The multivariate Bernoulli detector: change point estimation in discrete survival analysis.

Time-to-event data are often recorded on a discrete scale with multiple, competing risks as potential causes for the event. In this context, application of continuous survival analysis methods with a single risk suffers from biased estimation. Therefore, we propose the multivariate Bernoulli detector for competing risks with discrete times involving a multivariate change point model on the cause-specific baseline hazards. Through the prior on the number of change points and their location, we impose dependence between change points across risks, as well as allowing for data-driven learning of their number. Then, conditionally on these change points, a multivariate Bernoulli prior is used to infer which risks are involved. Focus of posterior inference is cause-specific hazard rates and dependence across risks. Such dependence is often present due to subject-specific changes across time that affect all risks. Full posterior inference is performed through a tailored local-global Markov chain Monte Carlo (MCMC) algorithm, which exploits a data augmentation trick and MCMC updates from nonconjugate Bayesian nonparametric methods. We illustrate our model in simulations and on ICU data, comparing its performance with existing approaches.

A holistic lifestyle mobile health intervention for the prevention of type 2 diabetes and common mental disorders in Asian women with a history of gestational diabetes: a randomised control trial with 3-year follow-up protocol.

BACKGROUND: Women with a history of gestational diabetes mellitus (GDM) are 12-fold more likely to develop type 2 diabetes (T2D) 4-6 years after delivery than women without GDM. Similarly, GDM is associated with the development of common mental disorders (CMDs) (e.g. anxiety and depression). Evidence shows that holistic lifestyle interventions focusing on physical activity (PA), dietary intake, sleep, and mental well-being strategies can prevent T2D and CMDs. This study aims to assess the effectiveness of a holistic lifestyle mobile health intervention (mHealth) with post-GDM women in preventing T2D and CMDs in a community setting in Singapore. METHODS: The study consists of a 1-year randomised controlled trial (RCT) with a 3-year follow-up period. Post-GDM women with no current diabetes diagnosis and not planning to become pregnant will be eligible for the study. In addition, participants will complete mental well-being questionnaires (e.g. depression, anxiety, sleep) and their child's socio-emotional and cognitive development. The participants will be randomised to either Group 1 (Intervention) or Group 2 (comparison). The intervention group will receive the "LVL UP App", a smartphone-based, conversational agent-delivered holistic lifestyle intervention focused on three pillars: Move More (PA), Eat Well (Diet), and Stress Less (mental wellbeing). The intervention consists of health literacy and psychoeducational coaching sessions, daily "Life Hacks" (healthy activity suggestions), slow-paced breathing exercises, a step tracker (including brisk steps), a low-burden food diary, and a journaling tool. Women from both groups will be provided with an Oura ring for tracking physical activity, sleep, and heart rate variability (a proxy for stress), and the "HAPPY App", a mHealth app which provides health promotion information about PA, diet, sleep, and mental wellbeing, as well as display body mass index, blood pressure, and results from the oral glucose tolerance tests. Short-term aggregate effects will be assessed at 26/27 weeks (midpoint) and a 1-year visit, followed by a 2, 3, and 4-year follow-up period. DISCUSSION: High rates of progression of T2D and CMDs in women with post-GDM suggest an urgent need to promote a healthy lifestyle, including diet, PA, sleep, and mental well-being. Preventive interventions through a holistic, healthy lifestyle may be the solution, considering the inextricable relationship between physical and psychological health. We expect that holistic lifestyle mHealth may effectively support behavioural changes among women with a history of GDM to prevent T2D and CMDs. TRIAL STATUS: The protocol study was approved by the National Healthcare Group in Singapore, Domain Specific Review Board (DSRB) [2023/00178]; June 2023. Recruitment began on October 18, 2023. TRIAL REGISTRATION: ClinicalTrials.gov NCT05949957. The first submission date is June 08, 2023.

Variability and Number of Circulating Complementary Sex Determiner (Csd) Alleles in a Breeding Population of Italian Honeybees under Controlled Mating.

In Apis mellifera, csd is the primary gene involved in sex determination: haploid hemizygous eggs develop as drones, while females develop from eggs heterozygous for the csd gene. If diploid eggs are homozygous for the csd gene, diploid drones will develop, but will be eaten by worker bees before they are born. Therefore, high csd allelic diversity is a priority for colony survival and breeding. This study aims to investigate the variability of the hypervariable region (HVR) of the csd gene in bees sampled in an apiary under a selection scheme. To this end, an existing dataset of 100 whole-genome sequences was analyzed with a validated pipeline based on de novo assembly of sequences within the HVR region. In total, 102 allelic sequences were reconstructed and translated into amino acid sequences. Among these, 47 different alleles were identified, 44 of which had previously been observed, while 3 are novel alleles. The results show a high variability in the csd region in this breeding population of honeybees.

Genetic Alterations in a Large Population of Italian Patients Affected by Neurodevelopmental Disorders.

Neurodevelopmental disorders are a group of complex multifactorial disorders characterized by cognitive impairment, communication deficits, abnormal behaviour, and/or motor skills resulting from abnormal neural development. Copy number variants (CNVs) are genetic alterations often associated with neurodevelopmental disorders. We evaluated the diagnostic efficacy of the array-comparative genomic hybridization (a-CGH) method and its relevance as a routine diagnostic test in patients with neurodevelopmental disorders for the identification of the molecular alterations underlying or contributing to the clinical manifestations. In the present study, we analysed 1800 subjects with neurodevelopmental disorders using a CGH microarray. We identified 208 (7%) pathogenetic CNVs, 2202 (78%) variants of uncertain significance (VOUS), and 504 (18%) benign CNVs in the 1800 patients analysed. Some alterations contain genes potentially related to neurodevelopmental disorders including CHRNA7, ANKS1B, ANKRD11, RBFOX1, ASTN2, GABRG3, SHANK2, KIF1A SETBP1, SNTG2, CTNNA2, TOP3B, CNTN4, CNTN5, and CNTN6. The identification of interesting significant genes related to neurological disorders with a-CGH is therefore an essential step in the diagnostic procedure, allowing a better understanding of both the pathophysiology of these disorders and the mechanisms underlying their clinical manifestations.

Is there a role for platelet rich plasma injection in vulvar lichen sclerosus? A self-controlled pilot study.

BACKGROUND: Owing to the evidence that as many as 30-40% of patients with vulvar lichen sclerosus (VLS) fail to report a remission of symptoms with first-line corticosteroid treatment (TCS), especially as what regards dyspareunia, we aimed to analyze patients' satisfaction following vulvar injection of autologous platelet-rich plasma (PRP). This is intended as an adjunctive treatment, to be used following TCS, and appears to promote tissue repair. It may also possibly have immunomodulatory proprieties. MATERIALS AND METHODS: Patients with VLS were considered eligible for this pilot study if, despite having been treated with a 3-month TCS regimen, they reported a persistence of symptoms. PRP was produced in a referral center using a manual method and a standardized protocol. Each patient received three treatments 4 to 6 weeks apart. RESULTS: A total of 50 patients with a median age of 53 years [IQR 38-59 years] were included in the study. 6 months after the last injection of PRP all patients were either satisfied or very satisfied with the treatment (100%; 95% CI 93-100%). Median NRS scores for itching, burning, dyspareunia and dysuria were significantly reduced (p < 0.05) and FSFI, HADS and SF-12 questionnaires revealed a significant improvement in sexual function, psychological wellbeing and quality of life (p < 0.05). The number of patients reporting the need for maintenance TCS treatment was reduced by 42% (p < 0.001) and an improvement in vulvar elasticity and color was reported in all patients. CONCLUSION: Following standard medical therapy, PRP may be effective not only in improving symptoms, but also in restoring function.

Maternal asthma symptoms during pregnancy on child behaviour and executive function: A Bayesian phenomics approach.

OBJECTIVE: Maternal history of inflammatory conditions has been linked to offspring developmental and behavioural outcomes. This phenomenon may be explained by the maternal immune activation (MIA) hypothesis, which posits that dysregulation of the gestational immune environment affects foetal neurodevelopment. The timing of inflammation is critical. We aimed to understand maternal asthma symptoms during pregnancy, in contrast with paternal asthma symptoms during the same period, on child behaviour problems and executive function in a population-based cohort. METHODS: Data were obtained from 844 families from the Growing Up in Singapore Towards healthy Outcomes (GUSTO) birth cohort. Parent asthma symptoms during the prenatal period were reported. Asthma symptoms in children were reported longitudinally from two to five years old, while behavioural problems and executive functioning were obtained at seven years old. Parent and child measures were compared between mothers with and without prenatal asthma symptoms. Generalized linear and Bayesian phenomics models were used to determine the relation between parent or child asthma symptoms and child outcomes. RESULTS: Children of mothers with prenatal asthma symptoms had greater behavioural and executive problems than controls (Cohen's d: 0.43-0.75; all p < 0.05). This association remained after adjustments for emerging asthma symptoms during the preschool years and fathers' asthma symptoms during the prenatal period. After adjusting for dependence between child outcomes, the Bayesian phenomics model showed that maternal prenatal asthma symptoms were associated with child internalising symptoms and higher-order executive function, while child asthma symptoms were associated with executive function skills. Paternal asthma symptoms during the prenatal period were not associated with child outcomes. CONCLUSIONS: Associations between child outcomes and maternal but not paternal asthma symptoms during the prenatal period suggests a role for MIA. These findings need to be validated in larger samples, and further research may identify behavioural and cognitive profiles of children with exposure to MIA.

Joint modelling of mental health markers through pregnancy: a Bayesian semi-parametric approach.

Maternal depression and anxiety through pregnancy have lasting societal impacts. It is thus crucial to understand the trajectories of its progression from preconception to postnatal period, and the risk factors associated with it. Within the Bayesian framework, we propose to jointly model seven outcomes, of which two are physiological and five non-physiological indicators of maternal depression and anxiety over time. We model the former two by a Gaussian process and the latter by an autoregressive model, while imposing a multidimensional Dirichlet process prior on the subject-specific random effects to account for subject heterogeneity and induce clustering. The model allows for the inclusion of covariates through a regression term. Our findings reveal four distinct clusters of trajectories of the seven health outcomes, characterising women's mental health progression from before to after pregnancy. Importantly, our results caution against the loose use of hair corticosteroids as a biomarker, or even a causal factor, for pregnancy mental health progression. Additionally, the regression analysis reveals a range of preconception determinants and risk factors for depressive and anxiety symptoms during pregnancy.

Joint modeling of association networks and longitudinal biomarkers: An application to childhood obesity.

The prevalence of chronic non-communicable diseases such as obesity has noticeably increased in the last decade. The study of these diseases in early life is of paramount importance in determining their course in adult life and in supporting clinical interventions. Recently, attention has been drawn to approaches that study the alteration of metabolic pathways in obese children. In this work, we propose a novel joint modeling approach for the analysis of growth biomarkers and metabolite associations, to unveil metabolic pathways related to childhood obesity. Within a Bayesian framework, we flexibly model the temporal evolution of growth trajectories and metabolic associations through the specification of a joint nonparametric random effect distribution, with the main goal of clustering subjects, thus identifying risk sub-groups. Growth profiles as well as patterns of metabolic associations determine the clustering structure. Inclusion of risk factors is straightforward through the specification of a regression term. We demonstrate the proposed approach on data from the Growing Up in Singapore Towards healthy Outcomes cohort study, based in Singapore. Posterior inference is obtained via a tailored MCMC algorithm, involving a nonparametric prior with mixed support. Our analysis has identified potential key pathways in obese children that allow for the exploration of possible molecular mechanisms associated with childhood obesity.

Bayesian dynamic network modelling: an application to metabolic associations in cardiovascular diseases.

We propose a novel approach to the estimation of multiple Graphical Models to analyse temporal patterns of association among a set of metabolites over different groups of patients. Our motivating application is the Southall And Brent REvisited (SABRE) study, a tri-ethnic cohort study conducted in the UK. We are interested in identifying potential ethnic differences in metabolite levels and associations as well as their evolution over time, with the aim of gaining a better understanding of different risk of cardio-metabolic disorders across ethnicities. Within a Bayesian framework, we employ a nodewise regression approach to infer the structure of the graphs, borrowing information across time as well as across ethnicities. The response variables of interest are metabolite levels measured at two time points and for two ethnic groups, Europeans and South-Asians. We use nodewise regression to estimate the high-dimensional precision matrices of the metabolites, imposing sparsity on the regression coefficients through the dynamic horseshoe prior, thus favouring sparser graphs. We provide the code to fit the proposed model using the software Stan, which performs posterior inference using Hamiltonian Monte Carlo sampling, as well as a detailed description of a block Gibbs sampling scheme.

Positive effects of physical activity in autism spectrum disorder: how influences behavior, metabolic disorder and gut microbiota.

Autism spectrum disorder is a neurodevelopmental disorder characterized by social interactions and communication skills impairments that include intellectual disabilities, communication delays and self-injurious behaviors; often are present systemic comorbidities such as gastrointestinal disorders, obesity and cardiovascular disease. Moreover, in recent years has emerged a link between alterations in the intestinal microbiota and neurobehavioral symptoms in children with autism spectrum disorder. Recently, physical activity and exercise interventions are known to be beneficial for improving communication and social interaction and the composition of microbiota. In our review we intend to highlight how different types of sports can help to improve communication and social behaviors in children with autism and also show positive effects on gut microbiota composition.

Perinatal Trajectories of Maternal Depressive Symptoms in Prospective, Community-Based Cohorts Across 3 Continents.

Importance: Depressive symptoms during pregnancy influence the development and health of the offspring, underscoring the need for timely intervention. However, the course of depressive symptoms across the perinatal period remains unclear, thus complicating screening and referral guidelines. Objective: To examine the course and stability of depressive symptoms across the perinatal period in multiple, ethnically diverse independent observational cohorts. Design, Setting, and Participants: This cohort study included self-reported depressive symptoms at multiple time points from 7 prospective cohorts spanning 3 continents (United Kingdom: Avon Longitudinal Study of Parents and Children from 1991 to 1995; Canada: Maternal Adversity, Vulnerability and Neurodevelopment from 2003 to 2007; Montreal Antenatal Well-being Study from 2019 to 2022; Alberta Pregnancy Outcomes and Nutrition from 2009 to 2014; and Singapore: Growing Up in Singapore Toward Healthy Outcomes from 2009 to 2013; Singapore Preconception Study of Long-Term Maternal and Child Outcomes from 2015 to 2019; and Mapping Antenatal Maternal Stress from 2019 to 2022). Participants were recruited either during preconception or pregnancy and observed into the postnatal period. All data from each cohort were analyzed from July 2022 to April 2023. Main Outcomes and Measures: Self-reported depressive symptoms from pregnancy to 2 years following childbirth using either the Edinburgh Postnatal Depression Scale or the Center for Epidemiological Studies Depression were analyzed independently within each cohort using item response theory (IRT) techniques. K-means clustering was used to identify groups of participants with similar trajectories. Results: A total of 11 563 pregnant women (mean [SD] age, 29 [5] years; 569 [4.9%] East Asian women; 304 [2.6%] Southeast Asian women; 10 133 [87.6%] White women) self-reported depressive symptoms from pregnancy to 2 years following childbirth. Analytic methods from Item Response Theory identified 3 groups of mothers based on depressive symptoms: low, mild, and high levels in each of the 7 cohorts. Mothers within and across all cohorts had stable trajectories of maternal depressive symptoms from pregnancy onwards. Mothers with clinical levels of depressive symptoms likewise showed stable trajectories from pregnancy into the postnatal period. Conclusions and Relevance: In this study, trajectories of depressive symptoms remained stable from pregnancy across the perinatal period, a finding that conflicts with a continuing emphasis on postpartum or postnatal onset of depression that persists in some health policy guidelines. Interventions and public health initiatives should focus on reducing depressive symptoms during pregnancy in addition to following birth.

Serum anti-Spike immunoglobulin G levels in random blood donors in Italy: High-titre convalescent plasma is easier than ever to procure.

BACKGROUND AND OBJECTIVES: COVID-19 convalescent plasma (CCP) has retained potency and clinical efficacy against SARS-CoV-2 and is currently of utmost value for seronegative immunocompromised patients. Since most of the effect is due to the vaccine boost of infection-elicited antibodies, there is a theoretical concern that the frequency of suitable donors is declining. MATERIALS AND METHODS: In this single-institution serosurvey, we screened 599 consecutive donors attending our area in two different seasons (300 in November 2022 and 299 in February 2023) using the Abbott Alinity® anti-Spike immunoglobulin G assay. RESULTS: More than 80% of random donors qualify according to the FDA criteria for high-titre CCP (>4350 AU/mL), with a stable trend. CONCLUSION: Despite reduced anti-Spike vaccine boost deployment in the general population, we have shown here that high-titre CCP units are easier than ever to procure. This finding also has implications for the derivation of standard immunoglobulins, which are finally approaching the potency of hyperimmune serum and could soon represent an alternative to CCP.

Bayesian modelling of response to therapy and drug-sensitivity in acute lymphoblastic leukemia.

Acute lymphoblastic leukemia (ALL) is a heterogeneous haematologic malignancy involving the abnormal proliferation of immature lymphocytes and accounts for most paediatric cancer cases. The management of ALL in children has seen great improvement in the last decades thanks to greater understanding of the disease leading to improved treatment strategies evidenced through clinical trials. Common therapy regimens involve a first course of chemotherapy (induction phase), followed by treatment with a combination of anti-leukemia drugs. A measure of the efficacy early in the course of therapy is the presence of minimal residual disease (MRD). MRD quantifies residual tumor cells and indicates the effiectiveness of the treatment over the course of therapy. MRD positivity is defined for values of MRD greater than 0.01%, yielding left-censored MRD observations. We propose a Bayesian model to study the relationship between patient features (leukemia subtype, baseline characteristics, and drug sensitivity profile) and MRD observed at two time points during the induction phase. Specifically, we model the observed MRD values via an auto-regressive model, accounting for left-censoring of the data and for the fact that some patients are already in remission after the first stage of induction therapy. Patient characteristics are included in the model via linear regression terms. In particular, patient-specific drug sensitivity based on ex vivo assays of patient samples is exploited to identify groups of subjects with similar profiles. We include this information as a covariate in the model for MRD. We adopt horseshoe priors for the regression coefficients to perform variable selection to identify important covariates. We fit the proposed approach to data from three prospective paediatric ALL clinical trials carried out at the St. Jude Children's Research Hospital. Our results highlight that drug sensitivity profiles and leukemic subtypes play an important role in the response to induction therapy as measured by serial MRD measures.

Bayesian clustering of multiple zero-inflated outcomes.

Several applications involving counts present a large proportion of zeros (excess-of-zeros data). A popular model for such data is the hurdle model, which explicitly models the probability of a zero count, while assuming a sampling distribution on the positive integers. We consider data from multiple count processes. In this context, it is of interest to study the patterns of counts and cluster the subjects accordingly. We introduce a novel Bayesian approach to cluster multiple, possibly related, zero-inflated processes. We propose a joint model for zero-inflated counts, specifying a hurdle model for each process with a shifted Negative Binomial sampling distribution. Conditionally on the model parameters, the different processes are assumed independent, leading to a substantial reduction in the number of parameters as compared with traditional multivariate approaches. The subject-specific probabilities of zero-inflation and the parameters of the sampling distribution are flexibly modelled via an enriched finite mixture with random number of components. This induces a two-level clustering of the subjects based on the zero/non-zero patterns (outer clustering) and on the sampling distribution (inner clustering). Posterior inference is performed through tailored Markov chain Monte Carlo schemes. We demonstrate the proposed approach on an application involving the use of the messaging service WhatsApp. This article is part of the theme issue 'Bayesian inference: challenges, perspectives, and prospects'.

High-grade vaginal intraepithelial neoplasia and recurrence risk: analysis of an Italian regional referral center series.

PURPOSE: The main aim of this study was to investigate the long-term risk of disease recurrence in women treated for high-grade vaginal intraepithelial neoplasia (HG-VaIN). METHODS: We conducted a retrospective analysis on a cohort of 82 women diagnosed with HG-VaIN between 2010 and 2021 at the "Regional Referral Center for Prevention, Diagnosis and Treatment of HPV-related Genital Disorders", Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy. All women underwent either ablative treatment (CO2 laser ablation or electrocoagulation) or cold-knife excision. RESULTS: In our series, the recurrence rate following treatment was 17%. The 5-year cumulative probability of recurrence was 30.4% and the median time to recurrence was 15.5 months. None of the patients progressed to invasive vaginal cancer during follow-up. A concomitant cervical or vulvar intraepithelial lesion was significatively associated with an increased risk of recurrence (p = 0.006). CONCLUSIONS: The results of our study suggest that women with HG-VaIN are at high risk of developing disease recurrence after treatment, especially patients with a concomitant cervical or vulvar intraepithelial lesion. In these women strict monitoring is mandatory to obtain an early identification of recurrence.

Genome-wide association study for antibody response to Mycobacterium avium ssp. paratubeculosis in goats.

Mycobacterium avium ssp. paratuberculosis (MAP), causes Johne's disease (JD), or paratuberculosis, a chronic enteritis of ruminants, which in goats is characterized by ileal lesions. The work described here is a case-control association study using the Illumina Caprine SNP50 BeadChip to unravel the genes involved in susceptibility of goats to JD. Goats in herds with a high occurrence of Johne's disease were classified as healthy or infected based on the level of serum antibodies against MAP, and 331 animals were selected for the association study. Goats belonged to the Jonica (157) and Siriana breeds (174). Whole-genome association analysis identified one region suggestive of significance associated with an antibody response to MAP on chromosome 7 (p-value = 1.23 × 10-5 ). These results provide evidence for genetic loci involved in the antibody response to MAP in goats.

NDUFS3 knockout cancer cells and molecular docking reveal specificity and mode of action of anti-cancer respiratory complex I inhibitors.

Inhibition of respiratory complex I (CI) is becoming a promising anti-cancer strategy, encouraging the design and the use of inhibitors, whose mechanism of action, efficacy and specificity remain elusive. As CI is a central player of cellular bioenergetics, a finely tuned dosing of targeting drugs is required to avoid side effects. We compared the specificity and mode of action of CI inhibitors metformin, BAY 87-2243 and EVP 4593 using cancer cell models devoid of CI. Here we show that both BAY 87-2243 and EVP 4593 were selective, while the antiproliferative effects of metformin were considerably independent from CI inhibition. Molecular docking predictions indicated that the high efficiency of BAY 87-2243 and EVP 4593 may derive from the tight network of bonds in the quinone binding pocket, although in different sites. Most of the amino acids involved in such interactions are conserved across species and only rarely found mutated in human. Our data make a case for caution when referring to metformin as a CI-targeting compound, and highlight the need for dosage optimization and careful evaluation of molecular interactions between inhibitors and the holoenzyme.

Immunohistochemical Distribution of Serotonin Transporter (SERT) in the Optic Lobe of the Honeybee, Apis mellifera.

Visual information is processed in the optic lobes, which consist of three retinotopic neuropils. These are the lamina, the medulla and the lobula. Biogenic amines play a crucial role in the control of insect responsiveness, and serotonin is clearly related to aggressiveness in invertebrates. Previous studies suggest that serotonin modulates aggression-related behaviours, possibly via alterations in optic lobe activity. The aim of this investigation was to immunohistochemically localize the distribution of serotonin transporter (SERT) in the optic lobe of moderate, docile and aggressive worker honeybees. SERT-immunoreactive fibres showed a wide distribution in the lamina, medulla and lobula; interestingly, the highest percentage of SERT immunoreactivity was observed across all the visual neuropils of the docile group. Although future research is needed to determine the relationship between the distribution of serotonin fibres in the honeybee brain and aggressive behaviours, our immunohistochemical study provides an anatomical basis supporting the role of serotonin in aggressive behaviour in the honeybee.

Conservative Treatment for Cervical Adenocarcinoma In Situ: Long-Term Results.

OBJECTIVE: This study aimed to evaluate the effectiveness of conservative treatment for cervical adenocarcinoma in situ (AIS). MATERIALS AND METHODS: This is a retrospective study on women with histologically confirmed AIS on cervical loop electrosurgical excision procedure specimen, treated conservatively between 2008 and 2020 in our center, Ospedale Maggiore Policlinico, Milan. The main outcome investigated was the risk of recurrence defined as a subsequent finding of recurrent AIS or invasive adenocarcinoma in a long-term follow-up. The disease-free survival curve was computed using the Kaplan-Meyer method. All patients underwent colposcopy with endocervical curettage and cytology every 6 months for the first 2 years after initial surgery and then annual cytology. RESULTS: Thirty women, aged 26 to 51 years, with histologically proven AIS on excisional specimen with negative margins, negative apex, and negative endocervical curettage were included. The median follow-up was 5.4 years. One woman had a recurrence of AIS after 8 years of follow-up and underwent total hysterectomy. No invasive cervical disease was detected during surveillance. CONCLUSIONS: Women with cervical AIS can be managed conservatively by an excisional procedure, provided that the margins are free and a close and long-term follow-up is guaranteed.

Analysis of Complementary Sex-Determiner (csd) Allele Diversity in Different Honeybee Subspecies from Italy Based on NGS Data.

Sexual regulation in Apis mellifera is controlled by the complementary sex-determiner (csd) gene: females (queens and workers) are heterozygous at this locus and males (drones) are hemizygous. When homozygous diploid drones develop, they are eaten by worker bees. High csd allelic diversity in honeybee populations is a priority for colony survival. The focus of this study is to investigate csd variability in the genomic sequence of the hypervariable region (HVR) of the csd gene in honeybee subspecies sampled in Italy. During the summer of 2017 and 2018, worker bees belonging to 125 colonies were sampled. The honeybees belonged to seven different A. mellifera subspecies: A. m. ligustica, A. m. sicula, A. m cecropia, A. m. carnica, A. m. mellifera, Buckfast and hybrid Carnica. Illumina genomic resequencing of all samples was performed and used for the characterization of global variability among colonies. In this work, a pipeline using existing resequencing data to explore the csd gene allelic variants present in the subspecies collection, based on de novo assembly of sequences falling within the HVR region, is described. On the whole, 138 allelic sequences were successfully reconstructed. Among these, 88 different alleles were identified, 68 of which match with csd alleles present in the NCBI GenBank database.