A validation study of data in the National Tonsil Surgery Register in Sweden: high agreement with medical records ensures that data can be used to monitor clinical practices and outcomes

Background The ambition of the National Tonsil Surgery Register in Sweden (NTSRS) is to improve otorhinolaryngological care by monitoring trends in the clinical practices, complications, and outcomes of tonsil surgery. The NTSRS collects data from both surgeons and patients and provides the participating clinics with daily updated data on a publicly available website. On the website, national and local results can be compared and monitored. The use of NTSRS data necessitates that the data is valid, but the NTSRS has not yet been validated. With approximately half of the registered patients responding to the postoperative questionnaires, an analysis of responders and non-responders is also necessary. The aim of this study was to assess the criterion validity of NTSRS data. Another aim was to compare the characteristics and rates of complications between postoperative questionnaire responders and non-responders. Methods Data in the NTSRS were compared with data in electronic medical records. The 200 most recent surgeries, up to 31 Dec 2019, in each of 11 surgical units were included. Criterion validity was analysed in terms of observed agreement, Cohens kappa, Gwet’s AC1, and positive and negative agreement. The sign test was used to analyse systematic differences between the NTSRS and the medical records. Comparisons of rates between groups were made with Fisher’s exact test, the chi-square test, and Fisher’s non-parametric permutation test. Results A total of 1991 registrations were included in the study. All variables showed very high observed agreement ranging from 0.91 to 1.00, and all variables had AC1 values corresponding to almost perfect agreement. The analysis of questionnaire responders and non-responders showed no statistically significant differences regarding age, indication, or type of surgery. The proportion of women was higher in the responder group. The rate of reoperation due to bleeding was higher in the responder group, but there were no differences regarding other complications. Conclusions The results of this study show that data in the NTSRS have criterion validity. The NTSRS is thus well suited for monitoring the clinical practices and outcomes of tonsil surgery. The quality of the data also implies that the registry can be used in both clinical improvement projects and research.

The Top 5 Causes of Death In China From 2000 To 2017

Background: Limited information is available on the epidemiological characteristics of major causes of death in the last 18 years. In this study, we investigated the epidemiological characteristics of the top 5 causes of death in China from 2000 to 2017. Methods: Data were obtained from the 18-year reports of Ministry of Health and analyzed by Grid Search Method, Permutation test, and log-linear regression model. Results: The top 5 consistent causes of death, malignant tumor, cerebrovascular disease, heart trouble, respiratory disease, trauma and toxicosis accounted for 82.6% in 2000, 86.49% in 2017 in urban areas and 83.31% in 2000, 88.34% in 2017 in rural areas. The increasing trends (P<0.05) of proportions of death of malignant tumor, cerebrovascular disease, and heart trouble have average annual percent change (AAPC) = 0.5%, 0.3%, 2.4% in urban areas and 1.7%, 1.5%, 4.3% in rural areas. The AAPCs of respiratory disease are -1.4% in urban areas and -3.6% in rural areas. Cardio-cerebrovascular disease increased (Urban: 39.02% to 43.56%, AAPC=1.3%, P<0.05; Rural: 32.03% to 45.91%, AAPC=2.7%, P<0.05) steeply from 2000 to 2017 which are higher than that of malignant tumor (P<0.05). Conclusion: The top 5 causes of death in China accounted for more than 85% of all deaths in 2017, in which cardio-cerebrovascular disease accounted for the largest proportion with the steepest increasing trend.

Metabolite Fingerprinting Using 1H-NMR Spectroscopy and Chemometrics for Classification of Three Curcuma Species from Different Origins

Curcuma longa, Curcuma xanthorrhiza, and Curcuma manga have been widely used for herbal or traditional medicine purposes. It was reported that turmeric plants provided several biological activities such as antioxidant, anti-inflammatory, hepatoprotector, cardioprotector, and anticancer activities. Authentication of the Curcuma species is important to ensure its authenticity and to avoid adulteration practices. Plants from different origins will have different metabolite compositions because metabolites are affected by soil nutrition, climate, temperature, and humidity. 1H-NMR spectroscopy, principal component analysis (PCA), and orthogonal projections to latent structures-discriminant analysis (OPLS-DA) were used for authentication of C. longa, C. xanthorrhiza, and C. manga from seven different origins in Indonesia. From the 1H-NMR analysis it was obtained that 14 metabolites were responsible for generating classification model such as curcumin, demethoxycurcumin, alanine, methionine, threonine, lysine, alpha-glucose, beta-glucose, sucrose, alpha-fructose, beta-fructose, fumaric acid, tyrosine, and formate. Both PCA and OPLS-DA model demonstrated goodness of fit (R2 value more than 0.8) and good predictivity (Q2 value more than 0.45). All OPLS-DA models were validated by assessing the permutation test results with high value of original R2 and Q2. It can be concluded that metabolite fingerprinting using 1H-NMR spectroscopy and chemometrics provide a powerful tool for authentication of herbal and medicinal plants.

The significance of time stages in different types of multiple sclerosis course for the formation of prognosis

Background. The purpose was to develop a prognosis assessment system based on clinical and mathematical analysis of indicators at different stages in various types of the course of multiple sclerosis. Materials and methods. Clinical (clinical neurological method and survey using a questionnaire developed at the Department of Autoimmune and Degenerative Pathology of the Nervous System of the State Institution “Institute of Neurology, Psychiatry and Narcology of the National Academy of Medical Sciences of Ukraine”) and mathematical and statistical (permutation test) methods were applied. Using the method of permutation (permutation test) in groups of patients with different types of multiple sclerosis, the differences in the mean values of clinical indicators were evaluated characterizing the type of multiple sclerosis course at different time stages: preclinical stage, the onset, recurrent stage for relapsing-remitting and secondary progressive multiple sclerosis, stage of progression — for secondary and primary progressive multiple sclerosis. On this basis, clinical indicators were identified, which with a high probability (confidence interval of 0.95) at each time stage of multiple sclerosis determine the final prognosis of the disease. Results. We have examined 280 patients: 80 (50 women and 30 men) with a relapsing-remitting course, 140 (80 women and 60 men) with a secondary progressive course and 60 (30 women and 30 men) with a primary progressive course of multiple sclerosis. The nature of prognosis (good and uncertain with a relapsing-remitting course, uncertain and poor with progressive types) was assessed on the basis of clinical and diagnostic criteria developed taking into account the features of the disease course as a whole. The studies have shown that a good prognosis is highly probable with a combination of clinical indicators such as mild onset, complete remission after onset, mild relapses developing rapidly, and long-term remission between relapses at a relapsing-remitting stage; uncertain prognosis — in the presence of moderate onset, stem symptoms at the onset, severe and moderate relapses, and a tendency to aggravate and lengthen relapses at a relapsing-remitting stage. A poor prognosis in a secondary progressive course is reliably associated with the chickenpox at the preclinical stage in a premorbid history, lightning-fast onset development, steady progression proceeding without clinically outlined periods of stabilization; uncertain prognosis — with a fast development of the onset. A poor prognosis in a primary progressive course was closely associated with severe traumatic brain injury at the preclinical stage in a premorbid history, cerebellar symptoms at the onset, formation of the progression stage immediately after the onset, without the stabilization period, steady type of progression at the stage of progression; uncertain prognosis — with herpetic infections at the preclinical stage in a premorbid history, mild onset, the formation of a progression stage after a stabilization period that occurred after the onset, incremental progression at the progression stage proceeding in the form of alternating periods of slow accumulation of neurological deficit, which, as a rule, has a local focus, and stages of stabilization with different duration. Conclusions. Thus, with the help of clinical and mathematical analysis, it was shown that the formation of alternative prognosis variants for different types of multiple sclerosis occurs through a selective involvement in a single pattern of clinical indicators that have diagnostic significance at different time stages of the course of the disease.

NPPA promoter hypomethylation predicts central obesity development: a prospective longitudinal study in Chinese adults

Introduction: Atrial natriuretic peptide (ANP) plays a potential role in obesity with unclear molecular mechanisms. The objective of this study was to examine the association between its coding gene (NPPA) methylation and obesity. Methods: Peripheral blood DNA methylation of NPPA promoter was quantified at baseline by targeted bisulfite sequencing for 2,497 community members (mean aged 53 years, 38% men) in the Gusu cohort. Obesity was repeatedly assessed by body mass index (BMI) and waist circumference (WC) at baseline and follow-up examinations. The cross-sectional, longitudinal, and prospective associations between NPPA promoter methylation and obesity were examined. Results: Of the 9 CpG loci assayed, DNA methylation levels at 6 CpGs were significantly lower in participants with central obesity than those without (all P<0.05 for permutation test). These CpG methylation levels at baseline were also inversely associated with dynamic changes in BMI or WC during follow-up (all P<0.05 for permutation test). After an average 4 years of follow-up, hypermethylation at the 6 CpGs (CpG2 located at Chr1: 11908348, CpG3 located at Chr1:11908299, CpG4 located at Chr1:11908200, CpG5 located at Chr1:11908182, CpG6 located at Chr1:11908178, and CpG8 located at Chr1:11908165) were significantly associated with a lower risk of incident central obesity (all P<0.05 for permutation test). Conclusions: Hypomethylation at NPPA promoter was associated with increased future risk of central obesity in Chinese adults. Aberrant DNA methylation of the NPPA gene may participate in the mechanisms of central obesity.

Changes in Habitat Conditions of Invaded Forest Communities in Podunajská Nížina and the Impact of Non-Native Species on Biodiversity (SW Slovakia)

With the phytocenological research of riparian mixed forests and pannonic woods in the Podunajská nížina in 2018 and 2019, we obtained 113 phytocenological relevés of invaded and non-invaded stands. Using the Modified Permutation Test, we derived modified Ellenberg indication values (EIVs) in order to determine statistically significant differences and correlation relationships between diversity indices and EIVs. We recorded 15 invasive species in the stands, for example, Ailanthus altissima, Ambrosia artemisiifolia, Asclepias syriaca, Aster lanceolatus, Helianthus tuberosus, Impatiens parviflora, Negundo aceroides, Solidago canadensis, S. gigantea and Robinia pseudoacacia. We also confirmed the occurrence of species important for conservation: Epipactis helleborine agg., E. voethii, Cephalanthera longifolia, Clematis integrifolia and the like. We tested the statistical significance of EIVs as explanatory variables by redundancy analysis and Monte Carlo permutation test (stepwise selection, number of permutations 499, p < 0.05). In addition to the EIV continentality, the contribution of light, moisture, nutrients, soil reaction and temperature was higher than random. The model explains 20.21% of the variability pursuant to the coefficient of determination (R 2), with its adjusted (more accurate) variant (R 2 adj) capturing 15.70% of the variability of the model. Using the Kruskal–Wallis test, we confirmed the statistically significant differences (p*) in mean values between count of species, Shannon–Wiener index, Simpson dominance index and taxonomic diversity of invaded and non-invaded vegetation. For EIVs, we found significant differences in the mean values for moisture and soil reaction factors. In our model, count of species, Shannon–Wiener index, Simpson dominance index and taxonomic diversity index were positively correlated with invaded stands. Non-invaded stands showed statistically significant negative correlation with the EIVs moisture, soil reaction and nutrients. Biotic indices are appropriate and sensitive metrics for assessing the rate of community invasion. Lowland riparian forests are dynamic ecosystems through the structure of their stands and the dynamics of the nutrient and energy cycle of the river landscape. After disturbance (fire, wind, logging), the high degree of invasibility makes them vulnerable to the infiltration and spread of non-native species, which is a problem, especially in protected areas.

Preliminary Assessment of Ecological Status of the Siversky Donets River Basin (Ukraine) Based on Phytoplankton Parameters and Its Verification by Other Biological Data

The river basin of Siversky Donets is of great scientific interest since this river runs through a territory with heavy industry (in particular, coal mining, chemical processing and metal industries). Within the basin, rivers of different sizes were explored (small, medium, large and extra-large) that flow through siliceous and calcareous rocks on the same elevation (lowland—below 200 m a.s.l.). Phytoplankton, as one of the Biological Quality Element, was used to perform the assessment of ecological status of the water bodies within the Siversky Donets river basin in 2019. The state monitoring program based on the updated approaches has been implemented in the river basin for the first time. The composition of phytoplankton species in the basin comprised 167 species (168 intraspecies taxa), mainly Bacillariophyta (63%) and Chlorophyta (22%) with the presence of other species (Cyanobacteria, Charophyta, Chrysophyta, Dinophyta and Euglenophyta). High species diversity and divisions amount are a distinctive property of the smaller rivers, while the bigger rivers show lower number of divisions. The “bloom” events, which are important ecological factors, were not detected in the Siversky Donets river basin. Algal species composition in plankton samples of the basin was identified and series of ecological parameters, such as habitat preferences, temperature, pH, salinity, oxygenation and organic water pollution according to Watanabe and Sládeček’s index of saprobity (S) trophic state and nitrogen uptake metabolism were analyzed. The ecological conclusions were also verified by a canonical correspondence analysis (CCA). The significance of the Canonical Correspondence Analysis (CCA) results was estimated of by a Monte-Carlo permutation test. The high concentrations of inorganic phosphorus compounds (permanganate index (CODMn)) and nitrite ions favored the diversity of Chlorophyta and Cyanobacteria diversity correlated with the levels of bicarbonate and CODMn. High diversity of diatoms was facilitated by the total amount of dissolved solids and chemical oxygen demand (COD). It was found that low water quality could be associated with conditions leading to predominant growth of the mentioned groups of algae. According to the analysis, the highest water quality was characterized by balanced phytoplankton composition and optimal values of the environmental variables. The sites with reference conditions are proposed for future monitoring.

Diagnostic performance of attenuated total reflection Fourier-transform infrared spectroscopy for detecting COVID-19 from routine nasopharyngeal swab samples

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) causing global COVID-19 pandemic since 2019 has led to increasing amount of research to study how to do fast screening and diagnosis to efficiently detect COVID-19 positive cases, and how to prevent spreading of the virus. Our research objective was to study whether SARS-CoV-2 could be detected from routine nasopharyngeal swab samples by using attenuated total reflection Fourier-transform infrared (ATR-FTIR) spectroscopy coupled with partial least squares discriminant analysis (PLS-DA). The advantage of ATR-FTIR is that measurements can be conducted without any sample preparation and no reagents are needed. Our study included 558 positive and 558 negative samples collected from Northern Finland. Overall, we found moderate diagnostic performance for ATR-FTIR when polymerase chain reaction (PCR) was used as the gold standard: the average area under the receiver operating characteristics curve (AUROC) was 0.67-0.68 (min. 0.65, max. 0.69) with 20, 10 and 5 k-fold cross validations. Mean accuracy, sensitivity and specificity was 0.62-0.63 (min. 0.60, max. 0.65), 0.61 (min. 0.58, max. 0.65) and 0.64 (min. 0.59, max. 0.67) with 20, 10 and 5 k-fold cross validations. As a conclusion, our study with relatively large sample set clearly indicate that measured ATR-FTIR spectrum contains specific information for SARS-CoV-2 infection (P<0.001 in label permutation test). However, the diagnostic performance of ATR-FTIR remained only moderate, potentially due to low concentration of viral particles in the transport medium. Further studies are needed before ATR-FTIR can be recommended for fast screening of SARS-CoV-2 from routine nasopharyngeal swab samples.

Identifying Microbial Interaction Networks Based on Irregularly Spaced Longitudinal 16S rRNA sequence data

Though being vital for human health, microbial interactions with their host and with each other are still largely obscure for researchers. To deepen the understanding, the analyses based on longitudinal data are a better choice than the cross-sectional data since the information provided by the former is usually more stable. To this end, in this paper, we first propose an EM-type algorithm to identify microbial interaction network for the irregularly spaced longitudinal measurements. Correlation functions are employed to account for the correlation across the temporal measurements for a given subject. The algorithms take advantage of the efficiency of the popular graphical lasso algorithm and can be implemented straightforwardly. Simulation studies show that the proposed algorithms can significantly outperform the conventional algorithms such as graphical lasso or neighborhood method when the correlation between measurements grows larger. In second part of the paper, based on a 16S rRNA sequence data set of gut microbiome, module-preserving permutation test is proposed to test the independence of the estimated network and the phylogeny of the microbe species. The results demonstrate evidences of strong association between the interaction network and the phylogenetic tree which indicates that the taxa closer in their genomes tend to have more/stronger interactions in their functions. The proposed algorithms can be implemented through R package lglasso at \url{https://github.com/jiezhou-2/lglasso