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BACKGROUNDMyotonic dystrophy type 1 (DM1) is a multisystemic, CTG repeat expansion disorder characterized by a slow, progressive decline in skeletal muscle function. A biomarker correlating RNA mis-splicing, the core pathogenic disease mechanism, and muscle performance is crucial for assessing response to disease-modifying interventions. We evaluated the Myotonic Dystrophy Splice Index (SI), a composite RNA splicing biomarker incorporating 22 disease-specific events, as a potential biomarker of DM1 muscle weakness.METHODSTotal RNA sequencing of tibialis anterior biopsies from 58 DM1 participants and 33 unaffected/disease controls was used to evaluate RNA splicing events across the disease spectrum. Targeted RNA sequencing was used to derive the SI from biopsies collected at baseline (n = 52) or a 3-month (n = 37) follow-up visit along with clinical measures of muscle performance.RESULTSThe SI demonstrated significant associations with measures of muscle strength and ambulation, including ankle dorsiflexion (ADF) strength and 10-meter run/fast walk (Pearson's r = -0.719 and -0.680, respectively). The SI was relatively stable over 3 months (intraclass correlation coefficient [ICC] = 0.863). Latent-class analysis identified 3 DM1 subgroups stratified by baseline SI (SIMild, SIModerate, and SISevere); SIModerate individuals had a significant increase in the SI over 3 months. Multiple linear regression modeling revealed that baseline ADF and SI were predictive of strength at 3 months (adjusted R² = 0.830).CONCLUSIONThe SI is a reliable biomarker that captures associations of RNA mis-splicing with physical strength and mobility and has prognostic utility to predict future function, establishing it as a potential biomarker for assessment of therapeutic target engagement.TRIAL REGISTRATIONClinicalTrials.gov NCT03981575.FUNDINGFDA (7R01FD006071), Myotonic Dystrophy Foundation, Wyck Foundation, Muscular Dystrophy Association, Novartis, Dyne, Avidity, PepGen, Takeda, Sanofi Genzyme, Pfizer, Arthex, and Vertex Pharmaceuticals.

A review of different modeling techniques, specifically in the framework of carbon-based nanomaterials (CNMs, including nanoparticles such as graphene and carbon nanotubes—CNTs) and the composites and devices that can be derived from them, is presented. The article emphasizes that the overall performance of these materials depends on mechanisms that operate across different time and spatial scales, requiring tailored approaches based on the material type, size, internal structure/configuration, and the specific properties of interest. Far from attempting to cover the entire spectrum of models, this review examines a wide range of analysis and simulation techniques, highlighting their potential use, some of their weaknesses and strengths, and presenting the latest developments and some application examples. In this way, it is shown how modeling can provide key information for tailoring or designing new materials for specific components or systems or to obtain certain functionalities. At the same time, it is revealed to be an area constantly undergoing development and improvement, as evidenced by the progress made by various of these techniques and the new modeling approaches that have emerged in recent years.

Background Preliminary data suggest that the urinary microbiome may play a role in bladder cancer. Information regarding the most suitable method of collecting urine specimens is needed for the large population studies needed to address this. To compare microbiome metrics resulting from 16S ribosomal RNA gene sequencing between midstream, voided specimens and those obtained at cystoscopy. Methods Adults, with a history of superficial urothelial cell carcinoma (non-muscle invasive bladder cancer) being followed with periodic surveillance cystoscopy had a urine sample collected by a mid-stream, voided technique and then from the bladder at cystoscopy. Urine samples underwent 16S ribosomal RNA gene sequencing on the Illumina MiSeq platform. Results 22 subjects (8 female, 14 male) were included. There was no significant difference in beta diversity (diversity between samples) in all samples between collection methods. However, analysis by sex revealed a difference between voided and cystoscopy samples from the same individual in males ( p  = 0.006, Adonis test) but not in females ( p  = 0.317, Adonis test). No differences were seen by collection method in any alpha diversity (diversity within a sample) measurement or differential abundance of taxa. Conclusions Beta diversity of the urine microbiome did differ by collection method for males only. This suggests that the urinary microbiomes of the two collection methods are not equivalent to each other, at least in males, which is the sex that bladder cancer occurs most frequently in. Therefore, the same collection method within a given study should be used.

Our case describes the serial microbiome changes in twins discordant for necrotizing enterocolitis (NEC), who shared similar intrauterine and early environmental exposures. The key findings were that the 2 neonates had distinctly different microbiome compositions from the first stool samples collected. Also, in the twin who developed NEC there was a decrease in bacterial diversity and an increase in Proteobacteria a week before developing any clinical symptoms, suggesting an early role of the intestinal microbiome in the development of NEC. Here we briefly review the literature on the role of the intestinal microbiome in NEC and how a greater understanding of the neonatal microbiome and host interactions may help mitigate this devastating disease.

The meconium microbiome may provide insight into intrauterine and peripartum exposures and the very earliest intestinal pioneering microbes. Prenatal antibiotics have been associated with later obesity in children, which is thought to be driven by microbiome dependent mechanisms. However, there is little data regarding associations of prenatal or peripartum antibiotic exposure, with or without cesarean section (CS), with the features of the meconium microbiome. In this study, 16S ribosomal RNA gene sequencing was performed on bacterial DNA of meconium samples from 105 infants in a birth cohort study. After multivariable adjustment, delivery mode (p = 0.044), prenatal antibiotic use (p = 0.005) and peripartum antibiotic use (p < 0.001) were associated with beta diversity of the infant meconium microbiome. CS (vs. vaginal delivery) and peripartum antibiotics were also associated with greater alpha diversity of the meconium microbiome (Shannon and Simpson, p < 0.05). Meconium from infants born by CS (vs. vaginal delivery) had lower relative abundance of the genus Escherichia (p < 0.001). Prenatal antibiotic use and peripartum antibiotic use (both in the overall analytic sample and when restricting to vaginally delivered infants) were associated with differential abundance of several bacterial taxa in the meconium. Bacterial taxa in the meconium microbiome were also differentially associated with infant excess weight at 12 months of age, however, sample size was limited for this comparison. In conclusion, prenatal and peripartum antibiotic use along with CS delivery were associated with differences in the diversity and composition of the meconium microbiome. Whether or not these differences in the meconium microbiome portend risk for long-term health outcomes warrants further exploration.

Objectives Dysregulated RNA alternative splicing is the hallmark of myotonic dystrophy type 1 (DM1). However, the association between RNA mis‐splicing and physical function in children with the most severe form of disease, congenital myotonic dystrophy (CDM), is unknown. Methods Eighty‐two participants (42 adults with DM1 and 40 children with CDM) with muscle biopsies and measures of myotonia, motor function, and strength were combined from five observational studies. Data were normalized and correlated with an aggregate measure of alternative splicing dysregulation, [MBNL]inferred, in skeletal muscle biopsies. Multiple linear regression analysis was performed to predict [MBNL]inferred using clinical outcome measures alone. Similar analyses were performed to predict 12‐month physical function using baseline metrics. Results Myotonia (measured via vHOT) was significantly correlated with RNA mis‐splicing in our cross‐sectional population of all DM1 individuals; CDM participants alone displayed no myotonia despite a similar range of RNA mis‐splicing. Measures of motor performance and muscle strength were significantly associated with [MBNL]inferred in our cohort of all DM1 individuals and when assessing children with CDM independently. Multiple linear regression analyses yielded two models capable of predicting [MBNL]inferred from select clinical outcome assessments alone in all subjects (adjusted R2 = 0.6723) or exclusively in children with CDM (adjusted R2 = 0.5875). Interpretation Our findings establish significant correlations between skeletal muscle performance and a composite measure of alternative splicing dysregulation, [MBNL]inferred, in DM1. The strength of these correlations and the development of predictive models will assist in designing efficacious clinical trials for individuals with DM1, particularly CDM.

Background Effective methods are needed to collect fecal samples from children for large-scale microbiota studies. Stool collected on fecal occult blood test (FOBT) cards that can be mailed provides an effective solution; however, the quality of sequencing resulting from this method is unknown. The aim of this study is to compare microbiota metrics of 16S ribosomal RNA (rRNA) gene sequencing from stool and meconium collected on FOBT cards with stool collected in an Eppendorf tube (ET) under different conditions. Methods Eight stool samples from children in diapers aged 0 month–2 years and three meconium samples were collected and stored as follows: (1) ≤ 2 days at room temperature (RT) in an ET, (2) 7 days at − 80 °C in an ET, (3) 3–5 days at RT on a FOBT card, (4) 7 days at RT on a FOBT card, and (5) 7 days at − 80 °C on a FOBT card. Samples stored at − 80 °C were frozen immediately. Each specimen/condition underwent 16S rRNA gene sequencing with replicates on the Illumina MiSeq. Alpha and beta diversity measures and relative abundance of major phyla were compared between storage conditions and container (ET vs. FOBT card), with pairwise comparison between different storage conditions and the “standard” of 7 days at − 80 °C in an ET and fresh stool in an ET. Results Stool samples clustered mainly by individual diaper ( P  < 10 −5 , Adonis), rather than by storage condition ( P  = 0.42) or container ( P  = 0.16). However, meconium samples clustered more by container ( P  = 0.002) than by individual diaper ( P  = 0.009) and storage condition ( P  = 0.02). Additionally, there were no differences in alpha diversity measures and relative abundance of major phyla after Bonferroni correction between stool stored on a FOBT card at RT for 7 days with stool stored in an ET tube at − 80 °C; differences in alpha diversity were seen however when compared to fresh stool in an ET. Overall, based on the intraclass correlation coefficient (ICC), the different storage containers/conditions are reliable in preserving the microbial memberships and slightly less reliable in preserving the alpha diversity and relative microbial composition of infant stool. Conclusions Acknowledging certain limitations, FOBT cards may be a useful tool in large-scale stool microbiota studies in children requiring outpatient follow-up where only small amounts of stool can be obtained, but should not be used when studying meconium.

This document explores the potential of quantum computing in Thermal Science. Conceived as a living document, it will be continuously updated with experimental findings and insights for the research community in Thermal Science. By experiments, we refer both to the search for the most effective algorithms and to the performance of real quantum hardware. Those are fields that are evolving rapidly, driving a technological race to define the best architectures. The development of novel algorithms for engineering problems aims at harnessing the unique strengths of quantum computing. Expectations are high, as users seek concrete evidence of quantum supremacy - a true game changer for engineering applications. Among all heat transfer mechanisms (conduction, convection, radiation), we start with conduction as a paradigmatic test case in the field being characterized by a rich mathematical foundation for our investigations.

This document explores the potential of quantum computing in Thermal Science. Conceived as a living document, it will be continuously updated with experimental findings and insights for the research community in Thermal Science. By experiments, we refer both to the search for the most effective algorithms and to the performance of real quantum hardware. Those are fields that are evolving rapidly, driving a technological race to define the best architectures. The development of novel algorithms for engineering problems aims at harnessing the unique strengths of quantum computing. Expectations are high, as users seek concrete evidence of quantum supremacy - a true game changer for engineering applications. Among all heat transfer mechanisms (conduction, convection, radiation), we start with conduction as a paradigmatic test case in the field being characterized by a rich mathematical foundation for our investigations.

Dysregulated RNA alternative splicing is the hallmark of myotonic dystrophy type 1 (DM1). However, the association between RNA mis-splicing and physical function in children with the most severe form of disease, congenital myotonic dystrophy (CDM), is unknown. 82 participants (42 DM1 adults & 40 CDM children) with muscle biopsies and measures of myotonia, motor function, and strength were combined from five observational studies. Data were normalized and correlated with an aggregate measure of alternative splicing dysregulation, [MBNL] in skeletal muscle biopsies. Multiple linear regression analysis was performed to predict [MBNL] using clinical outcome measures alone. Similar analyses were performed to predict 12-month physical function using baseline metrics. Myotonia (measured via vHOT) was significantly correlated with RNA mis-splicing in our cross-sectional population of all DM1 individuals; CDM participants alone displayed no myotonia despite a similar range of RNA mis-splicing. Measures of motor performance and muscle strength were significantly associated with [MBNL] in our cohort of all DM1 individuals and when assessing CDM children independently. Multiple linear regression analyses yielded two models capable of predicting [MBNL] from select clinical outcome assessments alone in all subjects (adjusted R = 0.6723) or exclusively in CDM children (adjusted R = 0.5875). Our findings establish significant correlations between skeletal muscle performance and a composite measure of alternative splicing dysregulation, [MBNL] in DM1. The strength of these correlations and the development of the predictive models will assist in designing efficacious clinical trials for individuals with DM1, particularly CDM.