Effect of critical illness insurance on the medical expenditures of rural patients in China: an interrupted time series study for universal health insurance coverage.

OBJECTIVE: The objective of this study is to determine if critical illness insurance (CII) promotes the universal health coverage to reduce out-of-pocket (OOP) medical expenditures and improve the effective reimbursement rate (ERR) in rural China. STUDY DESIGN: The 5-year monthly hospitalisation data, starting 2 years before the CII (ie, the 'intervention') began, were collected. Interrupted time series analysis models were used to evaluate the immediate and gradual effects of CII on OOP payment and ERR. SETTING: The study was conducted in Xiantao County, Hubei Province, China. PARTICIPANTS: A total of 511 221 inpatients within 5 years were included in the analysis. RESULTS: In 2016, 100 288 patients received in-patient services, among which 4137 benefited from CII. After the implementation of CII, OOP expenses increased 32.2% (95% CI 24.8% to 39.5%, p<0.001). Compared with the preintervention periods, the trend changes decline at a rate of 0.7% per month after the implementation of CII. Similarly, a significant decrease was observed in log ERR after the intervention started. The rate of level change is 16% change (95% CI -20.0% to -12.1%, p<0.001). CONCLUSION: CII did not decrease the OOP payments of rural inpatients in 2011-2016 periods. The limited extents of population coverage and financing resources can be attributed to these results. Therefore, the Chinese government must urgently raise the funds of CII and improve the CII policy reimbursement rate

Erratum to: ‘Integrated analysis of the local and systemic changes preceding the development of post-partum cytological endometritis’

ErratumErratum to: ‘Integrated analysis of the local and systemic changes preceding the development of post-partum cytological endometritis’ -http://hdl.handle.net/11019/90

Synthesis of renewable monomer 2, 5-bishydroxymethylfuran from highly concentrated 5-hydroxymethylfurfural in deep eutectic solvents

Abstract(#br)2, 5-Bishydroxymethylfuran (BHMF) has been currently emerged as a promising biomass-derived monomer. It is highly desirable to proceed a chemical process at a high substrate concentration, by which a facile and cost-effective separation of products can be expected. Herein, we report for the first time on the hydrogenation of highly concentrated 5-hydroxymethylfurfural (HMF) in deep eutectic solvents (DESs), giving a near quantitative selectivity towards BHMF in ChCl-glycerol DES at 25°C in 3h using NaBH 4 as the H-donor. DES is hailed as a new class of green solvent, in which HMF/BHMF could be stabilized by the strong hydrogen-bond interaction, and allowed the selective hydrogenation of HMF at high concentration up to 40wt%. Notably, the resulting BHMF could be facilely separated by extraction with ethyl acetate, and then high purity of BHMF with a desirable isolated yield around 80% was obtained after removing of ethyl acetate. Additionally, the reaction efficiency of HMF hydrogenation in DESs was verified to be strongly associated with the viscosity of DESs and the p K a value of hydrogen-bonding donor

Cascade conversion of furfural to fuel bioadditive ethyl levulinate over bifunctional zirconium-based catalysts

Abstract(#br)Biomass-derived ethyl levulinate (EL) is currently deemed as a promising fuel bioadditive to improve (bio)diesel combustion performance without the sacrifice of its octane number. In this contribution, a range of Zr–Al bimetallic catalysts were prepared for the cascade conversion of furfural to EL by the integration of transfer hydrogenation and ethanolysis in ethanol. The ratio of Lewis to Brønsted acid sites (L/B) could be tuned by the ratio of Al 2 O 3 to ZrO 2 over SBA-15 support. Among these catalysts, Zr–Al/SBA-15(30:10) with appropriate L/B ratio of 2.25 exhibited an outstanding catalytic performance to give a furfural (FF) conversion up to 92.8% with a EL selectivity as high as 71.4% at 453 K in 3 h

Delayed differentiation of vaginal and uterine microbiomes in dairy cows developing postpartum endometritis

Bacterial overgrowth in the uterus is a normal event after parturition. In contrast to the healthy cow, animals unable to control the infection within 21 days after calving develop postpartum endometritis. Studies on the Microbial Ecology of the bovine reproductive tract have focused on either vaginal or uterine microbiomes. This is the first study that compares both microbiomes in the same animals. Terminal Restriction Fragment Length Polymorphism of the 16S rRNA gene showed that despite large differences associated to individuals, a shared community exist in vagina and uterus during the postpartum period. The largest changes associated with development of endometritis were observed at 7 days postpartum, a time when vaginal and uterine microbiomes were most similar. 16S rRNA pyrosequencing of the vaginal microbiome at 7 days postpartum showed at least three different microbiome types that were associated with later development of postpartum endometritis. All three microbiome types featured reduced bacterial diversity. Taken together, the above findings support a scenario where disruption of the compartmentalization of the reproductive tract during parturition results in the dispersal and mixing of the vaginal and uterine microbiomes, which subsequently are subject to differentiation. This differentiation was observed early postpartum in the healthy cow. In contrast, loss of bacterial diversity and dominance of the microbiome by few bacterial taxa were related to a delayed succession at 7DPP in cows that at 21 DPP or later were diagnosed with endometritis.Department of Agriculture, Food and the MarineScience Foundation Irelan

Combination of Neutrophil Count and Gensini Score as a Prognostic Marker in Patients with ACS and Uncontrolled T2DM Undergoing PCI

Background: Several biomarkers have been studied as prognostic indicators among people with diabetes and coronary artery disease (CAD). The purpose of this study was to determine the prognostic value of neutrophil counts and the Gensini score in patients with diabetes and ACS undergoing percutaneous coronary intervention (PCI). Methods: A total of 694 people with ACS and T2DM who simultaneously had elevated HBA1c received PCI. Spearman rank correlation estimates were used for correlation evaluation. Multivariate Cox regression and Kaplan-Meier analysis were used to identify characteristics associated with major adverse cardiovascular and cerebrovascular events (MACCEs) and patient survival. The effects of single- and multi-factor indices on MACCEs were evaluated through receiver operating characteristic curve analysis. Results: The Gensini score and neutrophil count significantly differed between the MACCE and non-MACCE groups among patients receiving PCI who had concomitant ACS and T2DM with elevated HBA1c (P<0.001). The Gensini score and neutrophil count were strongly associated with MACCEs (log-rank, P<0.001). The Gensini score and neutrophil count, alone or in combination, were predictors of MACCEs, according to multivariate Cox regression analysis (adjusted hazard ratio [HR], 1.005; 95% confidence interval [CI], 1.002–1.008; P=0.002; adjusted HR, 1.512; 95% CI, 1.005–2.274; P=0.047, respectively). The Gensini score was strongly associated with neutrophil count (variance inflation factor ≥ 5). Area under the curve analysis revealed that the combination of multivariate factors predicted the occurrence of MACCEs better than any single variable. Conclusion: In patients with T2DM and ACS with elevated HBA1c who underwent PCI, both the Gensini score and neutrophil count were independent predictors of outcomes. The combination of both predictors has a higher predictability

A flexible Cu-based catalyst system for the transformation of fructose to furanyl ethers as potential bio-fuels

Abstract(#br)Biomass-derived furanyl ethers, such as 5-alkoxymethylfurfurals (AMFs) and 2,5-bis(alkoxymethyl)furans (BAMFs), can be employed as promising biofuels or additives. The development of multifunctional catalysts for the efficient production of furanyl ethers from sugars through 5-hydroxymethylfurfural (HMF) as an intermediate is highly desirable but challenging, because multiple reactions including dehydration, etherification and hydrogenation get involved and the side reaction of sugars and HMF to form humins is inevitable. In this contribution, we found that the introduction of CuO resulted in the generation of Lewis acid sites at the cost of Bronsted acid sites over CuO-USY catalysts through the formation of Al-O-Cu(II) species. The dispersity of CuO particles and the amount of Lewis acid sites could be manipulated by adjusting the loading of CuO. If 5 wt% CuO was supported on USY zeolite to give a CuO(5)-USY catalyst, CuO particles with a high dispersity (36.4%) afforded abundant Lewis acid sites (457.1 μ mol/g). Lewis acid over CuO(5)-USY greatly promoted the acid-catalyzed dehydration of fructose to HMF and HMF etherification to AMFs, resulting in a HMF yield up to 86.2% from fructose and AMFs yields greater than 90% from HMF. Interestingly, a combination of CuO(5)-USY and a small amount of metallic Cu powder was able to offer desirable BAMFs yields by the reductive etherification of HMF under hydrogen atmosphere. As a result, 5-methoxymethylfurfural (MMF) of 79.6% and 2,5-bis(methoxymethyl)furan (BMMF) yield of 74.5% were achieved from fructose through HMF as an intermediate in the presence of CuO(5)-USY alone or with metallic Cu as a co-catalyst. Therefore, the above Cu-based catalyst system holds the promise to flexibly produce a family of AMFs or BAMFs from fructose via a facile two-step approach

Automatic Recognition of Laryngoscopic Images Using a Deep-Learning Technique

Objectives/Hypothesis: To develop a deep-learning–based computer-aided diagnosis system for distinguishing laryngeal neoplasms (benign, precancerous lesions, and cancer) and improve the clinician-based accuracy of diagnostic assessments of laryngoscopy findings. Study Design: Retrospective study. Methods: A total of 24,667 laryngoscopy images (normal, vocal nodule, polyps, leukoplakia and malignancy) were collected to develop and test a convolutional neural network (CNN)-based classifier. A comparison between the proposed CNN-based classifier and the clinical visual assessments (CVAs) by 12 otolaryngologists was conducted. Results: In the independent testing dataset, an overall accuracy of 96.24% was achieved; for leukoplakia, benign, malignancy, normal, and vocal nodule, the sensitivity and specificity were 92.8% vs. 98.9%, 97% vs. 99.7%, 89% vs. 99.3%, 99.0% vs. 99.4%, and 97.2% vs. 99.1%, respectively. Furthermore, when compared with CVAs on the randomly selected test dataset, the CNN-based classifier outperformed physicians for most laryngeal conditions, with striking improvements in the ability to distinguish nodules (98% vs. 45%, P <.001), polyps (91% vs. 86%, P <.001), leukoplakia (91% vs. 65%, P <.001), and malignancy (90% vs. 54%, P <.001). Conclusions: The CNN-based classifier can provide a valuable reference for the diagnosis of laryngeal neoplasms during laryngoscopy, especially for distinguishing benign, precancerous, and cancer lesions. Level of Evidence: NA Laryngoscope, 130:E686–E693, 2020