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Background: As hypertensive heart disease (HHD) presents a significant public health challenge globally, we analysed its global, regional, and national burdens and trends from 1990 to 2019. Methods: We used data from the Global Burden of Disease (GBD) 2019 study, focussing on the age-standardised prevalence rates (ASPRs) of HHD prevalence, age-standardised disability-adjusted life year (DALY) rates, average annual percentage change (AAPC), and risk factor attributions. We compared the HHD burden across sociodemographic index (SDI) strata, gender, age groups, and 204 countries and territories. Results: In 2019, the global prevalence of HHD was estimated at 18 598 thousand cases, with DALYs reaching 21 508 thousand. From 1990 to 2019, the ASPRs increased (AAPC = 0.21; 95% confidence interval (CI) = 0.17, 0.24), while the age-standardised DALY rates decreased (AAPC = -0.45; 95% CI = -1.23, -0.93). We observed the highest increase in ASPRs in high-middle SDI quantile countries, and an overall negative correlation between age-standardised DALY rates and SDI. Individuals above 70 years of age were the most affected, particularly elderly women. There has been a significant increase in HHD burden attributed to high body mass index (BMI) since 1990. The burden of HHD is concentrated in the middle SDI quintile, with population ageing and growth being major drivers for the increase in DALYs. We identified opportunities for reducing age-standardised DALY rates in the middle SDI quintile or lower. Conclusion: Despite a declining trend in the age-standardised DALY rates, the ASPRs of HHD continue to rise, especially in high-middle SDI regions. Meanwhile, countries in middle and lower SDI quintiles face a higher burden of age-standardised DALY rates. Targeted attention towards elderly women and controlling high BMI, alongside enhancing hypertension and HHD management awareness, is crucial for reducing the global burden of HHD.

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The upper and lower respiratory tract may share microbiome because they are directly continuous, and the nasal microbiome contributes partially to the composition of the lung microbiome. But little is known about the upper and lower airway microbiome of early postoperative lung transplant recipients (LTRs). Using 16S rRNA gene sequencing, we compared paired nasal swab (NS) and bronchoalveolar lavage fluid (BALF) microbiome from 17 early postoperative LTRs. The microbiome between the two compartments were significantly different in Shannon diversity and beta diversity. Four and eight core NS-associated and BALF-associated microbiome were identified, respectively. NS samples harbored more Corynebacterium, Acinetobacter, and Pseudomonas, while BALF contained more Ralstonia, Stenotrophomonas, Enterococcus, and Pedobacter. The within-subject dissimilarity was higher than the between-subject dissimilarity, indicating a greater impact of sampling sites than sampling individuals on microbial difference. There were both difference and homogeneity between NS and BALF microbiome in early postoperative LTRs. High levels of pathogens were detected in both samples, suggesting that both of them can reflect the diseases characteristics of transplanted lung. The differences between upper and lower airway microbiome mainly come from sampling sites instead of sampling individuals. IMPORTANCE: Lung transplantation is the only therapeutic option for patients with end-stage lung disease, but its outcome is much worse than other solid organ transplants. Little is known about the NS and BALF microbiome of early postoperative LTRs. Here, we compared paired samples of the nasal and lung microbiome from 17 early postoperative LTRs and showed both difference and homogeneity between the two samples. Most of the "core" microbiome in both NS and BALF samples were recognized respiratory pathogens, suggesting that both samples can reflect the diseases characteristics of transplanted lung. We also found that the differences between upper and lower airway microbiome in early postoperative LTRs mainly come from sampling sites instead of sampling individuals.

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Infection and rejection are the two most common complications after lung transplantation (LT) and are associated with increased morbidity and mortality. We aimed to examine the association between the airway microbiota and infection and rejection in lung transplant recipients (LTRs). Here, we collected 181 sputum samples (event-free, n = 47; infection, n = 103; rejection, n = 31) from 59 LTRs, and performed 16S rRNA gene sequencing to analyze the airway microbiota. A significantly different airway microbiota was observed among event-free, infection and rejection recipients, including microbial diversity and community composition. Nineteen differential taxa were identified by linear discriminant analysis (LDA) effect size (LEfSe), with 6 bacterial genera, Actinomyces, Rothia, Abiotrophia, Neisseria, Prevotella, and Leptotrichia enriched in LTRs with rejection. Random forest analyses indicated that the combination of the 6 genera and procalcitonin (PCT) and T-lymphocyte levels showed area under the curve (AUC) values of 0.898, 0.919 and 0.895 to differentiate between event-free and infection recipients, event-free and rejection recipients, and infection and rejection recipients, respectively. In conclusion, our study compared the airway microbiota between LTRs with infection and acute rejection. The airway microbiota, especially combined with PCT and T-lymphocyte levels, showed satisfactory predictive efficiency in discriminating among clinically stable recipients and those with infection and acute rejection, suggesting that the airway microbiota can be a potential indicator to differentiate between infection and acute rejection after LT. IMPORTANCE Survival after LT is limited compared with other solid organ transplantations mainly due to infection- and rejection-related complications. Differentiating infection from rejection is one of the most important challenges to face after LT. Recently, the airway microbiota has been reported to be associated with either infection or rejection of LTRs. However, fewer studies have investigated the relationship between airway microbiota together with infection and rejection of LTRs. Here, we conducted an airway microbial study of LTRs and analyzed the airway microbiota together with infection, acute rejection, and clinically stable recipients. We found different airway microbiota between infection and acute rejection and identify several genera associated with each outcome and constructed a model that incorporates airway microbiota and clinical parameters to predict outcome. This study highlighted that the airway microbiota was a potential indicator to differentiate between infection and acute rejection after LT.

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Dysbiotic airway microbiota play important roles in the inflammatory progression of asthma, and exploration of airway microbial interactions further elucidates asthma pathogenesis. However, little is known regarding the airway bacterial-fungal interactions in asthma patients. We conducted a cross-sectional survey of the sputum bacterial and fungal microbiota from 116 clinically stable asthma patients and 29 healthy controls using 16S rRNA gene and ITS1 sequencing. Compared with healthy individuals, asthma patients exhibited a significantly altered microbiota and increased bacterial and fungal alpha diversities in the airway. Microbial genera Moraxella, Capnocytophaga, and Ralstonia (bacteria) and Schizophyllum, Candida, and Phialemoniopsis (fungi) were more abundant in the asthma airways, while Rothia, Veillonella and Leptotrichia (bacteria) and Meyerozyma (fungus) were increased in healthy controls. The Moraxellaceae family and their genus Moraxella were significantly enriched in asthma patients compared with healthy controls (80.5-fold, P = 0.007 and 314.7-fold, P = 0.027, respectively). Moreover, Moraxellaceae, along with Schizophyllum, Candida, and Aspergillus (fungal genera), were positively associated with fungal alpha diversity. Correlation networks revealed 3 fungal genera (Schizophyllum, Candida, and Aspergillus) as important airway microbes in asthma that showed positive correlations with each other and multiple co-exclusions with other common microbiota. Moraxellaceae members were positively associated with asthma-enriched fungal taxa but negatively related to several healthy-enriched bacterial taxa. Collectively, our findings revealed an altered microbiota and complex microbial interactions in the airways of asthma patients. The Moraxellaceae family and their genus Moraxella, along with 3 important fungal taxa, showed significant interactions with the airway microbiota, providing potential insights into the novel pathogenic mechanisms of asthma.

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The skin microbiome plays important roles in the pathogenesis and development of acne. We aimed to investigate the facial skin microbiome of acne and microbiome differences related to different grades of acne. Skin swabs from nine healthy controls and 67 acne patients were collected, and the skin microbiomes were analyzed using 16S rRNA gene sequencing. Compared with healthy controls, acne patients harbored significantly altered skin microbiomes. The skin microbiomes of patients with grade 1-3 acne were similar, but patients with grade 4 acne showed a significantly different skin microbiome compared with grade 1-3 acne, including increased alpha diversity and increased proportions of four Gram-negative bacteria (Faecalibacterium, Klebsiella, Odoribacter and Bacteroides). In conclusion, acne patients harbored an altered skin microbiome, and more significant dysbiosis was found in patients with grade 4 acne (severe acne). Our findings may provide evidence for the pathogenic mechanisms of acne and microbial-based strategies to avoid and treat acne, especially grade 4 acne.

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There is a continuing interest in the analysis of gene architecture and gene expression to determine the relationship that may exist. Advances in high-quality sequencing technologies and large-scale resource datasets have increased the understanding of relationships and cross-referencing of expression data to the large genome data. Although a negative correlation between expression level and gene (especially transcript) length has been generally accepted, there have been some conflicting results arising from the literature concerning the impacts of different regions of genes, and the underlying reason is not well understood. The research aims to apply quantile regression techniques for statistical analysis of coding and noncoding sequence length and gene expression data in the plant, Arabidopsis thaliana, and fruit fly, Drosophila melanogaster, to determine if a relationship exists and if there is any variation or similarities between these species. The quantile regression analysis found that the coding sequence length and gene expression correlations varied, and similarities emerged for the noncoding sequence length (5' and 3' UTRs) between animal and plant species. In conclusion, the information described in this study provides the basis for further exploration into gene regulation with regard to coding and noncoding sequence length.

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The information of copy number alterations (gains and losses) in tumour genomes can be used to discovery cancer-causing genes. The estimate of copy number can be obtained from the estimate copy number ratio. The higher the depth of underlying sequencing data, the more accurate the estimate of copy number ratio. At the same time, the higher depth of a sequencing data used in copy number analysis, the more cost of data analysis. To develop a method for identifying a necessary depth of sequencing data for copy number analysis before test data are produced is of interest. In this paper, we proposed an algorithm of equal acceptance regions for detecting copy number ratios. This algorithm can be used to determine the depth of sequencing data required for copy number analysis.

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In the title compound, [CoCl(C(10)H(7)N(3)S)(2)]Cl·2H(2)O, the Co(II) atom is five-coordinated by four N atoms from two chelating 2-(1,3-thia-zol-4-yl)-1H-benzimidazole ligands and one Cl atom in a distorted trigonal-bipyramidal geometry. In the crystal, N-H⋯O and O-H⋯Cl hydrogen bonds and π-π inter-actions between the thia-zole, imidazole and benzene rings [centroid-to-centroid distances 3.546 (2), 3.683 (2) and 3.714 (2) Å] link the complex cations, chloride anions and uncoordinating water mol-ecules into a three-dimensional network.

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In the centrosymmetric title compound, [Cu(2)(C(10)H(8)O(4))Cl(2)(C(10)H(8)N(2))(2)(H(2)O)(2)]·2H(2)O, the Cu(II) atom is five-coordinated in a distorted square-pyramidal geometry by two N atoms from a chelating 2,2'-bipyridine ligand, one O atom from a 1,4-phenyl-enediacetate ligand, one Cl atom and one water mol-ecule. The 1,4-phenyl-enediacetate ligand, lying on an inversion center, bridges two Cu(II) atoms. In the crystal, O-H⋯O and O-H⋯Cl hydrogen bonds and π-π inter-actions between the pyridine rings [centroid-centroid distance = 3.740 (5) Å] link the complex mol-ecules and uncoordinated water mol-ecules into a three-dimensional network.

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The availability of genomic DNA and cDNA sequence data has escalated the data mining and genomics era. We aim to investigate the length distributions of the non-coding and coding regions of protein genes of two model organisms, Arabidopsis thaliana and Drosophila melanogaster. A non-linear functional relationship model was applied and strong correlation was found between the Coding Sequence (CDS) and non-coding sequence regions, conditional on the 5' UTR data. Significant differences were found between the protein functional classes and each gene region. Examination of the non-coding and coding regions of these organisms has revealed possible correlations.

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OBJECTIVE: To understand the occurrence and development of adolescent students' type 2 diabetes mellitus (T2DM) by researching the characteristics of the adolescent students' impaired fasting glucose (IFG) and impaired glucose tolerance (IGT) effected by overweight or obesity. METHODS: From May to November 2007, 3856 middle school students aged 11 to 18 years old in Dongguan city were enrolled in the study. Overweight or obesity (b/Ob) depended on three indexes: the national unified school-age children and adolescent students' body mass index (BMI) and the temporary screening classification standard II established by the Working Group on Obesity in China, BP > or = 140/90 mm Hg (1mm Hg = 0.133 kPa) and fasting capillary whole glucose which was greater than or equal to 5.6 mmol/L. The fasting capillary whole glucose was screened by blood glucose meter from fingertips. Students who had any abnormal indexes were brought into this study. On basis of voluntary principle, blood lipid, fasting blood glucose (FPG) and 2-hour postprandial blood glucose (2 h PG), fasting insulin (FIns) of 368 male and 326 female students who conformed to these conditions were measured using their venous blood. By temporary BMI standard II, they were divided into overweight group (b) and obesity group (Ob). Data of different age groups (11 to 14; 15 to 18 years old) was analyzed. RESULTS: The BMI, low density lipoprotein cholesterol (LDL-C), insulin resistance index (IR), IFG and IGT of the same age stage in two groups were compared. The BMI value was (22.1 +/- 2.4) kg/m2, LDL-C was (2.38 +/- 0.65) mmol/L, IR was 1.15 +/- 0.58 and the detection rates of IFG and IGT were 3.5% and 1.4% respectively in female students aged 11 to 14 years old in b group. In Ob group, BMI value was (24.4 +/- 3.9) kg/m2, LDL-C was (2.70 +/- 0.73) mmol/L, IR was 1.36 +/- 0.67 and the detection rates of IFG and IGT were 14.6% and 6.3% respectively. t or chi2 values of two groups which were compared were 4.83, 2.45, 2.10, 7.41 and 7.99 (P < 0.01 or P < 0.05). BMI value was (25.8 +/- 3.1) kg/m2, LDL-C was (2.35 +/- 0.62) mmol/L, IR was 1.14 +/- 0.64 and the detection rates of IFG and IGT were 3.1% and 4.1% respectively in 15 to 18 years old in b group. In Ob group, BMI value was (28.0 +/- 4.3) kg/m2, LDL-C was (2.69 +/- 0.69) mmol/L, IR was 1.43 +/- 0.84 and the detection rates of IFG and IGT were 12.8% and 15.4% respectively. t or chi2 values of two groups which were compared were 3.33, 2.79, 1.87, 4.75 and 5.17 (P < 0.01 or P < 0.05). BMI value was (22.4 +/- 2.3) kg/m2, LDL-C was (2.36 +/- 0.67) mmol/L, IR was 1.19 +/- 0.65 and the detection rates of IFG and IGT were 3.6% and 1.8% respectively in male students of 11 to 14 years old in b group. In Ob group, BMI value was (24.6 +/- 4.2) kg/m2, LDL-C was (2.68 +/- 0.71) mmol/L, IR was 1.44 +/- 0.89 and the detection rates of IFG and IGT were 13.3% and 9.4% respectively. t or chi2 values of two groups which were compared were 4.85, 2.72, 2.19, 6.75 and 6.76 (P < 0.01 or P < 0.05). BMI value was (26.4 +/- 2.8) kg/m2, LDL-C was (2.35 +/- 0.70) mmol/L, IR was 1.24 +/- 0.68 and the detection rates of IFG and IGT were 4.7% and 5.6% respectively in 15 to 18 years old in b group. In Ob group, BMI value was (28.2 +/- 4.8) kg/m2, LDL-C was (2.71 +/- 0.73) mmol/L, IR was 1.50 +/- 0.95 and the detection rates of IFG and IGT were 17.9% and 17.9% respectively. t or chi2 values of two groups which were compared were 2.80, 2.69, 1.84, 6.68 and 6.27 (P < 0.01 or P < 0.05). The male students' FPG of 11 to 14 years old in b group was (4.88 +/- 0.76) mmol/L and FPG of Ob group was (5.09 +/- 0.80) mmol/L. Two groups were compared and t = 1.84 (P < 0.05). The statistical differences were all observed. We compared different age stages and found that the male students' 2-hour PG of 11 to 14 years old in Ob group was (5.13 +/- 1.18) mmol/L and the 2-hour PG of 15 to 18 years old was (5.36 +/- 1.24) mmol/L. Two groups were compared and t = 1.78 (P < 0.05) near the adults value. Male students' IGT of 11 to 14 years old (b/Ob) had 8 positive cases and the positive detection rate was 3.6%. IGT of 15 to 18 years old (b/Ob) had 13 positive cases and the positive detection rate was 8.9%. Two age stages were compared and chi2 = 6.86 (P < 0.01). Female students' IGT of 11 to 14 years old (b/Ob) had 5 positive cases and the positive detection rate was 2.6%. IGT of 15 to 18 years old (b/Ob) had 10 positive cases and the positive detection rate was 7.4%. Two age stages were compared and chi2 = 4.02 (P < 0.05). All had statistical significance. The high IGT incidence rate of b/Ob group's male and female students was in the stage of 15 - 18 years old. Male students were more obvious. CONCLUSION: T2DM prevention among adolescent students should start with body overweight control. Meanwhile, the adolescent students with high risk factors should be screened regularly and early measures should be taken to prevent the impaired glucose regulation (IFG, IGT) transforming into T2DM.

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A sensitive fluorescence quantitative determination for bovine serum albumin (BSA) or human serum albumin (HSA) has been developed by using a new hydrophilic cyanine dye 1, 1'-sulfonopropyl-3,3,3', 3'-tetramethylindolium-5,5'-disulfonic potassium (STDP) as a fluorescence probe. Using BSA as a representative protein, characteristics of the fluorescence reaction of STDP with protein were investigated. Effects of the concentration of the hydrophilic cyanine dye, pH value of the buffer solution, and ion-intensity of NaCl were also studied as well as the ratio of ethanol. In the citrate-HCl buffer solution, the fluorescence emission wavelength of BSA-STDP system was 562 nm with the maximum excitation wavelength of 548 nm, and the Stokes displacement was 14 nm. With the pH ranging from 1.0 to 2.0, the fluorescence was increasing and up to the maximum at pH 2.0. However, in the pH range of 3.0-5.0, the interaction of BSA and STDP was weakened due to the decrease in positive charge on the BSA chain, which resulted in an observable decrease of the enhancement of the fluorescence intensity. At the optimum pH of 2.0, electrostatic interactions of positive charges of the BSA chain and negative charges on the sulfonic groups of STDP were carried out. The interactions of the indole group of STDP and some active groups of BSA (viz. amido, carboxyl or sulfhydryl) were also achieved, and resulted in the combination of indole group of cyanine dye into the chain of BSA. So the hydrophobic effect and the protection provided by the skeleton chain of BSA were both improved to prevent the fluorescent energy of STDP from losing in the solution, which caused a notable fluorescence increase with an observable shift to the longer emission wavelength. Furthermore, with the augmentation of BSA, the alpha-helix structure of BSA molecular turned from the unwrapped state to the enfolded state, in favor of restraining free-oscillation of fluorescence probe in the solution and maintaining a high energy transfer efficiency. Such a fact fueled a highly enhancement of the fluorescence too. Besides, effects of the concentration of cyanine dye on the determination of BSA were also investigated. The fluorescence intensity (DeltaF) was enhanced with the increase in the quantity of STDP and gained the peak at 1.00 micromol x L(-1). However, when STDP ranged from 1.50 to 5.00 micromol x L(-1), some negative congregate effects on the nature of cyanine dye might happen and resulted in a too high fluorescence background. A rapid decrease of the fluorescence intensity was observed. The effects of ion-intensity of NaCl and ethanol on the fluorescence of BSA-STDP system were obvious. Though the fluorescence still remained high at the level of NaCl of 0.025 mol x L(-1), a rapid decrease happen at the level of NaCl from 0.05 to 0.15 mol x L(-1). With the addition of ethanol, the dissolvation capacity of both STDP and BSA was improved and their interactions were accelerated. An increasing fluorescence with the augment of ethanol was obtained and the maximum was achieved with the ratio of ethanol at 10%. Influences of coexistent substances such as amino acid, metal ions such as Cu2+, Na+, Ca2+, Mg2+, Al3+ and Fe3+ were also investigated. Most substances had no notable influences on the determination of BSA except Fe3+ and Cu2+ ions. Under the optimum conditions, the fluorescence of STDP was enhanced markedly with the addition of the BSA or HSA protein. Good calibration curves of the proteins were obtained in the range of 0.20-15.00 microg x mL(-1) for BSA and 0.20-12.00 microg x mL(-1) for HSA with detection limits (3sigma/K) of 0.01 microg x mL(-1). Applied to simulant BSA samples, this method was adaptable. And the results were satisfied with good recoveries ranging from 94.5% to 103.3% at the revels of 4.00, 6.00 and 8.00 microg x mL(-1) respectively.

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