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Natural selection generally favours phenotypic variability in camouflaged organisms, whereas aposematic organisms are expected to evolve a more uniform warning coloration. However, no comprehensive analysis of the phenotypic consequences of predator selection in aposematic and cryptic species exists. Using state-of-the-art image analysis, we examine 2800 wing images of 82 moth species accessed via three online museum databases. We test whether anti-predator strategy (i.e., camouflage or aposematism) explains intraspecific variation in wing colour and pattern across northern hemisphere moths. In addition, we test two mutually non-exclusive, ecological hypotheses to explain variation in colour pattern: diel-activity or dietary-niche. In this work, taking into account phylogenetic relationships, moth phenotypic variability is best explained by anti-predator strategy with camouflaged moths being more variable in wing patterning than aposematic species.

Recently, certain biological field experiments and research findings have revealed that predators not only reduce prey populations through direct predation (lethal effect) but also indirectly affect the growth rate of prey by inducing fear; these nonlethal effects can be carried over seasons or generations. In this paper, we proposed an autonomous and a nonautonomous Leslie–Gower model incorporating some biological factors such as fear and its carry‐over effects, prey refuge, and nonlinear predator harvesting. In the autonomous model, first, we examined the well‐posedness, positivity solutions, and their boundedness. Also, it is shown that new equilibrium points emerge and disappear with the change in intrinsic growth rate of predator. Further, we compute and analyzed the local and global stability at the interior equilibrium points. Furthermore, Hopf bifurcation and direction and stability of limit cycle at interior equilibrium points are established. Moreover, the sensitivity analysis of the biological parameters is carried out numerically with two statistical methods via Latin hypercube sampling and partial rank correlation coefficients. It was found that at the small values of fear factor, carry‐over effect, and refuge behavior of prey parameters, the autonomous system exhibits oscillatory behavior, whereas for small values of prey birth rate and harvesting effort, the system remains stable. However, when intrinsic growth rate of predator increases from a low value to a higher value, the system shows transition from stability to instability and back to stability. We also explore the effects of seasonal variations in biological parameters in the nonautonomous model. Additionally, we investigate the theoretical existence of positive periodic solutions using the continuation theorem. The influences of seasonal variations in some parameters such as prey's birth rate, fear, and its carry‐over effects; refuge behavior of prey; intrinsic growth rate of predator; and harvesting effort are then numerically investigated. The results reveal the emergence of positive periodic solutions and bursting patterns in the seasonally forced model. [ABSTRACT FROM AUTHOR]

Effective analysis of single-cell RNA sequencing (scRNA-seq) data requires a rigorous distinction between technical noise and biological variation. In this work, we propose a simple feature selection model, termed "Differentially Distributed Genes" or DDGs, where a binomial sampling process for each mRNA species produces a null model of technical variation. Using scRNA-seq data where cell identities have been established a priori, we find that the DDG model of biological variation outperforms existing methods. We demonstrate that DDGs distinguish a validated set of real biologically varying genes, minimize neighborhood distortion, and enable accurate partitioning of cells into their established cell-type groups. Author summary: Single-cell omics technologies measure tens of thousands of genes in up to millions of individual cells. Yet, the sheer dimensionality of the data poses a challenge to its intelligibility. A typical first step in reducing the dimensionality is to apply a feature selection model that distinguishes real biological signals from technical noise. Yet without an appropriate model of technical noise, feature selection can introduce bias into the downstream analysis of the data. In this work, we demonstrate that, in the analysis of single-cell RNA sequencing data, the standard approach of finding Highly Variable Genes (HVGs) induces severe distortion and bias into the analysis of data, when compared to true biological variation that is known a priori. To address this issue, we present a new feature selection model and demonstrate that our model outperforms existing methods in its ability to accurately identify real biological variation. [ABSTRACT FROM AUTHOR]

Summary Spatial transcriptomics (ST) technologies enable the measurement of mRNA expression while simultaneously capturing spot locations. By integrating ST data, the 3D structure of a tissue can be reconstructed, yielding a comprehensive understanding of the tissue's intricacies. Nevertheless, a computational challenge persists: how to remove batch effects while preserving genuine biological structure variations across ST data. To address this, we introduce Graspot, a gr aph a ttention network designed for sp atial transcriptomics data integration with unbalanced o ptimal t ransport. Graspot adeptly harnesses both gene expression and spatial information to align common structures across multiple ST datasets. It embeds multiple ST datasets into a unified latent space, facilitating the partial alignment of spots from different slices. Demonstrating superior performance compared to existing methods on four real ST datasets, Graspot excels in ST data integration, including tasks that require partial alignment. In particular, Graspot efficiently integrates multiple ST slices and guides coordinate alignment. In addition, Graspot accurately aligns the spatio-temporal transcriptomics data to reconstruct human heart developmental processes. Availability and implementation Graspot software is available at https://github.com/zhan009/Graspot. [ABSTRACT FROM AUTHOR]

The impact of seven hemoglobin variants (Hb Q-Thailand, Hb G-Honolulu, Hb Ube-2, Hb New York, Hb J-Bangkok, Hb G-Coushatta, and Hb E) on the outcome of HbA1c was investigated for six methods by comparing with liquid chromatography-tandem mass spectrometry (LC/MS/MS) reference method. Twenty-nine normal and 112 variant samples were measured by LC/MS/MS, Sebia Capillarys 3 TERA, Intelligene Biosystems QuanTOF, Premier Hb9210, Arkray HA-8190V, Bio-Rad D-100, and Tosoh G11, then evaluated for correlation, consistency, and mean relative bias among six methods. The lowest biological variation bias of ±2.8 % was an acceptable standard. All methods showed poor correlation and consistency with LC/MS/MS for Hb E. The unacceptable biases were observed for Capillarys 3 TERA (−14.4 to −3.7 % for Hb Q-Thailand, Hb Ube-2, Hb New York, Hb J-Bangkok and Hb E), QuanTOF (−8.3 to −2.9 % for Hb Ube-2, Hb New York and Hb G-Coushatta), Premier Hb9210 (−18.3 to −3.6 % for Hb Q-Thailand, Hb Ube-2, Hb New York, Hb J-Bangkok and Hb E), HA-8190V variant mode (−17.3 to 6.6 % for Hb G-Honolulu, Hb Ube-2, Hb New York, Hb G-Coushatta and Hb E). All variant samples showed larger biases than ±2.8 % comparing HA-8190V fast mode, D-100, and G11 with LC/MS/MS. The accuracy of different HbA1c methods was influenced by some Hb variants, especially Hb Ube-2 and Hb New York. Thus, laboratories need to choose appropriate methods to measure HbA1c with different Hb variants. [ABSTRACT FROM AUTHOR]

Laboratory results are increasingly interpreted against common reference intervals (CRIs), published clinical decision limits, or previous results for the same patient performed at different laboratories. However, there are no established systems to determine whether current analytical performance justifies these interpretations. We analysed data from a likely commutable external quality assurance program (EQA) to assess these interpretations. The use of CRIs was assessed by evaluating instrument group medians against minimum specifications for bias. The use of clinical decision limits was assessed using specifications from professional bodies, and the monitoring of patients by testing at different laboratories was assessed by comparing all-laboratory imprecision to within-subject biological variation. Five of the 18 analytes with Australasian CRIs did not meet specification for all instrument groups. Among these, calcium and magnesium failed for one instrument group out of seven, while bicarbonate, chloride, and lipase failed for two instrument groups. Of the 18 analytes reviewed currently without CRIs in Australasia, 10 candidates were identified. Among analytes with clinical decision limits, i.e. lipids, glucose, and vitamin D, only triglycerides met both bias and imprecision specifications, while vitamin D met the imprecision specification. Monitoring patients by testing at different laboratories was supported for 15 of the 46 (33 %) analyte-method principles groups that met minimum imprecision specifications. Analysis of data from commutable EQA programs can provide a mechanism for monitoring whether analytical performance justifies the interpretations made in contemporary laboratory practice. EQA providers should establish systems for routinely providing this information to the laboratory community. [ABSTRACT FROM AUTHOR]

Background Methods Results Conclusion Gastric fluid plays a key role in food digestion and drug dissolution, therefore, the amount of gastric fluid present in a fasted state may influence subsequent digestion and drug delivery. We aimed to describe intra‐ and interindividual variation in fasted gastric content volume (FGCV) and to determine the association with age, sex, and body size characteristics.Data from 24 MRI studies measuring FGCV in healthy, mostly young individuals after an overnight fast were pooled. The analysis included 366 participants who had up to 6 repeated measurements, with a total of 870 measurements. Linear mixed model analysis was performed to calculate intra‐ and interindividual variability and to assess the effects of age, sex, weight, height, weight*height as a proxy for body size, and body mass index (BMI).FGCV ranged from 0 to 156 mL, with a mean (± SD) value of 33 ± 25 mL. The overall coefficient of variation within the study population was 75.6%, interindividual SD was 15 mL, and the intraindividual SD was 19 mL. Age, weight, height, weight*height, and BMI had no effect on FGCV. Women had lower volumes compared to men (MD: −6 mL), when corrected for the aforementioned factors.FGCV is highly variable, with higher intraindividual compared to interindividual variability, indicating that FGCV is subject to day‐to‐day and within‐day variation and is not a stable personal characteristic. This highlights the importance of considering FGCV when studying digestion and drug dissolution. Exact implications remain to be studied. [ABSTRACT FROM AUTHOR]

An arrayed CRISPR screen is a high-throughput functional genomic screening method, which typically uses 384 well plates and has different gene knockouts in different wells. Despite various computational workflows, there is currently no systematic way to find what is a good workflow for arrayed CRISPR screening data analysis. To guide this choice, we developed a statistical simulation model that mimics the data generating process of arrayed CRISPR screening experiments. Our model is flexible and can simulate effects on phenotypic readouts of various experimental factors, such as the effect size of gene editing, as well as biological and technical variations. With two examples, we showed that the simulation model can assist making principled choice of normalization and hit calling method for the arrayed CRISPR data analysis. This simulation model is implemented in an R package and can be downloaded from Github. [ABSTRACT FROM AUTHOR]

Personalized reference intervals (prRI) have been proposed as a diagnostic tool for assessing measurands with high individuality. Here, we evaluate clinical performance of prRI using carcinoembryonic antigen (CEA) for cancer detection and compare it with that of reference change values (RCV) and other criteria recommended by clinical guidelines (e.g. 25 % of change between consecutive CEA results (RV25) and the cut-off point of 5 μg/L (CP5)).Clinical and analytical data from 2,638 patients collected over 19 years were retrospectively evaluated. A total 15,485 CEA results were studied. For each patient, we calculated prRI and RCV using computer algorithms based on the combination of different strategies to assess the number of CEA results needed, consideration of one or two limits of reference interval and the intraindividual biological variation estimate (CVI) used: (a) publicly available (CVI-EU), (b) CVI calculated using an indirect method (CVI-NOO) and (c) within-person BV (CVP). For each new result identified falling outside the prRI, exceeding the RCV interval, RV25 or CP5, we searched for records identifying the presence of tumour at 3 and 12 months after the test. The sensitivity, specificity and predictive power of each strategy were calculated.PrRI approaches derived using CVI-EU, and both limits of reference interval achieve the best sensitivity (87.5 %) and NPV (99.3 %) at 3 and 12 months of all evaluated criteria. Only 3 results per patients are enough to calculate prRIs that reach this diagnostic performance.PrRI approaches could be an effective tool to rule out new oncological findings during the active surveillance of patients. [ABSTRACT FROM AUTHOR]

Sepsis pathobiology is complex. Heterogeneity refers to the clinical and biological variation within sepsis cohorts. Sepsis subtypes refer to subpopulations within sepsis cohorts derived based on these observable variations and latent features. The overarching goal of such endeavors is to enable precision immunomodulation. However, we are yet to identify immune endotypes of sepsis to achieve this goal. The sepsis subtyping field is just starting to take shape. The current subtypes in the literature do not have a core set of shared features between studies. Thus, in this narrative review, we reason that there is a need to a priori state the purpose of sepsis subtyping and minimum set of features that would be required to achieve the goal of precision immunomodulation for future sepsis. [ABSTRACT FROM AUTHOR]

Summary Recent methodology advances in computational signal deconvolution have enabled bulk transcriptome data analysis at a finer cell-type level. Through deconvolution, identifying cell-type-specific differentially expressed (csDE) genes is drawing increasing attention in clinical applications. However, researchers still face a number of difficulties in adopting csDE genes detection methods in practice, especially in their experimental design. Here we present cypress , the first experimental design and statistical power analysis tool in csDE genes identification. This tool can reliably model purified cell-type-specific (CTS) profiles, cell-type compositions, biological and technical variations, offering a high-fidelity simulator for bulk RNA-seq convolution and deconvolution. cypress conducts simulation and evaluates the impact of multiple influencing factors, by various statistical metrics, to help researchers optimize experimental design and conduct power analysis. Availability and implementation cypress is an open-source R/Bioconductor package at https://bioconductor.org/packages/cypress/. [ABSTRACT FROM AUTHOR]

Preclinical evidence implicating cannabinoid receptor 2 (CB2) in various diseases has led researchers to question whether CB2 genetics influence aetiology or progression. Associations between conditions and genetic loci are often studied via single nucleotide polymorphism (SNP) prevalence in case versus control populations. In the CNR2 coding exon, ~36 SNPs have high overall population prevalence (minor allele frequencies [MAF] ~37%), including non‐synonymous SNP (ns‐SNP) rs2501432 encoding CB2 63Q/R. Interspersed are ~27 lower frequency SNPs, four being ns‐SNPs. CNR2 introns also harbour numerous SNPs. This review summarises CB2 ns‐SNP molecular pharmacology and evaluates evidence from ~70 studies investigating CB2 genetic variants with proposed linkage to disease. Although CNR2 genetic variation has been associated with a wide variety of conditions, including osteoporosis, immune‐related disorders, and mental illnesses, further work is required to robustly validate CNR2 disease links and clarify specific mechanisms linking CNR2 genetic variation to disease pathophysiology and potential drug responses. [ABSTRACT FROM AUTHOR]

Biological hallmarks of splenic marginal zone lymphoma (SMZL) remain poorly described. Herein, we performed in‐depth SMZL characterization through multimodal single‐cell analyses of paired blood/spleen samples. The 3'‐single‐cell RNA‐sequencing, Cellular Indexing of Transcriptomes and Epitopes by sequencing, and 5'‐V(D)J single‐cell RNA‐sequencing datasets were integrated to characterize SMZL transcriptome profiles, including B‐cell receptor and T‐cell receptor repertoires. Hyperexpanded B‐cell clones in the spleen were at a memory‐like stage, whereas recirculating tumor B‐cells in blood encompassed multiple differentiation stages, indicating an unexpected desynchronization of the B‐cell maturation program in SMZL cells. Spatial transcriptomics showed the enrichment of T‐effector and T‐follicular helper (TFH) signatures in the nodular subtype of SMZL. This latter also exhibited gene‐based cell–cell interactions suggestive of dynamic crosstalk between TFH and cancer cells in transcriptomics, further substantiated by using imaging mass cytometry. Our findings provide a comprehensive high‐resolution description of SMZL biological hallmarks and characterize, for the first time in situ, inter‐ and intra‐patient heterogeneity at both transcriptomic and protein levels. © 2024 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland. [ABSTRACT FROM AUTHOR]

Early life history traits of small pelagic fish are usually affected by environmental conditions. Patagonian sprat, Sprattus fuegensis, is a small pelagic fish that inhabits the continental shelf, fjords and channels of Patagonia. Their larvae are usually exposed to large variations in physical and biological conditions. We evaluated the effects of environmental conditions on early life history traits of this key species encompassing over 20 years of information. The characterization of oceanographic features, larval abundance and distribution was carried out in western Patagonia between 1996 and 2019, while the growth and mortality rates were estimated for the austral spring 2019 between 49°54′S and 53°55′S. Larval abundance decreased three to ten times from 1996 to 1997 to the rest of the study period (2008–2010 and 2014–2019), with larger abundances being found over the shelf. In spring 2019, the growth rate was 0.20 ± 0.05 mm d−1 for larvae between 9 and 19 days after hatching. The growth rate was similar in partially stratified (7–50 J m−3) and stratified waters (50–100 J m−3), but slower in mixed waters (< 7 J m−3). GAM modelling showed that the faster larval growth occurred in partially stratified waters with temperatures above 7.5°C. Natural mortality rates were higher in partially stratified waters (24% of daily loss), lower in stratified areas (14%) and the lowest in the mixed water column (12%). Accordingly, larvae living in channels had faster growth rates but higher daily mortality, while those that hatched or were advected to water parcels on the continental shelf had slower growth but lower daily mortality. Finally, these latter traits may be an example of an inverse growth‐selective survival strategy. [ABSTRACT FROM AUTHOR]

This paper proposes a full-automatic high-efficiency Mueller matrix microscopic imaging (MMMI) system based on the tissue microarray (TMA) for cancer inspection for the first time. By performing a polar decomposition on the sample's Mueller matrix (MM) obtained by a transmissive MMMI system we established, the linear phase retardance equivalent waveplate fast-axis azimuth and the linear phase retardance are obtained for distinguishing the cancerous tissues from the normal ones based on the differences in their polarization characteristics, where three analyses methods including statistical analysis, the gray-level co-occurrence matrix analysis (GLCM) and the Tamura image processing method (TIPM) are used. Previous MMMI medical diagnostics typically utilized discrete slices for inspection under a high-magnification objective (20×–50×) with a small field of view, while we use the TMA under a low-magnification objective (5×) with a large field of view. Experimental results indicate that MMMI based on TMA can effectively analyze the pathological variations in biological tissues, inspect cancerous cervical tissues, and thus contribute to the diagnosis of postoperative cancer biopsies. Such an inspection method, using a large number of samples within a TMA, is beneficial for obtaining consistent findings and good reproducibility. [ABSTRACT FROM AUTHOR]

Background: Although the inherited risk factors associated with fatty liver disease are well understood, little is known about the genetic background of metabolic dysfunction-associated steatotic liver disease (MASLD) and its related health impacts. Compared to non-alcoholic fatty liver disease (NAFLD), MASLD presents significantly distinct diagnostic criteria, and epidemiological and clinical features, but the related genetic variants are yet to be investigated. Therefore, we conducted this study to assess the genetic background of MASLD and interactions between MASLD-related genetic variants and metabolism-related outcomes. Methods: Participants from the UK Biobank were grouped into discovery and replication cohorts for an MASLD genome-wide association study (GWAS), and base and target cohorts for polygenic risk score (PRS) analysis. Autosomal genetic variants associated with NAFLD were compared with the MASLD GWAS results. Kaplan–Meier and Cox regression analyses were used to assess associations between MASLD and metabolism-related outcomes. Results: Sixteen single-nucleotide polymorphisms (SNPs) were identified at genome-wide significance levels for MASLD and duplicated in the replication cohort. Differences were found after comparing these SNPs with the results of NAFLD-related genetic variants. MASLD cases with high PRS had a multivariate-adjusted hazard ratio of 3.15 (95% confidence interval, 2.54–3.90) for severe liver disease (SLD), and 2.81 (2.60–3.03) for type 2 diabetes mellitus. The high PRS amplified the impact of MASLD on SLD and extrahepatic outcomes. Conclusions: High PRS of MASLD GWAS amplified the impact of MASLD on SLD and metabolism-related outcomes, thereby refining the process of identification of individuals at high risk of MASLD. Supplementation of this process with relevant genetic backgrounds may lead to more effective MASLD prevention and management. [ABSTRACT FROM AUTHOR]

An insulin resistant state is characteristic of patients with type 2 diabetes, polycystic ovary syndrome, and metabolic syndrome. Identification of insulin resistance (IR) is most readily achievable using formulae combining plasma insulin and glucose results. In this study, we have used data from the European Biological Variation Study (EuBIVAS) to examine the biological variability (BV) of IR using the Homeostasis Model Assessment for Insulin Resistance (HOMA-IR) and the Quantitative Insulin sensitivity Check Index (QUICKI).Ninety EuBIVAS non-diabetic subjects (52F, 38M) from five countries had fasting HOMA-IR and QUICKI calculated from plasma glucose and insulin samples collected concurrently on 10 weekly occasions. The within-subject (CVI) and between-subject (CVG) BV estimates with 95 % CIs were obtained by CV-ANOVA after analysis of trends, variance homogeneity and outlier removal.The CVI of HOMA-IR was 26.7 % (95 % CI 25.5–28.3), driven largely by variability in plasma insulin and the CVI for QUICKI was 4.1 % (95 % CI 3.9–4.3), reflecting this formula’s logarithmic transformation of glucose and insulin values. No differences in values or BV components were observed between subgroups of men or women below and above 50 years.The EuBIVAS, by utilising a rigorous experimental protocol, has produced robust BV estimates for two of the most commonly used markers of insulin resistance in non-diabetic subjects. This has shown that HOMA-IR, in particular, is highly variable in the same individual which limits the value of single measurements. [ABSTRACT FROM AUTHOR]

Integrating multiple single‐cell datasets is essential for the comprehensive understanding of cell heterogeneity. Batch effect is the undesired systematic variations among technologies or experimental laboratories that distort biological signals and hinder the integration of single‐cell datasets. However, existing methods typically rely on a selected dataset as a reference, leading to inconsistent integration performance using different references, or embed cells into uninterpretable low‐dimensional feature space. To overcome these limitations, a reference‐free method, Beaconet, for integrating multiple single‐cell transcriptomic datasets in original molecular space by aligning the global distribution of each batch using an adversarial correction network is presented. Through extensive comparisons with 13 state‐of‐the‐art methods, it is demonstrated that Beaconet can effectively remove batch effect while preserving biological variations and is superior to existing unsupervised methods using all possible references in overall performance. Furthermore, Beaconet performs integration in the original molecular feature space, enabling the characterization of cell types and downstream differential expression analysis directly using integrated data with gene‐expression features. Additionally, when applying to large‐scale atlas data integration, Beaconet shows notable advantages in both time‐ and space‐efficiencies. In summary, Beaconet serves as an effective and efficient batch effect removal tool that can facilitate the integration of single‐cell datasets in a reference‐free and molecular feature‐preserved mode. [ABSTRACT FROM AUTHOR]

Biological variation is a relevant component of diagnostic uncertainty. In addition to within-subject and between-subject variation, preanalytical variation also includes components that contribute to biological variability. Among these, daily recurring, i.e., diurnal physiological variation is of particular importance, as it contains both a random and a non-random component if the exact time of blood collection is not known.We introduce four time-dependent characteristics (TDC) of diurnal variations for measurands to assess the relevance and extent of time dependence on the evaluation of laboratory results.TDC address (i) a threshold for considering diurnality, (ii) the expected relative changes per time unit, (iii) the permissible time interval between two blood collections at different daytimes within which the expected time dependence does not exceed a defined analytical uncertainty, and (iv) a rhythm-expanded reference change value. TDC and their importance will be exemplified by the measurands aspartate aminotransferase, creatine kinase, glucose, thyroid stimulating hormone, and total bilirubin. TDCs are calculated for four time slots that reflect known blood collection schedules, i.e., 07:00–09:00, 08:00–12:00, 06:00–18:00, and 00:00–24:00. The amplitude and the temporal location of the acrophase are major determinates impacting the diagnostic uncertainty and thus the medical interpretation, especially within the typical blood collection time from 07:00 to 09:00.We propose to check measurands for the existence of diurnal variations and, if applicable, to specify their time-dependent characteristics as outlined in our concept. [ABSTRACT FROM AUTHOR]

Background and Purpose: Conclusions from prior literature regarding the impact of sex, age, and height on spinal cord (SC) MRI morphometrics are conflicting, while the effect of body weight on SC morphometrics has been found to be nonsignificant. The purpose of this case‐control study is to assess the associations between cervical SC MRI morphometric parameters and age, sex, height, and weight to establish their potential role as confounding variables in a clinical study of people with multiple sclerosis (MS) compared to a cohort of healthy volunteers. Methods: Sixty‐nine healthy volunteers and 31 people with MS underwent cervical SC MRI at 3 Tesla field strength. Images were centered at the C3/C4 intervertebral disc and processed using Spinal Cord Toolbox v.4.0.2. Mixed‐effects linear regression models were used to evaluate the effects of biological variables and disease status on morphometric parameters. Results: Sex, age, and height had significant effects on cord and gray matter (GM) cross‐sectional area (CSA) as well as the GM:cord CSA ratio. There were no significant effects of body weight on morphometric parameters. The effect of MS disease duration on cord CSA in the C4 level was significant when controlling for all other variables. Conclusions: Studies of disease‐related changes in SC morphometry should control for sex, age, and height to account for physiological variation. [ABSTRACT FROM AUTHOR]

Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a chronic disease presenting with severe fatigue, post‐exertional malaise, and cognitive disturbances—among a spectrum of symptoms—that collectively render the patient housebound or bedbound. Epigenetic studies in ME/CFS collectively confirm alterations and/or malfunctions in cellular and organismal physiology associated with immune responses, cellular metabolism, cell death and proliferation, and neuronal and endothelial cell function. The sudden onset of ME/CFS follows a major stress factor that, in approximately 70% of cases, involves viral infection, and ME/CFS symptoms overlap with those of long COVID. Viruses primarily linked to ME/CFS pathology are the symbiotic herpesviruses, which follow a bivalent latent–lytic lifecycle. The complex interaction between viruses and hosts involves strategies from both sides: immune evasion and persistence by the viruses, and immune activation and viral clearance by the host. This dynamic interaction is imperative for herpesviruses that facilitate their persistence through epigenetic regulation of their own and the host genome. In the current article, we provide an overview of the epigenetic signatures demonstrated in ME/CFS and focus on the potential strategies that latent viruses—particularly Epstein–Barr virus—may employ in long‐term epigenetic reprograming in ME/CFS. Epigenetic studies could aid in elucidating relevant biological pathways impacted in ME/CFS and reflect the physiological variations among the patients that stem from environmental triggers, including exogenous viruses and/or altered viral activity. [ABSTRACT FROM AUTHOR]

Analytical performance specifications (APS) are typically established through one of three models: (i) outcome studies, (ii) biological variation (BV), or (iii) state-of-the-art. Presently, The APS can, for most measurands that have a stable concentration, be based on BV. BV based APS, defined for imprecision, bias, total allowable error and allowable measurement uncertainty, are applied to many different processes in the laboratory. When calculating APS, it is important to consider the different APS formulae, for what setting they are to be applied and if they are suitable for the intended purpose. In this opinion paper, we elucidate the background, limitations, strengths, and potential intended applications of the different BV based APS formulas. When using BV data to set APS, it is important to consider that all formulae are contingent on accurate and relevant BV estimates. During the last decade, efficient procedures have been established to obtain reliable BV estimates that are presented in the EFLM biological variation database. The database publishes detailed BV data for numerous measurands, global BV estimates derived from meta-analysis of quality-assured studies of similar study design and automatic calculation of BV based APS. [ABSTRACT FROM AUTHOR]

This document discusses the concept of analytical performance specifications (APS) in laboratory medicine. It provides an overview of previous conferences and consensus documents on setting APS, including the 2014 EFLM Strategic Conference. The 2023 CELME conference aimed to explore the three models from the Milan conference and offer practical recommendations for their application. The document emphasizes the importance of APS in ensuring harmonized medical laboratory results for patient care. It also discusses the challenges in determining measurement uncertainty and the need for education on APS usage. The document concludes by highlighting important questions for further consideration, such as the creation of a single database for APS and the intended use and aspirational nature of APS. [Extracted from the article]

Analytical performance specifications (APS) are used for decisions about the required analytical quality of pathology tests to meet clinical needs. The Milan models, based on clinical outcome, biological variation, or state of the art, were developed to provide a framework for setting APS. An approach has been proposed to assign each measurand to one of the models based on a defined clinical use, physiological control, or an absence of quality information about these factors. In this paper we propose that in addition to such assignment, available information from all models should be considered using a risk-based approach that considers the purpose and role of the actual test in a clinical pathway and its impact on medical decisions and clinical outcomes in addition to biological variation and the state-of-the-art. Consideration of APS already in use and the use of results in calculations may also need to be considered to determine the most appropriate APS for use in a specific setting. [ABSTRACT FROM AUTHOR]

Even if the topic of the analytical quality required to provide laboratory results "fit for purpose" exists since the beginning of the modern medical laboratory, there is the suspect that the expression "Analytical Performance Specifications" (APS) is not well-known. To investigate this aspect a survey was conducted. A questionnaire with seven questions related to the knowledge about the topic, the sources of information and the criteria used by the laboratories to set the APS and their applications was prepared. It was distributed to all the clinical pathology laboratories of Lombardy Region (143) and to the members of SIBioC Laboratory Medicine (excluding Lombardy). We received 201 replies: 127 from Lombardy and 74 from the rest of Italy. Fifteen percent declared to ignore the meaning of APS and only 64 % of those knowing the meaning of the term declared to use them in the daily practice. The state-of-the-art was the principle used more frequently to set APS (about 48 %) followed by biological variation (41 %), and APS were typically applied to set goals for Internal Quality Control for selected measurands. Usually imprecision or total error APS were used, much less frequently uncertainty APS. In fact only 27 % of the laboratories declared to have calculated the measurement uncertainty for part or the majority of their measurands. Even considering the limits of a survey that relies upon self-declarations, it appears clearly that, at list in Italy, there is some work to be done to promote the concept and the use of APS. [ABSTRACT FROM AUTHOR]

Analytical performance specifications (APS) represent the criteria that specify the quality required for laboratory test information to satisfy clinical needs. In 2014 the European Federation of Clinical Chemistry and Laboratory Medicine (EFLM) considered timely to update the topic of APS by organizing a conference in Milan in which some strategic concepts were proposed. Here I summarize the essential points representing the EFLM Strategic Conference heritage and discuss the approaches that will permit us to become more concrete, including roles and main actions expected from each of involved stakeholders for contributing a quantum leap forward in the way of practicality of Milan consensus about APS. [ABSTRACT FROM AUTHOR]

The pre-analytical stability of various biochemical analytes requires careful consideration, as it can lead to the release of erroneous laboratory results. There is currently significant variability in the literature regarding the pre-analytical stability of various analytes. The aim of this study was to determine the pre-analytical stability of 65 analytes in whole blood, serum and plasma using a standardized approach. Blood samples were collected from 30 healthy volunteers (10 volunteers per analyte) into five vacutainers; either SST, Li-heparin, K2-EDTA, or Na-fluoride/K-oxalate. Several conditions were tested, including delayed centrifugation with storage of whole blood at room temperature (RT) for 8 h, delayed centrifugation with storage of whole blood at RT or 4 °C for 24 h, and immediate centrifugation with storage of plasma or serum at RT for 24 h. Percent deviation (% PD) from baseline was calculated for each analyte and compared to the maximum permissible instability (MPI) derived from intra- and inter-individual biological variation. The majority of the analytes evaluated remained stable across all vacutainer types, temperatures, and timepoints tested. Glucose, potassium, and aspartate aminotransferase, among others, were significantly impacted by delayed centrifugation, having been found to be unstable in whole blood specimens stored at room temperature for 8 h. The data presented provides insight into the pre-analytical variables that impact the stability of routine biochemical analytes. This study may help to reduce the frequency of erroneous laboratory results released due to exceeded stability and reduce unnecessary repeat phlebotomy for analytes that remain stable despite delayed processing. [ABSTRACT FROM AUTHOR]

The identification of changes in tumor markers (TMs) in cancer patients that indicate response to treatment, stabilization or disease progression is a challenge for laboratory medicine. Several approaches have been proposed: assessing percentage increases, applying discriminant values, and estimating half-life (t1/2) or doubling time (DT). In all of them it is assumed that the TM is a surrogate of the variation in tumor size. In general this variation is time-dependent, but this is not the case of intraindividual biological variability (CVi), which can range from 6 % in CA15-3 to 22 % in CA125. When decisions are made on the basis of DT or t1/2, these values can be affected by the CVi; if it is very large, the growth rate very slow and the period of time between determinations very short, the result obtained for DT may be due mainly to the CVi. The aim of this study is to establish the relationship between the CVi and temporal variables. We related equations for calculating DT and t1/2 to the reference change values in tumor markers. The application of the formula obtained allows the calculation of the optimal time between measurements to ensure that the influence of the CVi is minimal in different types of tumors and different scenarios. Intraindividual variation affects the calculation of DT and t1/2. It is necessary to establish the minimum time between two measurements to ensure that the CVi does not affect their calculation or lead to misinterpretation. [ABSTRACT FROM AUTHOR]

Humans have substantially transformed the global land surface, resulting in the decline in variation in biotic communities across scales, a phenomenon known as "biological homogenization." However, different biota are affected by biological homogenization to varying degrees, but this variation and the underlying mechanisms remain little studied, particularly in soil systems. To address this topic, we used metabarcoding to investigate the biogeography of soil protists and their prey/hosts (prokaryotes, fungi, and meso‐ and macrofauna) in three human land‐use ecosystem types (farmlands, residential areas, and parks) and natural forest ecosystems across subtropical and temperate regions in China. Our results showed that the degree of community homogenization largely differed between taxa and functional groups of soil protists, and was strongly and positively linked to their colonization ability of human land‐use systems. Removal analysis showed that the introduction of widespread, generalist taxa (OTUs, operational taxonomic units) rather than the loss of narrow‐ranged, specialist OTUs was the major cause of biological homogenization. This increase in generalist OTUs seemingly alleviated the negative impact of land use on specialist taxa, but carried the risk of losing functional diversity. Finally, homogenization of prey/host biota and environmental conditions were also important drivers of biological homogenization in human land‐use systems, with their importance being more pronounced in phagotrophic than parasitic and phototrophic protists. Overall, our study showed that the variation in biological homogenization strongly depends on the colonization ability of taxa in human land‐use systems, but is also affected by the homogenization of resources and environmental conditions. Importantly, biological homogenization is not the major cause of the decline in the diversity of soil protists, and conservation and study efforts should target at taxa highly sensitive to local extinction, such as parasites. [ABSTRACT FROM AUTHOR]

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With about 60%-70% of medical decisions based on laboratory investigations, modern medicine is increasingly more reliant on laboratory medicine. Pediatric healthcare particularly depends on laboratory testing, with reference intervals (RIs) serving as critical tools for accurate result interpretation. However, establishing pediatric RIs poses distinctive challenges due to developmental, growth, nutritional, and disease-related variations across age groups, along with technical, ethical, and logistical challenges. Despite these limitations, there are several ongoing initiatives for developing pediatric RIs globally, underscoring the importance of developing accurate pediatric RIs. This review outlines the particularities of pediatric laboratory medicine and the specific challenges in establishing pediatric RIs, highlighting the recent initiatives in this area. It also addresses biological and analytical variability issues and explores future perspectives aimed at enhancing diagnostic accuracy and elevating patient care standards.

Abstract Background Although the inherited risk factors associated with fatty liver disease are well understood, little is known about the genetic background of metabolic dysfunction-associated steatotic liver disease (MASLD) and its related health impacts. Compared to non-alcoholic fatty liver disease (NAFLD), MASLD presents significantly distinct diagnostic criteria, and epidemiological and clinical features, but the related genetic variants are yet to be investigated. Therefore, we conducted this study to assess the genetic background of MASLD and interactions between MASLD-related genetic variants and metabolism-related outcomes. Methods Participants from the UK Biobank were grouped into discovery and replication cohorts for an MASLD genome-wide association study (GWAS), and base and target cohorts for polygenic risk score (PRS) analysis. Autosomal genetic variants associated with NAFLD were compared with the MASLD GWAS results. Kaplan–Meier and Cox regression analyses were used to assess associations between MASLD and metabolism-related outcomes. Results Sixteen single-nucleotide polymorphisms (SNPs) were identified at genome-wide significance levels for MASLD and duplicated in the replication cohort. Differences were found after comparing these SNPs with the results of NAFLD-related genetic variants. MASLD cases with high PRS had a multivariate-adjusted hazard ratio of 3.15 (95% confidence interval, 2.54–3.90) for severe liver disease (SLD), and 2.81 (2.60–3.03) for type 2 diabetes mellitus. The high PRS amplified the impact of MASLD on SLD and extrahepatic outcomes. Conclusions High PRS of MASLD GWAS amplified the impact of MASLD on SLD and metabolism-related outcomes, thereby refining the process of identification of individuals at high risk of MASLD. Supplementation of this process with relevant genetic backgrounds may lead to more effective MASLD prevention and management.

• The Zulus engage in complementary and alternative medicine through a traditional healing system known as izangoma. • The first review of the antidiabetic medicinal plants commonly used by the Zulus of Kwazulu-Natal province of South Africa. • The list includes local and botanical names, the parts commonly used, isolated bioactive principles and their reported mechanisms of action. • 38 plants covering 20 families were identified with Asteraceae accounting for 34.2% and the leaves was the most used plant part (50 %). • 29 have been scientifically validated while nine lack scientific verification. Diabetes mellitus is a chronic metabolic disorder that affects millions of people worldwide. Its conventional management involves diet modification, exercise, and majorly the use of synthetic drugs, which may be ineffective, have adverse effects, and of relatively expensive costs. To mitigate the downsides of the available treatments, alternative therapies from medicinal plants are commonly sought by different ethnic groups including the Zulus. This paper appraised the antidiabetic plants used by the Zulus, their local and botanical names, the parts commonly used, isolated bioactive principles and their reported mechanisms of action. 38 plants covering 20 families were identified with Asteraceae accounting for 31.57 % and the leaves was the most used plant part (50 %). Out of the 38 plants identified, 28 have been scientifically validated using in vitro/in vivo models but identifying the plant with the most potent hypoglycemic activity remains challenging due to variations in biological activities. Important antidiabetic agents such as quercetin, squalene, kaempferol, isomukaadial acetate, phytol, sitosterol, apigenin, catechin and their derivates have been isolated and characterized from the verified plants though, more scientific exploration is required to develop these principles into valuable antidiabetic medications with establish mechanism of action. Scientists therefore needs to beam their searchlight and dedicate resources to the rich botanicals of the Zulu land with the view to providing indigenous solutions that can be incorporated into modern medicine for diabetes management. [ABSTRACT FROM AUTHOR]

Recent microbiome research has incorporated a higher number of samples through more participants in a study, longitudinal studies, and metanalysis between studies. Physical limitations in a sequencing machine can result in samples spread across sequencing runs. Here we present the results of sequencing nearly 1000 16S rRNA gene sequences in fecal (stabilized and swab) and oral (swab) samples from multiple human microbiome studies and positive controls that were conducted with identical standard operating procedures. Sequencing was performed in the same center across 18 different runs. The simplified mock community showed limitations in accuracy, while precision (e.g., technical variation) was robust for the mock community and actual human positive control samples. Technical variation was the lowest for stabilized fecal samples, followed by fecal swab samples, and then oral swab samples. The order of technical variation stability was inverse of DNA concentrations (e.g., highest in stabilized fecal samples), highlighting the importance of DNA concentration in reproducibility and urging caution when analyzing low biomass samples. Coefficients of variation at the genus level also followed the same trend for lower variation with higher DNA concentrations. Technical variation across both sample types and the two human sampling locations was significantly less than the observed biological variation. Overall, this research providing comparisons between technical and biological variation, highlights the importance of using positive controls, and provides semi-quantified data to better understand variation introduced by sequencing runs. Key points: • Mock community and positive control accuracy were lower than precision. • Samples with lower DNA concentration had increased technical variation across sequencing runs. • Biological variation was significantly higher than technical variation due to sequencing runs. [ABSTRACT FROM AUTHOR]

Invasive populations cause adverse impacts on ecosystems, agriculture, and economic activities. Advancing understanding of how populations respond to environmental changes and develop their invasive status will enable improved prediction, prevention, and management of ecological invasions. Here, we review recent literature and find that behavioural shifts within species across native and invasive populations are common during invasion. We collate examples which demonstrate how behaviours associated with invasion can be an outcome of plastic, pre-adaptive, and/or post-adaptive processes. However, we find that research investigating the molecular basis of observed behavioural shifts associated with invasion is limited. Important research (but perhaps the most challenging to conduct), is the long-term study of ongoing invasions that track species' behaviour and genetic change throughout the stages of the invasion process. Additionally, future research should aim to establish whether behavioural shifts originate from plasticity, microevolutionary processes, or a combination of both. Common garden experiments (using distinct populations grown under shared conditions), carried out in conjunction with genetic studies that track changes at the molecular level, could aid this endeavour. [ABSTRACT FROM AUTHOR]

Body colouration, a trait under strong selection, is influenced by the visual background of the environment. The stable influence of depth on visual background dynamics is due to light attenuation along the water column. Depth is also a key factor driving diversification in Sebastes rockfishes, influencing variations in several biological traits. Comparisons between closely related species suggest that brightly coloured species (red, orange, or yellow) tend to inhabit deeper waters and have slower growth rates compared to their shallow-water counterparts with dominance of dark colours (black, brown, or grey). Here, we used 377 photos from 100 Sebastes species, along with recently developed methods of colour quantification and phylogenetic comparative analyses, to assess this trend. Our analyses confirmed the separation of body colouration regarding depth, which was accompanied by differences in growth rates and morphological traits. This indicated that variations in body colourations are included in the ongoing correlational selection process dictated by depth. Analyses of closely related species indicated that depth is an initial driver of colour differentiation and that colour differences do not progressively increase with genetic divergences. We hypothesized that the bright-coloured rockfishes are found in deeper waters because in shallow environments they are more vulnerable to the potential negative effects of UV radiation and higher predation risk, while their predation successes are lessened, in comparison to dark-coloured rockfishes. Overall, this study emphasizes the intricate relationship between genetics, environment, adaptation, and the striking diversity of body colourations observed in Sebastes rockfishes. [ABSTRACT FROM AUTHOR]

Nutrient absorption is essential for animal survival and development. Our previous study on zebrafish reported that nutrient absorption in lysosome-rich enterocytes (LREs) is promoted by the voltage-sensing phosphatase (VSP), which regulates phosphoinositide (PIP) homeostasis via electrical signaling in biological membranes. However, it remains unknown whether this VSP function is shared by different absorptive tissues in other species. Here, we focused on the function of VSP in a viviparous teleost Xenotoca eiseni, whose intraovarian embryos absorb nutrients from the maternal ovarian fluid through a specialized hindgutderived pseudoplacental structure called trophotaenia. Xenotoca eiseni VSP (Xe-VSP) is expressed in trophotaenia epithelium, an absorptive tissue functionally similar to zebrafish LREs. Notably, the apical distribution of Xe-VSP in trophotaenia epithelial cells closely resembles zebrafish VSP (Dr-VSP) distribution in zebrafish LREs, suggesting a shared role for VSP in absorptive tissues between the two species. Electrophysiological analysis using a heterologous expression system revealed that Xe-VSP preserves functional voltage sensors and phosphatase activity with the leftward shifted voltage sensitivity compared with zebrafish VSP (Dr-VSP). We also identified a single amino acid variation in the S4 helix of Xe-VSP as one of the factors contributing to the leftward shifted voltage sensitivity. This study highlights the biological variation and significance of VSP in various animal species, as well as hinting at the potential role of VSP in nutrient absorption in X. eiseni trophotaenia. NEW & NOTEWORTHY We investigate the voltage-sensing phosphatase (VSP) in Xenotoca eiseni, a viviparous fish whose intraovarian embryos utilize trophotaenia for nutrient absorption. Although X. eiseni VSP (Xe-VSP) shares key features with known VSPs, its distinct voltage sensitivity arises from species-specific amino acid variation. Xe-VSP in trophotaenia epithelium suggests its involvement in nutrient absorption, similar to VSP in zebrafish enterocytes and potentially in species with similar absorptive cells. Our findings highlight the potential role of VSP across species. [ABSTRACT FROM AUTHOR]

Cereals are some of the most important global crops that contribute directly and indirectly to the production of food for human consumption. Cereal aphids can cause significant damage to wheat, barley and oats, particularly via the transmission of plant viruses that cause devastating plant diseases, such as yellow dwarf disease. High levels of yellow dwarf disease can result in yield losses of around 20%, rising to 80% if infection is severe. Yellow dwarf disease is caused by multiple viruses, including viruses within the families Tombusviridae and Solemoviridae. These include yellow dwarf virus species within the genus Luteovirus (Barley yellow dwarf virus) and Polerovirus (Cereal yellow dwarf virus, Wheat yellow dwarf virus, Maize yellow dwarf virus). Some yellow dwarf virus species are primarily vectored by one aphid species whereas others can be transmitted by multiple vectors. Biological diversity within a given vector species (e.g., genotype, biotype) can influence virus transmission efficiency. However, it is unclear what biological factors drive this variation within a given vector species. Understanding how biological variation in vector populations influences virus transmission efficiency can help to identify biological traits that underpin successful transmission in competent vector populations. Here, the available literature on yellow dwarf virus transmission efficiency is synthesized and significant variation in yellow dwarf virus transmission efficiency is detected between different populations for several vector species. Three biological mechanisms that potentially underpin this variation are proposed. [ABSTRACT FROM AUTHOR]

To analyze the inter-individual responsiveness of post-exercise hypotension after a single dose of l-arginine supplementation in hypertensive patients. A double-blind, randomized, placebo-controlled crossover trial was conducted. A total of 10 adults, hypertensive and sedentary, were randomly assigned to both experimental groups (placebo and l-arginine). The participants ingested a sachet containing 8 grams of l-arginine or placebo (corn starch). During the experimental sessions, individuals performed 40 min of walking/running on a treadmill at 60–70% of heart rate reserve. After the exercise sessions, blood pressure was measured every 10 min for 60 min. Considering systolic blood pressure, most participants responded favorably (lowering BP) in the "arginine" experimental arm. [ABSTRACT FROM AUTHOR]

Background: Biochemical measurements are commonly evaluated using populationbased reference intervals; however, there is a growing trend toward reassessing results with within-subject variation (CVI). Objectives: We aimed to estimate the CVI of 16 biochemical analytes using a large database of dogs and cats, which refers to the results of routine health checkups. Methods: Pairs of sequential results for 16 analytes were extracted from a database of adult patients. The second result was divided by the first result to produce the ratio of sequential results (rr), and the frequency distribution of rr was plotted. From the plots, the coefficient of variation (CVrr) was calculated. Analytical variation (CVA) was calculated using quality control data, and CVI was estimated as follows: CVI = ([CVrr∕21∕2]² −CVA²)1∕2. Estimated CVI was compared with previously reported CVI using the Bland–Altman plot analysis. Results: From the database, 9078 data points from 3610 dogs and 3743 data points from 1473 cats were extracted, with 5468 data pairs for dogs and 2270 for cats. Sampling intervals ranged from 10 to 1970 days (median 366) for dogs and 23 to 1862 days (median 365) for cats. Bland–Altman analysis showed most CVI plots fell within the limits of agreement; however, positive fixed biases were observed in both dogs and cats. Conclusions: Our study introduces a novel approach of estimating CVI using routine health checkup data in dogs and cats. Despite biases, our method holds promise for clinical application in assessing the significance of measurement result differences. [ABSTRACT FROM AUTHOR]

Diazotrophic communities contribute inorganic nitrogen for the primary productivity of the marine environment by biological nitrogen fixation (BNF). They play a vital role in the biogeochemical cycle of nitrogen in the marine ecological environment. However, there is still an incomplete understanding of BNF and diazotrophs in artificial seaweed farms. Therefore, this study comprehensively investigated the temporal variations of BNF associated with Gracilariopsis lemaneiformis, as well as the diazotrophic communities associated with macroalgae and its surrounding seawater. Our results revealed that a total of 13 strains belonging to Proteobacteria and Bacteroidetes were identified as N2-fixing bacteria using azotobacter selective solid medium and nifH gene cloning. Subsequently, BNF and diazotrophic communities were characterized using the acetylene reduction method and high-throughput sequencing of the nifH gene, respectively. The results showed that nitrogenase activity and nifH gene abundance of epiphytic bacteria on G. lemaneiformis varied significantly among four different cultivation periods, i.e., Cultivation Jan. (CJ), Cultivation Feb. (CF), Cultivation Mar. (CM), Cultivation Apr. (CA). Among them, the nitrogenase activity and nifH gene abundance of epiphytic bacteria on G. lemaneiformis in CM were significantly higher than those in CJ, CF, and CA, indicating that the BNF of eiphytic bacteria on G. lemaneiformis wasmarkedly enhanced. Combined with the data on environmental factors, it was found that the low concentration of nitrogen and phosphorus in CM might considerably boost the BNF of epiphytic bacteria in G. lemaneiformis. The sequencing results of the nifH gene showed that the adiversity of diazotrophic communities associated with G. lemaneiformis and seawater in CM was higher than that in other cultivation periods. In addition, the diazotrophic communities on G. lemaneiformis were significantly different in CJ, CF, CM, and CA, and they were significantly diverse from diazotrophic communities in seawater. LEfSe analysis indicated that Rhodobacterales, Hyphomonadaceae, Robiginitomaculum, and Robiginitomaculum antarcticum within a-proteobacteria played a remarkable role in BNF in response to nitrogen nutrient deficiency. Taken together, these results provide a unique insight into the interaction between macroalgae and its epiphytic bacteria and lay a foundation for further research on the mechanism of action of nitrogen-cycling microorganisms associated with macroalgae. [ABSTRACT FROM AUTHOR]

In this work, two new biscyclometalated Ir(III) complexes with diimine ligands were synthesized. The compounds were characterized by 1D and 2D NMR spectroscopy and HR ESI mass spectrometry. All complexes exhibit efficient phosphorescence with pronounced sensitivity to the presence of oxygen. The photophysical properties of the obtained compounds, including absorption, emission spectra, lifetimes and quantum yields of phosphorescence were measured in various aqueous and model biological media with variations in pH, temperature and at various O2 concentrations. The complexes exhibit a very good sensory response to the changes in oxygen concentration, resulting in an increase in quantum yields and lifetimes by 2.8–5.5 times upon oxygen removal from aerated aqueous solutions. Biological tests with CHO‐K1 cell line have shown that these compounds display low toxicity, rapid internalization into cells and localization predominantly in lysosomes. For the most promising complex the phosphorescence lifetime imaging experiments were conducted, revealing that this sensor markedly changes the phosphorescence lifetime values in cells from 1.8 to 4.1 μs upon transition from normoxia to simulated hypoxia. The obtained results indicate that this type of iridium chromophores can be effectively used for assessing the oxygen status of living objects by using time‐resolved luminescent microscopy. [ABSTRACT FROM AUTHOR]

Background: The C-type lectin family 18 (CLEC18) with lipid and glycan binding capabilities is important to metabolic regulation and innate immune responses against viral infection. However, human CLEC18 comprises three paralogous genes with highly similar sequences, making it challenging to distinguish genetic variations, expression patterns, and biological functions of individual CLEC18 paralogs. Additionally, the evolutionary relationship between human CLEC18 and its counterparts in other species remains unclear. Methods: To identify the sequence variation and evolutionary divergence of human CLEC18 paralogs, we conducted a comprehensive analysis using various resources, including human and non-human primate reference genome assemblies, human pangenome assemblies, and long-read-based whole-genome and -transcriptome sequencing datasets. Results: We uncovered paralogous sequence variants (PSVs) and polymorphic variants (PVs) of human CLEC18 proteins, and identified distinct signatures specific to each CLEC18 paralog. Furthermore, we unveiled a novel segmental duplication for human CLEC18A gene. By comparing CLEC18 across human and non-human primates, our research showed that the CLEC18 paralogy probably occurred in the common ancestor of human and closely related non-human primates, and the lipid-binding CAP/SCP/TAPS domain of CLEC18 is more diverse than its glycan-binding CTLD. Moreover, we found that certain amino acids alterations at variant positions are exclusive to human CLEC18 paralogs. Conclusions: Our findings offer a comprehensive profiling of the intricate variations and evolutionary characteristics of human CLEC18. [ABSTRACT FROM AUTHOR]

Information about cell composition in tissue samples is crucial for biomarker discovery and prognosis. Specifically, cancer tissue samples present challenges in deconvolution studies due to mutations and genetic rearrangements. Here, we optimized a robust, DNA methylation-based protocol, to be used for deconvolution of ovarian cancer samples. We compared several state-of-the-art methods (HEpiDISH, MethylCIBERSORT and ARIC) and validated the proposed protocol in an in-silico mixture and in an external dataset containing samples from ovarian cancer patients and controls. The deconvolution protocol we eventually implemented is based on MethylCIBERSORT. Comparing deconvolution methods, we paid close attention to the role of a reference panel. We postulate that a possibly high number of samples (in our case: 247) should be used when building a reference panel to ensure robustness and to compensate for biological and technical variation between samples. Subsequently, we tested the performance of the validated protocol in our own study cohort, consisting of 72 patients with malignant and benign ovarian disease as well as in five external cohorts. In conclusion, we refined and validated a reference-based algorithm to determine cell type composition of ovarian cancer tissue samples to be used in cancer biology studies in larger cohorts. [ABSTRACT FROM AUTHOR]

There is a growing interest in the relevance of salivary cortisol and cortisone concentrations in stress-related research. To correctly attribute the magnitude of salivary cortisol and cortisone variation as an effect of a stressful event, a coherent understanding of the day-to-day intra-individual and inter-individual variability across the diurnal cycle of the two steroids is required. However, such information is currently lacking.This study aimed to overcome these existing limitations by performing an investigation of the biological variation (BV) of salivary cortisol and cortisone within one day and between five days using an LC-MS/MS method. Saliva samples were collected from 20 healthy volunteers immediately after waking up, at 8:00, 12:00, 15:00, 19:00 and 23:00 on each day over five days. All samples were analyzed in duplicate in one run. Nested ANOVA was used to calculate the sums of squares for analytical and biological components of variation.The within-subject BV of salivary cortisol and cortisone (CVI) ranged from a minimum of 29.3 and 19.0 % to a maximum of 56.5 and 49.1 %, respectively, while the between-subject biological variation (CVG) ranged from 29.7 and 29.0 % to 51.6 and 43.6 %. The reference change values (RCVs) ranged from 96 to 245 % for cortisol and from 55 to 194 % for cortisone. A medium index of individuality was observed for both compounds at all time points.This study provides updated BV estimates and RCVs for different times of day that can be used to assess the magnitude of change in biomarkers in future stress-related research. [ABSTRACT FROM AUTHOR]

Liquid Chromatography Mass Spectrometry (LC-MS) is a powerful method for profiling complex biological samples. However, batch effects typically arise from differences in sample processing protocols, experimental conditions, and data acquisition techniques, significantly impacting the interpretability of results. Correcting batch effects is crucial for the reproducibility of omics research, but current methods are not optimal for the removal of batch effects without compressing the genuine biological variation under study. We propose a suite of Batch Effect Removal Neural Networks (BERNN) to remove batch effects in large LC-MS experiments, with the goal of maximizing sample classification performance between conditions. More importantly, these models must efficiently generalize in batches not seen during training. A comparison of batch effect correction methods across five diverse datasets demonstrated that BERNN models consistently showed the strongest sample classification performance. However, the model producing the greatest classification improvements did not always perform best in terms of batch effect removal. Finally, we show that the overcorrection of batch effects resulted in the loss of some essential biological variability. These findings highlight the importance of balancing batch effect removal while preserving valuable biological diversity in large-scale LC-MS experiments. Liquid Chromatography Mass Spectrometry (LC-MS) is a powerful method for profiling biological samples. Here, the authors have developed a suit of Batch Effect Removal Neural Networks (BERNN) to remove batch effects in large LC-MS experiments to maximize sample classification between conditions. [ABSTRACT FROM AUTHOR]

Although comparative analyses and meta-analyses appear different in their purpose, both often address similar hypotheses and have comparable, if not identical, mathematical foundations. Merging the strength of phylogenetic comparative analyses with the power of meta-analyses to decompose variation has the potential to improve the transparency, reproducibility, and reliability of comparative research. The integration of comparative and meta-analytic approaches can handle data with different structures and levels of organisation, uncovering variation within and between community assemblages, broadening taxonomic coverage, and shaping our understanding of complex (nonlinear) patterns. The marriage of comparative analysis and meta-analysis offers a promising avenue through which comparative biologists can assess generality and the evolutionary processes giving rise to macroecological patterns. Comparative analyses and meta-analyses are key tools to elucidate broad biological principles, yet the two approaches often appear different in purpose. We propose an integrated approach that can generate deeper insights into ecoevolutionary processes. Marrying comparative and meta-analytic approaches will allow for (i) a more accurate investigation of drivers of biological variation, (ii) a greater ability to account for sources of non-independence in experimental data, (iii) more effective control of publication bias, and (iv) improved transparency and reproducibility. Stronger integration of meta-analytic and comparative studies can also broaden the scope from species-centric investigations to community-level responses and function-valued traits (e.g., reaction norms). We illuminate commonalities, differences, and the transformative potential of combining these methodologies for advancing ecology and evolutionary biology. [ABSTRACT FROM AUTHOR]

Various cytochrome P450 enzymes (CYPs) that contribute to drug metabolism are expressed in the skin. However, variation among individuals in CYP expression profiles is not well-understood. To investigate CYPs related to the metabolism of transdermal preparations in Japan, multiple skin tissue specimens of individuals of Japanese descent were prepared, and the mRNA expression levels of CYP1A2, CYP3A4, and CYP3A5 were measured. Associations between the expression patterns of these CYPs and body mass index (BMI) were also investigated. There were considerable individual differences in epidermal CYP1A2 mRNA expression levels, and CYP1A2 showed a weak positive correlation with CYP3A4 mRNA expression levels. In contrast to previous results for other organs, epidermal CYP3A4 mRNA expression levels showed a weak positive correlation with BMI. CYP3A4 in the epidermis may have been locally enhanced as a defence mechanism against xenobiotics in response to impaired barrier function. These differences in mRNA expression in the skin may affect the transdermal absorption of drugs, such as lidocaine and fentanyl, which are metabolised by multiple overlapping CYPs. Our study provides new insights into drug metabolism in the skin. These results are valuable for predicting drug effects and transdermal drug transfer rates in Japanese patients. [ABSTRACT FROM AUTHOR]

The ability to sex individuals is an important component of many behavioural and ecological investigations and provides information for demographic models used in conservation and species management. However, many birds are difficult to sex using morphological characters or traditional molecular sexing methods. In this study, we developed probabilistic models for sexing birds using quantitative PCR (qPCR) data. First, we quantified distributions of gene copy numbers at a set of six sex‐linked genes, including the sex‐determining gene DMRT1, for individuals across 17 species and seven orders of birds (n = 150). Using these data, we built predictive logistic models for sex identification and tested their performance with independent samples from 51 species and 13 orders (n = 209). Models using the two loci most highly correlated with sex had greater accuracy than models using the full set of sex‐linked loci, across all taxonomic levels of analysis. Sex identification was highly accurate when individuals to be assigned were of species used in model building. Our analytical approach was widely applicable across diverse neognath bird lineages spanning millions of years of evolutionary divergence. Unlike previous methods, our probabilistic framework incorporates uncertainty around qPCR measurements as well as biological variation within species into decision‐making rules. We anticipate that this method will be useful for sexing birds, including those of high conservation concern and/or subsistence value, that have proven difficult to sex using traditional approaches. Additionally, the general analytical framework presented in this paper may also be applicable to other organisms with sex chromosomes. [ABSTRACT FROM AUTHOR]

Tube manufacturers use different composition of gels and blood clot activator formulations in serum tube production. Our aim was to investigate the within-tube (repeatability) and between-tube variation, concordance between comparison results of BD and VacuSEL tubes. Blood samples were collected from control subjects (n = 20) and patients (n = 30) in accordance with the CLSI GP41-A6 and CLSI GP34-A guidelines. Twenty-three clinical chemistry parameters were analysed via Roche Cobas C702 Chemistry Analyzer on T0 (0 hour) and T24 (24 hour). Mean differences % were compared with Wilcoxon matched pair test. Clinical significance was evaluated based on desirable bias according to total allowable error (TEa). VacuSEL tubes demonstrated acceptable performance for the results of 20 parameters with regards to desirable bias % limits. Lactate dehydrogenase (LD) [mean difference % (%95 confidence intervals (CI) values of BD and VacuSEL tubes at T0 [6.41% (4.80–8.01%)]; sodium (Na) and total protein (TP) at T24 [-0.27% (-0.46 to −0.07%) and −1.39% (-1.87 to −0.91), respectively] were over the desirable bias limits (LD: 4.3%, Na: 0.23% and TP: 1.36%, respectively) but not exceeding total biological variation CV % [Na: 0.5 (0.0–1.0) % and TP: 2.6 (2.3–2.7) %). %95 confidence intervals (CI) of T0 LD values overlap with within-subject biological variation % (CI) limits (LD: 5.2 (4.9–5.4) %). The differences between two tubes were not medically significant and necessarily conclusive. VacuSEL serum tubes presented comparable performance with BD serum tubes. [ABSTRACT FROM AUTHOR]