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A biomolecular coating, or biocorona, forms on the surface of engineered nanomaterials (ENMs) immediately as they enter biological or environmental systems, defining their biological and environmental identity and influencing their fate and performance. This biomolecular layer includes proteins (the protein corona) and other biomolecules, such as nucleic acids and metabolites. To ensure a meaningful and reproducible analysis of the ENMs-associated biocorona, it is essential to streamline procedures for its preparation, separation, identification and characterization, so that studies in different labs can be easily compared, and the information collected can be used to predict the composition, dynamics and properties of biocoronas acquired by other ENMs. Most studies focus on the protein corona as proteins are easier to monitor and characterize than other biomolecules and play crucial roles in receptor engagement and signaling; however, metabolites play equally critical roles in signaling. Here we describe how to reproducibly prepare and characterize biomolecule-coated ENMs, noting especially the steps that need optimization for different types of ENMs. The structure and composition of the biocoronas are characterized using general methods (transmission electron microscopy, dynamic light scattering, capillary electrophoresis-mass spectrometry and liquid chromatography-mass spectrometry) as well as advanced techniques, such as transmission electron cryomicroscopy, synchrotron-based X-ray absorption near edge structure and circular dichroism. We also discuss how to use molecular dynamic simulation to study and predict the interaction between ENMs and biomolecules and the resulting biocorona composition. The application of this protocol can provide mechanistic insights into the formation, composition and evolution of the ENM biocorona, ultimately facilitating the biomedical and agricultural application of ENMs and a better understanding of their impact in the environment.
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BACKGROUND: Semiparametric survival analysis such as the Cox proportional hazards (CPH) regression model is commonly employed in endometrial cancer (EC) study. Although this method does not need to know the baseline hazard function, it cannot estimate event time ratio (ETR) which measures relative increase or decrease in survival time. To estimate ETR, the Weibull parametric model needs to be applied. The objective of this study is to develop and evaluate the Weibull parametric model for EC patients' survival analysis. METHODS: Training (n = 411) and testing (n = 80) datasets from EC patients were retrospectively collected to investigate this problem. To determine the optimal CPH model from the training dataset, a bi-level model selection with minimax concave penalty was applied to select clinical and radiomic features which were obtained from T2-weighted MRI images. After the CPH model was built, model diagnostic was carried out to evaluate the proportional hazard assumption with Schoenfeld test. Survival data were fitted into a Weibull model and hazard ratio (HR) and ETR were calculated from the model. Brier score and time-dependent area under the receiver operating characteristic curve (AUC) were compared between CPH and Weibull models. Goodness of the fit was measured with Kolmogorov-Smirnov (KS) statistic. RESULTS: Although the proportional hazard assumption holds for fitting EC survival data, the linearity of the model assumption is suspicious as there are trends in the age and cancer grade predictors. The result also showed that there was a significant relation between the EC survival data and the Weibull distribution. Finally, it showed that Weibull model has a larger AUC value than CPH model in general, and it also has smaller Brier score value for EC survival prediction using both training and testing datasets, suggesting that it is more accurate to use the Weibull model for EC survival analysis. CONCLUSIONS: The Weibull parametric model for EC survival analysis allows simultaneous characterization of the treatment effect in terms of the hazard ratio and the event time ratio (ETR), which is likely to be better understood. This method can be extended to study progression free survival and disease specific survival. TRIAL REGISTRATION: ClinicalTrials.gov NCT03543215, https://clinicaltrials.gov/ , date of registration: 30th June 2017.
Subject(s)
Endometrial Neoplasms , Magnetic Resonance Imaging , Proportional Hazards Models , Humans , Female , Endometrial Neoplasms/mortality , Endometrial Neoplasms/diagnostic imaging , Middle Aged , Magnetic Resonance Imaging/methods , Retrospective Studies , Survival Analysis , Aged , ROC Curve , Adult , Models, Statistical , RadiomicsABSTRACT
Metabolic dysfunction is a hallmark of multiple amyotrophic lateral sclerosis (ALS) models with a majority of ALS patients exhibiting hypermetabolism. The central sites of metabolism in the cell are mitochondria, capable of utilising a multitude of cellular substrates in an array of ATP-generating reactions. With reactive oxygen species (ROS) production occurring during some of these reactions, mitochondria can contribute considerably to oxidative stress. Mitochondria are also very dynamic organelles, interacting with other organelles, undergoing fusion/fission in response to changing metabolic states and being turned over by the cell regularly. Disruptions to many of these mitochondrial functions and processes have been reported in ALS models, largely indicating compromised mitochondrial function, increased ROS production by mitochondria, disrupted interactions with the endoplasmic reticulum and reduced turnover. This chapter summarises methods routinely used to assess mitochondria in ALS models and the alterations that have been reported in these models.
Subject(s)
Amyotrophic Lateral Sclerosis , Mitochondria , Amyotrophic Lateral Sclerosis/metabolism , Amyotrophic Lateral Sclerosis/pathology , Humans , Mitochondria/metabolism , Animals , Reactive Oxygen Species/metabolism , Disease Models, Animal , Oxidative Stress/physiologyABSTRACT
BACKGROUND: Ovarian cancer is the most lethal and endometrial cancer the most common gynaecological cancer in the UK, yet neither have a screening program in place to facilitate early disease detection. The aim is to evaluate whether online search data can be used to differentiate between individuals with malignant and benign gynaecological diagnoses. METHODS: This is a prospective cohort study evaluating online search data in symptomatic individuals (Google user) referred from primary care (GP) with a suspected cancer to a London Hospital (UK) between December 2020 and June 2022. Informed written consent was obtained and online search data was extracted via Google takeout and anonymised. A health filter was applied to extract health-related terms for 24 months prior to GP referral. A predictive model (outcome: malignancy) was developed using (1) search queries (terms model) and (2) categorised search queries (categories model). Area under the ROC curve (AUC) was used to evaluate model performance. 844 women were approached, 652 were eligible to participate and 392 were recruited. Of those recruited, 108 did not complete enrollment, 12 withdrew and 37 were excluded as they did not track Google searches or had an empty search history, leaving a cohort of 235. RESULTS: The cohort had a median age of 53 years old (range 20-81) and a malignancy rate of 26.0%. There was a difference in online search data between those with a benign and malignant diagnosis, noted as early as 360 days in advance of GP referral, when search queries were used directly, but only 60 days in advance, when queries were divided into health categories. A model using online search data from patients (n = 153) who performed health-related search and corrected for sample size, achieved its highest sample-corrected AUC of 0.82, 60 days prior to GP referral. CONCLUSIONS: Online search data appears to be different between individuals with malignant and benign gynaecological conditions, with a signal observed in advance of GP referral date. Online search data needs to be evaluated in a larger dataset to determine its value as an early disease detection tool and whether its use leads to improved clinical outcomes.
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Genital Neoplasms, Female , Ovarian Neoplasms , Humans , Female , Young Adult , Adult , Middle Aged , Aged , Aged, 80 and over , Genital Neoplasms, Female/diagnosis , Prospective Studies , Early Detection of Cancer , London/epidemiologyABSTRACT
INTRODUCTION: The surgical consent process is a crucial discussion between patient and surgeon, which is predominantly documented utilizing hand-written forms. The exchange of individualized information allows the patient to make a truly informed decision. Digital consent (also known as electronic consent or e-consent) has been shown to improve accuracy of information provided without increasing the time taken to consent patients. We aimed to evaluate patient experience and effectiveness of digital consent in a gynecology department in a tertiary London Teaching Hospital. METHODS: A questionnaire was designed and completed by 100 patients undergoing gynecological surgery: 50 consented using paper and 50 consented digitally. The questionnaire included 8 statements, with five possible answers to select, ranging from strongly agree to strongly disagree, on a standard five-point Likert Scale. Patients were all female and categorized into age groups (deciles) and asked whether consent was taken digitally or on paper. Data were collected between January and July 2021. RESULTS: Most responses were positive with 87% (694/800) of responses to the questions being either strongly agree or agree. Patients who were consented using paper selected 'strongly agree' 43.5% (174/400) of the time in comparison to 64.8% (259/400) of the time when they were consented digitally. The majority, 86% (43/50), of digitally consented patients received a copy of the consent form in comparison to 18% (9/50) of those consented using paper. On average, the patients consented digitally were older than their paper-consented counterparts (49-58 and 59-68 respectively). The mean scores for the questions relating to the ease of reading the form, ease of understanding the form, understanding of the potential complications, and overall satisfaction were higher in those digitally consented (p < 0.05). DISCUSSION: Overall, patients were satisfied with both methods of consent. However, individuals who were consented digitally reported higher levels of satisfaction throughout the consent process, compared to paper consent. These data suggest that digital consent is an acceptable alternative to paper consent for patients and facilitates adherence to national consent guidance, which stipulates patients should be given the information they request.
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Gynecology , Humans , Female , Informed Consent , Surveys and Questionnaires , Hospitals, Teaching , Patient Outcome AssessmentABSTRACT
Female genital tract (FGT) microbiota has been associated with the development of gynaecological cancers. Thus, the possibility of whether manipulation of the FGT microbiota can help in the prevention of disease should be investigated. Various prebiotics, probiotics, and other non-clinician prescribed agents have been reported to have therapeutic effects in cervical disease. Numerous studies have reported an association between human papillomavirus infection and subsequent cervical dysplasia and a decrease in the abundance of Lactobacillus species. A continuum of microbiota composition is observed from the vagina to the upper parts of the FGT, but no evidence suggests that manipulation of the vaginal microbiota can help to modify the composition of other FGT compartments. Although prebiotics and probiotics have been reported to be beneficial, the studies are small and of varying design, and high-quality evidence to support their use is lacking. Currently, no studies have examined these therapeutics in other gynaecological malignancies. Thus, recommendation of probiotics, prebiotics, or other over-the-counter supplements for the prevention of gynaecological cancers warrants larger, well designed studies.
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Genital Neoplasms, Female , Microbiota , Probiotics , Female , Humans , Prebiotics , Genital Neoplasms, Female/prevention & control , Probiotics/therapeutic use , Genitalia, FemaleABSTRACT
Background: The COVID-19 pandemic has disproportionally affected traditionally marginalized groups. Both the Delta and Omicron variants raised concern amongst public health officials due to potentially higher infectivity rates and disease severity than prior variants. This study sought to compare disease severity between adults infected with the Omicron variant and adults infected with the Delta variant who presented to the Emergency Department at an academic, safety-net hospital in Virginia. Methods: This retrospective cohort study used electronic medical record data of patients who presented to the Emergency Department and received a positive SARS-CoV-2 test between September 1, 2021, and January 31, 2022. Positive tests were stratified by genotypic variant through whole genome sequencing. Participants with the Omicron variant were propensity scores matched with individuals with the Delta variant. Results: Among 500 Delta and 500 Omicron participants, 279 propensity score-matched pairs were identified. Participants were predominantly unvaccinated, with medical comorbidities, and self-identified as Black. Individuals infected with the Delta variant had more severe disease compared to those with the Omicron variant, regardless of vaccination status. Patients with kidney, liver, and respiratory disease, as well as cancer, are at higher risk for severe disease. Patients with 2 doses of COVID-19 immunization trended toward less severe disease. Conclusions: Overall, these data further support the literature regarding the disproportionate effects of the COVID-19 pandemic on vulnerable patient populations - such as those with limited access to care, people of color, and those with chronic medical conditions - and can be used to inform public health interventions.
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BACKGROUND: Persistent infection by oncogenic human papillomavirus (HPV) is necessary although not sufficient for development of cervical cancer. Behavioural, environmental, or comorbid exposures may promote or protect against malignant transformation. Randomised evidence is limited and the validity of observational studies describing these associations remains unclear. METHODS: In this umbrella review, we searched electronic databases to identify meta-analyses of observational studies that evaluated risk or protective factors and the incidence of HPV infection, cervical intra-epithelial neoplasia (CIN), cervical cancer incidence and mortality. Following re-analysis, evidence was classified and graded based on a pre-defined set of statistical criteria. Quality was assessed with AMSTAR-2. For all associations graded as weak evidence or above, with available genetic instruments, we also performed Mendelian randomisation to examine the potential causal effect of modifiable exposures with risk of cervical cancer. The protocol for this study was registered on PROSPERO (CRD42020189995). RESULTS: We included 171 meta-analyses of different exposure contrasts from 50 studies. Systemic immunosuppression including HIV infection (RR = 2.20 (95% CI = 1.89-2.54)) and immunosuppressive medications for inflammatory bowel disease (RR = 1.33 (95% CI = 1.27-1.39)), as well as an altered vaginal microbiome (RR = 1.59 (95% CI = 1.40-1.81)), were supported by strong and highly suggestive evidence for an association with HPV persistence, CIN or cervical cancer. Smoking, number of sexual partners and young age at first pregnancy were supported by highly suggestive evidence and confirmed by Mendelian randomisation. CONCLUSIONS: Our main analysis supported the association of systemic (HIV infection, immunosuppressive medications) and local immunosuppression (altered vaginal microbiota) with increased risk for worse HPV and cervical disease outcomes. Mendelian randomisation confirmed the link for genetically predicted lifetime smoking index, and young age at first pregnancy with cervical cancer, highlighting also that observational evidence can hide different inherent biases. This evidence strengthens the need for more frequent HPV screening in people with immunosuppression, further investigation of the vaginal microbiome and access to sexual health services.
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HIV Infections , Papillomavirus Infections , Uterine Cervical Dysplasia , Uterine Cervical Neoplasms , Female , Humans , Pregnancy , Follow-Up Studies , HIV Infections/complications , Human Papillomavirus Viruses , Papillomavirus Infections/complications , Papillomavirus Infections/epidemiology , Papillomavirus Infections/genetics , Risk Factors , Uterine Cervical Dysplasia/diagnosis , Uterine Cervical Dysplasia/epidemiology , Uterine Cervical Dysplasia/pathology , Uterine Cervical Neoplasms/diagnosis , Mendelian Randomization AnalysisABSTRACT
A number of reproductive outcomes have been increasingly found to be affected by the vaginal microbiota. Obesity has become a global epidemic, affecting increasing numbers of reproductive-age women, and has been shown to be a risk factor for a number of adverse female health outcomes. A healthy vaginal microbiome is characterized by Lactobacillus-dominance, in particular Lactobacillus crispatus; obesity has been found to be associated with higher diversity and a lower likelihood of Lactobacillus-dominance. In this review, we summarize the evidence on the vaginal microbiome in obese women and the impact on reproductive outcomes such as conception rates, early pregnancy, and preterm birth. We further explore the mechanisms by which obesity may result in an altered microbial composition and highlight future avenues for therapeutic targeting of the vaginal microbiota.
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Microbiota , Premature Birth , Pregnancy , Female , Infant, Newborn , Humans , Reproduction , Vagina , ObesityABSTRACT
INTRODUCTION: Human papillomavirus (HPV) is necessary but not sufficient for cervical cancer development. During cervical carcinogenesis, methylation levels increase across host and HPV DNA. DNA methylation has been proposed as a test to diagnose cervical intraepithelial neoplasia (CIN); we present a protocol to evaluate the accuracy of methylation markers to detect high-grade CIN and cervical cancer. METHODS AND ANALYSIS: We will search electronic databases (Medline, Embase and Cochrane Library), from inception, to identify studies examining DNA methylation as a diagnostic marker for CIN or cervical cancer, in a cervical screening population. The primary outcome will be to assess the diagnostic test accuracy of host and HPV DNA methylation for high-grade CIN; the secondary outcomes will be to examine the accuracy of different methylation cut-off thresholds, and accuracy in high-risk HPV positive women. Our reference standard will be histology. We will perform meta-analyses using Cochrane guidelines for diagnostic test accuracy. We will use the number of true positives, false negatives, true negatives and false positives from individual studies. We will use the bivariate mixed effect model to estimate sensitivity and specificity with 95% CIs; we will employ different bivariate models to estimate sensitivity and specificity at different thresholds if sufficient data per threshold. For insufficient data, the hierarchical summary receiver operating curve model will be used to calculate a summary curve across thresholds. If there is interstudy and intrastudy variation in thresholds, we will use a linear mixed effects model to calculate the optimum threshold. If few studies are available, we will simplify models by assuming no correlation between sensitivity and specificity and perform univariate, random-effects meta-analysis. We will assess the quality of studies using QUADAS-2 and QUADAS-C. ETHICS AND DISSEMINATION: Ethical approval is not required. Results will be disseminated to academic beneficiaries, medical practitioners, patients and the public. PROSPERO REGISTRATION NUMBER: CRD42022299760.
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Papillomavirus Infections , Uterine Cervical Dysplasia , Uterine Cervical Neoplasms , Humans , Female , Uterine Cervical Neoplasms/prevention & control , Early Detection of Cancer/methods , DNA Methylation , Papillomavirus Infections/epidemiology , Systematic Reviews as Topic , Meta-Analysis as Topic , Uterine Cervical Dysplasia/diagnosis , Sensitivity and Specificity , DNA , Diagnostic Tests, RoutineABSTRACT
The importance of the cladoceran Daphnia as a model organism for ecotoxicity testing has been well-established since the 1980s. Daphnia have been increasingly used in standardised testing of chemicals as they are well characterised and show sensitivity to pollutants, making them an essential indicator species for environmental stress. The mapping of the genomes of D. pulex in 2012 and D. magna in 2017 further consolidated their utility for ecotoxicity testing, including demonstrating the responsiveness of the Daphnia genome to environmental stressors. The short lifecycle and parthenogenetic reproduction make Daphnia useful for assessment of developmental toxicity and adaption to stress. The emergence of nanomaterials (NMs) and their safety assessment has introduced some challenges to the use of standard toxicity tests which were developed for soluble chemicals. NMs have enormous reactive surface areas resulting in dynamic interactions with dissolved organic carbon, proteins and other biomolecules in their surroundings leading to a myriad of physical, chemical, biological, and macromolecular transformations of the NMs and thus changes in their bioavailability to, and impacts on, daphnids. However, NM safety assessments are also driving innovations in our approaches to toxicity testing, for both chemicals and other emerging contaminants such as microplastics (MPs). These advances include establishing more realistic environmental exposures via medium composition tuning including pre-conditioning by the organisms to provide relevant biomolecules as background, development of microfluidics approaches to mimic environmental flow conditions typical in streams, utilisation of field daphnids cultured in the lab to assess adaption and impacts of pre-exposure to pollution gradients, and of course development of mechanistic insights to connect the first encounter with NMs or MPs to an adverse outcome, via the key events in an adverse outcome pathway. Insights into these developments are presented below to inspire further advances and utilisation of these important organisms as part of an overall environmental risk assessment of NMs and MPs impacts, including in mixture exposure scenarios.
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PURPOSE: To predict deep myometrial infiltration (DMI), clinical risk category, histological type, and lymphovascular space invasion (LVSI) in women with endometrial cancer using machine learning classification methods based on clinical and image signatures from T2-weighted MR images. METHODS: A training dataset containing 413 patients and an independent testing dataset consisting of 82 cases were employed in this retrospective study. Manual segmentation of the whole tumor volume on sagittal T2-weighted MRI was performed. Clinical and radiomic features were extracted to predict: (i) DMI of endometrial cancer patients, (ii) endometrial cancer clinical high-risk level, (iii) histological subtype of tumor, and (iv) presence of LVSI. A classification model with different automatically selected hyperparameter values was created. The area under the curve (AUC) of the receiver operating characteristic (ROC) curve, F1 score, average recall, and average precision were calculated to evaluate different models. RESULTS: Based on the independent external testing dataset, the AUCs for DMI, high-risk endometrial cancer, endometrial histological type, and LVSI classification were 0.79, 0.82, 0.91, and 0.85, respectively. The corresponding 95% confidence intervals (CI) of the AUCs were [0.69, 0.89], [0.75, 0.91], [0.83, 0.97], and [0.77, 0.93], respectively. CONCLUSION: It is possible to classify endometrial cancer DMI, risk, histology type, and LVSI using different machine learning methods.
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Primary malignant melanoma (MM) of the cervix uteri is a rare and aggressive malignancy of the female reproductive tract. Considering that clinical data on this cancer are scarce, we aimed to comprehensively examine the currently available literature and provide an overview of the reported cases of cervical MM focusing on the clinical characteristics, diagnosis and therapeutic management. We conducted a systematic review of the literature by screening three electronic databases until June 2022. The critical appraisal checklist provided by the Joanna Briggs Institute was employed to evaluate the overall quality of the studies. We included 96 reports, which comprised 137 patients diagnosed with MM of the cervix. The mean age of the patients was 56.5 (median: 58, age range: 33-88). Data regarding menopausal status were provided for 98 patients with 15 being premenopausal and 83 being postmenopausal. The most common presenting symptom was vaginal bleeding (83%, 100/121). Biopsy (either excisional or punch biopsy) was used as the first diagnostic modality in most of the patients (67%, 64/95), followed by cytology (18%, 17/95). In 74 cases, the FIGO staging system for cervical cancer was used with the most common stage being FIGO stage I (38%, 28/74), followed by FIGO stage II (36%, 27/74), FIGO stage III (19%, 14/74) and FIGO stage IV (7%, 5/74). Most of the patients were managed surgically (90%, 119/131) with a hysterectomy (either radical or total), and a salpingo-oophorectomy with/without lymphadenectomy was the most common approach utilized (40%, 48/119). The data of clinical outcomes were provided for 105 patients, of whom 61 died (58%, 61/105) and 44 survived (42%, 44/105). Knowledge regarding the rare occurrence of MM in the cervix and the increased awareness of clinicians can prevent clinical misdiagnosis and ultimately improve further the clinical outcomes of patients developing this rare malignancy.
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OBJECTIVES: Perinatal opioid use disorder is increasing. Integrated obstetric/addiction care models likely optimize parent-infant dyad outcomes, but the ideal combination of services is unknown. This study (1) describes pregnancy-to-postpartum service utilization by people receiving buprenorphine at an integrated Obstetric/Addiction Clinic and (2) explores the association between service utilization and postpartum buprenorphine continuation. METHODS: This retrospective medical record review study uses research registry data from an outpatient Obstetric/Addiction Clinic. All patients are invited to participate in the research registry. For patients who consent, monthly medical record abstractions are conducted beginning with their first clinic visit to collect demographic, obstetric, and substance use disorder treatment variables. Present analyses included patients who delivered an infant between June 2019 and June 2021, started buprenorphine during pregnancy, and were receiving buprenorphine at delivery. Overall service utilization was the number of services (range 0-12) used between 28-weeks gestation and 12-weeks postpartum. Bivariate analyses and multivariable logistic regression assessed associations between service utilization and buprenorphine continuation. RESULTS: Participants (n = 42) were primarily non-Latinx White (67%) with comorbid psychiatric diagnoses (95%). On average, participants used 6 services; prenatal care, mental health care, and postpartum contraception were most utilized. Overall, 69% of participants continued buprenorphine at 6 months postpartum. This did not differ by level of service utilization (bivariate [ P = 0.07], multivariable [ P = 0.16]). CONCLUSION: Integrated care with a harm reduction focus supports pregnancy-to-postpartum service utilization and buprenorphine continuation in a patient sample at high risk for medication for opioid use disorder discontinuation. Further work is needed to identify evidence-based methods to individualize integrated obstetric/addiction care.
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Buprenorphine , Delivery of Health Care, Integrated , Opioid-Related Disorders , Pregnancy , Female , Humans , Analgesics, Opioid/therapeutic use , Retrospective Studies , Opioid-Related Disorders/drug therapy , Opioid-Related Disorders/epidemiology , Buprenorphine/therapeutic use , Postpartum PeriodABSTRACT
BACKGROUND: Determination of survival time in women with endometrial cancer using clinical features remains imprecise. Features from MRI may improve the survival estimation allowing improved treatment planning. PURPOSE: To identify clinical features and imaging signatures on T2-weighted MRI that can be used in an integrated model to estimate survival time for endometrial cancer subjects. STUDY TYPE: Retrospective. POPULATION: Four hundred thirteen patients with endometrial cancer as training (N = 330, 66.41 ± 11.42 years) and validation (N = 83, 67.60 ± 11.89 years) data and an independent set of 82 subjects as testing data (63.26 ± 12.38 years). FIELD STRENGTH/SEQUENCE: 1.5-T and 3-T scanners with sagittal T2-weighted spin echo sequence. ASSESSMENT: Tumor regions were manually segmented on T2-weighted images. Features were extracted from segmented masks, and clinical variables including age, cancer histologic grade and risk score were included in a Cox proportional hazards (CPH) model. A group least absolute shrinkage and selection operator method was implemented to determine the model from the training and validation datasets. STATISTICAL TESTS: A likelihood-ratio test and decision curve analysis were applied to compare the models. Concordance index (CI) and area under the receiver operating characteristic curves (AUCs) were calculated to assess the model. RESULTS: Three radiomic features (two image intensity and volume features) and two clinical variables (age and cancer grade) were selected as predictors in the integrated model. The CI was 0.797 for the clinical model (includes clinical variables only) and 0.818 for the integrated model using training and validation datasets, the associated mean AUC value was 0.805 and 0.853. Using the testing dataset, the CI was 0.792 and 0.882, significantly different and the mean AUC was 0.624 and 0.727 for the clinical model and integrated model, respectively. DATA CONCLUSION: The proposed CPH model with radiomic signatures may serve as a tool to improve estimated survival time in women with endometrial cancer. EVIDENCE LEVEL: 4 TECHNICAL EFFICACY: Stage 2.
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Endometrial Neoplasms , Humans , Female , Retrospective Studies , Endometrial Neoplasms/diagnostic imaging , Magnetic Resonance Imaging , Area Under Curve , ROC CurveABSTRACT
Human papillomavirus (HPV) is detected in 99.7% of cervical cancers. Current vaccines target types 16 and 18. Prior to vaccination implementation, a prospective cohort study was conducted to determine baseline HPV prevalence in unvaccinated women in Wales; after HPV16 and HPV18, HPV 51 was found to be most prevalent. This study aimed to re-assess the unexpected high prevalence of HPV 51 and consider its potential for type-replacement. Two hundred HPV 51 positive samples underwent re-analysis by repeating the original methodology using HPV 51 GP5+/6+ PCR-enzyme immunoassay, and additionally a novel assay of HPV 51 E7 PCR. Data were correlated with age, social deprivation and cytology. Direct repeat of HPV 51 PCR-EIA identified 146/195 (75.0%) samples as HPV 51 positive; E7 PCR identified 166/195 (85.1%) samples as HPV 51 positive. HPV 51 prevalence increased with cytological grade. The prevalence of HPV 51 in the pre-vaccinated population was truly high. E7 DNA assays may offer increased specificity for HPV genotyping. Cross-protection of current vaccines against less-prevalent HPV types warrants further study. This study highlights the need for longitudinal investigation into the prevalence of non-vaccine HPV types, especially those phylogenetically different to vaccine types for potential type-replacement. Ongoing surveillance will inform future vaccines.
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Anosmia, loss of smell, is a prevalent symptom of SARS-CoV-2 infection. Anosmia may be explained by several mechanisms driven by infection of non-neuronal cells and damage in the nasal epithelium rather than direct infection of olfactory sensory neurons (OSNs). Previously, we showed that viral proteins are sufficient to cause neuroimmune responses in the teleost olfactory organ (OO). We hypothesize that SARS-CoV-2 spike (S) protein is sufficient to cause olfactory damage and olfactory dysfunction. Using an adult zebrafish model, we report that intranasally delivered SARS-CoV-2 S RBD mostly binds to the non-sensory epithelium of the olfactory organ and causes severe olfactory histopathology characterized by loss of cilia, hemorrhages and edema. Electrophysiological recordings reveal impaired olfactory function to both food and bile odorants in animals treated intranasally with SARS-CoV-2 S RBD. However, no loss of behavioral preference for food was detected in SARS-CoV-2 S RBD treated fish. Single cell RNA-Seq of the adult zebrafish olfactory organ indicated widespread loss of olfactory receptor expression and inflammatory responses in sustentacular, endothelial, and myeloid cell clusters along with reduced numbers of Tregs. Combined, our results demonstrate that intranasal SARS-CoV-2 S RBD is sufficient to cause structural and functional damage to the zebrafish olfactory system. These findings may have implications for intranasally delivered vaccines against SARS-CoV-2.
Subject(s)
COVID-19 , Spike Glycoprotein, Coronavirus , Animals , Anosmia , COVID-19 Vaccines , Humans , Inflammation/metabolism , Olfactory Mucosa/metabolism , SARS-CoV-2 , Spike Glycoprotein, Coronavirus/metabolism , ZebrafishABSTRACT
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