Delivering universal health coverage for an aging population : an analysis of the Chinese rural health insurance program

There is now high level international commitment to the goal of universal health coverage. But how can countries make this a reality in the face of a limited budget and an aging population? Since 2008, China has been rolling out an ambitious reform program, which aims to achieve affordable health insurance coverage for all Chinese citizens. Under this reform program, Chinese living in rural areas are eligible to enroll in a subsidized scheme called the New Cooperative Medical System (NCMS). Using a three stage game model involving a government, a private fund manager and population, we explore the impact of population aging on NCMS. Our model highlights the role of government regulation and subsidy in ensuring operation efficiency of the system. We show that at optimality the government sets the operating framework for the fund manager to constrain the potential for monopoly profits. The Government subsidizes the scheme to prevent an adverse selection death spiral. However, the effectiveness of the subsidy in achieving this goal is moderated by the age structure of the population. Our model gives insights into the strengths of the NCMS framework and also can be used to support decisions about resource allocation and understand how scheme dynamics may unfold as the Chinese population ages further

Suppression of self-discharge in a non-flowing bromine battery via <i>in situ </i>generation of countercharged groups

Bromine is attractive for next-generation energy-storage systems because of its high capacity and natural abundance. However, because of issues relating to self-discharging processes, prototypes involving bromide/bromine redox couples are largely limited to the design of flow cells. Here we propose a method to exploit bromine redox chemistry and demonstrate the feasibility of mitigating ion depletion in a stationary device. A cell using polyaniline vapor-grown carbon fiber (PANI-VGCF) as the electrode material exhibits close to 100% Coulombic efficiency at a low current density (50 mA/g). Electrochemical results, operando Raman spectroscopy, and theoretical analysis provide clues that the strong interaction between protonated PANI and Br−/ Br3− makes their decoupling unfavorable, thereby suppressing self-discharge processes. This strategy could be utilized for rational design of other conjugated materials/bromine systems without self-discharge issues

PTPRO-related CD8⁺ T-cell signatures predict prognosis and immunotherapy response in patients with breast cancer

Background: Poor immunogenicity and extensive immunosuppressive T-cell infiltration in the tumor immune microenvironment (TIME) have been identified as potential barriers to immunotherapy success in “immune-cold” breast cancers. Thus, it is crucial to identify biomarkers that can predict immunotherapy efficacy. Protein tyrosine phosphatase receptor type O (PTPRO) regulates multiple kinases and pathways and has been implied to play a regulatory role in immune cell infiltration in various cancers. Methods: ESTIMATE and single-sample gene set enrichment analysis (ssGSEA) were performed to uncover the TIME landscape. The correlation analysis of PTPRO and immune infiltration was performed to characterize the immune features of PTPRO. Univariate and multivariate Cox analyses were applied to determine the prognostic value of various variables and construct the PTPRO-related CD8+ T-cell signatures (PTSs). The Kaplan–Meier curve and the receiver operating characteristic (ROC) curve were used to estimate the performance of PTS in assessing prognosis and immunotherapy response in multiple validation datasets. Results: High PTPRO expression was related to high infiltration levels of CD8+ T cells, as well as macrophages, activated dendritic cells (aDCs), tumor-infiltrating lymphocytes (TILs), and Th1 cells. Given the critical role of CD8+ T cells in the TIME, we focused on the impact of PTPRO expression on CD8+ T-cell infiltration. The prognostic PTS was then constructed using the TCGA training dataset. Further analysis showed that the PTS exhibited favorable prognostic performance in multiple validation datasets. Of note, the PTS could accurately predict the response to immune checkpoint inhibitors (ICIs). Conclusion: PTPRO significantly impacts CD8+ T-cell infiltration in breast cancer, suggesting a potential role of immunomodulation. PTPRO-based PTS provides a new immune cell paradigm for prognosis, which is valuable for immunotherapy decisions in cancer patients

Estimation of the Age and Amount of Brown Rice Plant Hoppers Based on Bionic Electronic Nose Use

The brown rice plant hopper (BRPH), Nilaparvata lugens (Stal), is one of the most important insect pests affecting rice and causes serious damage to the yield and quality of rice plants in Asia. This study used bionic electronic nose technology to sample BRPH volatiles, which vary in age and amount. Principal component analysis (PCA), linear discrimination analysis (LDA), probabilistic neural network (PNN), BP neural network (BPNN) and loading analysis (Loadings) techniques were used to analyze the sampling data. The results indicate that the PCA and LDA classification ability is poor, but the LDA classification displays superior performance relative to PCA. When a PNN was used to evaluate the BRPH age and amount, the classification rates of the training set were 100% and 96.67%, respectively, and the classification rates of the test set were 90.67% and 64.67%, respectively. When BPNN was used for the evaluation of the BRPH age and amount, the classification accuracies of the training set were 100% and 48.93%, respectively, and the classification accuracies of the test set were 96.67% and 47.33%, respectively. Loadings for BRPH volatiles indicate that the main elements of BRPHs’ volatiles are sulfur-containing organics, aromatics, sulfur-and chlorine-containing organics and nitrogen oxides, which provide a reference for sensors chosen when exploited in specialized BRPH identification devices. This research proves the feasibility and broad application prospects of bionic electronic noses for BRPH recognition

Chicken IFI6 inhibits avian reovirus replication and affects related innate immune signaling pathways

Interferon-alpha inducible protein 6 (IFI6) is an important interferon-stimulated gene. To date, research on IFI6 has mainly focused on human malignant tumors, virus-related diseases and autoimmune diseases. Previous studies have shown that IFI6 plays an important role in antiviral, antiapoptotic and tumor-promoting cellular functions, but few studies have focused on the structure or function of avian IFI6. Avian reovirus (ARV) is an important virus that can exert immunosuppressive effects on poultry. Preliminary studies have shown that IFI6 expression is upregulated in various tissues and organs of specific-pathogen-free chickens infected with ARV, suggesting that IFI6 plays an important role in ARV infection. To analyze the function of avian IFI6, particularly in ARV infection, the chicken IFI6 gene was cloned, a bioinformatics analysis was conducted, and the roles of IFI6 in ARV replication and the innate immune response were investigated after the overexpression or knockdown of IFI6 in vitro. The results indicated that the molecular weight of the chicken IFI6 protein was approximately 11 kDa and that its structure was similar to that of the human IFI27L1 protein. A phylogenetic tree analysis of the IFI6 amino acid sequence revealed that the evolution of mammals and birds was clearly divided into two branches. The evolutionary history and homology of chickens are similar to those of other birds. Avian IFI6 localized to the cytoplasm and was abundantly expressed in the chicken lung, intestine, pancreas, liver, spleen, glandular stomach, thymus, bursa of Fabricius and trachea. Further studies demonstrated that IFI6 overexpression in DF-1 cells inhibited ARV replication and that the inhibition of IFI6 expression promoted ARV replication. After ARV infection, IFI6 modulated the expression of various innate immunity-related factors. Notably, the expression patterns of MAVS and IFI6 were similar, and the expression patterns of IRF1 and IFN-β were opposite to those of IFI6. The results of this study further advance the research on avian IFI6 and provide a theoretical basis for further research on the role of IFI6 in avian virus infection and innate immunity

PathNarratives: Data annotation for pathological human-AI collaborative diagnosis

Pathology is the gold standard of clinical diagnosis. Artificial intelligence (AI) in pathology becomes a new trend, but it is still not widely used due to the lack of necessary explanations for pathologists to understand the rationale. Clinic-compliant explanations besides the diagnostic decision of pathological images are essential for AI model training to provide diagnostic suggestions assisting pathologists practice. In this study, we propose a new annotation form, PathNarratives, that includes a hierarchical decision-to-reason data structure, a narrative annotation process, and a multimodal interactive annotation tool. Following PathNarratives, we recruited 8 pathologist annotators to build a colorectal pathological dataset, CR-PathNarratives, containing 174 whole-slide images (WSIs). We further experiment on the dataset with classification and captioning tasks to explore the clinical scenarios of human-AI-collaborative pathological diagnosis. The classification tasks show that fine-grain prediction enhances the overall classification accuracy from 79.56 to 85.26%. In Human-AI collaboration experience, the trust and confidence scores from 8 pathologists raised from 3.88 to 4.63 with providing more details. Results show that the classification and captioning tasks achieve better results with reason labels, provide explainable clues for doctors to understand and make the final decision and thus can support a better experience of human-AI collaboration in pathological diagnosis. In the future, we plan to optimize the tools for the annotation process, and expand the datasets with more WSIs and covering more pathological domains

Substantial transition to clean household energy mix in rural China

The household energy mix has significant impacts on human health and climate, as it contributes greatly to many health- and climate-relevant air pollutants. Compared to the well-established urban energy statistical system, the rural household energy statistical system is incomplete and is often associated with high biases. Via a nationwide investigation, this study revealed high contributions to energy supply from coal and biomass fuels in the rural household energy sector, while electricity comprised ∼20%. Stacking (the use of multiple sources of energy) is significant, and the average number of energy types was 2.8 per household. Compared to 2012, the consumption of biomass and coals in 2017 decreased by 45% and 12%, respectively, while the gas consumption amount increased by 204%. Increased gas and decreased coal consumptions were mainly in cooking, while decreased biomass was in both cooking (41%) and heating (59%). The time-sharing fraction of electricity and gases (E&G) for daily cooking grew, reaching 69% in 2017, but for space heating, traditional solid fuels were still dominant, with the national average shared fraction of E&G being only 20%. The non-uniform spatial distribution and the non-linear increase in the fraction of E&G indicated challenges to achieving universal access to modern cooking energy by 2030, particularly in less-developed rural and mountainous areas. In some non-typical heating zones, the increased share of E&G for heating was significant and largely driven by income growth, but in typical heating zones, the time-sharing fraction was <5% and was not significantly increased, except in areas with policy intervention. The intervention policy not only led to dramatic increases in the clean energy fraction for heating but also accelerated the clean cooking transition. Higher income, higher education, younger age, less energy/stove stacking and smaller family size positively impacted the clean energy transition

A Novel Universal Primer-Multiplex-PCR Method with Sequencing Gel Electrophoresis Analysis

In this study, a novel universal primer-multiplex-PCR (UP-M-PCR) method adding a universal primer (UP) in the multiplex PCR reaction system was described. A universal adapter was designed in the 5′-end of each specific primer pairs which matched with the specific DNA sequences for each template and also used as the universal primer (UP). PCR products were analyzed on sequencing gel electrophoresis (SGE) which had the advantage of exhibiting extraordinary resolution. This method overcame the disadvantages rooted deeply in conventional multiplex PCR such as complex manipulation, lower sensitivity, self-inhibition and amplification disparity resulting from different primers, and it got a high specificity and had a low detection limit of 0.1 ng for single kind of crops when screening the presence of genetically modified (GM) crops in mixture samples. The novel developed multiplex PCR assay with sequencing gel electrophoresis analysis will be useful in many fields, such as verifying the GM status of a sample irrespective of the crop and GM trait and so on

An efficient approach to finding Siraitia grosvenorii triterpene biosynthetic genes by RNA-seq and digital gene expression analysis

<p>Abstract</p> <p>Background</p> <p><it>Siraitia grosvenorii </it>(Luohanguo) is an herbaceous perennial plant native to southern China and most prevalent in Guilin city. Its fruit contains a sweet, fleshy, edible pulp that is widely used in traditional Chinese medicine. The major bioactive constituents in the fruit extract are the cucurbitane-type triterpene saponins known as mogrosides. Among them, mogroside V is nearly 300 times sweeter than sucrose. However, little is known about mogrosides biosynthesis in <it>S. grosvenorii</it>, especially the late steps of the pathway.</p> <p>Results</p> <p>In this study, a cDNA library generated from of equal amount of RNA taken from <it>S. grosvenorii </it>fruit at 50 days after flowering (DAF) and 70 DAF were sequenced using Illumina/Solexa platform. More than 48,755,516 high-quality reads from a cDNA library were generated that was assembled into 43,891 unigenes. De novo assembly and gap-filling generated 43,891 unigenes with an average sequence length of 668 base pairs. A total of 26,308 (59.9%) unique sequences were annotated and 11,476 of the unique sequences were assigned to specific metabolic pathways by the Kyoto Encyclopedia of Genes and Genomes. cDNA sequences for all of the known enzymes involved in mogrosides backbone synthesis were identified from our library. Additionally, a total of eighty-five cytochrome P450 (CYP450) and ninety UDP-glucosyltransferase (UDPG) unigenes were identified, some of which appear to encode enzymes responsible for the conversion of the mogroside backbone into the various mogrosides. Digital gene expression profile (DGE) analysis using Solexa sequencing was performed on three important stages of fruit development, and based on their expression pattern, seven <it>CYP450</it>s and five <it>UDPG</it>s were selected as the candidates most likely to be involved in mogrosides biosynthesis.</p> <p>Conclusion</p> <p>A combination of RNA-seq and DGE analysis based on the next generation sequencing technology was shown to be a powerful method for identifying candidate genes encoding enzymes responsible for the biosynthesis of novel secondary metabolites in a non-model plant. Seven <it>CYP450</it>s and five <it>UDPG</it>s were selected as potential candidates involved in mogrosides biosynthesis. The transcriptome data from this study provides an important resource for understanding the formation of major bioactive constituents in the fruit extract from <it>S. grosvenorii</it>.</p