O efeito conjunto de gemelaridade e prematuridade no aleitamento materno exclusivo na alta hospitalar / The joint effect of twinning and prematurity on exclusive breastfeeding at hospital discharge / El efecto conjunto de la gemelaridad y la prematuridad en la lactancia materna exclusiva al momento del alta hospitalaria

Objetivo: estimar a prevalência de Aleitamento Materno Exclusivo (AME) entre gemelares pré-termos e investigar o efeito de nascer gemelar e pré-termo no AME na alta hospitalar. Método: coorte prospectiva de recém-nascidos em uma instituição localizada no Rio de Janeiro, no período de 13 de março de 2017 a 12 de outubro de 2018. Dados coletados em questionário e prontuário médico. Foi utilizado DAG para construção do modelo conceitual, análise exploratória dos dados e regressão logística múltipla. Resultados: a prevalência de AME na alta hospitalar de gemelares pré-termos foi de 47,8%. Pré-termos apresentaram maior chance de não estarem em AME na alta hospitalar. Não gemelares apresentaram maior chance de não estarem em AME na alta hospitalar. Conclusão: pouco mais da metade dos gemelares pré-termo não estavam em AME na alta hospitalar. Prematuros tiveram maior chance de não estarem em AME. Não gemelares pré-termo apresentaram maior chance de não estarem em AME.

Objective: to estimate the prevalence of Exclusive Breastfeeding (EBF) in preterm twins and to investigate the effect of twin and preterm birth on EBF at hospital discharge. Method: prospective cohort of newborns in an institution located in Rio de Janeiro, from March 13, 2017, to October 12, 2018. Data collected through a questionnaire and medical records. A DAG was used to build the conceptual model, exploratory data analysis and multiple logistic regression. Results: prevalence of EBF at hospital discharge of preterm twins of 47.8%. Preterm infants were more likely to not be on EBF at hospital discharge. Non-twins were more likely to not be on EBF at hospital discharge. Conclusion: just over half of preterm twins were not on EBF at hospital discharge. Preterm infants had a greater chance of not being on EBF. Preterm non-twins were more likely to not be on EBF.

Objetivo: estimar la prevalencia de Lactancia Materna Exclusiva (LME) entre gemelos prematuros y investigar el efecto de nacer gemelo y prematuro en la LME al momento del alta hospitalaria. Método: cohorte prospectiva de recién nacidos en una institución ubicada en Rio de Janeiro, entre 13//marzo/2017 y 12/octubre/2018. Los datos se recolectaron mediante cuestionario y expediente médico. Se utilizó DAG para la construcción del modelo conceptual, análisis exploratorio de los datos y regresión logística múltiple. Resultados: la prevalencia de LME en el alta hospitalaria de gemelos prematuros fue del 47,8%. Los prematuros tuvieron mayor probabilidad de no estar en LME en el alta hospitalaria. Los no gemelares tuvieron mayor probabilidad de no estar en LME en el alta hospitalaria. Conclusión: poco más de la mitad de los gemelos prematuros no estaban en LME en el alta hospitalaria. Los prematuros tuvieron mayor probabilidad de no estar en LME. Los no gemelos prematuros presentaron mayor probabilidad de no estar en LME.

Genetic Influence on Social Support: A Twin Study.

Social support is often considered an environmental factor affecting health, especially in aging populations. However, its genetic underpinnings suggest a more complex origin. This study investigates the heritability of social support through applying a threshold model on data of a large adult sample of twins (N = 8019) from the Netherlands Twin Register, collected between 2009 and 2011. The study employed the Duke - UNC Functional Social Support Questionnaire to assess social support quality. Our analysis revealed genetic contributions to social support, with heritability estimated at 37%, without a contribution of shared environment and no differences between men and women in heritability. The study's results underscore the complexity of social support as a trait influenced by genetic and environmental factors, challenging the notion that it is solely an environmental construct.

Twin Data Support a Sensitive Period for Singing Ability.

As with many other musical traits, the social environment is a key influence on the development of singing ability. While the familial singing environment is likely to be formative, its role relative to other environmental influences such as training is unclear. We used structural equation modeling to test relationships among demographic characteristics, familial environmental variables (early and current singing with family), vocal training, and singing ability in a large, previously documented sample of Australian twins (N = 1163). Notably, early singing with family, and to a lesser extent vocal training, predicted singing ability, whereas current singing with family did not. Early familial singing also mediated the relationship between sex and singing ability, with men who sang less with family during childhood showing poorer ability. Bivariate twin models between early familial singing and singing ability showed the phenotypic correlation was largely explained by shared environmental influences. This raises the possibility of a sensitive period for singing ability, with sociocultural expectations around singing potentially differentiating the developmental trajectories of this skill for men and women.

Zygosity Effects on Human Voice: Fundamental Frequency Analysis of Brazilian Twins' Speech.

Voice production can be influenced by interindividual variations related to genetic, physiological, behavioral, and several environmental factors. Here we examined the effect of zygosity on speaking fundamental frequency (F0) statistical descriptors. Our aims were: (1) to determine whether the genetic similarity between monozygotic (MZ) and dizygotic (DZ) twins affects F0 characteristics, and (2) to quantify the contribution of genetic factors to these characteristics. The study involved 79 same-sex twin pairs of Brazilian Portuguese speakers, comprising 65 MZ and 14 DZ twins, aged 18 to 66 years (31.7 ± 11.6 years), with 21 male and 58 female pairs. Participants were recorded while uttering a greeting phrase and the Brazilian Portuguese version of the 'Happy Birthday to You' song. Speech segments were analyzed using Praat free software, and F0 measures were automatically extracted in both Hertz and semitone scales. Statistical descriptors, including centrality, dispersion, and extreme values of F0 were examined, and the ACE model (i.e., total genetic effects, A; shared environmental influences, C; and nonshared environmental influences, E) was employed to estimate the additive effect;ts of monozygosity. As anticipated, we observed a zygosity effect on several F0 parameters, with more similarity between MZ twins compared to DZ twins. We discuss the genetic influences on F0 parameters and the absence of a monozygosity effect in two of them. Additionally, we briefly address potential biases associated with the selected measurement scale for statistical modeling. Finally, we explore the influence of genetic factors on F0 patterns, as well as environmental, life history and linguistic factors, particularly concerning F0 variation in speech.

Fabry disease in female monozygotic twins with complex intronic haplotype variants: a case report.

BACKGROUND: Fabry disease is an X-linked lysosomal storage disease caused by the impairment of α-galactosidase A. The complex intronic haplotype (CIH) variants, located in promoter and intronic regulatory lesions, has been found in patients with classical forms of Fabry disease. We present a case of Fabry disease in female monozygotic twins exhibiting the CIH mutation and classical manifestations. CASE PRESENTATION: A 61-year-old woman with a history of stroke, carotid artery occlusion, hypertrophic cardiomyopathy, and chronic kidney disease was referred to the nephrology clinic for management of her chronic kidney disease. Her monozygotic twin sister also presented with hypertrophic cardiomyopathy, atrial flutter, carotid stenosis, and proteinuria. Clinical symptoms and a comprehensive family history strongly suggested the presence of Fabry disease. Genetic analysis revealed the presence of 5 variants within a complex intronic haplotype (CIH): c.-10 C > T, c.369 + 990 C > A, c.370 - 81_370-77delCAGCC, c.640-16 A > G, and c.1000-22 C > T. We conducted a review of the patient's previous kidney biopsy findings, which demonstrated the presence of lamellated inclusion bodies in electron microscopy. Remarkably, both the monozygotic twin sister and her son exhibited the same genetic mutation. Enzyme replacement therapy was initiated for the patient. Her kidney function decreased throughout a thorough 2-year follow-up period, while there was a slight decrease in the left ventricular mass index. CONCLUSIONS: This is the first reported case of female monozygotic twins with the CIH variants representing cardiac, cerebrovascular, and renal manifestations suggestive of Fabry disease.

Network-level enrichment provides a framework for biological interpretation of machine learning results.

Machine learning algorithms are increasingly being utilized to identify brain connectivity biomarkers linked to behavioral and clinical outcomes. However, research often prioritizes prediction accuracy at the expense of biological interpretability, and inconsistent implementation of ML methods may hinder model accuracy. To address this, our paper introduces a network-level enrichment approach, which integrates brain system organization in the context of connectome-wide statistical analysis to reveal network-level links between brain connectivity and behavior. To demonstrate the efficacy of this approach, we used linear support vector regression (LSVR) models to examine the relationship between resting-state functional connectivity networks and chronological age. We compared network-level associations based on raw LSVR weights to those produced from the forward and inverse models. Results indicated that not accounting for shared family variance inflated prediction performance, the k-best feature selection via Pearson correlation reduced accuracy and reliability, and raw LSVR model weights produced network-level associations that deviated from the significant brain systems identified by forward and inverse models. Our findings offer crucial insights for applying machine learning to neuroimaging data, emphasizing the value of network enrichment for biological interpretation.

Enhancing efficiency and quality control: The impact of Digital Twins in drinking water networks.

This paper showcases the successful development and implementation of two Digital Twin prototypes within the Lab Digital Twins project, designed to enhance the efficiency and quality control of Aigües de Barcelona's drinking water network. The first prototype focuses on asset management, using (near) real-time data and statistical models, and achieving a 70% success rate in predicting pump station failures 137 days in advance. The second prototype addresses water quality monitoring, leveraging machine learning to accurately forecast trihalomethane levels at key points in the distribution system, and enabling proactive water quality management strategies, ensuring compliance with stringent safety standards and safeguarding public health. The paper details the methodology of both prototypes, highlighting their potential to revolutionize water network management. PRACTITIONER POINTS: Digital representation of assets and processes in the drinking water treatment network Early fault detection in assets, and predictions of trihalomethane formation in the drinking water distribution network Reduction on monitoring time and incident response for target assets by means of Digital Twins Improvement in visualization, prediction, and proactive measures for asset management and water quality control Contribution to the growing knowledge on Digital Twins and their potential to revolutionize water network operations.

Personality and COMT gene: molecular-genetic and epigenetic associations with NEO-PI-R personality domains and facets in monozygotic twins.

Background: This study investigates the relationship between MB-COMT DNA methylation (DNAm) and the personality traits outlined in the NEO-PI-R model through an epigenetic study of monozygotic twins. DNAm, a critical epigenetic mechanism, regulates gene expression and has been linked to various biological processes and disorders. By leveraging the genetic similarities of monozygotic twins, this research explores how epigenetic variations influenced by environmental factors correlate with personality differences. Methods: The study utilized the Five-Factor Model (FFM) to categorize personality traits into five domains: Neuroticism, Extraversion, Conscientiousness, Agreeableness, and Openness to Experience. Each domain comprises six facets, providing a granular view of personality. The research centered on the catechol-O-methyltransferase (COMT) gene, focusing on its role in dopamine metabolism, which is hypothesized to influence personality traits through the dopaminergic system. DNAm status in the MB-COMT promoter region was examined to determine its association with personality facets. Results: Preliminary findings suggest a complex interaction between MB-COMT DNAm patterns and personality traits. Specific methylation patterns at different CpG sites were linked to varying expressions of traits such as impulsivity and aggression, highlighting the nuanced impact of epigenetics on personality. Conclusion: This study underscores the potential of integrating genetic, epigenetic, and environmental data to enhance our understanding of personality formation. The results contribute to a broader understanding of how genetic predispositions shaped by environmental factors manifest in complex trait differences, paving the way for future research in genetic psychiatry and personalized medicine.

Heredity and Forensic Implications of Lip Prints among Indian Twins and Non-Twin Siblings: A Cheiloscopy Study.

Objectives: This study aimed to assess the lip prints of Indian twins and non-twin siblings to evaluate the existence of heredity in the lip prints of these individuals. Materials and Methods: The study employed a blind, cross-sectional, quantitative approach with an inductive method and extensive direct observation. The sample consisted of 30 twins and 30 non-twin siblings, divided into three groups based on gender with 10 subjects in each subgroup. All participants were aged between 10 and 30 years and were instructed on the methods and techniques involved in the study. Results: The lip prints of participants were recorded using dark-colored lipstick, bond paper, cellophane tape, and a brush, and were examined for lip thickness measurement (in mm), classification of lip commissures, and assessment of groove patterns. The findings were then analyzed to determine the pattern of lip prints among twins and non-twin siblings. Conclusion: Cheiloscopy, the forensic investigation technique based on lip trace identification, could benefit from this study's findings as it explores the existence of heredity in lip prints of Indian twins and non-twin siblings.

Digital twins for managing bridge climate change adaptation.

Background: Bridges are vital construction infrastructures that almost every nation needs in order to function. Climate change is a significant issue, that especially affects the construction industry. It is very important that bridges are able to withstand the impacts of climate change and adaptation measures will be required to achieve this. Methods: The digital twin will be developed using BIM to manage the climate change adaptation measures for the bridges. A 6D BIM model will be created that includes the 3D Revit model of a bridge featuring climate change measures, the climate change adaptation measures timeline schedule, climate change adaptation cost estimation, and carbon emission estimation, which will be produced using Revit software, Navisworks, and Granta EduPack. The results will show how 6D BIM can be used to support the adaptation of bridges to the effects of climate change. Results: The findings underscore the efficacy of 6D BIM in enhancing bridge resilience against climate change impacts. The 3D model demonstrates integration of adaptation measures without compromising bridge functionality. Moreover, the 4D model's timeline scheduling facilitates hazard anticipation, project planning, communication enhancement, collaborative efforts, and project visualization. Cost estimations from the 5D model reveal varying costs among adaptation measures, while the 6D model highlights differences in carbon footprints. These BIM dimensions enable stakeholders to analyse effects on project costs and energy consumption, aiding sustainability and cost-efficiency considerations. Conclusions: The study exhibits the literature review analysis, the risk assessment, research on climate change adaptation strategies, and implementation using Revit 2022, Navisworks 2022, and Granta EduPack software. By contributing to the adaptation of bridges to climate change effects, the research has provided valuable insights and practical implications for enhancing bridge resilience globally.

Bridges are vital construction infrastructures that almost every nation needs in order to function. Climate change is a significant issue, that especially affects the construction industry. It is very important that bridges are able to withstand the impacts of climate change and adaptation measures will be required to achieve this. The digital twin or virtual replica of the bridge will be developed to manage the climate change adaptation measures for the bridges. A 6D BIM model will be created that includes the 3D Revit model of a bridge featuring climate change measures, the climate change adaptation measures timeline schedule, climate change adaptation cost estimation, and carbon emission estimation, which will be produced using Revit software, Navisworks, and Granta EduPack. The results will show how an interactive 6D BIM (transforming into a digital twin) can be used to support the adaptation of bridges to the effects of climate change. Our study contributes to the adaptation of bridges to climate change effects, the research has provided valuable insights and practical implications for enhancing bridge resilience globally.

Diagnosing Cataracts in the Digital Age: A Survey on AI, Metaverse, and Digital Twin Applications.

PURPOSE: The study explores the evolving landscape of cataract diagnosis, focusing on both traditional methods and innovative technological integrations. It aims to address challenges with subjectivity in traditional cataract grading and to evaluate how new technologies can enhance diagnostic accuracy and accessibility. METHODS: The research introduces and examines the use of Artificial Intelligence (AI), Machine Learning (ML), and Deep Learning (DL) in automating and improving cataract screening processes. It also explores the role of the Metaverse, Digital Twins, and Teleophthalmology for immersive patient education, real-time virtual replicas of eyes, and remote access to specialized care. RESULTS: Various ML and DL techniques demonstrated significant accuracy in cataract detection. The integration of these technologies, along with the Metaverse, Digital Twins, and Teleophthalmology, provides a comprehensive framework for accurate and accessible cataract diagnosis. CONCLUSION: There is a notable paradigm shift toward individualized, predictive, and transformative eye care. The advancements in technology address existing diagnostic challenges and mitigate the shortage of ophthalmologists by extending high-quality care to underserved regions. These developments pave the way for improved cataract management and broader accessibility.

COMPARING vaccine manufacturing technologies recombinant DNA vs in vitro transcribed (IVT) mRNA.

Vaccine manufacturing fosters the prevention, control, and eradication of infectious diseases. Recombinant DNA and in vitro (IVT) mRNA vaccine manufacturing technologies were enforced to combat the recent pandemic. Despite the impact of these technologies, there exists no scientific announcement that compares them. Digital Shadows are employed in this study to simulate each technology, investigating root cause deviations, technical merits, and liabilities, evaluating cost scenarios. Under this lens we provide an unbiased, advanced comparative technoeconomic study, one that determines which of these manufacturing platforms are suited for the two types of vaccines considered (monoclonal antibodies or antigens). We find recombinant DNA technology to exhibit higher Profitability Index due to lower capital and starting material requirements, pertaining to lower Minimum Selling Price per Dose values, delivering products of established quality. However, the potency of the mRNA, the streamlined and scalable synthetic processes involved and the raw material availability, facilitate faster market penetration and product flexibility, constituting these vaccines preferable whenever short product development cycles become a necessity.

Implementing Autonomous Control in the Digital-Twins-Based Internet of Robotic Things for Remote Patient Monitoring.

Conventional patient monitoring methods require skin-to-skin contact, continuous observation, and long working shifts, causing physical and mental stress for medical professionals. Remote patient monitoring (RPM) assists healthcare workers in monitoring patients distantly using various wearable sensors, reducing stress and infection risk. RPM can be enabled by using the Digital Twins (DTs)-based Internet of Robotic Things (IoRT) that merges robotics with the Internet of Things (IoT) and creates a virtual twin (VT) that acquires sensor data from the physical twin (PT) during operation to reflect its behavior. However, manual navigation of PT causes cognitive fatigue for the operator, affecting trust dynamics, satisfaction, and task performance. Also, operating manual systems requires proper training and long-term experience. This research implements autonomous control in the DTs-based IoRT to remotely monitor patients with chronic or contagious diseases. This work extends our previous paper that required the user to manually operate the PT using its VT to collect patient data for medical inspection. The proposed decision-making algorithm enables the PT to autonomously navigate towards the patient's room, collect and transmit health data, and return to the base station while avoiding various obstacles. Rather than manually navigating, the medical personnel direct the PT to a specific target position using the Menu buttons. The medical staff can monitor the PT and the received sensor information in the pre-built virtual environment (VE). Based on the operator's preference, manual control of the PT is also achievable. The experimental outcomes and comparative analysis verify the efficiency of the proposed system.

Developing Inclusive Community Platforms: A Catalyst for DEI Community.

Developing inclusive communities is important to enhance individuals' well-being yet this brings the challenge of actively engaging and leveraging the diversity of residents in communities. Such significant social challenges are prominent in Japan, a focus of this article, as the most advanced aging society in the world and thus relevant to European and other countries. This paper explains a major government initiative that takes an innovative approach through leveraging a social technology, a Digital Twin of a community, to understand and address inclusiveness of a community leveraging population approach. The purpose of this letter is to provide researchers and policy makers insights into the approach taken to stimulate reflection on the potential for adaptation and replication.

Dichorionic Diamniotic Twin Anencephaly and Exencephaly.

We present a rare case of dichorionic diamniotic twin anencephaly and exencephaly discovered in a 35-year-old female at 13.1 weeks of gestation. Anencephaly and exencephaly are neural tube defects (NTD) with devastating consequences caused by the failure of the anterior neural groove closure leading to exencephaly, followed by brain disintegration causing anencephaly. While NTD themselves are common congenital anomalies, their presence in both twins of a dichorionic diamniotic gestation is exceedingly rare and has only been documented in one other instance. The uncertainty surrounding risk factors involved in this specific case underscores the importance of ongoing research to elucidate other potential determinants in the pathogenesis of NTD and to discover novel preventive strategies, particularly in twin pregnancies. Future research endeavors should explore the interplay of genetic, environmental, and other anomalous factors to deepen our understanding and improve clinical outcomes for affected pregnancies.

Is cancer associated with frailty? Results from a longitudinal study of old Danish twins.

BACKGROUND: While age is an important risk factor for both cancer and frailty, it is unclear whether cancer itself increases the risk of frailty. We aimed to assess the association between cancer and frailty in a longitudinal cohort of older Danish twins, taking familial effect into account. METHODS: Using the Danish Cancer Registry, cancer cases were identified among participants aged 70 and over in the Longitudinal Study of Aging Danish Twins (LSADT). Frailty was evaluated over 10 years of follow-up using the frailty index (FI) and defined as FI > 0.21. Stratified Cox regressions were performed on discordant twin pairs (pairs where one twin had incident cancer and the other was cancer-free), and on all LSADT individual twins (twin pairs and singletons) with no history of cancer. RESULTS: Among the 72 discordant pairs (n=144, median age at inclusion=75) included in the study, the median FI at inclusion was 0.08 for both cancer twins and cancer-free co-twins. From the stratified Cox regression, twins with cancer had an increased hazard of developing frailty (HR=3.67, 95%CI=1.02,13.14) compared to their cancer-free co-twins. The analyses on individual twins (n=4,027) provided similar results, showing an increased hazard of frailty in individuals with cancer (HR=2.57, 95%CI= 1.77,3.74) compared to those without cancer. CONCLUSIONS: We showed a higher risk of becoming frail following a cancer diagnosis in both discordant twin pairs and individual twins. These findings support the importance of monitoring of frailty in older adults with cancer through geriatric assessments and implementation of frailty interventions.

Lifestyle differences between co-twins are associated with decreased similarity in their internal and external exposome profiles.

Whether differences in lifestyle between co-twins are reflected in differences in their internal or external exposome profiles remains largely underexplored. We therefore investigated whether within-pair differences in lifestyle were associated with within-pair differences in exposome profiles across four domains: the external exposome, proteome, metabolome and epigenetic age acceleration (EAA). For each domain, we assessed the similarity of co-twin profiles using Gaussian similarities in up to 257 young adult same-sex twin pairs (54% monozygotic). We additionally tested whether similarity in one domain translated into greater similarity in another. Results suggest that a lower degree of similarity in co-twins' exposome profiles was associated with greater differences in their behavior and substance use. The strongest association was identified between excessive drinking behavior and the external exposome. Overall, our study demonstrates how social behavior and especially substance use are connected to the internal and external exposomes, while controlling for familial confounders.

A computational study on the influence of antegrade accessory pathway location on the 12-lead electrocardiogram in Wolff-Parkinson-White syndrome.

Wolff-Parkinson-White syndrome is a cardiovascular disease characterized by abnormal atrio-ventricular conduction facilitated by accessory pathways (APs). Invasive catheter ablation of the AP represents the primary treatment modality. Accurate localization of APs is crucial for successful ablation outcomes, but current diagnostic algorithms based on the 12 lead electrocardiogram (ECG) often struggle with precise determination of AP locations. In order to gain insight into the mechanisms underlying localization failures observed in current diagnostic algorithms, we employ a virtual cardiac model to elucidate the relationship between AP location and ECG morphology. We first introduce a cardiac model of electrophysiology that was specifically tailored to represent antegrade APs in the form of a short atrio-ventricular bypass tract. Locations of antegrade APs were then automatically swept across both ventricles in the virtual model to generate a synthetic ECG database consisting of 9271 signals. Regional grouping of antegrade APs revealed overarching morphological patterns originating from diverse cardiac regions. We then applied variance-based sensitivity analysis relying on polynomial chaos expansion on the ECG database to mathematically quantify how variation in AP location and timing relates to morphological variation in the 12 lead ECG. We utilized our mechanistic virtual model to showcase limitations of AP localization using standard ECG-based algorithms and provide mechanistic explanations through exemplary simulations. Our findings highlight the potential of virtual models of cardiac electrophysiology not only to deepen our understanding of the underlying mechanisms of Wolff-Parkinson-White syndrome but also to potentially enhance the diagnostic accuracy of ECG-based algorithms and facilitate personalized treatment planning.

Predicting resistance and pseudoprogression: are minimalistic immunoediting mathematical models capable of forecasting checkpoint inhibitor treatment outcomes in lung cancer?

BACKGROUND: The increased application of immune checkpoint inhibitors (ICIs) targeting PD-1/PD-L1 in lung cancer treatment generates clinical need to reliably predict individual patients' treatment outcomes. METHODS: To bridge the prediction gap, we examine four different mathematical models in the form of ordinary differential equations, including a novel delayed response model. We rigorously evaluate their individual and combined predictive capabilities with regard to the patients' progressive disease (PD) status through equal weighting of model-derived outcome probabilities. RESULTS: Fitting the complete treatment course, the novel delayed response model (R2=0.938) outperformed the simplest model (R2=0.865). The model combination was able to reliably predict patient PD outcome with an overall accuracy of 77% (sensitivity = 70%, specificity = 81%), solely through calibration with primary tumor longest diameter measurements. It autonomously identified a subset of 51% of patients where predictions with an overall accuracy of 81% (sensitivity = 81%, specificity = 81%) can be achieved. All models significantly outperformed a fully data-driven machine learning-based approach. IMPLICATIONS: These modeling approaches provide a dynamic baseline framework to support clinicians in treatment decisions by identifying different treatment outcome trajectories with already clinically available measurement data. LIMITATIONS AND FUTURE DIRECTIONS: Conjoint application of the presented approach with other predictive tools and biomarkers, as well as further disease information (e.g. metastatic stage), could further enhance treatment outcome prediction. We believe the simple model formulations allow widespread adoption of the developed models to other cancer types. Similar models can easily be formulated for other treatment modalities.

Maternal Characteristics in Natural and Medically Assisted Reproduction Dizygotic Twin Pregnancies.

Previous studies have shown that mothers of naturally conceived dizygotic (DZ) twins tend to be taller, older, and smoke more than mothers of naturally conceived monozygotic (MZ) twin and mothers of singletons. Here, we investigate whether mothers of naturally conceived DZ twins differ from mothers who conceived their DZ twins after medically assisted reproduction (MAR) in eight maternal traits related to fertility based on observational survey data. We include data from 33,648 mothers from the Netherlands Twin Register (NTR) and 1660 mothers of twins from the Norwegian Mother, Father and Child Cohort Study (MoBA). We contrast mothers of naturally conceived DZ twins with mothers of MAR DZ twins. Next, we further segment the MAR group into mothers who underwent hormonal induction of ovulation but not in vitro fertilization (IVF) and those who IVF twins, comparing them both to each other and against the mothers of naturally conceived DZ twins. Mothers of naturally conceived DZ twins smoke more often, differ in body composition, have a higher maternal age and have more offspring before the twins than mothers of MZ twins. Compared to MAR DZ twin mothers, mothers of naturally conceived DZ twins have fewer miscarriages, lower maternal age and increased height, more offspring and are more often smokers. BMI before the twin pregnancy is similar in both natural and MAR DZ twin mothers. Mothers who received hormonal induction of ovulation (OI) have a lower maternal age, fewer miscarriages, and a higher number of offspring before their twin pregnancy than twin mothers who received IVF and/or intracytoplasmic sperm injection (ICSI) treatments. Our study shows that twin mothers are a heterogenous group and the differences between twin mothers should be taken into account in epidemiological and genetic research that includes twins.