The current coronavirus disease 2019 (COVID-19) pandemic is a challenge for physicians in triaging patients in emergency rooms. We found a potentially dangerous overlap of classical urinary symptoms and the as yet not fully described symptoms of COVID-19. After a patient was primarily triaged as a urosepsis case and then subsequently diagnosed with COVID-19, we focused on an increase in urinary frequency as a symptom of COVID-19 and identified this in seven males out of 57 patients currently being treated in our COVID-19 wards. In the absence of any other causes, urinary frequency may be secondary to viral cystitis due to underlying COVID-19 disease. We propose consideration of urinary frequency as an anamnestic tool in patients with infective symptoms to increase awareness among urologists during the current COVID-19 pandemic to prevent fatal implications of misinterpreting urological symptoms.
(1) Background: Biomarkers might play a significant role in predicting the clinical outcomes of patients with ovarian cancer. By analyzing lipid metabolism genes, future perspectives may be uncovered; (2) Methods: RNA-seq data for serous ovarian cancer were downloaded from The Cancer Genome Atlas and Gene Expression Omnibus databases. The non-negative matrix factorization package in programming language R was used to classify molecular subtypes of lipid metabolism genes and the limma package in R was performed for functional enrichment analysis. Through lasso regression, we constructed a multi-gene prognosis model; (3) Results: Two molecular subtypes were obtained and an 11-gene signature was constructed (PI3, RGS, ADORA3, CH25H, CCDC80, PTGER3, MATK, KLRB1, CCL19, CXCL9 and CXCL10). Our prognostic model shows a good independent prognostic ability in ovarian cancer. In a nomogram, the predictive efficiency was notably superior to that of traditional clinical features. Related to known models in ovarian cancer with a comparable amount of genes, ours has the highest concordance index; (4) Conclusions: We propose an 11-gene signature prognosis prediction model based on lipid metabolism genes in serous ovarian cancer.
The chemokine CCL22 recruits regulatory T (T-reg) cells into tumor tissues and is expressed in many human tumors. However, the prognostic role of CCL22 in cervical cancer (CC) has not been determined. This study retrospectively analyzed the clinical significance of the expression of CCL22 and FOXP3 in 230 cervical cancer patients. Immunohistochemical staining analyses of CCL22 and FOXP3 were performed with a tissue microarray. Double immunofluorescence staining, cell coculture, and ELISA were used to determine CCL22 expressing cells and mechanisms. The higher number of infiltrating CCL22+ cells (CCL22 high ) group was associated with lymph node metastasis (p = 0.004), Fédération Internationale de Gynécologie et d'Obstétrique (FIGO) stages (p = 0.010), therapeutic strategies (p = 0.007), and survival status (p = 0.002). The number of infiltrating CCL22+ cells was positively correlated with that of infiltrating FOXP3+ cells (r = 0.210, p = 0.001). The CCL22 high group had a lower overall survival rate (OS), compared to the CCL22 low group (p = 0.001). However, no significant differences in progression free survival (PFS) were noted between the two groups. CCL22 high was an independent predictor of shorter OS (HR, 4.985; p = 0.0001). The OS of the combination group CCL22 high FOXP3 high was significantly lower than that of the combination group CCL22 low FOXP3 low regardless of the FIGO stage and disease subtype. CCL22 high FOXP3 high was an independent indictor of shorter OS (HR, 5.284; p = 0.009). The PFS of group CCL22 high FOXP3 high was significantly lower than that of group CCL22 low FOXP3 low in cervical adenocarcinoma, but CCL22 high FOXP3 high was not an independent indicator (HR, 3.018; p = 0.068). CCL22 was primarily expressed in M2-like macrophages in CC and induced by cervical cancer cells. The findings of our study indicate that cervical cancer patients with elevated CCL22+ infiltrating cells require more aggressive treatment. Moreover, the results provide a basis for subsequent, comprehensive studies to advance the design of immunotherapy for cervical cancer.
Background Preliminary empirical data indicates a substantial impact of the COVID-19 pandemic on well-being and mental health. Individuals with minoritized sexual and gender identities are at a higher risk of experiencing such negative changes in their well-being. The objective of this study was to compare levels of well-being among cis-heterosexual individuals and individuals with minoritized sexual and gender identities during the COVID-19 pandemic. Methods Using data obtained in a cross-sectional online survey between April 20 to July 20, 2020 (N = 2332), we compared levels of well-being (WHO-5) across subgroups (cis-individuals with minoritized sexual identities, individuals with minoritized gender identities and cis-heterosexual individuals) applying univariate (two-sample t-test) and multivariate analysis (multivariate linear regression). Results Results indicate overall lower levels of well-being as well as lower levels of well-being in minoritized sexual or gender identities compared to cis-heterosexual individuals. Further, multivariate analyses revealed that living in urban communities as well as being in a relationship were positively associated with higher levels of well-being. Furthermore, a moderation analysis showed that being in a relationship reduces the difference between groups in terms of well-being. Conclusion Access to mental healthcare for individuals with minoritized sexual and gender identities as well as access to gender-affirming resources should be strengthened during COVID-19 pandemic. Healthcare services with low barriers of access such as telehealth and online peer support groups should be made available, especially for vulnerable groups.
The aim of this study was to assess the prognostic value of the steroid hormone receptor expression, counting the retinoid X receptor (RXR) and thyroid hormone receptors (THRs), on the two different breast cancer (BC) entities: multifocal/multicentric versus unifocal. The overall and disease-free survival were considered as the prognosis determining aspects and analyzed by uni- and multi-variate analysis. Furthermore, histopathological grading and TNM staging (T = tumor size, N = lymph node involvement, M = distant metastasis) were examined in relation to RXR and THRs expression. A retrospective statistical analysis was carried out on survival-related events in a series of 319 sporadic BC patients treated at the Department of Gynecology and Obstetrics at the Ludwig-Maximillian’s University in Munich between 2000 and 2002. The expression of RXR and THRs, including its two major isoforms THRα1 and THRα2, was analyzed by immunohistochemistry and showed to have a significant correlation for both BC entities in regard to survival analysis. Patients with multifocal/multicentric BC were exposed to a significantly worse disease-free survival (DFS) when expressing RXR. Patients with unifocal BC showed a significantly worse DFS when expressing THRα1. In contrast, a statistically significant positive association between THRα2 expression and enhanced DFS in multifocal/multicentric BC was shown. Especially the RXR expression in multifocal/multicentric BC was found to play a remarkably contradictory role for BC prognosis. The findings imply the need for a critical review of possible molecular therapies targeting steroid hormone receptors in BC treatment. Our results strengthen the need to further investigate the behavior of the nuclear receptor family, especially in relation to BC focality.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.