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"Zou, Xi"
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Turning sulfonyl and sulfonimidoyl fluoride electrophiles into sulfur(VI) radicals for alkene ligation
Sulfonyl and sulfonimidoyl fluorides are versatile substrates in organic synthesis and medicinal chemistry. However, they have been exclusively used as S(VI)
+
electrophiles for defluorinative ligations. Converting sulfonyl and sulfonimidoyl fluorides to S(VI) radicals is challenging and underexplored due to the strong bond dissociation energy of S
VI
−F and high reduction potentials, but once achieved would enable dramatically expanded synthetic utility and downstream applications. In this report, we disclose a general platform to address this issue through cooperative organosuperbase activation and photoredox catalysis. Vinyl sulfones and sulfoximines are obtained with excellent
E
selectivity under mild conditions by coupling reactions with alkenes. The synthetic utility of this method in the preparation of functional polymers and dyes is also demonstrated.
Sulfonyl and sulfonimidoyl fluorides (SFs) are versatile substrates in organic synthesis but conversion to S(VI) radicals is challenging. Here, the authors show that organosuperbase activated SFs can be converted to S(VI) radicals under photocatalytic conditions and demonstrate application of this synthetic pathway in the preparation of functional polymers and dyes.
Journal Article
Machine learning algorithms for diabetic kidney disease risk predictive model of Chinese patients with type 2 diabetes mellitus
Diabetic kidney disease (DKD) is a common and serious complication of diabetic mellitus (DM). More sensitive methods for early DKD prediction are urgently needed. This study aimed to set up DKD risk prediction models based on machine learning algorithms (MLAs) in patients with type 2 DM (T2DM).
The electronic health records of 12,190 T2DM patients with 3-year follow-ups were extracted, and the dataset was divided into a training and testing dataset in a 4:1 ratio. The risk variables for DKD development were ranked and selected to establish forecasting models. The performance of models was further evaluated by the indexes of sensitivity, specificity, positive predictive value, negative predictive value, accuracy, as well as F1 score, using the testing dataset. The value of accuracy was used to select the optimal model.
Using the importance ranking in the random forest package, the variables of age, urinary albumin-to-creatinine ratio, serum cystatin C, estimated glomerular filtration rate, and neutrophil percentage were selected as the predictors for DKD onset. Among the seven forecasting models constructed by MLAs, the accuracy of the Light Gradient Boosting Machine (LightGBM) model was the highest, indicated that the LightGBM algorithms might perform the best for predicting 3-year risk of DKD onset.
Our study could provide powerful tools for early DKD risk prediction, which might help optimize intervention strategies and improve the renal prognosis in T2DM patients.
Journal Article
Spatiotemporal analysis and forecasting model of hemorrhagic fever with renal syndrome in mainland China
Hemorrhagic fever with renal syndrome (HFRS) caused by hantaviruses is a serious public health problem in China, accounting for 90% of HFRS cases reported globally. In this study, we applied geographical information system (GIS), spatial autocorrelation analyses and a seasonal autoregressive-integrated moving average (SARIMA) model to describe and predict HFRS epidemic with the objective of monitoring and forecasting HFRS in mainland China. Chinese HFRS data from 2004 to 2016 were obtained from National Infectious Diseases Reporting System (NIDRS) database and Chinese Centre for Disease Control and Prevention (CDC). GIS maps were produced to detect the spatial distribution of HFRS cases. The Moran's I was adopted in spatial global autocorrelation analysis to identify the integral spatiotemporal pattern of HFRS outbreaks, while the local Moran's Ii was performed to identify ‘hotspot’ regions of HFRS at province level. A fittest SARIMA model was developed to forecast HFRS incidence in the year 2016, which was selected by Akaike information criterion and Ljung–Box test. During 2004–2015, a total of 165 710 HFRS cases were reported with the average annual incidence at province level ranged from 0 to 13.05 per 100 000 persons. Global Moran's I analysis showed that the HFRS outbreaks presented spatially clustered distribution, with the degree of cluster gradually decreasing from 2004 to 2009, then turned out to be randomly distributed and reached lowest point in 2012. Local Moran's Ii identified that four provinces in northeast China contributed to a ‘high–high’ cluster as a traditional epidemic centre, and Shaanxi became another HFRS ‘hotspot’ region since 2011. The monthly incidence of HFRS decreased sharply from 2004 to 2009 in mainland China, then increased markedly from 2010 to 2012, and decreased again since 2013, with obvious seasonal fluctuations. The SARIMA ((0,1,3) × (1,0,1)12) model was the most fittest forecasting model for the dataset of HFRS in mainland China. The spatiotemporal distribution of HFRS in mainland China varied in recent years; together with the SARIMA forecasting model, this study provided several potential decision supportive tools for the control and risk-management plan of HFRS in China.
Journal Article
Effect of Post-Heat Treatment on the Mechanical and Residual Stress Behavior of Pulsed Wave S316L Fabricated by Directed Energy Deposition
The influence of annealing at various temperatures on the phase stability and microstructure of pulsed-wave laser mode (PW) 316L stainless steel fabricated via Directed Energy Deposition (DED) was systematically investigated. The microstructural alterations resulting from heat treatment were examined to clarify their influence on the mechanical properties of the specimens subjected to tensile loading. The results showed that cell size increased with annealing temperature, with the cellular microstructure disappearing at higher temperatures (T ≥ 1000 °C). A decrease in the mechanical strength of the specimens was observed as annealing temperature increased. Additionally, the influence of different laser pulse frequencies and duty cycles on residual stresses was examined, revealing that moderate laser frequencies and duty cycles effectively reduced residual stress levels.
Journal Article
Non-volatile memory based on the ferroelectric photovoltaic effect
The quest for a solid state universal memory with high-storage density, high read/write speed, random access and non-volatility has triggered intense research into new materials and novel device architectures. Though the non-volatile memory market is dominated by flash memory now, it has very low operation speed with ~10 μs programming and ~10 ms erasing time. Furthermore, it can only withstand ~10
5
rewriting cycles, which prevents it from becoming the universal memory. Here we demonstrate that the significant photovoltaic effect of a ferroelectric material, such as BiFeO
3
with a band gap in the visible range, can be used to sense the polarization direction non-destructively in a ferroelectric memory. A prototype 16-cell memory based on the cross-bar architecture has been prepared and tested, demonstrating the feasibility of this technique.
Ferroelectric RAM is considered a promising candidate on the quest for a universal memory, but the concept is still problem prone. Here, the authors use the ferroelectric photovoltaic effect as a non-destructive read-out method for a new prototype memory, which shows good data retention and fatigue resistance.
Journal Article
The ortholog of human REEP1-4 is required for autophagosomal enclosure of ER-phagy/nucleophagy cargos in fission yeast
Selective macroautophagy of the endoplasmic reticulum (ER) and the nucleus, known as ER-phagy and nucleophagy, respectively, are processes whose mechanisms remain inadequately understood. Through an imaging-based screen, we find that in the fission yeast Schizosaccharomyces pombe , Yep1 (also known as Hva22 or Rop1), the ortholog of human REEP1-4, is essential for ER-phagy and nucleophagy but not for bulk autophagy. In the absence of Yep1, the initial phase of ER-phagy and nucleophagy proceeds normally, with the ER-phagy/nucleophagy receptor Epr1 coassembling with Atg8. However, ER-phagy/nucleophagy cargos fail to reach the vacuole. Instead, nucleus- and cortical-ER-derived membrane structures not enclosed within autophagosomes accumulate in the cytoplasm. Intriguingly, the outer membranes of nucleus-derived structures remain continuous with the nuclear envelope-ER network, suggesting a possible outer membrane fission defect during cargo separation from source compartments. We find that the ER-phagy role of Yep1 relies on its abilities to self-interact and shape membranes and requires its C-terminal amphipathic helices. Moreover, we show that human REEP1-4 and budding yeast Atg40 can functionally substitute for Yep1 in ER-phagy, and Atg40 is a divergent ortholog of Yep1 and REEP1-4. Our findings uncover an unexpected mechanism governing the autophagosomal enclosure of ER-phagy/nucleophagy cargos and shed new light on the functions and evolution of REEP family proteins.
Journal Article
Prediction models for risk of diabetic kidney disease in Chinese patients with type 2 diabetes mellitus
Diabetic kidney disease (DKD) is a common and serious complication in patients with diabetic mellitus (DM), the risk of cardiovascular events and all-cause mortality also increases in DKD patients. This study aimed to detect the influencing factors of DKD in type 2 DM (T2DM) patients, and construct DKD prediction models and nomogram for clinical decision-making.
A total of 14,628 patients with T2DM were included. These patients were divided into pre-DKD and non-DKD groups, depending on the occurrence of DKD during a 3-year follow-up from first clinic attendance. The influencing indicators of DKD were analyzed, the prediction models were established by multivariable logistic regression, and a nomogram was drawn for DKD risk assessment.
Two prediction models for DKD were built by multivariate logistic regression analysis. Model 1 was created based on 17 variables using the forward selection method, Model 2 was established by 19 variables using the backward elimination method. The Somers' D values of both models were 0.789. Four independent predictors were selected to build the nomogram, including age, UACR, eGFR, and neutrophil percentages. The C-index of the nomogram reached 0.864, suggesting a good predictive accuracy for DKD development.
Our prediction models had strong predictive powers, and our nomogram provided visual aids to DKD risk calculation, which was simple and fast. These algorithms can provide early DKD risk prediction, which might help to improve the medical care for early detection and intervention in T2DM patients, and then consequently improve the prognosis of DM patients.
Journal Article
Prevalence, incidence and mortality of hypertrophic cardiomyopathy based on a population cohort of 21.9 million in China
There are limited studies on the prevalence and incidence of clinically diagnosed hypertrophic myocardiopathy (HCM) and its mortality in the Chinese population, and the projected population burden of HCM over the next decades. We collected data on HCM and its mortality from the Beijing Municipal Health Commission Information Center (BMHCIC) database and estimated the prevalence and incidence based on the whole Beijing population. Calculation of population trends was performed using annual percentage change (APC) and average annual percentage change (AAPC). Finally, future HCM incidence was built by modelling projection of HCM to the next decades using Poisson regression analysis and Gray Model 1,1(GM [1,1]). The prevalence of HCM was 0.0069% (95%CI, 0.0065–0.0072%;
N
= 1343) in 2010, rising to 0.076% (95% CI, 0.074–0.077%;
N
= 16,616) in 2019, and the incidence of HCM was 6.85 per 100 000 person-year in 2010, rising to 11.76 per 100 000 person-year in 2019. Males had higher prevalence and incidence of HCM than females. The APPC for the rising incidence of HCM was 5.8% and the expected numbers will double increase in 2029 by assuming the same increase trend as the last decades. HCM had increased annual incidence of HF (APPC: 8.4, 4.4–12.6,
p
< 0.05), and relatively stable annual incidence of mortality (APPC: 1.2%, − 2.3% to 4.8%,
p
> 0.05) during the studied period. Males had lower mortality (2.70% vs. 4.20%,
p
< 0.001) than females. The calculated HCM prevalence was much lower compared to prior screening studies from 2004, although the predicted HCM incidence would double over the next decades. HCM was associated with a stable risk of mortality during the studied period.
Journal Article
Descriptive norms for me, injunctive norms for you: Using norms to explain the risk gap
People are more likely to rely on descriptive norms (i.e., what their peers are doing) when deciding whether to take a risk themselves than when deciding whether to recommend others to take a risk. We proposed and found that people also attend to normative information when making risk recommendations to others, but in this case they attend to a different type of normative information — injunctive norms (i.e., whether their peers approve of this behavior). Descriptive norm plays a bigger role in influencing people’s own decisions, whereas injunctive norm plays a bigger role in influencing people’s recommendations to others. This research demonstrates the importance of differentiating descriptive versus injunctive norms in risky decision-making and provides further evidence that perceived norms significantly influence risky decision-making.
Journal Article