Search

Several previous studies in the field of assisted reproduction have focused on the use of blood gel derivatives, such as platelet-rich fibrin (PRF), as a treatment for endometrial rehabilitation. However, the ability to release growth factors and the gel form of this product led to the evolution of platelet lysates. In this study, blood gel derivatives, including PRF lysate, which was in liquid form, and PRF gel, were collected and evaluated for growth factors. It was shown to be effective in endometrial wound healing and regeneration in mouse injured uterine tissue models through structure and function (pinopode expression, embryo implantation) evaluation. The results demonstrated that the concentrations of growth factors, including PDGF-AB and VEGF-A, were higher in the PRF lysate compared to the PRF gel (p < 0.05). PRF lysate could release these growth factors for 8 days. Furthermore, both PRF gel and PRF lysate restored the morphology of injured endometrial tissues in terms of luminal and glandular epithelia, as well as uterine gland secretory activity. However, the presence of pinopodes and embryonic implantation were only observed in the PRF lysate group. It can be concluded that PRF lysate promotes wound healing in mouse injured tissue models in vitro, which can act as healing products in tissue repair. [ABSTRACT FROM AUTHOR]

Vietnam is a country that experiences extreme climate conditions and annual accumulated damage due to typhoons and floods, which seriously destroy houses and cause many deaths. Approximately half a million people currently living within 200 m from the coastline live in unsafe houses. Therefore, the Coastal Resilience Project (the project) was implemented to build 4000 storm- and flood-resistant houses for five coastal provinces in Central Vietnam. The paper is carried out to review existing policies and practices related to the maintenance of resilient houses, as well as to propose feasible maintenance solutions for houses to ensure the sustainability of the project. The result shows that currently, there are no technical instructions or manuals on the maintenance and repair of individual houses in general, or the project houses in particular. Most of the households in the project also have very low and unstable incomes. In addition, as they lack knowledge of how construction works, they know little to nothing about the maintenance of a house. From these findings, the authors recommend several solutions for better maintenance policies and practices on the resilient houses of the project in Vietnam. The project provides several lessons in terms of the maintenance of the resilient houses of future projects in Vietnam and elsewhere, by reviewing existing policies and current practices, as well as proposing feasible measures to ensure the sustainability of the project. The findings in this paper provide valuable information for better maintenance policies and practices of resilient houses for other vulnerable coastal provinces in Vietnam and similar contexts elsewhere. [ABSTRACT FROM AUTHOR]

At the end of the year 2021, all 4000 resilient houses that are under the project "Improving the resilience of vulnerable coastal communities to climate change-related impacts in Vietnam" were completed. However, the project sponsor and implementor need to be aware of the level of satisfaction of the stakeholders of these resilient houses, especially for local beneficiaries. This study is carried out to answer several practical questions such as what are the strengths and weaknesses of the project house designs, focusing on the basic needs of beneficiaries. Or, are the beneficiaries satisfied with the house constructed with support from the project, and what are their suggestions to improve either the relevant procedures and processes or future houses to be built by the project or other stakeholders. The findings show several aspects of design and construction of resilient houses such as utilization effectiveness, satisfaction of beneficiaries, and participation of local communities. However, several practical limitations of this phase have been identified, namely, the approved designs do not fully reflect the needs of beneficiaries, the designs lack some essential and basic functionalities, some technical shortcomings exist in design drawings, and support funding is limited. On the basis of that, the authors recommended several valuable measures for effective and sustainable designing and constructing resilient houses. [ABSTRACT FROM AUTHOR]

Publicly available gene expression datasets were analyzed to develop a chromophobe and oncocytoma related gene signature (COGS) to distinguish chRCC from RO. The datasets GSE11151, GSE19982, GSE2109, GSE8271 and GSE11024 were combined into a discovery dataset. The transcriptomic differences were identified with unsupervised learning in the discovery dataset (97.8% accuracy) with density based UMAP (DBU). The top 30 genes were identified by univariate gene expression analysis and ROC analysis, to create a gene signature called COGS. COGS, combined with DBU, was able to differentiate chRCC from RO in the discovery dataset with an accuracy of 97.8%. The classification accuracy of COGS was validated in an independent meta-dataset consisting of TCGA-KICH and GSE12090, where COGS could differentiate chRCC from RO with 100% accuracy. The differentially expressed genes were involved in carbohydrate metabolism, transcriptomic regulation by TP53, beta-catenin-dependent Wnt signaling, and cytokine (IL-4 and IL-13) signaling highly active in cancer cells. Using multiple datasets and machine learning, we constructed and validated COGS as a tool that can differentiate chRCC from RO and complement histology in routine clinical practice to distinguish these two tumors. [ABSTRACT FROM AUTHOR]

Simple Summary: Molecular classification of cancers has the potential to automate and decrease errors in cancer classification. We previously showed that transcriptomic classification is comparable to methylomic and mutation methods for glioma classification and may provide benefit in predicting survival prognosis. Here we validate the transcriptomic classification method on a single molecule counting gene expression platform using formalin-fixed paraffin embedded samples. Gene expression profiling has been shown to be comparable to other molecular methods for glioma classification. We sought to validate a gene-expression based glioma classification method. Formalin-fixed paraffin embedded tissue and flash frozen tissue collected at the Augusta University (AU) Pathology Department between 2000–2019 were identified and 2 mm cores were taken. The RNA was extracted from these cores after deparaffinization and bead homogenization. One hundred sixty-eight genes were evaluated in the RNA samples on the nCounter instrument. Forty-eight gliomas were classified using a supervised learning algorithm trained by using data from The Cancer Genome Atlas. An ensemble of 1000 linear support vector models classified 30 glioma samples into TP1 with classification confidence of 0.99. Glioma patients in TP1 group have a poorer survival (HR (95% CI) = 4.5 (1.3–15.4), p = 0.005) with median survival time of 12.1 months, compared to non-TP1 groups. Network analysis revealed that cell cycle genes play an important role in distinguishing TP1 from non-TP1 cases and that these genes may play an important role in glioma survival. This could be a good clinical pipeline for molecular classification of gliomas. [ABSTRACT FROM AUTHOR]

Simple Summary: Cervical cancer is the most common gynecological cancer caused by persistent infections with human papilloma viruses. Over time, this infection leads to secretion of inflammatory proteins in the cervix, which exacerbates the neoplastic and senescent changes to the cervical epithelial lining. We measured nineteen serum proteins in retrospectively collected samples from cervical cancer patients. We show here that 10 out of 19 proteins are associated with senescence phenotype in cervical cancer patients. This senescence associated protein signature influences how cervical cancer patients responds to therapy. Molecular biomarkers that can predict survival and therapeutic outcome are still lacking for cervical cancer. Here we measured a panel of 19 serum proteins in sera from 565 patients with stage II or III cervical cancer and identified 10 proteins that have an impact on disease specific survival (DSS) (Hazzard's ratio; HR = 1.51–2.1). Surprisingly, all ten proteins are implicated in senescence-associated secreted phenotype (SASP), a hallmark of cellular senescence. Machine learning using Ridge regression of these SASP proteins can robustly stratify patients with high SASP, which is associated with poor survival, and patients with low SASP associated with good survival (HR = 3.09–4.52). Furthermore, brachytherapy, an effective therapy for cervical cancer, greatly improves survival in SASP-high patients (HR = 3.3, p < 5 × 10−5) but has little impact on survival of SASP-low patients (HR = 1.5, p = 0.31). These results demonstrate that cellular senescence is a major determining factor for survival and therapeutic response in cervical cancer and suggest that senescence reduction therapy may be an efficacious strategy to improve the therapeutic outcome of cervical cancer. [ABSTRACT FROM AUTHOR]