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International Journal of Circumpolar... Dec 2024serotype a (Hia) has recently emerged as an important cause of invasive disease in the North American Arctic and Sub-Arctic regions, mainly affecting young Indigenous...
serotype a (Hia) has recently emerged as an important cause of invasive disease in the North American Arctic and Sub-Arctic regions, mainly affecting young Indigenous children. In this study, we addressed the question of whether the prevalence of Hia and all in the nasopharynx differed between paediatric populations from regions with high low incidence of invasive Hia disease. Nasopharyngeal specimens from children with acute respiratory tract infections (ARTI) collected for routine diagnostic detection of respiratory viruses were analysed with molecular-genetic methods to identify and serotype . In Nunavut, a region with a high incidence of invasive Hia disease, all and particularly Hia were found in the nasopharynx of 60.6% and 3.0% children. In Southern Ontario (Hamilton region), where Hia invasive disease is rare, the frequencies of all and Hia detection were 38.5% and 0.6%, respectively. In both cohorts, non-typeable was prevalent (57.0% and 37.9%, respectively). Considering that Hia is an important cause of severe invasive disease in Nunavut children, 3% prevalence of Hia among children with ARTI can reflect continuing circulation of the pathogen in the Northern communities that may result in invasive disease outbreaks.
Topics: Humans; Haemophilus influenzae; Haemophilus Infections; Child, Preschool; Nasopharynx; Prevalence; Infant; Male; Female; Incidence; Ontario; Child; Arctic Regions; Nunavut; Respiratory Tract Infections; Canada; Serogroup
PubMed: 38941555
DOI: 10.1080/22423982.2024.2371111 -
Bioinformatics (Oxford, England) Jun 2024Errors in the processing of genetic information during protein synthesis can lead to phenotypic mutations, such as amino acid substitutions, e.g. by transcription or...
MOTIVATION
Errors in the processing of genetic information during protein synthesis can lead to phenotypic mutations, such as amino acid substitutions, e.g. by transcription or translation errors. While genetic mutations can be readily identified using DNA sequencing, and mutations due to transcription errors by RNA sequencing, translation errors can only be identified proteome-wide using mass spectrometry.
RESULTS
Here, we provide a Python package implementation of a high-throughput pipeline to detect amino acid substitutions in mass spectrometry datasets. Our tools enable users to process hundreds of mass spectrometry datasets in batch mode to detect amino acid substitutions and calculate codon-specific and site-specific translation error rates. deTELpy will facilitate the systematic understanding of amino acid misincorporation rates (translation error rates), and the inference of error models across organisms and under stress conditions, such as drug treatment or disease conditions.
AVAILABILITY
deTELpy is implemented in Python 3 and is freely available with detailed documentation and practical examples at https://git.mpi-cbg.de/tothpetroczylab/detelpy and https://pypi.org/project/deTELpy/ and can be easily installed via pip install deTELpy.
SUPPLEMENTARY INFORMATION
Supplementary data are available at Bioinformatics online.
PubMed: 38941503
DOI: 10.1093/bioinformatics/btae424 -
Journal of the National Cancer Institute Jun 2024Neurocognitive impairments are sequelae of childhood cancer treatment, however little guidance is given to clinicians on common phenotypes of impairment, or modifiable...
BACKGROUND
Neurocognitive impairments are sequelae of childhood cancer treatment, however little guidance is given to clinicians on common phenotypes of impairment, or modifiable risk factors that could lead to personalized interventions in survivorship.
METHODS
Standardized clinical testing of neurocognitive function was conducted in 2,958 (74.1%) eligible survivors, who were ≥5 years post-diagnosis and >18 years old, and 477 community controls. Impairment was examined across 20 measures and phenotypes were determined by latent class analysis. Multinomial logistic regression was used to estimate risk for phenotype, predicted by cancer diagnosis and treatment exposures, chronic health conditions, and lifestyle, adjusted for sex and age. Associations between phenotypes and social attainment were examined.
RESULTS
Five neurocognitive phenotypes were identified in survivors (global impairment 3.7%, impaired attention 5.0%, memory impairment 7.2%, processing speed/executive function impairment 9.3%, no impairment 74.8%). Risk of global impairment was associated with severe chronic health condition burden (odds ratio [OR]=20.17, 95% confidence interval [95%CI] 11.41-35.63) including cerebrovascular disease (OR = 14.5, 95%CI = 5.47-38.44) and cerebrovascular accident (OR = 14.7, 95%CI = 7.50-26.40). Modifiable risk factors, like quitting smoking reduced risk for global impairment (OR = 0.21, 95%CI 0.06-0.66). Low physical activity increased risk for global impairment (OR = 4.54, 95%CI 2.86-7.21), attention impairment (OR 2.01, 95%CI 1.41-2.87), processing speed/executive function impairment (OR 1.90, 95%CI 1.46-2.48), and memory impairment (OR 2.09, 95%CI 1.54-2.82).
CONCLUSIONS
Results support the clinical utility of neurocognitive phenotyping to develop risk profiles and personalized clinical interventions, such as preventing cerebrovascular disease in anthracycline treated survivors by preventing hypercholesterolemia, smoking, and sedentary lifestyle, to reduce the risk for global impairment.
PubMed: 38941494
DOI: 10.1093/jnci/djae149 -
Science Advances Jun 2024The formation of vascular niche is pivotal during the early stage of peripheral nerve regeneration. Nevertheless, the mechanisms of vascular niche in the regulation of...
The formation of vascular niche is pivotal during the early stage of peripheral nerve regeneration. Nevertheless, the mechanisms of vascular niche in the regulation of peripheral nerve repair remain unclear. Netrin-1 (NTN1) was found up-regulated in nerve stump after peripheral nerve injury (PNI). Herein, we demonstrated that NTN1-high endothelial cells (NTN1+ECs) were the critical component of vascular niche, fostering angiogenesis, axon regeneration, and repair-related phenotypes. We also found that NTN1+EC-derived exosomes (NTN1 EC-EXO) were involved in the formation of vascular niche as a critical role. Multi-omics analysis further verified that NTN1 EC-EXO carried a low-level expression of let7a-5p and activated key pathways associated with niche formation including focal adhesion, axon guidance, phosphatidylinositol 3-kinase-AKT, and mammalian target of rapamycin signaling pathway. Together, our study suggested that the construction of a pre-regenerative niche induced by NTN1 EC-EXO could establish a beneficial microenvironment for nerve repair and facilitate functional recovery after PNI.
Topics: Netrin-1; Exosomes; Nerve Regeneration; Animals; Endothelial Cells; Peripheral Nerve Injuries; Mice; Neovascularization, Physiologic; Signal Transduction; Humans; Peripheral Nerves
PubMed: 38941462
DOI: 10.1126/sciadv.adm8454 -
PLOS Digital Health Jun 2024Traditional cognitive assessments in schizophrenia are time-consuming and necessitate specialized training, making routine evaluation challenging. To overcome these...
Traditional cognitive assessments in schizophrenia are time-consuming and necessitate specialized training, making routine evaluation challenging. To overcome these limitations, this study investigates the feasibility and advantages of utilizing smartphone-based assessments to capture both cognitive functioning and digital phenotyping data and compare these results to gold standard measures. We conducted a secondary analysis of data from 76 individuals with schizophrenia, who were recruited across three sites (one in Boston, two in India) was conducted. The open-source mindLAMP smartphone app captured digital phenotyping data and Trails A/B assessments of attention / memory for up to 12 months. The smartphone-cognitive tasks exhibited potential for normal distribution and these scores showed small but significant correlations with the results from the Brief Assessment of Cognition in Schizophrenia, especially the digital span and symbol coding tasks (r2 = 0.21). A small but significant correlation (r2 = 0.29) between smartphone-derived cognitive scores and health-related behaviors such as sleep duration patterns was observed. Smartphone-based cognitive assessments show promise as cross-cultural tools that can capture relevant data on momentary states among individuals with schizophrenia. Cognitive results related to sleep suggest functional applications to digital phenotyping data, and the potential of this multimodal data approach in research.
PubMed: 38941349
DOI: 10.1371/journal.pdig.0000526 -
PloS One 2024Medaka fish (Oryzias latipes) is a powerful model to study genetics underlying the developmental and functional traits of the vertebrate visual system. We established a...
Medaka fish (Oryzias latipes) is a powerful model to study genetics underlying the developmental and functional traits of the vertebrate visual system. We established a simple and high-throughput optomotor response (OMR) assay utilizing medaka larvae to study visual functions including visual acuity and contrast sensitivity. Our assay presents multiple adjustable stripes in motion to individual fish in a linear arena. For that the OMR assay employs a tablet display and the Fish Stripes software to adjust speed, width, color, and contrast of the stripes. Our results demonstrated that optomotor responses were robustly induced by black and white stripes presented from below in the linear-pool-arena. We detected robust strain specific differences in the OMR when comparing long established medaka inbred strains. We observed an interesting training effect upon the initial exposure of larvae to thick stripes, which allowed them to better respond to narrower stripes. The OMR setup and protocol presented here provide an efficient tool for quantitative phenotype mapping, addressing visual acuity, trainability of cortical neurons, color sensitivity, locomotor response, retinal regeneration and others. Our open-source setup presented here provides a crucial prerequisite for ultimately addressing the genetic basis of those processes.
Topics: Animals; Oryzias; Larva; Visual Acuity; Photic Stimulation; Contrast Sensitivity; Vision, Ocular; High-Throughput Screening Assays
PubMed: 38941325
DOI: 10.1371/journal.pone.0302092 -
PloS One 2024Art v4.01 is a well-known profilin protein belonging to the pan-allergens group and is commonly involved in triggering allergic asthma, polyallergy, and...
Art v4.01 is a well-known profilin protein belonging to the pan-allergens group and is commonly involved in triggering allergic asthma, polyallergy, and cross-sensitization. It is also referred to as Wormwood due to its origin. Crude wormwood extracts are applied for allergen-specific immunotherapy (AIT). Whether the recombinant Art v4.01 (rArt v4.01) can produce in vivo immunological tolerance by subcutaneous immunotherapy (SCIT) remains elusive. In this study, to investigate the in vivo immunological response of rArt v4.01, Th2, Th1, Treg, Th17 type-related cytokines and phenotypes of immune cells were tested, facilitating the exploration of the underlying mechanisms. The expression and purification of Art v4.01 were carried out using recombinant techniques. Allergic asthma female BALB/c mice were induced by subcutaneous sensitization of wormwood pollen extract and intranasal challenges. SCIT without adjuvant was performed using the rArt v4.01 and wormwood pollen extract for 2 weeks. Following exposure to challenges, the levels of immunoglobulin E (IgE), cytokines, and inflammatory cells were assessed through enzyme-linked immunosorbent assay (ELISA) and histological examination of sera, bronchoalveolar lavage fluid (BALF), and lung tissue. These parameters were subsequently compared between treatment groups receiving rArt v4.01 and wormwood pollen extract. The rArt v4.01 protein was expressed, which had a high purity (>90%) and an allergenic potency. Compared with the pollen extract, rArt v4.01 was superior in terms of reducing the number of white blood cells (WBCs), total nucleated cells (TNCs), and monocytes (MNs) in BALF and the degree of lung inflammation (1.77±0.99 vs. 2.31±0.80, P > 0.05). Compared with the model group, only rArt v4.01 reduced serum IgE level (1.19±0.25 vs. 1.61±0.17 μg/ml, P = 0.062), as well as the levels of Th2 type-related cytokines (interleukin-4 (IL-4) (107.18±16.17 vs. 132.47±20.85 pg/ml, P < 0.05) and IL-2 (19.52±1.19 vs. 24.02±2.14 pg/ml, P < 0.05)). The study suggested that rArt v4.01 was superior to pollen extract in reducing the number of inflammatory cells in BALF, pneumonitis, levels of pro-inflammatory cytokines, and serum IgE level. These findings confirmed that Art v4.01 could be a potential candidate protein for allergen-specific immunotherapy.
Topics: Animals; Female; Asthma; Mice; Mice, Inbred BALB C; Disease Models, Animal; Immune Tolerance; Recombinant Proteins; Cytokines; Immunoglobulin E; Pollen; Desensitization, Immunologic; Allergens; Profilins; Bronchoalveolar Lavage Fluid; Injections, Subcutaneous
PubMed: 38941291
DOI: 10.1371/journal.pone.0280418 -
PloS One 2024In this study, we employed various machine learning models to predict metabolic phenotypes, focusing on thyroid function, using a dataset from the National Health and...
In this study, we employed various machine learning models to predict metabolic phenotypes, focusing on thyroid function, using a dataset from the National Health and Nutrition Examination Survey (NHANES) from 2007 to 2012. Our analysis utilized laboratory parameters relevant to thyroid function or metabolic dysregulation in addition to demographic features, aiming to uncover potential associations between thyroid function and metabolic phenotypes by various machine learning methods. Multinomial Logistic Regression performed best to identify the relationship between thyroid function and metabolic phenotypes, achieving an area under receiver operating characteristic curve (AUROC) of 0.818, followed closely by Neural Network (AUROC: 0.814). Following the above, the performance of Random Forest, Boosted Trees, and K Nearest Neighbors was inferior to the first two methods (AUROC 0.811, 0.811, and 0.786, respectively). In Random Forest, homeostatic model assessment for insulin resistance, serum uric acid, serum albumin, gamma glutamyl transferase, and triiodothyronine/thyroxine ratio were positioned in the upper ranks of variable importance. These results highlight the potential of machine learning in understanding complex relationships in health data. However, it's important to note that model performance may vary depending on data characteristics and specific requirements. Furthermore, we emphasize the significance of accounting for sampling weights in complex survey data analysis and the potential benefits of incorporating additional variables to enhance model accuracy and insights. Future research can explore advanced methodologies combining machine learning, sample weights, and expanded variable sets to further advance survey data analysis.
Topics: Humans; Machine Learning; Thyroid Gland; Male; Female; Phenotype; Middle Aged; Adult; Nutrition Surveys; Thyroid Function Tests; ROC Curve; Neural Networks, Computer
PubMed: 38941283
DOI: 10.1371/journal.pone.0304785 -
PloS One 2024In the field of microbiome studies, it is of interest to infer correlations between abundances of different microbes (here referred to as operational taxonomic units,...
In the field of microbiome studies, it is of interest to infer correlations between abundances of different microbes (here referred to as operational taxonomic units, OTUs). Several methods taking the compositional nature of the sequencing data into account exist. However, these methods cannot infer correlations between OTU abundances and other variables. In this paper we introduce the novel methods SparCEV (Sparse Correlations with External Variables) and SparXCC (Sparse Cross-Correlations between Compositional data) for quantifying correlations between OTU abundances and either continuous phenotypic variables or components of other compositional datasets, such as transcriptomic data. SparCEV and SparXCC both assume that the average correlation in the dataset is zero. Iterative versions of SparCEV and SparXCC are proposed to alleviate bias resulting from deviations from this assumption. We compare these new methods to empirical Pearson cross-correlations after applying naive transformations of the data (log and log-TSS). Additionally, we test the centered log ratio transformation (CLR) and the variance stabilising transformation (VST). We find that CLR and VST outperform naive transformations, except when the correlation matrix is dense. SparCEV and SparXCC outperform CLR and VST when the number of OTUs is small and perform similarly to CLR and VST for large numbers of OTUs. Adding the iterative procedure increases accuracy for SparCEV and SparXCC for all cases, except when the average correlation in the dataset is close to zero or the correlation matrix is dense. These results are consistent with our theoretical considerations.
Topics: Microbiota; Algorithms; Humans
PubMed: 38941272
DOI: 10.1371/journal.pone.0305032 -
Journal of Molecular Endocrinology Jun 2024Pregnancy requires metabolic adaptations in order to meet support fetal growth with nutrient availability. In this study, the influence of pregnancy on metabolically...
Pregnancy requires metabolic adaptations in order to meet support fetal growth with nutrient availability. In this study, the influence of pregnancy on metabolically active organs (adipose tissues in particular) was investigated. Our results showed that maternal weight and adipose mass presented dynamic remodeling in the periparturient mice. Meanwhile, pregnancy mice displayed obvious glucose intolerance and insulin resistance in late pregnancy as compared to non-pregnancy, which were partially reversed at parturition. Further analysis revealed that different fat depots exhibited site-specific adaptions of morphology and functionality as pregnancy advanced. Brown and inguinal white adipose tissue (BAT and IngWAT) exhibited obviously decreased thermogenic activity; by contrast, gonadal white adipose tissue (GonWAT) displayed remarkably increased lipid mobilization. Notably, we found that mammary gland differentiation was enhanced in IngWAT, followed by BAT, but not in GonWAT. These result indicated that brown and white adipose tissues might synergistically play a crucial role in maintaining the maxicum of energy supply for mother and fetus, which facilitates the mammary duct luminal epithelium development as well as the growth and development of fetus. Accompanied with adipose adaptation, however, our results revealed that the liver and pancreas also displayed significant metabolic adaptability, which together tended to trigger the risk of maternal metabolic diseases. Importantly, pregnancy-dependent obesity in our mice model resembled the disturbed metabolic phenotypes of pregnant women such as hyperglyceridemia and hypercholesterolemia. Our findings in this study could provide valuable clues for better understanding the underlying mechanisms of metabolic maladaptation, and facilitate the development of the prevention and treatment of metabolic diseases.
PubMed: 38941267
DOI: 10.1530/JME-24-0012