Supra-additive effect of chronic inflammation and atherogenic dyslipidemia on developing type 2 diabetes among young adults: A prospective cohort study

Background: Both elevated inflammation and atherogenic dyslipidemia are prominent in young-onset diabetes and are increasingly identified as biologically intertwined processes that contribute to diabetogenesis. We aimed to investigate the age-specific risks of type 2 diabetes (T2D) upon concomitant chronic inflammation and atherogenic dyslipidemia. Methods: Age-stratified Cox regression analysis of the risk of incident diabetes upon co-exposure to time-averaged cumulative high-sensitivity C-reactive protein (CumCRP) and atherogenic index of plasma (CumAIP) among 42,925 nondiabetic participants from a real-world, prospective cohort (Kailuan Study). Results: During a median 6.41 years of follow-up, 3987 T2D developed. Isolated CumAIP and CumCRP were significantly associated with incident T2D in the entire cohort and across all age subgroups. Both CumAIP and CumCRP were jointly associated with an increased risk of diabetes (P-interaction = 0.0126). Compared to CumAIP \u3c -0.0699 and CumCRP \u3c 1 mg/L, co-exposure to CumAIP ≥ − 0.0699 and CumCRP ≥ 3 mg/L had a significant hazard ratio (HR) [2.55 (2.23–2.92)] after adjusting for socio-demographic, life-style factors, family history of diabetes, blood pressure, renal function and medication use. The co-exposure-associated risks varied greatly by age distribution (P-interaction = 0.0193): \u3c 40 years, 6.26 (3.47–11.28); 40–49 years, 2.26 (1.77–2.89); 50–59 years, 2.51 (2.00–3.16); 60–69 years, 2.48 (1.86–3.30); ≥ 70 years, 2.10 (1.29–3.40). In young adults ( \u3c 45 years), both exposures had a significant supra-additive effect on diabetogenesis (relative excess risk due to interaction: 0.80, 95% CI 0.10–1.50). Conclusions: These findings highlight the need for age-specific combined assessment and management of chronic inflammation and dyslipidemia in primary prevention against T2D, particularly for young adults. The clinical benefit derived from dual-target intervention against dyslipidemia and inflammation will exceed the sum of each part alone in young adults

Finishing the euchromatic sequence of the human genome

The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead

A Systematic Review on the Status and Progress of Homomorphic Encryption Technologies

With the emergence of big data and the continued growth in cloud computing applications, serious security and privacy concerns emerged. Consequently, several researchers and cybersecurity experts have embarked on a quest to extend data encryption to big data systems and cloud computing applications. As most cloud users turn to using public cloud services, confidentiality becomes and even more complicated issue. Cloud clients storing their data on a public cloud always seek solutions to confidentiality problem. Homomorphic encryption emerged as a possible solution where client’s data is encrypted on the cloud in a way that allows some search and manipulation operations without proper decryption. In this paper, we present a systematic review of research paper published in the field of homomorphic encryption. This paper uses PRISMA checklist alongside some items of Cochrane’s Quality Assessment to review studies retrieved from various resources. It was highly noticeable in the reviewed papers that security in big data and cloud computing has received most attention. Most papers suggested the use of homomorphic encryption although the thematic analysis has identified other potential concerns. Regarding the quality of the articles, 38% of the articles failed to meet three checklist items, including explicit statement of research objectives, procedure recognition and sources of funding used in the study. The review also presented compendium textual analysis of different homomorphic encryption algorithms, application areas, and areas of future developments. Results of the evaluation through PRISMA and the Cochrane tool showed that a majority of research articles discussed the potential use and application of Homomorphic Encryption as a solution to the growing demands of big data and absence of security and privacy mechanisms therein. This was evident from 26 of the total 59 articles that met the inclusion criteria. The term Homomorphic Encryption appeared 1802 times in the word cloud derived from the selected articles, which speaks of its potential to ensure security and privacy, while also preserving the CIA triad in the context of big data and cloud computing

High Levels of Zinc Affect Nitrogen and Phosphorus Transformation in Rice Rhizosphere Soil by Modifying Microbial Communities

Due to global industrialization in recent decades, large areas have been threatened by heavy metal contamination. Research about the impact of excessive Zn on N and P transformation in farmland has received little attention, and its mechanism is still not completely known. In this study, we planted rice in soils with toxic levels of Zn, and analyzed the plant growth and nutrient uptake, the N and P transformation, enzyme activities and microbial communities in rhizosphere soil to reveal the underlying mechanism. Results showed high levels of Zn severely repressed the plant growth and uptake of N and P, but improved the N availability and promoted the conversion of organic P into inorganic forms in rice rhizosphere soil. Moreover, high levels of Zn significantly elevated the activities of hydrolases including urease, protease, acid phosphatase, sucrase and cellulose, and dehydrogenase, as well as the abundances of Flavisolibacter, Sphingomonas, Gemmatirosa, and subgroup_6, which contributed to the mineralization of organic matter in soil. Additionally, toxic level of Zn repressed the nitrifying process by decreasing the abundance of nitrosifying bacteria Ellin6067 and promoted denitrification by increasing the abundance of Noviherbaspirillum, which resulted in decreased NO3− concentration in rice rhizosphere soil under VHZn condition

Treatment of Alcohols with Tosyl Chloride Does Not always Lead to the Formation of Tosylates

Treatment of substituted benzyl alcohols with tosyl chloride resulted in the formation of the corresponding chlorides, not the usual tosylates. A series of experiments demonstrated that it was possible to predict whether chlorination or tosylation would occur for substituted benzyl alcohols and pyridine methanols. Treatment of electron withdrawing group-substituted benzyl alcohols with tosyl chloride gave the corresponding chlorides in moderate yields under mild conditions, which provided a simple way to directly prepare chlorides from alcohols

Artificial luminescent protein as a bioprobe for time-gated luminescence bioimaging

An artificial luminescent protein, apoferritin-encapsulated luminescent europium complex, has been designed/fabricated and displays good biocompatibility and long-lived luminescence, which means it can be used as a bioprobe to image living cells with a time-gated mode

Variations in bacterial diversity and community structure in the sediments of an alkaline lake in Inner Mongolia plateau, China

Alkaline lakes are a special aquatic ecosystem that act as important water and alkali resource in the arid-semiarid regions. The primary aim of the study is to explore how environmental factors affect community diversity and structure, and to find whether there are key microbes that can indicate changes in environmental factors in alkaline lakes. Therefore, four sediment samples (S1, S2, S3, and S4) were collected from Hamatai Lake which is an important alkali resource in Ordos’ desert plateau of Inner Mongolia. Samples were collected along the salinity and alkalinity gradients and bacterial community compositions were investigated by Illumina Miseq sequencing. The results revealed that the diversity and richness of bacterial community decreased with increasing alkalinity (pH) and salinity, and bacterial community structure was obviously different for the relatively light alkaline and hyposaline samples (LAHO; pH 8.5; salinity > 20‰). Firmicutes, Proteobacteria and Bacteriodetes were observed to be the dominant phyla. Furthermore, Acidobacteria, Actinobacteria, and low salt-tolerant alkaliphilic nitrifying taxa were mainly distributed in S1 with LAHO characteristic. Firmicutes, Clostridia, Gammaproteobacteria, salt-tolerant alkaliphilic denitrifying taxa, haloalkaliphilic sulfur cycling taxa were mainly distributed in S2, S3 and S4, and were well adapted to haloalkaline conditions. Correlation analysis revealed that the community diversity (operational taxonomic unit numbers and/or Shannon index) and richness (Chao1) were significantly positively correlated with ammonium nitrogen (r = 0.654, p < 0.05; r = 0.680, p < 0.05) and negatively correlated with pH (r = −0.924, p < 0.01; r = −0.800, p < 0.01; r = −0.933, p < 0.01) and salinity (r = −0.615, p < 0.05; r = −0.647, p < 0.05). A redundancy analysis and variation partitioning analysis revealed that pH (explanation degrees of 53.5%, pseudo-F = 11.5, p < 0.01), TOC/TN (24.8%, pseudo-F = 10.3, p < 0.05) and salinity (9.2%, pseudo-F = 9.5, p < 0.05) were the most significant factors that caused the variations in bacterial community structure. The results suggested that alkalinity, nutrient salt and salinity jointly affect bacterial diversity and community structure, in which one taxon (Acidobacteria), six taxa (Cyanobacteria, Nitrosomonadaceae, Nitrospira, Bacillus, Lactococcus and Halomonas) and five taxa (Desulfonatronobacter, Dethiobacter, Desulfurivibrio, Thioalkalivibrio and Halorhodospira) are related to carbon, nitrogen and sulfur cycles, respectively. Classes Clostridia and Gammaproteobacteria might indicate changes of saline-alkali conditions in the sediments of alkaline lakes in desert plateau

Quantitative Inversion Modeling Method for Grading Deerni Copper Deposits Based on Visible and Near-Infrared Hyperspectral Data

Quantitative metal grade inversion based on hyperspectral data is an effective approach to achieve the real-time in situ determination of ore body grades and has the advantages of low cost compared with traditional chemical analysis methods. However, the redundant nature of hyperspectral data and the parameter-limiting nature of machine learning algorithms reduce the modeling accuracy and precision, resulting in severe limitations on the application of hyperspectral techniques for the grade inversion of Deerni copper ore bodies. In this paper, we first obtained visible-NIR hyperspectral data for 190 ore samples using a spectrometer and determined the copper content of the sample set using chemical analysis; then, we processed the raw hyperspectral data using three dimensionality reduction algorithms and optimized a BP neural network based on an evolutionary algorithm. Finally, a Deerni copper grade inversion model was established using the hyperspectral data before and after dimensionality reduction, and the inversion accuracy and precision was compared and analyzed with that obtained by the BP neural network, the random forest and the variable hidden layer nodes models. The combination of the LLE dimensionality reduction algorithm and the optimized BP neural network algorithm achieves the highest modeling precision, with an R2 of 0.950

IGF2BP3 drives gallbladder cancer progression by m6A-modified CLDN4 and inducing macrophage immunosuppressive polarization

Introduction: N6-methyladenosine (m6A) is an emerging epigenetic modification, which plays a crucial role in the development of cancer. Nevertheless, the underlying mechanism of m6A-associated proteins and m6A modification in gallbladder cancer remains largely unknown. Materials and methods: The Gene Expression Omnibus database and tissue microarray were used to identify the key m6A-related gene in gallbladder cancer. The function and mechanism of IGF2BP3 were further investigated by knockdown and overexpression techniques in vitro and in vivo. Results: We found that IGF2BP3 was elevated and correlated with poor prognosis in gallbladder cancer, which can be used as an independent prognostic factor for gallbladder cancer. IGF2BP3 accelerated the proliferation, invasion and migration of gallbladder cancer cells in vitro and in vivo. Mechanistically, IGF2BP3 interacted with and augmented the stability of CLDN4 mRNA by m6A modification. Enhancement of CLDN4 reversed the inhibitory effect of IGF2BP3 deficiency on gallbladder cancer. Furthermore, we demonstrated that IGF2BP3 promotes the activation of NF-κB signaling pathway by up-regulation of CLDN4. Overexpression of IGF2BP3 in gallbladder cancer cells obviously promoted the polarization of immunosuppressive phenotype in macrophages. Besides, Gallbladder cancer cells-derived IGF2BP3 up-regulated the levels of STAT3 in M2 macrophages, and promoted M2 polarization. Conclusions: We manifested IGF2BP3 promotes the aggressive phenotype of gallbladder cancer by stabilizing CLDN4 mRNA in an m6A-dependent manner and induces macrophage immunosuppressive polarization, which might offer a new theoretical basis for against gallbladder cancer