Formation of a Porous Crystalline Mg1-xAl2Oy Overlayer on Metal Catalysts via Controlled Solid-State Reactions for High-temperature Stable Catalysis.

Catalyst deactivation by sintering and coking is a long-standing issue in metal-catalyzed harsh high-temperature hydrocarbon reactions. Ultrathin oxide coatings of metal nanocatalysts have recently appeared attractive to address this issue, while the porosity of the overlayer is difficult to control to preserve the accessibility of embedded metal nanoparticles, thus often leading to a large decrease in activity. Here, we report that a nanometer-thick alumina coating of MgAl2O4-supported metal catalysts followed by high-temperature reduction can transform a nonporous amorphous alumina overlayer into a porous Mg1-xAl2Oy crystalline spinel structure with a pore size of 2-3 nm and weakened acidity. The high porosity stems from the restrained Mg migration from the MgAl2O4 support to the alumina overlayer through solid-state reactions at high temperatures. The resulting Ni/MgAl2O4 and Pt/MgAl2O4 catalysts with a porous crystalline Mg1-xAl2Oy overlayer achieved remarkably high stability while preserving much higher activity than the corresponding alumina-coated Ni and Pt catalysts on MgO and Al2O3 supports in the reactions of dry reforming of methane and propane dehydrogenation, respectively.

Dehydrogenation of Ammonia Borane by Platinum-Nickel Dimers: Regulation of Heteroatom Interspace Boosts Bifunctional Synergetic Catalysis.

Regulation of the atom-atom interspaces of dual-atom catalysts is essential to optimize the dual-atom synergy to achieve high activity but remains challenging. Herein, we report an effective strategy to regulate the Pt1 -Ni1 interspace to achieve Pt1 Ni1 dimers and Pt1 +Ni1 heteronuclear dual-single-atom catalysts (HDSACs) by tailoring steric hindrance between metal precursors during synthesis. Spectroscopic characterization reveals obvious electron transfers in Pt1 Ni1 oxo dimers but not in Pt1 +Ni1 HDSAC. In the hydrolysis of ammonia borane (AB), the H2 formation rates show an inverse proportion to the Pt1 -Ni1 interspace. The rate of Pt1 Ni1 dimers is ≈13 and 2 times higher than those of Pt1 and Pt1 +Ni1 HDSAC, manifesting the interspace-dependent synergy. Theoretical calculations reveal that the bridging OH group in Pt1 Ni1 dimers promotes water dissociation, while Pt1 facilitates the cleavage of B-H bonds in AB, which boosts a bifunctional synergy to accelerate H2 production cooperatively.

Factors Associated With Prolonged Viral Shedding in Patients With Avian Influenza A(H7N9) Virus Infection.

Background: Data are limited on the impact of neuraminidase inhibitor (NAI) treatment on avian influenza A(H7N9) virus RNA shedding. Methods: In this multicenter, retrospective study, data were collected from adults hospitalized with A(H7N9) infection during 2013-2017 in China. We compared clinical features and A(H7N9) shedding among patients with different NAI doses and combination therapies and evaluated factors associated with A(H7N9) shedding, using Cox proportional hazards regression. Results: Among 478 patients, the median age was 56 years, 71% were male, and 37% died. The median time from illness onset to NAI treatment initiation was 8 days (interquartile range [IQR], 6-10 days), and the median duration of A(H7N9) RNA detection from onset was 15.5 days (IQR, 12-20 days). A(H7N9) RNA shedding was shorter in survivors than in patients who died (P < .001). Corticosteroid administration (hazard ratio [HR], 0.62 [95% confidence interval {CI}, .50-.77]) and delayed NAI treatment (HR, 0.90 [95% CI, .91-.96]) were independent risk factors for prolonged A(H7N9) shedding. There was no significant difference in A(H7N9) shedding duration between NAI combination treatment and monotherapy (P = .65) or between standard-dose and double-dose oseltamivir treatment (P = .70). Conclusions: Corticosteroid therapy and delayed NAI treatment were associated with prolonged A(H7N9) RNA shedding. NAI combination therapy and double-dose oseltamivir treatment were not associated with a reduced A(H7N9) shedding duration as compared to standard-dose oseltamivir.

Understanding the Relationship Between Mood Symptoms and Mobile App Engagement Among Patients With Breast Cancer Using Machine Learning: Case Study.

BACKGROUND: Health interventions delivered via smart devices are increasingly being used to address mental health challenges associated with cancer treatment. Engagement with mobile interventions has been associated with treatment success; however, the relationship between mood and engagement among patients with cancer remains poorly understood. A reason for this is the lack of a data-driven process for analyzing mood and app engagement data for patients with cancer. OBJECTIVE: This study aimed to provide a step-by-step process for using app engagement metrics to predict continuously assessed mood outcomes in patients with breast cancer. METHODS: We described the steps involved in data preprocessing, feature extraction, and data modeling and prediction. We applied this process as a case study to data collected from patients with breast cancer who engaged with a mobile mental health app intervention (IntelliCare) over 7 weeks. We compared engagement patterns over time (eg, frequency and days of use) between participants with high and low anxiety and between participants with high and low depression. We then used a linear mixed model to identify significant effects and evaluate the performance of the random forest and XGBoost classifiers in predicting weekly mood from baseline affect and engagement features. RESULTS: We observed differences in engagement patterns between the participants with high and low levels of anxiety and depression. The linear mixed model results varied by the feature set; these results revealed weak effects for several features of engagement, including duration-based metrics and frequency. The accuracy of predicting depressed mood varied according to the feature set and classifier. The feature set containing survey features and overall app engagement features achieved the best performance (accuracy: 84.6%; precision: 82.5%; recall: 64.4%; F1 score: 67.8%) when used with a random forest classifier. CONCLUSIONS: The results from the case study support the feasibility and potential of our analytic process for understanding the relationship between app engagement and mood outcomes in patients with breast cancer. The ability to leverage both self-report and engagement features to analyze and predict mood during an intervention could be used to enhance decision-making for researchers and clinicians and assist in developing more personalized interventions for patients with breast cancer.

Acute myocardial necrosis caused by aconitine poisoning: A case report.

BACKGROUND: Herbal medicine has a long history of use in the prevention and treatment of disease and is becoming increasingly popular globally. However, there are also widespread concerns about its safety. Among them, the cardiotoxicity of aconitine has been described. CASE SUMMARY: We report a case of a 61-year-old male with aconitine poisoning presenting with malignant arrhythmia and severe cardiogenic shock, which was successfully managed with aggressive advanced life support and heart transplantation. CONCLUSION: This is the first case wherein in vivo cardiac pathology was obtained, confirming that aconitine caused acute myocardial necrosis.

Cognitive bias modification for threat interpretations: using passive Mobile Sensing to detect intervention effects in daily life.

BACKGROUND: Social anxiety disorder is associated with distinct mobility patterns (e.g., increased time spent at home compared to non-anxious individuals), but we know little about if these patterns change following interventions. The ubiquity of GPS-enabled smartphones offers new opportunities to assess the benefits of mental health interventions beyond self-reported data. OBJECTIVES: This pre-registered study (https://osf.io/em4vn/?view_only=b97da9ef22df41189f1302870fdc9dfe) assesses the impact of a brief, online cognitive training intervention for threat interpretations using passively-collected mobile sensing data. DESIGN: Ninety-eight participants scoring high on a measure of trait social anxiety completed five weeks of mobile phone monitoring, with 49 participants randomly assigned to receive the intervention halfway through the monitoring period. RESULTS: The brief intervention was not reliably associated with changes to participant mobility patterns. CONCLUSIONS: Despite the lack of significant findings, this paper offers a framework within which to test future intervention effects using GPS data. We present a template for combining clinical theory and empirical GPS findings to derive testable hypotheses, outline data processing steps, and provide human-readable data processing scripts to guide future research. This manuscript illustrates how data processing steps common in engineering can be harnessed to extend our understanding of the impact of mental health interventions in daily life.

An analysis of the implementation effects of new paths and methods of occupational ethics education for medical students in higher vocational colleges.

OBJECTIVE: To investigate the implementation effects of new paths and methods of occupational ethics education for medical students in higher vocational colleges. METHODS: A total of 668 students in higher vocational colleges were selected as the study subjects, and divided into traditional group (n=349) and innovative group (n=319) in accordance with their grades. The data pertaining to the students' views on the educational model of medical and occupational ethics, occupational passion, spirit of occupational risk, occupational ethics and codes, and doctor-patient rights and obligations and communication abilities and skills in the two groups were compared, so as to explore the influences of new paths and methods of occupational ethics education on the occupational ethics of medical students in higher vocational colleges. RESULTS: The study results showed that the innovative group was significantly superior to the traditional group in the satisfaction with the courses of occupational ethics, pedagogical effects, occupational dedication and passion, doctor-patient communication ability, the fulfillment of doctor-patient rights and obligations, and the cognition of occupational ethics and codes (P < 0.05). CONCLUSION: The implementation of innovative methods of occupational ethics education for medical students in higher vocational colleges can produce significant feedback effects. The improved teachers' abilities and pedagogical methods, innovative teaching approaches and optimized curriculum can effectively improve the occupational ethics of medical students in higher vocational colleges.

Improved cancer biomarkers identification using network-constrained infinite latent feature selection.

Identifying biomarkers that are associated with different types of cancer is an important goal in the field of bioinformatics. Different researcher groups have analyzed the expression profiles of many genes and found some certain genetic patterns that can promote the improvement of targeted therapies, but the significance of some genes is still ambiguous. More reliable and effective biomarkers identification methods are then needed to detect candidate cancer-related genes. In this paper, we proposed a novel method that combines the infinite latent feature selection (ILFS) method with the functional interaction (FIs) network to rank the biomarkers. We applied the proposed method to the expression data of five cancer types. The experiments indicated that our network-constrained ILFS (NCILFS) provides an improved prediction of the diagnosis of the samples and locates many more known oncogenes than the original ILFS and some other existing methods. We also performed functional enrichment analysis by inspecting the over-represented gene ontology (GO) biological process (BP) terms and applying the gene set enrichment analysis (GSEA) method on selected biomarkers for each feature selection method. The enrichments analysis reports show that our network-constraint ILFS can produce more biologically significant gene sets than other methods. The results suggest that network-constrained ILFS can identify cancer-related genes with a higher discriminative power and biological significance.

The timing of continuous renal replacement therapy initiation in sepsis-associated acute kidney injury in the intensive care unit: the CRTSAKI Study (Continuous RRT Timing in Sepsis-associated AKI in ICU): study protocol for a multicentre, randomised controlled trial.

INTRODUCTION: Acute kidney injury (AKI) is one of the most common organ dysfunction in sepsis, and increases the risk of unfavourable outcomes. Renal replacement therapy (RRT) is the predominant treatment for sepsis-associated AKI (SAKI). However, to date, no prospective randomised study has adequately addressed whether initiating RRT earlier will attenuate renal injury and improve the outcome of sepsis. The objective of the trial is to compare the early strategy with delayed strategy on the outcomes in patients with SAKI in the intensive care unit (ICU). METHODS AND ANALYSIS: This is a large-scale, multicentre, randomised controlled trial about SAKI. In total, 460 patients with sepsis and evidence of AKI stage 2 of Kidney Disease Improving Global Outcomes (KDIGO) will be recruited and equally randomised into the early group and the delay group in a ratio of 1:1. In the early group, continuous RRT (CRRT) will be started immediately after randomisation. In the delay group, CRRT will initiated if at least one of the following criteria was met: stage 3 of KDIGO, severe hyperkalaemia, pulmonary oedema, blood urea nitrogen level higher than 112 mg/dL after randomisation. The primary outcome is overall survival in a 90-day follow-up period (90-day all-cause mortality). Other end points include 28-day, 60-day and 1-year mortality, recovery rate of renal function by day 28 and day 90, ICU and hospital length of stay, the numbers of CRRT-free days, mechanical ventilation-free days and vasopressor-free days, the rate of complications potentially related to CRRT, CRRT-related cost, and concentrations of inflammatory mediators in serum. ETHICS AND DISSEMINATION: The trial has been approved by the Clinical Research and Application Institutional Review Board of the Second Affiliated Hospital of Guangzhou Medical University (2017-31-ks-01). Participants will be screened and enrolled from patients in the ICU with SAKI by clinicians, with no public advertisement for recruitment. Results will be disseminated in research journals and through conference presentations. TRIAL REGISTRATION: NCT03175328.

Clinical Findings of COVID-19 Patients Admitted to Intensive Care Units in Guangdong Province, China: A Multicenter, Retrospective, Observational Study.

Background: Information about critically ill patients with coronavirus disease 2019 (COVID-19) in China but outside of Wuhan is scarce. We aimed to describe the clinical features, treatment, and outcomes of patients with COVID-19 admitted to the intensive care unit (ICU) in Guangdong Province. Methods: In this multicenter, retrospective, observational study, we enrolled consecutive patients with COVID-19 who were admitted to seven ICUs in Guangdong Province. Demographic data, symptoms, laboratory findings, comorbidities, treatment, and outcomes were collected. Data were compared between patients with and without intubation. Results: A total of 45 COVID-19 patients required ICU admission in the study hospitals [mean age 56.7 ± 15.4 years, 29 males (64.4%)]. The most common symptoms at onset were fever and cough. Most patients presented with lymphopenia and elevated lactate dehydrogenase. Treatment with antiviral drugs was initiated in all patients. Thirty-six patients (80%) developed acute respiratory distress syndrome at ICU admission, and 15 (33.3%) septic shock. Twenty patients (44.4%) were intubated, and 10 (22.2%) received extracorporeal membrane oxygenation. The 60-day mortality was 4.4% (2 of 45). Conclusion: COVID-19 patients admitted to ICU were characterized by fever, lymphopenia, acute respiratory failure, and multiple organ dysfunction. The mortality of ICU patients in Guangdong Province was relatively low with a small sample size.

Total alkaloids from Alstonia scholaris inhibit influenza a virus replication and lung immunopathology by regulating the innate immune response.

BACKGROUND: Alstonia scholaris is a folk medicine used to treat cough, asthma and chronic obstructive pulmonary disease in China. Total alkaloids (TA) from A. scholaris exhibit anti-inflammatory properties in acute respiratory disease, which suggests their possible anti-inflammatory effect on influenza virus infection. PURPOSE: To assess the clinical use of TA by demonstrating their anti-influenza and anti-inflammatory effects and the possible mechanism underlying the effect of TA on influenza A virus (IAV) infection in vitro and to reveal the inhibitory effect of TA on lung immunopathology caused by IAV infection. METHODS: Antiviral and anti-inflammatory activities were assessed in Madin-Darby canine kidney (MDCK) and A549 cells and U937-derived macrophages infected with influenza A/PR/8/34 (H1N1) virus. Proinflammatory cytokine levels were measured by real-time quantitative PCR and Bio-Plex assays. The activation of innate immune signaling induced by H1N1 virus in the absence or presence of TA was detected in A549 cells by Western blot. Furthermore, mice were infected intranasally with H1N1 virus and treated with TA (50, 25 and 12.5 mg/kg/d) or oseltamivir (60 mg/kg/d) for 5 days in vivo. The survival rates and body weight were recorded, and the viral titer, proinflammatory cytokine levels, innate immune cell populations and histopathological changes in the lungs were analyzed. RESULTS: TA significantly inhibited viral replication in A549 cells and U937-derived macrophages and markedly reduced cytokine and chemokine production at the mRNA and protein levels. Furthermore, TA blocked the activation of pattern recognition receptor (PRR)- and IFN-activated signal transduction in A549 cells. Critically, TA also increased the survival rate, reduced the viral titer, suppressed proinflammatory cytokine production and innate immune cell infiltration and improved lung histopathology in a lethal PR8 mouse model. CONCLUSION: TA exhibits anti-viral and anti-inflammatory effects against IAV infection by interfering with PRR- and IFN-activated signal transduction.

Construction of stabilized bulk-nano interfaces for highly promoted inverse CeO2/Cu catalyst.

As the water-gas shift (WGS) reaction serves as a crucial industrial process, strategies for developing robust WGS catalysts are highly desiderated. Here we report the construction of stabilized bulk-nano interfaces to fabricate highly efficient copper-ceria catalyst for the WGS reaction. With an in-situ structural transformation, small CeO2 nanoparticles (2-3 nm) are stabilized on bulk Cu to form abundant CeO2-Cu interfaces, which maintain well-dispersed under reaction conditions. This inverse CeO2/Cu catalyst shows excellent WGS performances, of which the activity is 5 times higher than other reported Cu catalysts. Long-term stability is also very solid under harsh conditions. Mechanistic study illustrates that for the inverse CeO2/Cu catalyst, superb capability of H2O dissociation and CO oxidation facilitates WGS process via the combination of associative and redox mechanisms. This work paves a way to fabricate robust catalysts by combining the advantages of bulk and nano-sized catalysts. Catalysts with such inverse configurations show great potential in practical WGS applications.

Metagenomics Biomarkers Selected for Prediction of Three Different Diseases in Chinese Population.

The dysbiosis of human microbiome has been proven to be associated with the development of many human diseases. Metagenome sequencing emerges as a powerful tool to investigate the effects of microbiome on diseases. Identification of human gut microbiome markers associated with abnormal phenotypes may facilitate feature selection for multiclass classification. Compared with binary classifiers, multiclass classification models deploy more complex discriminative patterns. Here, we developed a pipeline to address the challenging characterization of multilabel samples. In this study, a total of 300 biomarkers were selected from the microbiome of 806 Chinese individuals (383 controls, 170 with type 2 diabetes, 130 with rheumatoid arthritis, and 123 with liver cirrhosis), and then logistic regression prediction algorithm was applied to those markers as the model intrinsic features. The estimated model produced an F1 score of 0.9142, which was better than other popular classification methods, and an average receiver operating characteristic (ROC) of 0.9475 showed a significant correlation between these selected biomarkers from microbiome and corresponding phenotypes. The results from this study indicate that machine learning is a vital tool in data mining from microbiome in order to identify disease-related biomarkers, which may contribute to the application of microbiome-based precision medicine in the future.

Type 2 Diabetes Biomarkers of Human Gut Microbiota Selected via Iterative Sure Independent Screening Method.

Type 2 diabetes, which is a complex metabolic disease influenced by genetic and environment, has become a worldwide problem. Previous published results focused on genetic components through genome-wide association studies that just interpret this disease to some extent. Recently, two research groups published metagenome-wide association studies (MGWAS) result that found meta-biomarkers related with type 2 diabetes. However, One key problem of analyzing genomic data is that how to deal with the ultra-high dimensionality of features. From a statistical viewpoint it is challenging to filter true factors in high dimensional data. Various methods and techniques have been proposed on this issue, which can only achieve limited prediction performance and poor interpretability. New statistical procedure with higher performance and clear interpretability is appealing in analyzing high dimensional data. To address this problem, we apply an excellent statistical variable selection procedure called iterative sure independence screening to gene profiles that obtained from metagenome sequencing, and 48/24 meta-markers were selected in Chinese/European cohorts as predictors with 0.97/0.99 accuracy in AUC (area under the curve), which showed a better performance than other model selection methods, respectively. These results demonstrate the power and utility of data mining technologies within the large-scale and ultra-high dimensional genomic-related dataset for diagnostic and predictive markers identifying.

Retrospective review on obstetric cases of critically ill and dead patients in Dongguan.

This retrospective analysis was set to understand the epidemiological status of the critically ill obstetric patients in Dongguan city, Guangdong, China. Understanding the risk factors for the death cases can provide scientific evidences for future preventive strategies to decrease the maternal mortality rate. This retrospective included the statistical data and clinical data on the cases of critically ill and dead obstetric patients admitted to Dongguan People's Hospital and Dongguan Maternal & Child Health Hospital from September 1st, 2009 to August 31st, 2013. Data included numbers of the critically ill maternal and obstetric women, common obstetric and maternal comorbidities and complications in the critically ill patients, the basic characteristics of maternal and obstetric deaths, records of regular prenatal examinations, the time intervals between onset of acute symptoms and ICU admission, blood purification, and the acute physiology and chronic health evaluation II (APACHE II) score. During the 5-year period, there were increasing trend of critically ill pregnant and obstetric patients, and the prevalence rate of critically ill obstetric patients was 8.99-9.28 %. The most common obstetric causes of admission were massive postpartum hemorrhage (63.54 %), followed by pregnancy-associated hypertension (15.85 %) and placenta previa (8.92 %). The most common non-obstetric causes of admission were acute heart failure (1.98 %). In the observed period, 20 critically ill obstetric patients died in these two hospitals (mortality rate 0.24 %, 20/8,129). The mean age of dead women was (30.3 ± 6.6) years old and mean gestational age was (30.1 ± 9.3) weeks. 75 % of the patient had more than two pregnancies. Over 90 % of the patients received education below junior high school level. 85 % of the patients were non-Dongguan natives and regular prenatal care rate was only 15 % on dead cases. The most common causes of death were pregnancy-associated hypertension, acute heart failure, and massive postpartum hemorrhage. The dead patients experienced longer interval between onset of acute symptoms and ICU admission (media = 62.5 h), higher APACHE II score (25.4 ± 5.4), and lower blood purification treatment rate (10 %). The incidence of critically ill pregnant and obstetric patients is high in Dongguan city. The group of dead obstetric patients, the majority of which were non-Dongguan natives, usually experienced above-average pregnancies, lower educational level, lower regular prenatal care rate, and longer interval between onset of acute symptoms and ICU admission. Critically ill obstetric patients may benefit from publicized informed relevant education, government-supported health care, preventative interventions of critical obstetric and medical complications, timely ICU admission after onset of acute symptoms, and the enhanced support of organ functions within the ICU.

MiR-204/miR-211 downregulation contributes to candidemia-induced kidney injuries via derepression of Hmx1 expression.

AIMS: This study was aimed to exploit the role of heme oxygenase Hmx1 and the potential miRNA mechanisms in the kidney injuries induced by urinary tract infection by Candida species/Candidemia. MAIN METHODS: We employed a mouse model of systemic Candidiasis by injection of the Candida albicans strain SC5314 into C57BL/6 mice. Kidney injuries were assessed by measuring serum cystatin C (CysC), serum ß2-microglobulin (ß2-MG) and blood urea nitrogen (BUN). Validation of miRNA target gene was conducted by luciferase reporter gene assay, Western blot analysis and real-time RT-PCR. KEY FINDINGS: We showed here that Candidemia caused significant downregulation of microRNAs miR-204 and miR-211. In sharp contrast, Hmx1 expression was remarkably upregulated, particularly at the protein level. Computational analysis predicted Hmx1 as a target gene for both miR-204 and miR-211 that share the same seed site sequence. We then experimentally validated the targeting relationship between miR-204/miR-211 and Hmx1, which explains the reciprocal changes of expression of miR-204/miR-211 and Hmx1 in Candidemia. Administration of miR-204/miR-211 mimics substantially downregulated Hmx1 and mitigated the severity of the kidney injuries induced by Candidemia, as reflected by improved renal glomerular filtration rate (GFR) determined by serum cystatin C (CysC), serum ß2-microglobulin (ß2-MG) and blood urea nitrogen (BUN). Knockdown of miR-204/miR-211 worsened while forced expression of miR-204/miR-211 ameliorated kidney injuries in mice with systemic Candidiasis. SIGNIFICANCE: Our findings indicate that miR-204/miR-211 downregulation accounts at least partially for the Hmx1 upregulation and the miR-204/miR-211-Hmx1 signaling axis may contribute to immune-suppression in the host thereby the Candidemia-induced kidney dysfunction.

Palladium, iridium and ruthenium complexes with acyclic imino-N-heterocyclic carbenes and their application in aqua-phase Suzuki-Miyaura cross-coupling reaction and transfer hydrogenation.

Palladium (4a­4c), iridium (5a­5c) and ruthenium (6a­6c) complexes have been prepared by in situ transmetalation from the corresponding silver complexes of acyclic imino-functionalized imidazolium chlorides [1-(Me)-imidazolium-3-{C(p-CH(3)-Ph)=N(Ar)}]Cl (3) (Ar = 2,4,6-trimethylphenyl (3a), 2,6-diisopropylphenyl (3b) and phenyl (3c)) with [Pd(COD)Cl(2)], [Cp*IrCl(2)](2) or [Ru(p-cymene)Cl(2)](2), respectively. Iridium and ruthenium complexes, 5a[PF(6)]­5c[PF(6)], 6a[PF(6)]­6c[PF(6)], 6c[BF(4)], 6c[BPh(4)] and 6c[NTf(2)], were obtained directly from 5a­5c and 6a­6c through an anion-exchange process with KPF(6), NaBF(4), NaBPh(4) and LiNTf(2) (bis(trifluoromethylsulfonyl)imide lithium), respectively. All complexes were characterized by FT-IR, (1)H and (13)C NMR spectroscopy and elemental analysis. Crystal structures of 4a, 5a and 6c[NTf(2)], and show that five-membered chelate ring is formed in these complexes by the coordination of the carbene carbon and the imino nitrogen atom, and the latter two are cationic compounds with Cl(-) and NTf(2)(-) as counteranion respectively. The catalytic performance of Pd complexes for Suzuki-Miyaura cross-coupling reactions in pure water and Ir and Ru complexes for transfer hydrogenation of ketones and imines was tested in a wide scope of substrates. Pd complex 4b with the largest steric hinder exhibited the best performance to gain moderate to excellent yields on catalyzing Suzuki-Miyaura cross-coupling of aryl chlorides and arylboronic acids in water. While in transfer hydrogenation of various ketones, all the Ir and Ru complexes were effective with good to excellent yields. Among all these complexes, 6c[PF(6)] was found most effective, and moderate yields could be obtained even in the transfer hydrogenation of imines. Moreover, different counteranions of Ru complexes are influential on catalyzing the transfer hydrogenation, with the sequence of PF(6)(-) ≈ BF(4)(-) > BPh(4)(-) > Cl(-) > NTf(2)(-).