Biology

In view of the outstanding progress of machine learning (ML) and growing cost of health systems, it is a current challenge to incorporate artificial intelligence tools into actual medical practice. Here we explored the feasibility and reliability of using machine learning to perform an important immunological investigation that currently requires experienced biologists : Anti-nuclear cytoplasmic antibodies (ANCAs) are important markers for vasculitis and they may be evidenced by microscopic examination of cells labeled with patients' sera. The use of a reliable ML classifier to discriminate between positive and negative samples would increase the rapidity and decrease the cost of immunofluorescence-based ANCA detection. Here, we tested seven well-documented ML algorithms, ranging from simple models such as k nearest neighbors to more complex convolutional neural networks involving millions of adjustable parameter. We studied the feasibility and reliability of classifying 1114 serum samples that had been collected for about 3 years and assayed with conventional procedure. We compared four strategies consisting of assaying either whole microscope fields or individual cell images, and natural images or histograms. The following conclusions were obtained : (i) Several different strategies allowed us to build models stable enough to discriminate between positive and negative samples collected during about 27 months, with a comparison to human classification yielding a kappa index of about 0.7, that may be considered as fairly good and intermediate between the performance of junior and senior biologists. (ii) Simpler ML models combined with theoretical thinking might provide the most rapid and efficient way of developing a reliable test within the framework of a single institution. (iii) In addition, the interpretability of the simplest model provided some theoretical insight into important classification parameters. (iv) An important point and caveat is that the multiplicity and versatility of currently available tools make it an essential requirement to test repeatedly a given model, that must be chosen as simple as possible, to achieve a reliability compatible with medical use. It is concluded that our study provides a strong incentive to incorporate ML tools in well defined medical tests, which might reduce the risk of human errors and pave the way to fully automatic procedures.

In spite of well-established global immune landscape, SARS-CoV-2 is still able to further spread and continue causing infection waves. The current understanding about the reason behind is limited, and it is still difficult to predict the evolution or spreading tread of SARS-CoV-2. Therefore, it is necessary to investigate whether the establishment of population immunity has changed the virus evolution or spreading pattern. In this investigation, one overall analysis of the SARS-CoV-2 spreading in the past several years have been carried out through one thorough genomic epidemiology study, with Germany being chosen as one representative location in view of the systemic efforts for genomic surveillance. The growth advantage of a few predominant variants in its early spreading period has been evaluated through a logistic regression model. The results have revealed that the major circulating SARS-CoV-2 variants since 2023 are mainly derived from the Omicron BA.2 family. Since middle of 2024, most predominant variants were produced primarily through recombination, indicating that the evolution derived from recombination might be the major driving force for the continuous spread of SARS-CoV-2 despite the existence of population immunity. Furthermore, the lower growth advantage of recently emerged variants might possibly lead to a tread of reduction in the frequency of infection wave. The information revealed from this investigation suggests that although short-term spreading tread can be affected by specific virus feature as well as local immunity landscape, the long-term spreading tread is mainly decided by the genomic diversity of the viruses, and can be predicted through phylogenetic and genomic epidemiology investigation. The results have emphasized the importance of maintaining the efforts for genomic surveillance of SARS-CoV-2, which is essential from both medical and research perspectives.

Intraspecific morphological variability presents a complex challenge for biological systematics and biomonitoring, particularly for organisms with high phenotypic plasticity, such as zooplankton. Morphological differences between individuals of the water flea species Bosmina longirostris (Crustacea: Cladocera) are difficult to distinguish visually, parthenogenetic females look morphologically uniform within the species; nevertheless, they demonstrate differences attributable to their geographic origin and developmental stage. A reference dataset of microscopic images was created for the study, including populations from two geographically separated regions (seven ones from European Russia and seven ones from Sakhalin Island in the Pacific Ocean (Far East of Russia) and two age groups, demonstrating the ability of a neural network classify to successfully the intraspecific morphological variation. This study demonstrates that deep learning methods are prospective for the detection and understanding of fine morphological intraspecific differences in the cladocerans.

Whole genome duplication is a common mutation in eukaryotes with far-reaching phenotypic effects. The resulting morphological, physiological, and fitness consequences and how they affect the survival probability of newly polyploid lineages are intensively studied, but very little is known about the effect of genome doubling on the short-term evolvability of populations. Understanding the effect of polyploidization on the adaptive potential of populations is of crucial importance to predict the future of polyploid populations. In this paper, I investigate the immediate consequences of genome doubling on the genetic variance of populations. To do so, I performed numerical iterations and simulations of how the genetic variance of a quantitative trait changes after polyploidization, under different genetic architectures (additivity, dominance, and epistasis). I found that genetic variance generally decreases after genome doubling. Non-additive gene actions can make autotetraploid populations genetically more diverse than their diploid progenitors in rare cases, notably with overdominance and directional epistasis. By collecting estimates from the agronomic literature, I found that both dominance and epistatic variance contribute to the genetic variance of polyploid populations. These results bring new insights into the adaptive potential of newly formed tetraploid populations, and call for further experimental investigations of how polyploidization is associated with a short-term decrease in evolvability.

This work focuses on the global and partial identification problem for fractional differential equations. We provide a general numerical procedure based on global and local optimization algorithms with two refinements for biological systems that ensure solution positivity and homogeneous parameter units. The method is applied to a new fractional model of Dengue outbreak called the Fractional Homogeneous Nishiura (FHN) model, calibrated using data of newly infected people in Cape Verde. We show that our identification method yields a better fit between data and model solutions than previous approaches and that our FHN model captures the dynamics of Dengue more closely than existing systems.

Gestational diabetes mellitus (GDM) is a major metabolic complication of pregnancy with significant maternal and fetal adverse consequences. Beyond classical mechanisms, emerging evidence suggests that gut-derived metabolic endotoxemia may contribute to dysglycemia. Intestinal alkaline phosphatase (IAP), a key enzyme involved in maintaining gut barrier integrity and detoxifying lipopolysaccharides, has been linked to type 2 diabetes mellitus; however, its role in GDM remains largely unexplored. This hospital-based cross-sectional analytical study evaluated fecal IAP levels and their association with GDM among 198 pregnant women recruited from three antenatal care clinics representing three tiers of ANC services. Participants were screened for GDM using a 75-g oral glucose tolerance test and classified as having GDM (n=55) or normal glucose tolerance (NGT; n=143) according to WHO 2013 criteria. Stool samples were collected, and fecal IAP levels were measured using an enzymatic colorimetric assay. Fecal IAP level was significantly lower in women with GDM than in those with NGT (median 23.59 vs 46.48 U/g stool; p<0.001). Lower IAP level remained independently associated with GDM after adjustment for body mass index and previous GDM (adjusted OR 0.98 per unit increase; 95% CI 0.97-0.99; p<0.001). A graded relationship was observed between declining IAP level and GDM. Receiver operating characteristic analysis demonstrated modest discrimination (AUC 0.676), while a threshold of approximately 65 U/g stool yielded high sensitivity (89.1%) but lower specificity. Reduced fecal IAP is independently associated with GDM, supporting a potential role of gut-derived metabolic dysregulation in gestational glucose intolerance. While not suitable as a standalone diagnostic tool, fecal IAP may serve as a complementary biomarker for risk stratification during pregnancy. Prospective studies are warranted to determine its predictive value and explore its potential as a therapeutic target.

Biological sequences are known to be not random. Thus, the comparison of in silico restriction fragment distributions of random and biological sequences may be an indicator of this non-randomness. Our analyses show that for most of the tested combinations of restriction enzyme and genome sequence the fragments per Megabase of the biological sequence deviate at least more then 10% from the corresponding random sequence. This deviation goes into both directions, i.e. clearly increased values are as common as clearly decreased values. Although there is no species- or restriction-enzyme-specific effect, a clear impact of the GC content both of the restriction site and of the genome sequence can be seen. In contrast to the random sequences, the genome sequences show distinct peaks in their fragment length distributions, hinting to repetitive elements such as transposons.

Nucleobindin 1 (NUCB1) is a multifunctional conserved protein located in Golgi luminal, nucleus, extracellular and cytosolic pools. NUCB1 is multidomain protein comprised of a signal peptide, a DNA-binding domain, a leucine zipper and Ca2+ -binding domain. The multiple domains and localization of NUCB1 potentiates its interactions with various partners, such as DNA, Gi3 protein, cyclooxygenase 2, LRP10 and RNA suggests its importance in the regulation of many cellular events. We revealed that NUCB1 contains three RNA-binding regions and able to interact with two RNA fragments. It was suggested possible variants of the participation of NUCB1 in the interaction of the two partially complementary RNAs. The RNA-binding properties of the NUCB1 were also confirmed in vivo experiments.

Celiac disease (CD) is strongly associated with specific HLA DQ heterodimers, formed by HLA DQA1 and HLA DQB1 proteins. In particular DQ2.5 (DQB1*02 associated to DQA1*05) and DQ8 (DQB1*03:02 with DQA1*03) are present in virtually all celiac patients. HLA DQB1*02 is considered the main single genetic susceptibility marker and has been reported in 90 to 95% of CD patients. However, the distribution of these alleles may vary across populations, potentially impacting the performance of genetic screening strategies. In this study, we evaluated the prevalence of HLA DQ2.5 and DQ8 genotypes in celiac patients (n = 41) and an unbiased general population cohort (n = 60) from San Luis, Argentina, using a PCR-based genotyping approach. In addition, we assessed the feasibility of a simplified saliva direct PCR protocol for large scale testing. Overall, 95.1% of CD patients carried DQ2.5 and/or DQ8. Notably, 41.5% of patients were DQ8(+)/DQ2.5(-), and 36.6% lacked the DQB1*02 allele, indicating that DQB1*02 based screening alone would have reduced sensitivity in this population. In the general population, 53.3% of individuals carried CD associated genotypes, with a markedly higher prevalence of DQ8 compared to European cohorts. Genotype distributions deviated from Hardy Weinberg equilibrium in CD patients but not in the general population. We show that DQB1*03:02 is a reliable proxy for DQ8, allowing simplification of genotyping strategies, whereas DQA1*05 typing remains essential to discriminate DQ2.5 from other lower risk DQB1*02 carrying heterodimers. We also describe a saliva direct PCR approach showing a performance comparable to purified DNA based assays. These findings highlight the importance of population specific genetic data for optimizing CD screening strategies and foster the development of simplified, cost effective genotyping approaches for large scale applications.

BackgroundThe increase in human lifespan without a proportional increase in healthspan imposes a substantial burden on individuals and society. Exceptionally long-lived individuals and members of long-lived families exhibit compression of multi-morbidity. Genetics, and in particular rare protein-altering variants, appear to play an important role in their longevity. MethodsIn this study, we employed a targeted pathway approach to provide functional evidence of the significance of rare variants in the insulin/insulin-like growth factor 1 signalling - mechanistic target of rapamycin (IIS/mTOR) signalling pathway identified in long-lived individuals. To this end, we used CRISPR/Cas9 to introduce these rare genetic variants into mouse embryonic stem cells (mESCs). We subsequently assessed several functional readouts that have previously been associated with lifespan regulation in model organisms and/or IIS/mTOR and mitogen-activated protein kinase/extracellular signal-regulated kinase (MAPK/ERK) signalling pathway activity. ResultsFunctional characterisation revealed that the variants exhibit both shared and distinct effects on the signalling pathways. Principal component analysis of omics-based datasets showed that the variants clustered into two groups, a distribution that corresponds with the grouping observed for a subset of functional readouts. All variant mESC lines exhibited a downregulation in IIS/mTOR and MAPK/ERK signalling pathway activity as well as an increase in Foxo3 expression and FOXO3 binding activity. We identified alterations in lipid and mitochondrial metabolism, including a reduction in mitochondrial DNA levels, which were mostly shared among all variants. All variant mESC lines exhibited a signature implying increased pluripotency. The effects on stress resistance and growth rate diverged between the two variant groups, with partially opposing effects. Group 1 demonstrated a reduced growth rate and increased resistance to a subset of stressors, while Group 2 demonstrated an increased growth rate and reduced resistance to a subset of stressors. ConclusionsHere, we provide evidence that rare genetic variants in the IIS/mTOR and MAPK/ERK signalling pathways identified in long-lived human individuals result in shared functional effects associated with longevity in model organisms. These insights can serve as a foundation to better understand the role of rare variants in the insulin signalling network in the regulation of human longevity. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=68 SRC="FIGDIR/small/728260v1_ufig1.gif" ALT="Figure 1"> View larger version (18K): org.highwire.dtl.DTLVardef@1bf5ebdorg.highwire.dtl.DTLVardef@e4e5dcorg.highwire.dtl.DTLVardef@1aee276org.highwire.dtl.DTLVardef@95f170_HPS_FORMAT_FIGEXP M_FIG C_FIG

Cetaceans are key sentinel species for environmental health monitoring. Although sampling from free-ranging animals is challenging, the analysis of cetacean blow offers a minimally invasive approach to assess their health status. Extracellular vesicles (EVs) are cell-derived nanostructures present in biological fluids and widely studied as disease biomarkers in humans. Despite the potential for similar uses, EVs have not been studied in cetacean blow to date . This proof-of-concept study aims to assess the feasibility of the isolation and characterization of EVs from blow samples collected from five bottlenose dolphins (Tursiops truncatus) kept under human care and from a free ranging specimen of long-finned pilot whale (Globicephala melas). EVs were purified from bottlenose dolphin blows by ultracentrifugation (UC) or size exclusion chromatography (SEC) and from the long-finned pilot whale by SEC. Particle concentration and size distribution were assessed by Nanoparticle Tracking Analysis (NTA), morphology by Air-atomic force microscopy (AFM) and protein expression by Western Blotting (WB). NTA revealed a higher mean particle concentration in bottlenose dolphin EVs isolated by UC compared to SEC, while EVs isolated from the long-finned pilot whale presented a lower particle concentration. AFM confirmed the presence of EV-like particles within the typical EV size range in bottlenose dolphins EVs obtained both by SEC or UC. All EV samples were positive for CD9 and integrin-{beta} and negative to Calnexin. SEC was more sensitive to detect OmpA, a membrane protein of Gram-negative bacteria, in EVs from both species. Our pilot study demonstrates that EVs are present in cetacean blow and can be isolated and characterized. Future investigations focused on characterizing and quantifying a wider array of EV associated molecules may further the application of blow EV analysis for cetacean health assessments.

This study analyzes 794,811 digitized medical examina- tions from Indian life-insurance applicants, a working-age, urban-skewed demographic often undersampled by national surveys. The cohort exhibits a pronounced South-Asian car- diometabolic risk profile: among valid adult records, 41.9% met the criteria for dyslipidemia (driven heavily by low HDL and elevated triglycerides), and 61.4% met AHA 2017 crite- ria for stage 1 hypertension. However, canonicalizing this dataset across 33,244 diagnostic centers revealed significant heterogeneity in laboratory reference ranges. At the clinical prediabetes threshold of 110 mg/dL for fasting blood sugar, the record-pair disagreement rate across laboratories was 49.7%, with similar variance across other common tests. This structural inconsistency materially affects patient classi- fication and the tracking of disease prevalence, underscoring a critical need for the national standardization of laboratory reporting in India

Citrus yellow vein clearing virus (CYVCV) is the causal agent of an emerging disease representing a potentially high-impact threat for citrus production. Despite remaining outside Europe for decades, CYVCV has now expanded towards two important European citrus producers, Italy and, more recently, Spain. The presence of this virus in the EPPO region represents a current threat with unpredictable and potentially devastating consequences for European citriculture. Therefore, urgent protective measures need to be taken to prevent CYVCV spread and minimize its impact. Diagnostics is a key measure in the management of viral diseases, highlighting the need for harmonized methods suitable for reliable routine detection of the currently known CYVCV diversity. In this study, an inclusive, efficient and highly sensitive real-time RT-qPCR for the detection of CYVCV in plant material and transmission vectors has been developed and validated according to EPPO standards. Moreover, the validated method has been successfully adapted to both PCR digital platforms, that allow high-sensitive absolute quantitative detection, essential in the diagnostics at low viral concentrations; and PCR portable tools, that can be applied in a real diagnostic context for on-site detection. This versatility combines standard validated performance, absolute sensitive quantitation and real on-site detection. The study has also addressed sampling strategies to support reliable molecular diagnostic performance. Our results represent an improvement in the detection of CYVCV to be applied in epidemiological studies and different real diagnostic contexts for the containment of this important citrus pathogen.

Background: Acute pancreatitis (AP) is an established risk factor for diabetes, with approximately 20% of children developing either prediabetes or diabetes within one year of their first episode. Little is known about the diabetes pathophysiology or which individuals are at highest risk. We aimed to evaluate whether genetic risk scores (GRS) for type 1 (T1D) and polygenic risk scores (PRS) type 2 diabetes (T2D) are associated with progression to dysglycemia following AP. Methods: Clinical data were available for 123 children (mean age (IQR), 12 (8-15) years; mean body mass index (BMI), 21.8) with AP who were followed for >1 year. Array genotyping coupled with imputation using the TOPMed reference panel was performed. Genetic ancestry was predicted using a random forest classifier. GRS for T1D and T2D were calculated using either an ancestry-appropriate (T1D-GRS) or a multi-ancestry (T2D-PRS) weighted framework. To evaluate risk compared to the population we used predefined GRS thresholds from UK Biobank. Results: Among the 123 subjects, 24 developed dysglycemia (5 with diabetes and 19 with prediabetes). The majority (75.6%, n=93) of children were of European ancestry. Comparison of the T1D-GRS burden with the UK BioBank showed numerically higher proportions for any given threshold. At the top 5% threshold, 9.7% of our cohort were classified as high-risk compared to 5% in UK Biobank (p<0.05). The elevated T1D-GRS could be primarily attributed to non-HLA variants and was more enriched in those testing positive for [&ge;]1 islet-autoantibody. The T2D-PRS was also elevated in the dysglycemic group but only reached statistical significance in those who were obese. Conclusion: These findings highlight the potential role of both T1D-GRS and T2D-PRS in investigating diabetes susceptibility following AP.

Male infertility has emerged as a significant concern in modern society, with genetic defects as one of the major underlying cause behind it. This impairment negatively impacts sperm motility and morphology, leading to conditions such as Asthenozoospermia (reduced sperm motility), Teratozoospermia (abnormal sperm morphology) and sometimes Asthenoteratozoospermia (both motility and morphology defects). Assisted reproductive technologies (ART), such as in-vitro fertilization (IVF), offer a potential solution for such cases but with a low success rate. Classical semen analysis provides only a phenotypic snapshot without revealing the fertilizing potential of the sperms. Hence, in order to screen the functional sperm population as well as to get a deeper insight into the reasons underlying the aberrant sperm population, it is important to study their genetic profile. In this work, we have performed a meta analysis of the transcriptomic data of infertile sperms from Asthenozoospermia and Teratozoospermia patients with that from fertile sperms of normal individuals. Thereafter we have screened a signature gene set which has been used to develop a prediction model named Explainable Infertility Test (E-InfertilityTest) to classify between fertile versus infertile sperm at the preliminary level. For each prediction, it will also provide the set of genes which are playing a dominant role towards such prediction. Thus, it will provide patient specific dominant gene expression profile responsible for the aberration. This work warrants validation experiments in future to substantiate the models performance in a clinical setting. User can access the tool named E-InfertilityTest as a standalone version on GitHub. Github Linkhttps://github.com/zglabDIB/einfertility.git

Introduction: Adenoviral vectors such as chimpanzee ChAdOx1 were selected for COVID-19 vaccines due to their low seroprevalence in humans, minimizing the impact of neutralising anti-vector immunity that could attenuate vaccine responses. However, the influence of pre-existing adenoviral immunity on vaccine response remains incompletely understood. We have previously shown that SARS-CoV-2 spike-specific T cells were enhanced in ChAdOx1 nCoV-19 vaccinated immunodeficient patients compared to mRNA-based BNT162b2. Here, we assess immune cross-reactivity between ChAdOx1 and human adenovirus 5 (HuAd5), and test the hypothesis that in antibody-deficient individuals, cross-neutralisation may be impaired, allowing bystander enhancement of SARS-CoV-2 spike-specific T cell responses following ChAdOx1 nCoV-19 vaccination. Methods: We studied healthy healthcare workers (HCWs) and immunodeficient patients (IDPs) who received homologous ChAdOx1 nCoV-19 or BNT162b2 vaccines. HCWs samples were collected pre-vaccination and 4-6 weeks after the second dose, while IDP samples were obtained 4-6 weeks after the second dose. Serum anti-HuAd5 hexon IgG was quantified using a Luminex multiplex assay, and neutralizing antibodies were assessed using a replication-deficient HuAd5-GFP virus neutralization assay with flow cytometry readout. Ex vivo ELISpot and flow cytometry assays were used to measure T cell responses to HuAd5 hexon. These data were compared with previously published ChAdOx1 nCoV-19 vaccine responses in the same cohorts. Results: HuAd5 hexon-binding IgG titres were significantly higher in ChAdOx1 nCoV-19 compared to BNT162b2 vaccine recipients in both HCWs (p = 0.0043) and IDPs (p = 0.0328). Within ChAdOx1 nCoV-19 vaccine group, titres were lower in IDPs than HCWs (p = 0.0015) but not within the BNT162b2 group (p = 0.1261). HuAd5 neutralisation titres did not differ between cohorts or vaccine groups. In ChAdOx1 nCoV-19 vaccinated IDPs and HCWs, there was a significant negative correlation between HuAd5 hexon IgG titres and SARS-CoV-2 spike-specific T cell responses. Similarly, HuAd5 neutralisation titres showed an inverse correlation with spike-specific T cell responses in ChAdOx1 nCoV-19 vaccinated IDPs and HCWs. ChAdOx1 nCoV-19 vaccination induced significantly higher frequencies of HuAd5 hexon-reactive T cells compared with BNT162b2 vaccination in IDPs (p < 0.0001), consistent with cross-reactive adenoviral T cell responses. In IDPs, HuAd5 hexon-specific T cell frequencies positively correlated with SARS-CoV-2 spike-specific T cell responses following ChAdOx1 nCoV-19 vaccination but not following BNT162b2 vaccination. Functional profiling in ChAdOx1 nCoV-19 vaccinated IDPs demonstrated expansion of HuAd5 hexon-specific CD4IFN-{gamma}TNF T cells in high SARS-CoV-2 spike responders (p = 0.0002) compared to low responders, and the frequency of these cells strongly correlated with spike-specific T cell response. Discussion: ChAdOx1 nCoV-19 has been associated with stronger T cell responses than BNT162b2 in certain populations, including immunodeficient and elderly individuals. While this has been attributed to antigen persistence and innate adjuvant effects, our findings support a mechanism whereby heterologous pre-existing adenovirus immunity modulates vaccine-induced responses. Specifically, cross-reactive HuAd5-specific T cells may enhance spike-specific T cell responses via bystander enhancement, while cross-reactive binding antibodies may exert opposing effects. An implication of this study is that vaccine protocols could incorporate therapies that suppress vector-specific or cross-reactive antibodies while preserving T cell responses especially in cases where T cell-specific responses are most desirable. Also, safe vector-based vaccines can be developed for patient groups with predominant antibody deficiency. Targeted vaccination strategy could be implemented for clinical cohorts based on immune competence.

Vocal communication depends not only on the acoustic features and rate of vocalizations, but also on their timing relative to the vocalizations of others. In this study, we examined whether ultrasonic vocalizations (USVs) produced by adult female Mongolian gerbils during freely moving social interactions are temporally related to the vocal timing of a partner. Using USVCAM, we assigned each USV to an individual caller and evaluated whether brief USVs exhibit turn-taking-like temporal organization by analyzing response latency after partner calls, call overlap rate, and circular-shift surrogate data. The offset-to-onset gaps of alternating vocalizations were concentrated within a short time range, with a median of 130 ms. In addition, the call overlap rate was significantly lower in the observed data than in the circularly shifted surrogate data, indicating that USVs occurred with short latencies after partner calls while being less likely to overlap with ongoing partner calls. Furthermore, USV counts were reduced in unoperated Ctrl animals that interacted with devocalized Mute animals. These findings suggest that gerbil USVs may be coordinated in relation to partner vocal timing and vocal input. This study provides a basis for understanding rodent USVs not merely as individual vocal outputs, but as temporally organized dyadic social signals.

The transition to flowering in Arabidopsis thaliana is a complex process governed by many biological and environmental stimuli. Although many of the genes which regulate this process have been identified over the past 30 years, it remains unclear how these networks are integrated. In this study, we used the transcriptional responses of Col-0, Ler-1, and three mutant lines, to build a genome wide regulatory network of Arabidopsis thaliana during the flowering transition. The expression profiles of 22,810 genes across five genotypes were collected from the GEO database Series GSE57 from which we assigned flowering-time genes to different interacting modules by an adapted form of Hierarchical Complete Linkage Clustering (HCLC) after reconstruction of regulatory networks according to the Position Weight Matrix (PWM)-based method. Within these modules, we identified 77 core genes and 31 controller or driver genes. We identify two genes, LHY and, less expectedly, the transcription factor TCP16, to be topographically positioned at the regulatory hubs a nine-gene transcriptional control unit, implying they have the capacity to integrate information from across the flowering time pathways which interpret different environmental or endogenous cues during the vegetative-reproductive transition. Interrogating their behaviour across transcriptional datasets, we show that both LHY and TCP16 show transcriptional oscillations during the flowering transition, with a wavelength that varies depending on environmental conditions. We suggest that the transcriptional responses of LHY and TCP16 allow them to regulate the flow of information through the genetic networks which integrates different floral transition cues, and that genetic modelling approaches can provide new insights into the regulation of well-studied biological processes such as the flowering transition. Author summaryHow plants decide when to flower is a critical stage for completing their life cycles. It is also of key agricultural importance, as crops need to flower at the right time of year to allow efficient pollination and harvesting. Many genes are known to affect flowering time control in plants. Here, we use computational approaches to estimate how different genes interact in flowering time control in Arabidopsis, a small plant in the mustard family which is widely used for molecular studies. We use large-scale studies of how gene expression changes in different plant lines which have disrupted or adjusted flowering time to group the many genes involved in flowering into different interacting pathway, which we visualise as sets of coloured nodes controlling one another in a network. We show that two genes may have new rols in integrating information from different pathways, and discuss how their behaviour might help them to function as intregrators of biological information - including the daily oscaillations in their expression.

We sequenced the nearly complete mitochondrial genome of the hammerhead flatworm Bipalium nobile Kawakatsu and Makino, 1982 using short-read sequencing technology, yielding a 16,018 bp genome comprising 12 protein-coding genes, 22 tRNA genes, and 2 rRNA genes. The composition and order of genes were consistent with those observed in the closely related species Bipalium kewense and Diversibipalium multilineatum, except for the position of tRNA-Glu. Phylogenetic analysis based on all mitochondrial proteins from species within the family Geoplanidae supports the monophyly of a clade comprising B. nobile, B. kewense, and D. multilineatum. The mitochondrial genome sequence obtained in this study provides a valuable resource for investigating the genetic diversity and population structure of B. nobile, a soil-dwelling predator with the potential for global spread as an invasive organism.

Background: Colon capsule endoscopy (CCE) has been proposed as a non-invasive alternative to colonoscopy for colorectal cancer (CRC) screening, offering greater patient comfort and potentially reducing healthcare burden. However, its cost-effectiveness in population-based screening remains uncertain. Methods: This study used a state-transition (Markov) model to simulate lifetime outcomes of CRC screening in Denmark, Scotland, and Spain, comparing the standard pathway based on fecal immunochemical testing (FIT) followed by colonoscopy with an alternative pathway replacing colonoscopy with CCE after a positive FIT result. The model incorporated costs (2024 euros), quality-adjusted life-years (QALYs), and CRC cases avoided, applying a yearly discount rate of 3%. Deterministic sensitivity analyses explored uncertainty in capsule cost, adherence, and reinvestigation rates for non-advanced polyps. Results: Across all settings, CCE resulted in higher costs but slightly increased effectiveness and utility (mean QALYs 28.7 vs. 28.8; CRC detected 0.032-0.034 vs. 0.035-0.037 per person). Incremental cost-effectiveness ratios (ICER) ranged from 43,538EUR in Spain to 136,930EUR in Denmark per additional CRC detected. Capsule cost was the main driver of ICER variation, whereas adherence rates had minimal effect on cost-effectiveness. Changes in the prevalence of non-advanced polyps had a modest impact, except when capsule prices were high. Conclusions: Overall, replacing colonoscopy with CCE slightly increases detection and health gains at the expense of higher costs. Cost-effectiveness largely depends on capsule price and adherence. Artificial intelligence-assisted CCE interpretation may further improve diagnostic and economic performance, potentially supporting adoption in large-scale CRC screening programs.