General Reaction Mode of Hypervalent Iodine Trifluoromethylation Reagent: A Density Functional Theory Study

The mechanisms of trifluoromethylation with hypervalent iodine trifluoromethylation reagent (Togni’s reagent <b>1</b>) have been comprehensively studied by density functional theory (DFT) calculations. The results show that there are two general reaction modes for reagent <b>1</b>: <b>(I) Mode-A, acting as a CF</b>_<b>3</b>^<b>•</b> <b>free radical source</b>. When one-electron reductants are available in the reaction system, such as Cu^I, Fe^II, TEMPONa, or electron-rich lithium enolate, <b>1</b> will be reduced via single-electron transfer (SET) and give out CF₃^• free radical concertedly. In the Cu^I-catalyzed trifluoromethylation of terminal olefins, Cu^I promotes the <i>homo</i>-cleavage of the F₃C–I bond in <b>1</b> via SET to produce Cu^II species and CF₃^• free radical. Then the CF₃^• free radical attacks the olefin, leading to trifluoromethyl alkyl radical intermediate. Subsequently, the Cu^II species act as a one-electron oxidant oxidizing the alkyl radical to carbocation intermediate, and the following deprotonation leads to the final product. Other mechanisms, such as formation of F₃C–Cu^III species via oxidative addition, formation of allylic radical intermediate, were considered and excluded. <b>(II) Mode-B</b>, <b>acting as a CF</b>_<b>3</b>^<b>+</b> <b>cation source</b>. <b>1</b> can be activated by a Lewis acid such as Zn^II and becomes more inclined to undergo an S_N2 type nucleophilic attack at the CF₃ group by nucleophiles (pentanol in this work). For substrates studied in this paper, such as the lithium enolate, pentanol, and sodium 2,4,6-trimethylphenolate, the competition between their reducibility and nucleophilicity determines the reaction mode of regent <b>1</b>

Association of periostin level with echocardiography parameters and Killip class.

<p>(A) Serum periostin level was in negative correlation with left ventricle ejection fraction in AMI patients (r = −0.472, <i>p</i><0.01). (B) Serum periostin level was in negative correlation with left atrium diameter in AMI patients (r = −0.328, <i>p</i><0.05). (C) Serum periostin level was in positive correlation with Killip class in AMI patients (r = 0.395, <i>p</i><0.01).</p

Cardiovascular Events of AMI Patients after Six Months Follow Up.

<p>TIA: transient ischemic attack; <i>*p</i><0.05.</p

Association of Serum Periostin with Cardiac Function and Short-Term Prognosis in Acute Myocardial Infarction Patients

<div><p>Background</p><p>Periostin was proved to play an important role in extra-cellular matrix remodeling after acute myocardial infarction (AMI). Myocardial periostin was markedly up-regulated after AMI and participated in the maladaptive process of cardiac remodeling. However, few researches focused on the circulating periostin and its significance. This study aims to investigate the association of serum periostin level with cardiac function and short-term prognosis in AMI patients.</p><p>Methodology/Principal Findings</p><p>We totally recruited 50 patients diagnosed as ST-elevation myocardial infarction. Blood samples were taken within 12 hours after the onset of AMI before emergency coronary revascularization procedures. Serum periostin was measured using enzyme-linked immunosorbent assay. All patients received echocardiography examination within one week after hospitalization. Correlations of serum periostin with echocardiography parameters, Killip class and myocardium injury biomarkers (CK-MB/troponin T) were investigated. AMI patients were divided into two groups by serum periostin level (higher/lower periostin group) and followed up for six months. Primary endpoints included cardiovascular mortality, nonfatal stroke/transient ischemic attack, chest pain occurrence and re-hospitalization. Secondary endpoint referred to composite cardiovascular events including all the primary endpoints.</p><p>Result</p><p>Serum periostin was in negative association with left ventricular ejection fraction (LVEF) (r = −0.472, *<i>p</i><0.01) and left atrium diameter (LAD) (r = −0.328, *<i>p</i><0.05). Positive correlation was found between serum periostin level and Killip class (r = 0.395, *<i>p</i><0.01). There was no association between serum periostin and CK-MB or troponin T (<i>p</i>>0.05). After six months follow up, patients in higher periostin group showed increased composite cardiovascular events (*<i>p</i><0.05). Patients showed no significant difference in primary endpoints between the two groups.</p><p>Conclusions/Significance</p><p>Serum periostin was in negative correlation with LVEF and LAD, in positive association with Killip class and higher serum periostin level may be predictive for worse short-term disease prognosis indicated as more composite cardiovascular events six months post AMI.</p></div

Effect of serum periostin on cardiovascular outcomes six months post AMI.

<p>Effect of serum periostin on cardiovascular outcomes six months post AMI.</p

Clinical Characteristics of AMI Patients at follow up.

<p>All determinations were performed in the fasting state.</p><p>ACEI: Angiotensin-converting enzyme inhibitor; ARB: Angiotensin II receptor antagonists; HDLc: high density lipoprotein cholesterol; LDLc: low density lipoprotein cholesterol; Cr: creatinine; BUN: blood urea nitrogen.</p><p>Date presented as mean±SD.</p

Correlation of Periostin with Coronary/Echocardiography Parameters after AMI.

<p>LVEF: left ventricular systolic ejection fraction; LVDd: left ventricular end diastolic diameter; LVPWT: left ventricular posterior wall thickness; IVSTd: inter-ventricular septal thickness in diastole; LAD: left atrium diameter; AoD: aorta dimension. Date presented as mean±SD; Spearman correlation was used to analyze the relationship between periostin level and variables. <i>*p</i><0.05.</p

Relationship between Clinical Characteristics and Serum Periostin Level in AMI Patients.

<p>All determinations were performed in the fasting state. CHD: coronary heart disease; HDLc: high density lipoprotein cholesterol; LDLc: low density lipoprotein cholesterol; BUN: blood urea nitrogen; Date presented as mean±SD; Spearman correlation was used to analyze the relationship between periostin level and variables.</p

Industry connection before the epidemic.

Understanding the dynamic link between the development of COVID-19 pandemic and industry sector risk spillovers is crucial to explore the underlying mechanisms by which major public health events affect economic systems. This paper applies ElasticNet method proposed by Diebold and Yilmaz (2009, 2012, 2014) to estimate the dynamic risk spillover indicators of 20 industrial sectors in China from 2016 to 2022, and systematically examines the impact of industry risk network fluctuations and the transmission path caused by COVID-19 shock. The findings reveal that risk spillovers of Chinese industries show a dynamic change of "decline-fluctuation-rebound" with the three phases of COVID-19 epidemic. At the beginning of the epidemic, machinery and equipment, paper and printing, tourism and hotels, media and information services, and agriculture were the exporters of epidemic risk, while materials, transportation equipment, commercial trade, health care, and environmental protection were the importers of epidemic risk; However, as the epidemic developed further, the direction and effect of risk transmission in the industry was reversed. Examining the network characteristics of the pair sectors, we found that under the epidemic shock, the positive risk spillover from tourism and hotels, culture, education and sports to consumer goods, finance, and energy industries was significantly increased, and finance and real estate industries were affected by the risk impact of more industries, while the number of industries affected by information technology and computer industry was significantly reduced. This paper shows that there is inter-industry risk transmission of the COVID-19 epidemic shock, and the risk transmission feeds back in a cycle between industries as the epidemic develops, driving the economy into a vicious circle. The role of the service sector in blocking the spread of negative shocks from the epidemic should be emphasized and brought into play to avoid increasing the overall economic vulnerability. This study will help to deepen the understanding of scholars and policy makers on the network transmission effects of the epidemic.</div

Phloem transport capacity of transgenic rice T1c-19 (<i>Cry1C*</i>) under several potassium fertilizer levels

<div><p>Genetic modification of Cry-proteins from <i>Bacillus thuringiensis (Bt)</i> is a common practice in economically important crops to improve insecticide resistance and reduce the use of pesticides. However, introduction of these genes can have unintended side effects, which should be closely monitored for effective breeding and crop management. To determine the potential cause of these negative effects, we explored assimilate partitioning in the transgenic <i>Bt</i> rice line T1c-19 (<i>Cry1C*</i>), which was compared with that of its wild-type counterpart Minghui 63 (MH63) under different potassium fertilization application treatment conditions. In a pot experiment, 0, 0.4, and 0.6 g K₂O was applied per kg of dry soil to determine the phloem transport characteristics of the two rice lines. We used a variety of assessment indicators ranging from morphological to physiological aspects, including the number of large and small vascular bundles in the neck internode at the heading stage, the diameter and bleeding intensity of the neck internode at the filling stage, and the content and apparent ratio of transferred non-structural carbohydrates (NSC) in the culm and sheath from the heading to maturing stages. The K utilization and grain yield at the maturing stage were also concerned. Results presented that the mean setting rate and grain yield of T1c-19 (<i>Cry1C*</i>) decreased by 22.3% and 26.2% compared to those in MH63, respectively. Compared to MH63, the K concentration and accumulation were significantly higher in the culms and leaves, but significantly lower in grain of T1c-19 (<i>Cry1C*</i>). T1c-19 (<i>Cry1C*</i>) had less apparent NSC efflux in the culm and sheath, fewer small vascular bundles, and a smaller diameter and bleeding intensity of the neck internode than MH63. In addition, linear correlation analysis indicated that there were positive correlations among grain yield, setting rate, the apparent NSC efflux in the culm and sheath, number of small vascular bundles, and the neck internode diameter and bleeding intensity. These unintended effects may directly or indirectly be caused by insertion of exogenous <i>Bt</i> (<i>Cry1C*</i>) gene, which should be further considered in the future breeding of transgenic crops.</p></div