ObjectivesTo explore the clinical value of subendometrial enhancement (SEE), irregular thin-layered peritumoral early enhancement (ITLPE) and focal irregular peritumoral early enhancement (FIPE) on dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) for myometrial invasion in patients with low-risk endometrial carcinoma.MethodsSeventy-seven patients with low-risk endometrial carcinoma who preoperatively underwent DCE-MRI were included. Two radiologists independently evaluated and recorded the occurrences of SEE, ITLPE and FIPE on DCE-MRI in all patients. Interobserver agreement was calculated between the two radiologists, and the relationships between SEE, ITLPE, FIPE, and myometrial invasion were analyzed based on histologic findings. For statistically significant findings, the sensitivity and specificity were calculated, and the differences in myometrial invasion evaluations were analyzed. For those with no statistical significance, images were compared with the histopathologic sections.ResultsInter-observer agreement was good (k = 0.80; 95%CI, 0.577–0.955) for SEE, and very good (k = 0.88; 95%CI, 0.761–0.972) (k = 0.86; 95%CI, 0.739–0.973) for ITLPE and FIPE. After consensus, SEE was identified in 12/77 (15.6%) patients; ITLPE and FIPE were found in 53/77 (68.8%) and 30/77 (39.0%) patients, respectively. SEE and ITLPE were significantly correlated with myometrial infiltration (P = 0.000), but FIPE were not (P = 0.725).The sensitivity and specificity of SEE and ITLPE for myometrial invasion in patients with low-risk endometrial carcinoma were 95.0 and 52.9%, and 85.0 and 88.0%, respectively. The area under the curve (AUC) of SEE and ITLPE for myometrial invasion were 0.740 (95%CI, 0.584–0.896), and 0.866 (95%CI, 0.763–0.970), respectively. The sensitivity and specificity were statistically different between SEE and ITLPE for the detection of myometrial invasion (P = 0.031, 0.016). According to the comparison between FIPE and histopathologic findings, the irregular endomyometrial junction was found in 30/77 (38.9%) cases, 24/30 (80.0%) with myometrial infiltration and 6/30 (20.0%) cases without myometrial infiltration.ConclusionsFIPE was the irregular endomyometrial junction. It can be found in patients with or without myometrial infiltration and may lead to the overestimation of myometrial invasion by SEE on DCE-MRI. ITLPE presented high diagnostic performance and specificity for myometrial invasion in patients with low-risk endometrial carcinoma.
PurposeThe portfolio of low-risk stocks outperforms the portfolio of high-risk stocks and market portfolios on a risk-adjusted basis. This phenomenon is called the low-risk effect. There are several economic and behavioral explanations for the existence and persistence of such an effect. However, it is still unclear whether specific sector orientation drives the low-risk effect. The study seeks to answer the following important questions in Indian equity markets: (a) Whether sector bets or stock bets mainly drive the low-risk effect? (b) Is it a mere proxy for the well-known value effect? (c) Does the low-risk effect prevail in long-only portfolios?Design/methodology/approachThe study is based on all the listed stocks on the National Stock Exchange (NSE) of India from December 1994 to September 2018. It classifies them into 11 Global Industry Classification Standard (GICS) sectors to construct stock-level and sector-level BAB (Betting Against Beta) and long-only low-risk portfolios. It follows the study of Asness et al. (2014) to construct various BAB portfolios. It applies Fama–French (FF) three-factor and Fama–French–Carhart (FFC) four-factor asset pricing models in addition to Capital Asset Pricing Model (CAPM) to examine the strength of BAB, sector-level BAB, stock-level BAB and long-only low-beta portfolios.FindingsBoth sector- and stock-level bets contribute to the return of the low-risk investing strategy, but the stock-level effect is dominant. Only betting on safe sectors or industries will not earn economically significant alpha. The low-risk effect is unique and not a value effect in disguise. Both long-short and long-only portfolios within sectors and industry groups deliver positive excess returns. Consumer staples, financial, materials and healthcare sectors mainly contribute to the returns of the low-risk effect in India. This study offers empirical evidence against the Samuelson (1998) micro-efficient market given the strong performance of the stock-level low-risk effect.Practical implicationsThe superior performance of the low-risk investment strategies at both stock and sector levels offers investors an opportunity to strategically invest in stocks from the right sectors and earn high risk-adjusted returns with lower drawdowns over an entire market cycle. Besides, it paves the way for stock exchanges and index manufacturers to launch sector-specific low-volatility indices for relevant sectors. Passive funds can launch index funds and exchange-traded funds by tracking these indices. Active fund managers can espouse sector-specific low-risk investment strategies based on the results of this and similar other studies.Originality/valueThe study is the first of its kind. It offers insights into the portfolio characteristics and performance of the long-short and the long-only variant of low-risk portfolios within sectors and industry groups. It decomposes the low-risk effect into sector-level and stock-level effects.
Acute myeloid leukemia (AML) is a clonal malignant proliferative blood disorder with a poor prognosis. Ferroptosis, a novel form of programmed cell death, holds great promise for oncology treatment, and has been demonstrated to interfere with the development of various diseases. A range of genes are involved in regulating ferroptosis and can serve as markers of it. Nevertheless, the prognostic significance of these genes in AML remains poorly understood. Transcriptomic and clinical data for AML patients were acquired from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO). Univariate Cox analysis was performed to identify ferroptosis-related genes with prognostic value, and the least absolute shrinkage and selection operator (LASSO) algorithm and stepwise multivariate Cox regression analysis were utilized to optimize gene selection from the TCGA cohort (132 samples) for model construction. Tumor samples from the GEO database (136 samples and 104 samples) were used as validation groups to estimate the predictive performance of the risk model. Finally, an eight-gene prognostic signature (including CHAC1, CISD1, DPP4, GPX4, AIFM2, SQLE, PGD, and ACSF2) was identified for the prediction of survival probability and was used to stratify AML patients into high- and low-risk groups. Survival analysis illustrated significantly prolonged overall survival and lower mortality in the low-risk group. The area under the receiver operating characteristic curve demonstrated good results for the training set (1-year: 0.846, 2-years: 0.826, and 3-years: 0.837), which verified the accuracy of the model for predicting patient survival. Independent prognostic analysis indicated that the model could be used as a prognostic factor (p ≤ 0.001). Functional enrichment analyses revealed underlying mechanisms and notable differences in the immune status of the two risk groups. In brief, we conducted and validated a novel ferroptosis-related prognostic model for outcome prediction and risk stratification in AML, with great potential to guide individualized treatment strategies in the future.
ObjectiveCalcium supplementation can prevent gestational hypertension and pre-eclampsia. However, besides the non-consensus of existing studies, there is a lack of evidence regarding the optimal dosing of calcium.MethodEight electronic databases, namely, the Cochrane Library, PUBMED, Web of Science, EMBASE, WANGFANG, VIP, CBM, and CNKI, were searched. The studies were retrieved from inception to July 13, 2021. Two researchers independently screened the literature, extracted data, and evaluated the methodological quality based on the inclusion criteria. In particular, the calcium supplementation doses were divided into three groups, namely, the high-dose (≥1.5 g), medium-dose (1.0–1.49 g), and the low-dose group (<1.0 g). The participants were also divided into high-risk and low-risk groups, according to the risk of developing gestational hypertension and pre-eclampsia.Results and DiscussionA total of 48 studies were incorporated into the final analyses. All doses of calcium supplementation reduced the incidence of gestational hypertension in the low-risk population (low dose - three studies; medium dose- 11 studies; high dose- 28 studies), whereas the medium-dose (three studies) reduced the incidence of gestational hypertension in high-risk groups. Moreover, a medium dose of calcium supplementation had the maximum effect in reducing gestational hypertension in low-risk and high-risk populations. The medium (three studies) and high doses (13 studies) of calcium supplementation reduced the incidence of pre-eclampsia in the low-risk groups. However, a medium-dose calcium supplementation maximally prevented pre-eclampsia in the low-risk population. The authenticity and reliability of the results were reduced due to the limitations of contemporary studies in terms of experimental design, result measurement, statistics, and evidence quality. Therefore, high-quality studies with larger sample size are required to evaluate further the effect of calcium supplementation in preventing gestational hypertension and pre-eclampsia.
Background and Objectives: Preterm infants are at higher risk of neurodevelopmental impairment both at preschool and school ages, even in the absence of major neurological deficits. The early identification of children at risk is essential for early intervention with rehabilitation to optimize potential outcomes during school years. The aim of our study is to assess cognitive outcomes at preschool age in a cohort of low-risk very preterm infants, previously studied at 12 and 24 months using the Griffiths scales. Materials and Methods: Sixty-six low-risk very preterm infants born at a gestational age of <32 weeks were assessed at 12 and 24 months corrected age using the Griffiths Mental Development Scales (second edition) and at preschool age with the Wechsler Preschool and Primary Scales of Intelligence (third edition) (WPPSI-III). Results: At 12 and 24 months and at preschool age, low-risk very preterm infants showed scores within normal ranges with similar scores in males and females. A statistically significant correlation was observed in the general developmental quotient between 12 and 24 months; a further significant correlation was observed between the early cognitive assessments and those performed at preschool age, with a better correlation using the assessments at 24 months. Conclusion: The present study showed a favourable trajectory of cognitive development in low-risk very preterm infants, from 12 months to preschool age.
Cervical cancer is caused by infection with high-risk human papillomaviruses (HR-HPVs). It is one of the leading causes of cancer-related deaths in Ethiopia and globally. To develop efficient vaccination and HPV-based cervical cancer screening approaches, data on genotype distribution of HPVs is crucial. Hence, the study was aimed to review HPV genotype distribution in Ethiopia.
Research articles were systematically searched using comprehensive search strings from PubMed/Medline and SCOPUS. Besides, Google Scholar was searched manually for grey literature. The last search was conducted on 18 August 2021. The first two authors independently appraised the studies for scientific quality and extracted the data using Excel sheet. The pooled HPV genotype distribution was presented with descriptive statistics.
We have included ten studies that were reported from different parts of the country during 2005 and 2019. These studies included 3633 women presented with different kinds of cervical abnormalities, from whom 29 different HPV genotypes with a sum of 1926 sequences were reported. The proportion of high-risk, possible/probable high-risk and low-risk HPVs were at 1493 (77.5%), 182 (9.4%) and 195 (10.1%), respectively. Of the reported genotypes, the top five were HPV 16 (37.3%; 95% CI 35.2.1–39.5%), HPV 52 (6.8%; 95% CI 5.8–8.0%), HPV 35 (4.8%; 95% CI 3.9–5.8%), HPV 18 (4.4%; 95% CI 3.5–5.3%) and HPV 56 (3.9%: 95% CI 3.1–4.9%). Some of other HR-HPV groups include HPV 31 (3.8%), HPV 45 (3.5%), HPV 58 (3.1%), HPV 59(2.3%), and HPV 68 (2.3%). Among the high-risk types, the combined prevalence of HPV 16/18 was at 53.7% (95% CI 51.2–56.3%). HPV 11 (2.7%: 95% CI 2.1–3.5%), HPV 42 (2.1%: 95% CI 1.5–2.8%) and HPV 6 (2.1%: 95% CI 1.4–2.7%) were the most common low-risk HPV types.
We noted that the proportion of HR-HPV types was higher and HPV 16 in particular, but also HPV 52, HPV 35 and HPV 18, warrant special attention in Ethiopian’s vaccination and HPV based cervical screening program. Additional data from other parts of the country where there is no previous HPV genotype report are needed to better map the national HPV genotypes distribution of Ethiopia.
Long noncoding RNAs (lncRNAs) are important regulators of gene expression and can affect a variety of physiological processes. Recent studies have shown that immune-related lncRNAs play an important role in the tumour immune microenvironment and may have potential application value in the treatment and prognosis prediction of tumour patients. Epithelial ovarian cancer (EOC) is characterized by a high incidence and poor prognosis. However, there are few studies on immune-related lncRNAs in EOC. In this study, we focused on immune-related lncRNAs associated with survival in EOC.
We downloaded mRNA data for EOC patients from The Cancer Genome Atlas (TCGA) database and mRNA data for normal ovarian tissue from the Genotype-Tissue Expression (GTEx) database and identified differentially expressed genes through differential expression analysis. Immune-related lncRNAs were obtained through intersection and coexpression analysis of differential genes and immune-related genes from the Immunology Database and Analysis Portal (ImmPort). Samples in the TCGA EOC cohort were randomly divided into a training set, validation set and combination set. In the training set, Cox regression analysis and LASSO regression were performed to construct an immune-related lncRNA signature. Kaplan–Meier survival analysis, time-dependent ROC curve analysis, Cox regression analysis and principal component analysis were performed for verification in the training set, validation set and combination set. Further studies of pathways and immune cell infiltration were conducted through Gene Set Enrichment Analysis (GSEA) and the Timer data portal.
An immune-related lncRNA signature was identified in EOC, which was composed of six immune-related lncRNAs (KRT7-AS, USP30-AS1, AC011445.1, AP005205.2, DNM3OS and AC027348.1). The signature was used to divide patients into high-risk and low-risk groups. The overall survival of the high-risk group was lower than that of the low-risk group and was verified to be robust in both the validation set and the combination set. The signature was confirmed to be an independent prognostic biomarker. Principal component analysis showed the different distribution patterns of high-risk and low-risk groups. This signature may be related to immune cell infiltration (mainly macrophages) and differential expression of immune checkpoint-related molecules (PD-1, PDL1, etc.).
We identified and established a prognostic signature of immune-related lncRNAs in EOC, which will be of great value in predicting the prognosis of clinical patients and may provide a new perspective for immunological research and individualized treatment in EOC.
BackgroundsEpithelial–mesenchymal transition (EMT) is a sequential process where tumor cells develop from the epithelial state to the mesenchymal state. EMT contributes to various tumor functions including initiation, propagating potential, and resistance to therapy, thus affecting the survival time of patients. The aim of this research is to set up an EMT-related prognostic signature for endometrial cancer (EC).MethodsEMT-related gene (ERG) expression and clinical data were acquired from The Cancer Genome Atlas (TCGA). The entire set was randomly divided into two sets, one for contributing the risk model (risk score) and the other for validating. Univariate and multivariate Cox proportional hazards regression analyses were applied to the training set to select the prognostic ERGs. The expression of 10 ERGs was confirmed by qRT-PCR in clinical samples. Then, we developed a nomogram predicting 1-/3-/5-year survival possibility combining the risk score and clinical factors. The entire set was stratified into the high- and low-risk groups, which was used to analyze the immune infiltrating, tumorigenesis pathways, and response to drugs.ResultsA total of 220 genes were screened out from 1,316 ERGs for their differential expression in tumor versus normal. Next, 10 genes were found to be associated with overall survival (OS) in EC, and the expression was validated by qRT-PCR using clinical samples, so we constructed a 10-ERG-based risk score to distinguish high-/low-risk patients and a nomogram to predict survival rate. The calibration plots proved the predictive value of our model. Gene Set Enrichment Analysis (GSEA) discovered that in the low-risk group, immune-related pathways were enriched; in the high-risk group, tumorigenesis pathways were enriched. The low-risk group showed more immune activities, higher tumor mutational burden (TMB), and higher CTAL4/PD1 expression, which was in line with a better response to immune checkpoint inhibitors. Nevertheless, response to chemotherapeutic drugs turned out better in the high-risk group. The high-risk group had higher N6-methyladenosine (m6A) RNA expression, microsatellite instability level, and stemness indices.ConclusionWe constructed the ERG-related signature model to predict the prognosis of EC patients. What is more, it might offer a reference for predicting individualized response to immune checkpoint inhibitors and chemotherapeutic drugs.