Zero leakage design for ducts and tube connections for deep space travel. Volume 5 - Tube connector design principles and evaluation Final report, 5 Jul. 1963 - 30 Jun. 1967

Principles of connector testing, design evaluation of commercial connectors, and assessment of design rules for threaded connector

Diffusion bonding makes strong seal at flanged connector

Copper strip seals a high pressure fluid system connector so that it is insensitive to relaxation of the bolt loads. The copper strip is diffusion bonded to the surfaces of the connector flange by application of high pressure and temperature

The vaginal microbiota associates with the regression of untreated cervical intraepithelial neoplasia 2 lesions

Emerging evidence suggests associations between the vaginal microbiota (VMB) composition, human papillomavirus (HPV) infection, and cervical intraepithelial neoplasia (CIN); however, causal inference remains uncertain. Here, we use bacterial DNA sequencing from serially collected vaginal samples from a cohort of 87 adolescent and young women aged 16–26 years with histologically confirmed, untreated CIN2 lesions to determine whether VMB composition affects rates of regression over 24 months. We show that women with a Lactobacillus-dominant microbiome at baseline are more likely to have regressive disease at 12 months. Lactobacillus spp. depletion and presence of specific anaerobic taxa including Megasphaera, Prevotella timonensis and Gardnerella vaginalis are associated with CIN2 persistence and slower regression. These findings suggest that VMB composition may be a future useful biomarker in predicting disease outcome and tailoring surveillance, whilst it may offer rational targets for the development of new prevention and treatment strategies

Advances in structure elucidation of small molecules using mass spectrometry

The structural elucidation of small molecules using mass spectrometry plays an important role in modern life sciences and bioanalytical approaches. This review covers different soft and hard ionization techniques and figures of merit for modern mass spectrometers, such as mass resolving power, mass accuracy, isotopic abundance accuracy, accurate mass multiple-stage MS(n) capability, as well as hybrid mass spectrometric and orthogonal chromatographic approaches. The latter part discusses mass spectral data handling strategies, which includes background and noise subtraction, adduct formation and detection, charge state determination, accurate mass measurements, elemental composition determinations, and complex data-dependent setups with ion maps and ion trees. The importance of mass spectral library search algorithms for tandem mass spectra and multiple-stage MS(n) mass spectra as well as mass spectral tree libraries that combine multiple-stage mass spectra are outlined. The successive chapter discusses mass spectral fragmentation pathways, biotransformation reactions and drug metabolism studies, the mass spectral simulation and generation of in silico mass spectra, expert systems for mass spectral interpretation, and the use of computational chemistry to explain gas-phase phenomena. A single chapter discusses data handling for hyphenated approaches including mass spectral deconvolution for clean mass spectra, cheminformatics approaches and structure retention relationships, and retention index predictions for gas and liquid chromatography. The last section reviews the current state of electronic data sharing of mass spectra and discusses the importance of software development for the advancement of structure elucidation of small molecules

The vaginal microbiota, human papillomavirus and cervical dysplasia: a systematic review and network meta‐analysis

Background: Persistent infection with high-risk human papillomavirus can lead to cervical dysplasia and cancer. Recent studies have suggested associations between the composition of the vaginal microbiota, infection with human papillomavirus (HPV) and progression to cervical dysplasia and cancer. Objective: To assess how specific cervico-vaginal microbiota compositions are associated with HPV infection, cervical dysplasia and cancer, we conducted a systematic review and network meta-analysis (registered in PROSPERO: CRD42018112862). Search strategy: PubMed, Web of science, Embase and Cochrane database. Selection criteria: All original studies describing at least two community state types of bacteria (CST), based on molecular techniques enabling identification of bacteria, and reporting the association with HPV infection, cervical dysplasia and/or cervical cancer. Data collection and analysis: For the meta-analysis, a network map was constructed to provide an overview of the network relationships and to assess how many studies provided direct evidence for the different vaginal microbiota compositions and HPV, cervical dysplasia or cancer. Thereafter, the consistency of the model was assessed, and forest plots were constructed to pool and summarise the available evidence, presenting odds ratios and 95% confidence intervals. Main results: Vaginal microbiota dominated by non-Lactobacilli species or Lactobacillus iners were associated with three to five times higher odds of any prevalent HPV and two to three times higher for high-risk HPV and dysplasia/cervical cancer compared with Lactobacillus crispatus. Conclusions: These findings suggest an association between certain bacterial community types of the vaginal microbiota and HPV infection and HPV-related disease. This may be useful for guiding treatment options or serve as biomarkers for HPV-related disease. Tweetable abstract This network meta-analysis suggests an association between different vaginal bacterial community types and the risk of HPV

Multi-omics data integration reveals metabolome as the top predictor of the cervicovaginal microenvironment

Emerging evidence suggests that host-microbe interaction in the cervicovaginal microenvironment contributes to cervical carcinogenesis, yet dissecting these complex interactions is challenging. Herein, we performed an integrated analysis of multiple "omics"datasets to develop predictive models of the cervicovaginal microenvironment and identify characteristic features of vaginal microbiome, genital inflammation and disease status. Microbiomes, vaginal pH, immunoproteomes and metabolomes were measured in cervicovaginal specimens collected from a cohort (n = 72) of Arizonan women with or without cervical neoplasm. Multi-omics integration methods, including neural networks (mmvec) and Random Forest supervised learning, were utilized to explore potential interactions and develop predictive models. Our integrated analyses revealed that immune and cancer biomarker concentrations were reliably predicted by Random Forest regressors trained on microbial and metabolic features, suggesting close correspondence between the vaginal microbiome, metabolome, and genital inflammation involved in cervical carcinogenesis. Furthermore, we show that features of the microbiome and host microenvironment, including metabolites, microbial taxa, and immune biomarkers are predictive of genital inflammation status, but only weakly to moderately predictive of cervical neoplastic disease status. Different feature classes were important for prediction of different phenotypes. Lipids (e.g. sphingolipids and long-chain unsaturated fatty acids) were strong predictors of genital inflammation, whereas predictions of vaginal microbiota and vaginal pH relied mostly on alterations in amino acid metabolism. Finally, we identified key immune biomarkers associated with the vaginal microbiota composition and vaginal pH (MIF), as well as genital inflammation (IL-6, IL-10, MIP-1α). © 2022 Bokulich et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.Open access journalThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

Preoperative quality of life at time of gynecologic surgery: considerations for postoperative management

BACKGROUND: Patients presenting for gynecologic surgery are a heterogeneous group. Preoperative quality of life may be a useful tool to guide postoperative management. OBJECTIVE: This study aimed to examine the key drivers of preoperative quality of life to improve counseling and postoperative management. STUDY DESIGN: This study analyzed preoperative survey results from 154 participants using the following surveys: National Institutes of Health Toolbox Global Health v1.2, Gastrointestinal: Gas and Bloating v1.1 13a, Gastrointestinal: Diarrhea v1.0 6a, and Sexual Function and Satisfaction Brief Profile (Female) v2.0, Perceived Stress Scale, the Vaginal Assessment Scale, and the Vulvar Assessment Scale. Survey results in the form of T-scores were compared in patients with endometrial cancer and patients with benign gynecologic conditions using the Kruskal-Wallis test. The multivariate analysis was performed using linear regression to adjust the comparisons for age, body mass index, and comorbidity. RESULTS: Of the 154 patients, preoperative diagnosis was benign in 66% (n=102) and endometrial cancer in 34% (n=52). Patients with endometrial cancer were more likely to be older, non-White, in lower income brackets, have higher body mass index, and be postmenopausal (P.05), when adjusted for age, the differences in global health quality of life between patients with benign gynecologic conditions and those with endometrial cancer became significant, because the endometrial cancer group was older than the benign group (P.05). Sexual interest was decreased in the patients with endometrial cancer both in the unadjusted and adjusted model; and vulvar complaints became significantly different between the groups when controlling for body mass index, age, and comorbidities (P<.05). CONCLUSION: Despite substantial differences in preoperative diagnosis, preoperative quality of life is highly influenced by age, body mass index, and comorbidities. Therefore, these factors should be explored in surgical outcomes and postoperative management trials. © 2023 The AuthorsOpen access JournalThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]