Category: Statistics

Environ Sci Pollut Res Int. 2023 Dec 1. doi: 10.1007/s11356-023-31130-2. Online ahead of print.

ABSTRACT

Microplastic (MP) contamination in commercially sold spirulina products has not been previously investigated. In this study, 29 spirulina samples in various packaging types were purchased from different brands and origins to assess the presence of MPs. Microplastic analysis was conducted using microscopic and μ-Raman techniques. To ascertain whether the content is indeed spirulina and make a comparison with the MP level, C-Phycocyanin levels were also analyzed. A total of 251 MP-like particles were observed. Out of the 29 examined packaged spirulina brands, 26 showed potential MPs upon visual inspection, with 35 particles confirmed as MPs (73% of the analyzed particles). The mean abundance of MPs was estimated at 13.77 ± 2.45 MPs/100 g dw. Powdered spirulina had a higher but not statistically significant MP abundance (17.34 ± 4.22 MPs/100 g dw) compared to capsule/tablet forms (10.43 ± 2.45 MPs/100 g dw). Fragments accounted for 38.3% while fibers constituted 61.7% of the identified MPs, with sizes ranging from 0.07 to 2.15 mm for fragments and 0.19 to 5.691 mm for fibers. The color distribution of MPs in spirulina samples was predominantly blue (52.8%), followed by black (25.4%), white (10.9%), and others (10.9%). Ten synthetic polymers and cellulose were identified through μ-Raman analysis, with polypropylene (31.6%) and polystyrene (8.3%) being the most prevalent. The correlation between C-Phycocyanin and MPs concentrations, was not found statistically significant. The abundance and composition of MPs were found to be influenced by packaging and processing stages. Identifying potential sources of MPs in spirulina products and evaluating their risks to human health is crucial.

PMID:38036911 | DOI:10.1007/s11356-023-31130-2

Environ Sci Pollut Res Int. 2023 Dec 1. doi: 10.1007/s11356-023-30974-y. Online ahead of print.

ABSTRACT

We present the results of an in situ study of a set of blood parameters in adult marsh frogs (Pelophylax ridibundus (Pallas 1771) from populations inhabiting the largest system of rice fields in Bulgaria, the Tsalapitsa rice fields (TRF), under chronic stress conditions. This study was conducted in spring 2022 to assess the health status of TRF frogs compared to that of frogs occupying a reference site (RS). Furthermore, this study also compared the results obtained for the TRF population with those obtained in a study conducted at the exact same location with P. ridibundus individuals in 2013 (Zhelev et al. 2018). This comparison highlights the potential effects of persistent use of agrochemicals (pesticides and fertilizers) on the marsh frogs of later generations. Our results suggest that the general health of marsh frogs in the polluted site (PS) in southern Bulgaria has severely deteriorated. Frogs of both sexes were anemic with weakened immune systems compared to those living in the RS. The long-term use of agrochemicals in the PS affected males to a greater extent than it did females. Statistically significant hypochromia was observed in males, combined with general leukopenia, neutrophilia, lymphopenia, monocytosis, eosinophilia, and higher neutrophil/lymphocyte (N/L) ratios.

PMID:38036908 | DOI:10.1007/s11356-023-30974-y

Metabolomics. 2023 Nov 30;20(1):2. doi: 10.1007/s11306-023-02065-z.

ABSTRACT

INTRODUCTION: In metabolomics, the investigation of associations between the metabolome and one trait of interest is a key research question. However, statistical analyses of such associations are often challenging. Statistical tools enabling resilient verification and clear presentation are therefore highly desired.

OBJECTIVES: Our aim is to provide a contribution for statistical analysis of metabolomics data, offering a widely applicable open-source statistical workflow, which considers the intrinsic complexity of metabolomics data.

METHODS: We combined selected R packages tailored for all properties of heterogeneous metabolomics datasets, where metabolite parameters typically (i) are analyzed in different matrices, (ii) are measured on different analytical platforms with different precision, (iii) are analyzed by targeted as well as non-targeted methods, (iv) are scaled variously, (v) reveal heterogeneous variances, (vi) may be correlated, (vii) may have only few values or values below a detection limit, or (viii) may be incomplete.

RESULTS: The code is shared entirely and freely available. The workflow output is a table of metabolites associated with a trait of interest and a compact plot for high-quality results visualization. The workflow output and its utility are presented by applying it to two previously published datasets: one dataset from our own lab and another dataset taken from the repository MetaboLights.

CONCLUSION: Robustness and benefits of the statistical workflow were clearly demonstrated, and everyone can directly re-use it for analysis of own data.

PMID:38036896 | DOI:10.1007/s11306-023-02065-z

Nat Methods. 2023 Nov 30. doi: 10.1038/s41592-023-02101-9. Online ahead of print.

ABSTRACT

Although the subcellular dynamics of RNA and proteins are key determinants of cell homeostasis, their characterization is still challenging. Here we present an integrative framework to simultaneously interrogate the dynamics of the transcriptome and proteome at subcellular resolution by combining two methods: localization of RNA (LoRNA) and a streamlined density-based localization of proteins by isotope tagging (dLOPIT) to map RNA and protein to organelles (nucleus, endoplasmic reticulum and mitochondria) and membraneless compartments (cytosol, nucleolus and cytosolic granules). Interrogating all RNA subcellular locations at once enables system-wide quantification of the proportional distribution of RNA. We obtain a cell-wide overview of localization dynamics for 31,839 transcripts and 5,314 proteins during the unfolded protein response, revealing that endoplasmic reticulum-localized transcripts are more efficiently recruited to cytosolic granules than cytosolic RNAs, and that the translation initiation factor eIF3d is key to sustaining cytoskeletal function. Overall, we provide the most comprehensive overview so far of RNA and protein subcellular localization dynamics.

PMID:38036857 | DOI:10.1038/s41592-023-02101-9

Nat Methods. 2023 Nov 30. doi: 10.1038/s41592-023-02069-6. Online ahead of print.

ABSTRACT

Complete, telomere-to-telomere (T2T) genome assemblies promise improved analyses and the discovery of new variants, but many essential genomic resources remain associated with older reference genomes. Thus, there is a need to translate genomic features and read alignments between references. Here we describe a method called levioSAM2 that performs fast and accurate lift-over between assemblies using a whole-genome map. In addition to enabling the use of several references, we demonstrate that aligning reads to a high-quality reference (for example, T2T-CHM13) and lifting to an older reference (for example, Genome reference Consortium (GRC)h38) improves the accuracy of the resulting variant calls on the old reference. By leveraging the quality improvements of T2T-CHM13, levioSAM2 reduces small and structural variant calling errors compared with GRC-based mapping using real short- and long-read datasets. Performance is especially improved for a set of complex medically relevant genes, where the GRC references are lower quality.

PMID:38036856 | DOI:10.1038/s41592-023-02069-6

Methods Mol Biol. 2024;2737:359-375. doi: 10.1007/978-1-0716-3541-4_33.

ABSTRACT

Fatalities due to opioids and other controlled substances continue to increase year over year and maintain an epidemic level nationally. CDC data indicates that drug overdoses killed more than 100,000 Americans in 2021 with synthetic opioids being the main driver of the national crisis (Wide-ranging online data for epidemiologic research (WONDER). Multiple Cause of Death 1999-2020. Centers for Disease Control and Prevention, National Center on Health Statistics. http://wonder.cdc.gov . Accessed 28 Feb 2023, 2021). Response to this crisis includes the development of laboratory testing to support the evolving drug trends. Urine drug testing provides clinicians with objective information to assist in making treatment decisions by identifying the presence of potential drugs of abuse and assessing patient compliance to a controlled substance prescription regimen. In this chapter, we describe a rapid LC-MS/MS method for the simultaneous quantitation of 21 opiate, opioid, and benzodiazepine drugs in less than 4 min. The method requires 100 uL of urine and includes enzymatic hydrolysis of glucuronide conjugates using β-glucuronidase to provide total drug measurement. Quantitation is accomplished using multiple reaction monitoring (MRM), a seven-point calibration curve, and deuterated internal standards. This method provides a robust and reliable means to measure commonly prescribed opioid (including natural, semi-synthetic, and synthetic) and benzodiazepine drugs in urine.

PMID:38036837 | DOI:10.1007/978-1-0716-3541-4_33

Arch Osteoporos. 2023 Dec 1;18(1):148. doi: 10.1007/s11657-023-01350-7.

ABSTRACT

We used cluster analysis to determine the profiles of individuals who sustained wrist fractures. We found two groups: (1) young and active and (2) older and less active. This information may be used to identify individuals who require further bone health interventions to optimize healthy aging.

INTRODUCTION: Distal radial fractures (DRF) are the most common of all fractures, with 6% of males and 33% of females having one at some point in their lifetime. We hypothesize that DRF consists of two subpopulations: one with compromised bone health that is early in the osteoporosis (OP) trajectory and another which are active and healthy and suffer a misfortune fracture due to their high activity levels or risk-taking behaviors. The latter is likely to recover with a minimal disability, while the former may signal a negative health trajectory of disability and early mortality.

OBJECTIVE: To determine the profiles of individuals who sustained wrist fractures using cluster analysis within the Comprehensive Cohort of the Canadian Longitudinal Study on Aging (CLSA) database considering factors that reflect bone health and activity levels.

METHODS: We included all the individuals who had a wrist fracture within the CLSA comprehensive cohort of the database (n = 968). The baseline data was used for this analysis. A 2-step cluster analysis was used to identify profiles that were both statistically and clinically meaningful. Variables that were used in the cluster analysis include demographic variables, physical activity status indicators, general health indicators, mobility indicators, bone health indicators, comorbid conditions, and lifestyle factors.

RESULTS: We were able to identify two distinct profiles that were statistically and clinically meaningful confirming our hypothesis. One cluster included a predominantly younger cohort, who are physically active, with less comorbid conditions, better bone health, and better general health, while the opposite was true of the first cohort.

CONCLUSION: We were able to identify two clusters-a healthy profile and a bone health compromised profile. This information may be used to identify the subgroup of people who should be targeted in the future for more intensive preventive health services to optimize healthy aging.

PMID:38036802 | DOI:10.1007/s11657-023-01350-7

AAPS PharmSciTech. 2023 Nov 30;24(8):250. doi: 10.1208/s12249-023-02695-5.

ABSTRACT

Kinetic modeling of accelerated stability data serves an important purpose in the development of pharmaceutical products, providing support for shelf life claims and expediting the path to clinical implementation. In this context, a Bayesian kinetic modeling framework is considered, accommodating different types of nonlinear kinetics with temperature and humidity dependent rates of degradation and accounting for the humidity conditions within the packaging to predict the shelf life. In comparison to kinetic modeling based on nonlinear least-squares regression, the Bayesian approach allows for interpretable posterior inference, flexible error modeling and the opportunity to include prior information based on historical data or expert knowledge. While both frameworks perform comparably for high-quality data from well-designed studies, the Bayesian approach provides additional robustness when the data are sparse or of limited quality. This is illustrated by modeling accelerated stability data from two solid dosage forms and is further examined by means of artificial data subsets and simulated data.

PMID:38036798 | DOI:10.1208/s12249-023-02695-5

Nat Genet. 2023 Nov 30. doi: 10.1038/s41588-023-01597-3. Online ahead of print.

ABSTRACT

Fine-mapping aims to identify causal genetic variants for phenotypes. Bayesian fine-mapping algorithms (for example, SuSiE, FINEMAP, ABF and COJO-ABF) are widely used, but assessing posterior probability calibration remains challenging in real data, where model misspecification probably exists, and true causal variants are unknown. We introduce replication failure rate (RFR), a metric to assess fine-mapping consistency by downsampling. SuSiE, FINEMAP and COJO-ABF show high RFR, indicating potential overconfidence in their output. Simulations reveal that nonsparse genetic architecture can lead to miscalibration, while imputation noise, nonuniform distribution of causal variants and quality control filters have minimal impact. Here we present SuSiE-inf and FINEMAP-inf, fine-mapping methods modeling infinitesimal effects alongside fewer larger causal effects. Our methods show improved calibration, RFR and functional enrichment, competitive recall and computational efficiency. Notably, using our methods’ posterior effect sizes substantially increases polygenic risk score accuracy over SuSiE and FINEMAP. Our work improves causal variant identification for complex traits, a fundamental goal of human genetics.

PMID:38036779 | DOI:10.1038/s41588-023-01597-3

Environ Monit Assess. 2023 Dec 1;195(12):1555. doi: 10.1007/s10661-023-12165-x.

ABSTRACT

This research quantitatively evaluated the diversity of plants to protect vulnerable species. To measure vegetation information, the appropriate sampling plot size was determined based on the canopy cover of the dominant species of the study area (1 m²). Then, in each unit, sampling was done along 3 transects of 100 m. Along each transect, 10 plots with dimensions of one square meter were placed at a distance of 10 m from each other. In each plot, the type, life forms, frequency of plant species, and species density were recorded. Species diversity indices were calculated using Ecological Methodology software. The values obtained from these indicators were analyzed in SPSS 24 statistical software and using the F test. The results of the Analysis of variance (ANOVA) showed that the highest values of the species diversity indices are in the middle altitudes (ecotone) class. ANOVA of the richness, evenness, and heterogeneity indices in different altitude classes showed that the values of the richness indices were not significant, but among the indices related to the heterogeneity, the Hill index and all the evenness indices were significant. Comparing the numerical indices of our communities enables us to determine the impact of environmental stress in a single community to choose the best habitat among a similar group for conservation. A community that has high diversity and richness is important for conservation. Therefore, the authorities must prevent the destruction of the vegetation of the study area in connection with the implementation of principled and correct management by the potential of the region, but also to reduce the pressure of livestock grazing and carry out corrective and restoration operations, to turn these rangelands towards rich diversity.

PMID:38036716 | DOI:10.1007/s10661-023-12165-x