Bramsenhusted9072

Lineage plasticity and histologic transformation to small cell neuroendocrine prostate cancer (NEPC) is an increasingly recognized mechanism of treatment resistance in advanced prostate cancer. This is associated with aggressive clinical features and poor prognosis. Recent work has identified genomic, epigenomic, and transcriptome changes that distinguish NEPC from prostate adenocarcinoma, pointing to new mechanisms and therapeutic targets. Treatment-related NEPC arises clonally from prostate adenocarcinoma during the course of disease progression, retaining early genomic events and acquiring new molecular features that lead to tumor proliferation independent of androgen receptor activity, and ultimately demonstrating a lineage switch from a luminal prostate cancer phenotype to a small cell neuroendocrine carcinoma. Identifying the subset of prostate tumors most vulnerable to lineage plasticity and developing strategies for earlier detection and intervention for patients with NEPC may ultimately improve prognosis. Clinical trials focused on drug targeting of the lineage plasticity process and/or NEPC will require careful patient selection. Here, we review emerging targets and discuss biomarker considerations that may be informative for the design of future clinical studies.In this study, faecal samples of four American Staffordshire terrier dogs (used for illegal fighting) were analysed by DNA extraction, molecular-phylogenetic and parasitological methods, in order to examine the occurrence of protozoan, apicomplexan parasites. In one sample, the DNA of Sarcocystis morae was shown to be present. This species was identified based on 100% identity with already reported sequences of S. morae from cervids in Lithuania and Spain. The result was also confirmed by phylogenetic analysis. The sporocysts of the canine S. morae isolate measured 14.95 × 9.75 μm on average. This is the first molecular evidence in support of the final host role of domestic dogs in the life cycle of S. morae. The most likely source of the infection was raw meat given to the examined dog to increase its physical achievement. In conclusion, under similar circumstances dogs may participate in the life cycle of S. morae in a 'natural way', shedding sporocysts/oocysts when used for hunting or taken to walks in forested areas.Mast cell tumour (MCT) is the most frequent skin neoplasm in dogs. These tumours are characterised by variable behaviour and clinical presentation that make prognosis an important and challenging task in the veterinary practice. Galectin-3 (Gal-3) is known to influence several biological processes that are important in the cancer context and has been described as a prognostic marker for several human cancers. The aim of the present work was to characterise Gal-3 immunolabelling in canine cutaneous MCTs and to investigate its value as a prognostic marker for the disease. Thirty-four random cases of canine cutaneous MCT that were surgically treated with wide margins were included in this study. Gal-3 expression was evaluated using immunohistochemistry and the results were compared with the expression of apoptosis-related proteins, Ki67 index, histopathological grades, mortality due to the disease and post-surgical survival. The majority of the MCTs (65.8%) were positive for Gal-3. Gal-3 immunolabelling was variable among the samples (2.7%-86.8% of the neoplastic cells). The protein was located in the cytoplasm or in the cytoplasm and the nucleus. Gal-3 positivity was correlated with BCL2 expression (P less then 0.001; r = 0.604), but not with Ki67 and BAX. No significant differences were detected between histological grades or in the survival analysis. Gal-3 expression correlates with BCL2 expression in MCTs. Although an efficient marker for several human neoplasms, the results presented herein suggest that Gal-3 immunolabelling is not an independent prognostic indicator for this disease.[This corrects the article DOI 10.2196/25507.].[This corrects the article DOI 10.2196/24260.].

With increasing type 2 diabetes prevalence, there is a need for effective programs that support diabetes management and improve type 2 diabetes outcomes. Mobile health (mHealth) interventions have shown promising results. With advances in wearable sensors and improved integration, mHealth programs could become more accessible and personalized.

The study aimed to evaluate the feasibility, acceptability, and effectiveness of a personalized mHealth-anchored intervention program in improving glycemic control and enhancing care experience in diabetes management. The program was coincidentally implemented during the national-level lockdown for COVID-19 in Singapore, allowing for a timely study of the use of mHealth for chronic disease management.

Patients with type 2 diabetes or prediabetes were enrolled from the Singapore Armed Forces and offered a 3-month intervention program in addition to the usual care they received. The program was standardized to include (1) in-person initial consultation with a clinic2 diabetes. Such mHealth programs could overcome challenges posed to chronic disease management by COVID-19, including disruptions to in-person health care access.

The personalized mHealth program was feasible, acceptable, and produced significant reductions in HbA1c (P=.004) and body weight (P less then .001) in individuals with type 2 diabetes. Such mHealth programs could overcome challenges posed to chronic disease management by COVID-19, including disruptions to in-person health care access.MicroRNAs (miRNAs) have been proved to play critical roles in diverse biological processes, including the human disease development process. Exploring the potential associations between miRNAs and diseases can help us better understand complex disease mechanisms. Given that traditional biological experiments are expensive and time-consuming, computational models can serve as efficient means to uncover potential miRNA-disease associations. This study presents a new computational model based on variational graph auto-encoder with matrix factorization (VGAMF) for miRNA-disease association prediction. More specifically, VGAMF first integrates four different types of information about miRNAs into an miRNA comprehensive similarity network and two types of information about diseases into a disease comprehensive similarity network, respectively. Then, VGAMF gets the non-linear representations of miRNAs and diseases, respectively, from those two comprehensive similarity networks with variational graph auto-encoders. PF-04620110 Simultaneously, a non-negative matrix factorization is conducted on the miRNA-disease association matrix to get the linear representations of miRNAs and diseases.