Prediction of adverse perinatal outcome by fetal biometry: comparison of customized and populationâ based standards

ObjectiveTo compare the predictive performance of estimated fetal weight (EFW) percentiles, according to eight growth standards, to detect fetuses at risk for adverse perinatal outcome.MethodsThis was a retrospective cohort study of 3437 Africanâ American women. Populationâ based (Hadlock, INTERGROWTHâ 21st, World Health Organization (WHO), Fetal Medicine Foundation (FMF)), ethnicityâ specific (Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD)), customized (Gestationâ Related Optimal Weight (GROW)) and Africanâ American customized (Perinatology Research Branch (PRB)/NICHD) growth standards were used to calculate EFW percentiles from the last available scan prior to delivery. Prediction performance indices and relative risk (RR) were calculated for EFW â 90th percentiles, according to each standard, for individual and composite adverse perinatal outcomes. Sensitivity at a fixed (10%) falseâ positive rate (FPR) and partial (FPR â 90th percentile were also at risk for any adverse perinatal outcome according to the INTERGROWTHâ 21st (RRâ =â 1.4; 95%â CI, 1.0â 1.9) and Hadlock (RRâ =â 1.7; 95%â CI, 1.1â 2.6) standards, many times fewer cases (2â 5â fold lower sensitivity) were detected by using EFW >â 90th percentile, rather than EFW â 90th percentile were at increased risk of adverse perinatal outcomes according to all or some of the eight growth standards, respectively. The RR of a composite adverse perinatal outcome in pregnancies with EFW <â 10th percentile was higher for the mostâ stringent (NICHD) compared with the leastâ stringent (FMF) standard. The results of the complementary analysis of AUC suggest slightly improved detection of adverse perinatal outcome by more recent populationâ based (INTERGROWTHâ 21st) and customized (PRB/NICHD) standards compared with the Hadlock and FMF standards. Published 2019. This article is a U.S. Government work and is in the public domain in the USA.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/153734/1/uog20299.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/153734/2/uog20299_am.pd

Does surgeon sex and anthropometry matter for tool usability in traditional laparoscopic surgery? A systematic review and meta-analysis

Copyright © The Author(s) 2023 Introduction: Hand size, strength, and stature all impact a surgeon’s ability to perform Traditional Laparoscopic Surgery (TLS) comfortably and effectively. This is due to limitations in instrument and operating room design. This article aims to review performance, pain, and tool usability data based on biological sex and anthropometry. Methods: PubMed, Embase, and Cochrane databases were searched in May 2023. Retrieved articles were screened based on whether a full-text, English article was available in which original results were stratified by biological sex or physical proportions. Article quality was discussed using the Mixed Methods Appraisal Tool (MMAT). Data were summarized in three main themes: task performance, physical discomfort, and tool usability and fit. Task completion times, pain prevalence, and grip style results between male and female surgeons formed three meta-analyses. Results: A total of 1354 articles were sourced, and 54 were deemed suitable for inclusion. The collated results showed that female participants, predominantly novices, took 2.6–30.1 s longer to perform standardized laparoscopic tasks. Female surgeons reported pain at double the frequency of their male colleagues. Female surgeons and those with a smaller glove size were consistently more likely to report difficulty and require modified (potentially suboptimal) grip techniques with standard laparoscopic tools. Conclusions: The pain and stress reported by female or small-handed surgeons when using laparoscopic tools demonstrates the need for currently available instrument handles, including robotic hand controls, to become more size-inclusive. However, this study is limited by reporting bias and inconsistencies; furthermore, most data was collected in a simulated environment. Additional research into how anthropometric tool design impacts the live operating performance of experienced female surgeons would further inform this area of investigation.Open Access funding enabled and organized by CAUL and its Member Institutions. This review was commissioned and funded by CMR Surgical Ltd

Evidence-based decision support for pediatric rheumatology reduces diagnostic errors.

BACKGROUND: The number of trained specialists world-wide is insufficient to serve all children with pediatric rheumatologic disorders, even in the countries with robust medical resources. We evaluated the potential of diagnostic decision support software (DDSS) to alleviate this shortage by assessing the ability of such software to improve the diagnostic accuracy of non-specialists. METHODS: Using vignettes of actual clinical cases, clinician testers generated a differential diagnosis before and after using diagnostic decision support software. The evaluation used the SimulConsult® DDSS tool, based on Bayesian pattern matching with temporal onset of each finding in each disease. The tool covered 5405 diseases (averaging 22 findings per disease). Rheumatology content in the database was developed using both primary references and textbooks. The frequency, timing, age of onset and age of disappearance of findings, as well as their incidence, treatability, and heritability were taken into account in order to guide diagnostic decision making. These capabilities allowed key information such as pertinent negatives and evolution over time to be used in the computations. Efficacy was measured by comparing whether the correct condition was included in the differential diagnosis generated by clinicians before using the software ( unaided ), versus after use of the DDSS ( aided ). RESULTS: The 26 clinicians demonstrated a significant reduction in diagnostic errors following introduction of the software, from 28% errors while unaided to 15% using decision support (p \u3c 0.0001). Improvement was greatest for emergency medicine physicians (p = 0.013) and clinicians in practice for less than 10 years (p = 0.012). This error reduction occurred despite the fact that testers employed an open book approach to generate their initial lists of potential diagnoses, spending an average of 8.6 min using printed and electronic sources of medical information before using the diagnostic software. CONCLUSIONS: These findings suggest that decision support can reduce diagnostic errors and improve use of relevant information by generalists. Such assistance could potentially help relieve the shortage of experts in pediatric rheumatology and similarly underserved specialties by improving generalists\u27 ability to evaluate and diagnose patients presenting with musculoskeletal complaints. TRIAL REGISTRATION: ClinicalTrials.gov ID: NCT02205086

Single-cell RNA-seq highlights intratumoral heterogeneity in primary glioblastoma

Human cancers are complex ecosystems composed of cells with distinct phenotypes, genotypes, and epigenetic states, but current models do not adequately reflect tumor composition in patients. We used single-cell RNA sequencing (RNA-seq) to profile 430 cells from five primary glioblastomas, which we found to be inherently variable in their expression of diverse transcriptional programs related to oncogenic signaling, proliferation, complement/immune response, and hypoxia. We also observed a continuum of stemness-related expression states that enabled us to identify putative regulators of stemness in vivo. Finally, we show that established glioblastoma subtype classifiers are variably expressed across individual cells within a tumor and demonstrate the potential prognostic implications of such intratumoral heterogeneity. Thus, we reveal previously unappreciated heterogeneity in diverse regulatory programs central to glioblastoma biology, prognosis, and therapy.National Institutes of Health (U.S.) (U24 CA180922

Tumor innate immunity primed by specific interferon-stimulated endogenous retroviruses.

Mesenchymal tumor subpopulations secrete pro-tumorigenic cytokines and promote treatment resistance1-4. This phenomenon has been implicated in chemorefractory small cell lung cancer and resistance to targeted therapies5-8, but remains incompletely defined. Here, we identify a subclass of endogenous retroviruses (ERVs) that engages innate immune signaling in these cells. Stimulated 3 prime antisense retroviral coding sequences (SPARCS) are oriented inversely in 3' untranslated regions of specific genes enriched for regulation by STAT1 and EZH2. Derepression of these loci results in double-stranded RNA generation following IFN-γ exposure due to bi-directional transcription from the STAT1-activated gene promoter and the 5' long terminal repeat of the antisense ERV. Engagement of MAVS and STING activates downstream TBK1, IRF3, and STAT1 signaling, sustaining a positive feedback loop. SPARCS induction in human tumors is tightly associated with major histocompatibility complex class 1 expression, mesenchymal markers, and downregulation of chromatin modifying enzymes, including EZH2. Analysis of cell lines with high inducible SPARCS expression reveals strong association with an AXL/MET-positive mesenchymal cell state. While SPARCS-high tumors are immune infiltrated, they also exhibit multiple features of an immune-suppressed microenviroment. Together, these data unveil a subclass of ERVs whose derepression triggers pathologic innate immune signaling in cancer, with important implications for cancer immunotherapy

Global Mapping of DNA Conformational Flexibility on Saccharomyces cerevisiae

In this study we provide the first comprehensive map of DNA conformational flexibility in Saccharomyces cerevisiae complete genome. Flexibility plays a key role in DNA supercoiling and DNA/protein binding, regulating DNA transcription, replication or repair. Specific interest in flexibility analysis concerns its relationship with human genome instability. Enrichment in flexible sequences has been detected in unstable regions of human genome defined fragile sites, where genes map and carry frequent deletions and rearrangements in cancer. Flexible sequences have been suggested to be the determinants of fragile gene proneness to breakage; however, their actual role and properties remain elusive. Our in silico analysis carried out genome-wide via the StabFlex algorithm, shows the conserved presence of highly flexible regions in budding yeast genome as well as in genomes of other Saccharomyces sensu stricto species. Flexibile peaks in S. cerevisiae identify 175 ORFs mapping on their 3’UTR, a region affecting mRNA translation, localization and stability. (TA)n repeats of different extension shape the central structure of peaks and co-localize with polyadenylation efficiency element (EE) signals. ORFs with flexible peaks share common features. Transcripts are characterized by decreased half-life: this is considered peculiar of genes involved in regulatory systems with high turnover; consistently, their function affects biological processes such as cell cycle regulation or stress response. Our findings support the functional importance of flexibility peaks, suggesting that the flexible sequence may be derived by an expansion of canonical TAYRTA polyadenylation efficiency element. The flexible (TA)n repeat amplification could be the outcome of an evolutionary neofunctionalization leading to a differential 3’-end processing and expression regulation in genes with peculiar function. Our study provides a new support to the functional role of flexibility in genomes and a strategy for its characterization inside human fragile sites

The gene SMART study: Method, study design, and preliminary findings

Abstract The gene SMART (genes and the Skeletal Muscle Adaptive Response to Training) Study aims to identify genetic variants that predict the response to both a single session of High-Intensity Interval Exercise (HIIE) and to four weeks of High-Intensity Interval Training (HIIT). While the training and testing centre is located at Victoria University, Melbourne, three other centres have been launched at Bond University, Queensland University of Technology, Australia, and the University of Brighton, UK. Currently 39 participants have already completed the study and the overall aim is to recruit 200 moderately-trained, healthy Caucasians participants (all males 18–45 y, BMI < 30). Participants will undergo exercise testing and exercise training by an identical exercise program. Dietary habits will be assessed by questionnaire and dietitian consultation. Activity history is assessed by questionnaire and current activity level is assessed by an activity monitor. Skeletal muscle biopsies and blood samples will be collected before, immediately after and 3 h post HIIE, with the fourth resting biopsy and blood sample taken after four weeks of supervised HIIT (3 training sessions per week). Each session consists of eight to fourteen 2-min intervals performed at the pre-training lactate threshold (LT) power plus 40 to 70% of the difference between pre-training lactate threshold (LT) and peak aerobic power (Wpeak). A number of muscle and blood analyses will be performed, including (but not limited to) genotyping, mitochondrial respiration, transcriptomics, protein expression analyses, and enzyme activity. The participants serve as their own controls. Even though the gene SMART study is tightly controlled, our preliminary findings still indicate considerable individual variability in both performance (in-vivo) and muscle (in-situ) adaptations to similar training. More participants are required to allow us to better investigate potential underlying genetic and molecular mechanisms responsible for this individual variability