 19.50; P < 0.001). H. pylori infection was also associated with marital status (P = 0.0243), source of drinking water (P = 0.0433), frequency of eating raw garlic (P = 0.0310), alcohol drinking (P = 0.0207), knowledge about H. pylori transmission route (P = 0.0125) and related diseases (P = 0.0257). Age, alcohol drinking and knowledge about transmission route were found to be independent predictors of H. pylori infection. CONCLUSIONS: More than half of the population was infected with H. pylori in Jidong community. The socio-demographic profiles, socio-economic factors and lifestyle are worthy taking into consideration to prevent diseases associated with H. pylori infection. Understanding the prevalence and risk patterns for H. pylori infection in China will help in prioritizing public health efforts to better manage the H. pylori infection.

Large-scale in silico identification of drugs exerting sex-specific effects in the heart.

BACKGROUND: Major differences exist between men and women in both physiology and pathophysiology. Dissecting the underlying processes and contributing mechanisms of sex differences in health and disease represents a crucial step towards precision medicine. Considering the significant differences between men and women in the response to pharmacotherapies, our aim was to develop an in silico model able to predict sex-specific drug responses in a large-scale. METHODS: For this purpose, we focused on cardiovascular effects because of their high morbidity and mortality. Our model predicted several drugs (including acebutolol and tacrine) with significant differences in the heart between men and women. To validate the sex-specific drug responses identified by our model, acebutolol was selected to lower blood pressure in spontaneous hypertensive rats (SHR), tacrine was used to assess cardiac injury in mice and metformin as control for a non-sex-specific response. RESULTS: As our model predicted, acebutolol exhibited a stronger decrease in heart rate and blood pressure in female than male SHRs. Tacrine lowered heart rate in male but not in female mice, induced higher plasma cTNI level and increased cardiac superoxide (DHE staining) generation in female than male mice, indicating stronger cardiac toxicity in female than male mice. To validate our model in humans, we employed two Chinese cohorts, which showed that among patients taking a beta-receptor blocker (metoprolol), women reached significantly lower diastolic blood pressure than men. CONCLUSIONS: We conclude that our in silico model could be translated into clinical practice to predict sex-specific drug responses, thereby contributing towards a more appropriate medical care for both men and women.

China Medical Team: Medical rescue for "4.25" Nepal earthquake.

In recent years, global natural disasters have been frequent and resulted in great casualties and property loss. Since Wenchuan earthquake, the disaster emergency rescue system of China has obtained considerable development in various aspects including team construction, task scheduling, personnel training, facilities and equipments, logistics, etc. On April 25, 2015, an earthquake that measured 8.1 on the Richter scale attacked Nepal. Chinese government firstly organized a medical team, named China Medical Team, and sent it to the attacked region in Nepal to implement medical rescue. The medical team completed the rescue mission successfully and creatively based on their experiences.

Thermoelectric Performance Enhancement in SnS Polycrystals Owing to Hole Doping Combined with Textured Microstructures.

Recently, the earth-abundant tin sulfide (SnS) has emerged as a promising thermoelectric material due to its phonon and electron structure similar to that of tin selenide (SnSe). However, compared with SnSe, limited progress has been achieved in the thermoelectric property enhancement of SnS. Textured SnS polycrystals with an enhanced thermoelectric performance have been developed in this work. The high carrier mobility benefited from the enhanced texture through the repressing strategy of spark plasma sintering, improving the electrical conductivity. In addition, Sn atom deficiencies in the texture sample led to an increased hole concentration, further boosting the electrical conductivity and power factor. The power factor exceeded 4.10 µW/cm·K2 at 423 K and 5.50 µW/cm·K2 at 850 K. The phonon scattering was strengthened by adjusting the multiscale microstructures including dislocations, defect clusters, etc., leading to an ultralow lattice thermal conductivity of 0.23 W/m·K at 850 K. A figure of merit zT > 1.3 at 850 K and an average zTave of 0.58 in the temperature range 373-850 K were achieved in the SnS polycrystal.

APOE ε4 allele status modulates the spatial patterns of progressive atrophy in the temporal lobes after mild traumatic brain injury.

INTRODUCTION: We evaluated how the apolipoprotein E (APOE) ε4 allele modulated the spatial patterns of longitudinal atrophy in the Alzheimer's disease-vulnerable brain areas of patients with mild traumatic brain injury (mTBI) from the acute to chronic phase post injury. METHODS: Fifty-nine adult patients with acute mTBI and 48 healthy controls with APOE ε4 allele testing underwent T1-weighted magnetic resonance imaging and neuropsychological assessments with 6 to 12 months of follow-up. Progressive brain volume loss was compared voxel-wise in the temporal lobes. RESULTS: Patients with the APOE ε4 allele presented significant longitudinal atrophy in the left superior and middle temporal gyri, where the progressive gray matter volume loss predicted longitudinal impairment in language fluency, whereas mTBI APOE ε4 allele noncarriers showed mainly significant longitudinal atrophy in the medial temporal lobes, without significant neuropsychological relevance. DISCUSSION: The atrophy progression observed in mTBI patients with the APOE ε4 allele may increase the possibility of developing a specific phenotype of Alzheimer's disease with language dysfunction. Highlights: The apolipoprotein E (APOE) ε4 allele and mild traumatic brain injury (mTBI) are risk factors for Alzheimer's disease (AD) progression.It is unclear how the interaction of mTBI with the APOE ε4 allele impacts the progressive atrophy topography in AD-vulnerable brain regions.In this study, patients with the APOE ε4 allele showed progressive atrophy patterns similar to the early stage of logopenic variant of primary progressive aphasia (lvPPA) phenotype of AD. APOE ε4 allele carriers with mTBI history may be at the risk of developing a given AD phenotype with language dysfunction.

A Novel Machine Learning Model for Predicting Stroke-Associated Pneumonia After Spontaneous Intracerebral Hemorrhage.

BACKGROUND: Pneumonia is one of the most common complications after spontaneous intracerebral hemorrhage (sICH), i.e., stroke-associated pneumonia (SAP). Timely identification of targeted patients is beneficial to reduce poor prognosis. So far, there is no consensus on SAP prediction, and application of existing predictors is limited. The aim of this study was to develop a machine learning model to predict SAP after sICH. METHODS: We retrospectively reviewed 748 patients diagnosed with sICH and collected data from 4 dimensions-demographic features, clinical features, medical history, and laboratory tests. Five machine learning algorithms-logistic regression, gradient boosting decision tree, random forest, extreme gradient boosting, and category boosting-were used to build and validate the predictive model. We also applied recursive feature elimination with cross-validation to obtain the best feature combination for each model. Predictive performance was evaluated by area under the receiver operating characteristic curve. RESULTS: SAP was diagnosed in 237 patients. The model developed by category boosting yielded the most satisfactory outcomes overall with area under the receiver operating characteristic curves in the training set and test set of 0.8307 and 0.8178, respectively. CONCLUSIONS: The incidence of SAP after sICH in our center was 31.68%. Machine learning could potentially provide assistance in the prediction of SAP after sICH.

Intensified Phonon Scattering in ZrCoBi Half-Heusler by Noble Metals Doping.

ZrCoBi-based half-Heuslers have great potential in power generation applications because of their high thermoelectric performance in both p- and n-type constituents. In this work, n-type ZrCoBi with improved thermoelectric performance has been realized by intensifying the phonon scattering via noble metal doping, e.g., Pd and Pt doping. The carrier concentration was effectively tuned to the optimal range, and the lattice thermal conductivity was greatly suppressed via the strong strain field and mass fluctuation scattering brought about by the large difference in atomic size and mass between Pd or Pt and Co. Consequently, the state-of-art figure of merit zT ∼1 was achieved in Pd- or Pt-doped ZrCoBi. In addition, the average zTavg values for ZrCo0.95Pd0.05Bi and ZrCo0.925Pt0.075Bi have reached 0.58 and 0.51, respectively, which are higher than those of most of the reported n-type ZrCoBi-based and ZrCoSb-based half-Heusler alloys.

Terminally differentiated cytotoxic CD4+ T cells were clonally expanded in the brain lesion of radiation-induced brain injury.

BACKGROUND: Accumulating evidence supports the involvement of adaptive immunity in the development of radiation-induced brain injury (RIBI). Our previous work has emphasized the cytotoxic function of CD8+ T cells in RIBI. In this study, we aimed to investigate the presence and potential roles of cytotoxic CD4+ T cells (CD4+ CTLs) in RIBI to gain a more comprehensive understanding of adaptive immunity in this context. MAIN TEXT: Utilizing single-cell RNA sequencing (scRNA-seq), we analyzed 3934 CD4+ T cells from the brain lesions of four RIBI patients and identified six subclusters within this population. A notable subset, the cytotoxic CD4+ T cells (CD4+ CTLs), was marked with high expression of cytotoxicity-related genes (NKG7, GZMH, GNLY, FGFBP2, and GZMB) and several chemokine and chemokine receptors (CCL5, CX3CR1, and CCL4L2). Through in-depth pseudotime analysis, which simulates the development of CD4+ T cells, we observed that the CD4+ CTLs exhibited signatures of terminal differentiation. Their functions were enriched in protein serine/threonine kinase activity, GTPase regulator activity, phosphoprotein phosphatase activity, and cysteine-type endopeptidase activity involved in the apoptotic signaling pathway. Correspondingly, mice subjected to gamma knife irradiation on the brain showed a time-dependent infiltration of CD4+ T cells, an increase of MHCII+ cells, and the existence of CD4+ CTLs in lesions, along with an elevation of apoptotic-related proteins. Finally, and most crucially, single-cell T-cell receptor sequencing (scTCR-seq) analysis at the patient level determined a large clonal expansion of CD4+ CTLs in lesion tissues of RIBI. Transcriptional factor-encoding genes TBX21, RORB, and EOMES showed positive correlations with the cytotoxic functions of CD4+ T cells, suggesting their potential to distinguish RIBI-related CD4+ CTLs from other subsets. CONCLUSION: The present study enriches the understanding of the transcriptional landscape of adaptive immune cells in RIBI patients. It provides the first description of a clonally expanded CD4+ CTL subset in RIBI lesions, which may illuminate new mechanisms in the development of RIBI and offer potential biomarkers or therapeutic targets for the disease.

Effect of Cu2O morphology on photocatalytic hydrogen generation and chemical stability of TiO2/Cu2O composite.

Improving photocatalytic activity and stability of TiO2/Cu2O composite is a challenge in generating hydrogen from water. In this paper, the TiO2 film/Cu2O microgrid composite was prepared via a microsphere lithography technique, which possesses a remarkable performance of producing H2 under UV-vis light irradiation, in comparison with pure TiO2 film, Cu2O film and TiO2 film/Cu2O film. More interesting is that in TiO2 film/Cu2O microgrid, photo-corrosion of Cu2O can be retarded. After deposition of Pt on its surface, the photocatalytic activity of TiO2/Cu2O microgrid in producing H2 is improved greatly.

The Impact of Preservation Techniques on Methane-Arrested Anaerobic Digestion of Nutrient-Rich Feedstocks.

The carboxylate platform is a promising biomass-to-energy pathway that uses methane-arrested anaerobic digestion (MAAD) to convert biomass to carboxylic acids, which can be chemically converted to industrial chemicals and liquid fuels. Lignocellulose is an energy-rich carbon source, but lacks nutrients necessary for microbial growth. Chicken manure (rural waste) and sewage sludge (urban waste) are rich in nitrogen and useful macronutrients; therefore, co-digesting these wastes with lignocellulose improves MAAD performance. However, waste nutrients must be digested immediately, or preserved. This study investigated the effects of various preservation techniques - frozen (fresh), air-dried, and baked - on chicken manure and sewage sludge. Batch experiments were performed with office paper (carbon source) and chicken manure or sewage sludge (nutrient source) with different methods of preservation. Fresh substrates produced higher acid yields and biomass conversion (the amount of biomass consumed during digestion) than dried substrates. Baked chicken manure showed reduced conversion and total acid production, which suggests that oven-drying reduces digestibility. From the batch data, the Continuum Particle Distribution Model (CPDM) predicted results of a four-stage countercurrent digestion. The data are displayed on maps showing the impact of liquid residence time (LRT) and volatile solids loading rate (VSLR) on conversion and product concentration. Co-digesting office paper and wet chicken manure at a non-acid volatile solid (NAVS) concentration of 300 g/Lliq, the model predicted a high total acid concentration of 52.8 g/L and conversion of 0.89 g NAVSdigested/NAVSfed at a volatile solid loading rate of 4 g/(Lliq·day) and liquid retention time of 35 days.

Therapeutic effect and mechanism prediction of Fuzi-Gancao Herb couple on non-alcoholic fatty liver disease (NAFLD) based on network pharmacology and molecular docking.

BACKGROUND: Fuzi-Gancao herb couple is one of the most common herb couples involved in the TCM formula, which was used for the treatment of chronic diseases. The herb couple has a hepatoprotective effect. However, its main components and therapeutic mechanism are not yet clear. This study aims to elucidate the therapeutic effect and mechanism of the Fuzi-Gancao herb couple on NAFLD from animal experiments, network pharmacology, and molecular docking. METHODS: 60 Male C57BL/6 mice (20 g ± 2 g) were randomly divided into six groups including the blank group (n=10) and NALFD group (n=50). The mice of the NALFD group were fed with a high-fat diet for 20 weeks to establish the NAFLD model and the NALFD mice were randomly divided into five groups including positive group (berberine), model group and F-G groups with three dosages (0.257, 0.514, 0.771 g/kg) (n=10). After 10 weeks of administration, the serum was collected for the analysis of ALT, AST, LDL-c, HDL-c, and TC, and liver tissues were collected for pathological analysis. The TCMAS database was used to collect the main components and targets of the Fuzi-Gancao herb couple. The GeneCards database was used to collect NAFLD-related targets, and the key targets were obtained by intersecting with herbal targets. The disease-component-target relationship diagram was constructed by Cytoscape 3.9.1. The obtained key targets were imported into the String database to obtain the PPI network, and imported into the DAVID database for KEGG pathway analysis and GO analysis. Finally, the key targets and key gene proteins were imported into Discovery Studio 2019 for molecular docking verification. RESULTS: In this study, H-E staining indicated the pathological changes of liver tissue in Fuzi-Gancao groups were significantly improved, and the levels of AST, ALT, TC, HDL-c, and LDL-c in serum of Fuzi-Gancao groups decreased in a dose-dependent manner, compared with the model group. 103 active components and 299 targets in the Fuzi-Gancao herb couple were confirmed in the TCMSP database and 2062 disease targets in NAFLD were obtained. 142 key targets and 167 signal pathways were screened, such as the AGE-RAGE signaling pathway in diabetic complications, HIF-1 signaling pathway, IL-17 signaling pathway, TNF signaling pathway, and so on. The main bioactive ingredients of Fuzi-Gancao herb couple in the treatment of NAFLD are quercetin, kaempferol, naringenin, inermine, (R)-norcoclaurine, isorhamnetin, ignavine, 2,7-Dideacetyl-2,7-dibenzoyl-taxayunnanine F, glycyrol mainly involving IL6, AKT1, TNF, TP53, IL1B, VEGFA and other core targets. Molecular docking analysis indicated that there is a good affinity between the key components and the key targets. CONCLUSION: This study preliminarily explained the main components and mechanism of the Fuzi-Gancao herb couple in the treatment of NAFLD and provided an idea for subsequent research.

Mitochondrial SENP2 regulates the assembly of SDH complex under metabolic stress.

Succinate dehydrogenase (SDH) is a heterotetrameric enzyme complex belonging to the mitochondrial respiratory chain and uniquely links the tricarboxylic acid (TCA) cycle with oxidative phosphorylation. Cancer-related SDH mutations promote succinate accumulation, which is regarded as an oncometabolite. Post-translational modifications of SDH complex components are known to regulate SDH activity, although the contribution of SUMOylation remains unclear. Here, we show that SDHA is SUMOylated by PIAS3 and deSUMOylated by SENP2, events dictating the assembly and activity of the SDH complex. Moreover, CBP acetylation of SENP2 negatively regulates its deSUMOylation activity. Under glutamine deprivation, CBP levels decrease, and the ensuing SENP2 activation and SDHA deSUMOylation serve to concurrently dampen the TCA cycle and electron transport chain (ETC) activity. Along with succinate accumulation, this mechanism avoids excessive reactive oxygen species (ROS) production to promote cancer cell survival. This study elucidates a major function of mitochondrial-localized SENP2 and expands our understanding of the role of SUMOylation in resolving metabolic stress.