Introduction: Merkel cell carcinoma (MCC) is a rare, aggressive cutaneous neuroendocrine cancer that typically arises in sun-exposed areas of the skin, especially in the elderly. Significant advances have recently been made regarding skin cancers, but data on cases of MCC are rather limited as these patients are frequently grouped together with other non-melanoma skin cancers (NMSC). Here, we performed an analysis of the clinical profile of patients with MCC in Poland to identify major factors influencing the prognosis.
Methods: Approximately 13,000 pathology and medical records were examined to identify patients with MCC diagnosed between 2010 and 2019. The management and outcomes of patients with histologically confirmed MCC were retrospectively evaluated.
Results: Thirty-one patients diagnosed with MCC were identified. The tumor occurred predominantly in women (61.3%) and in the elderly (mean 75.6 years). Twenty-nine patients had locoregional MCC and two had metastatic MCC at the time of diagnosis. Patients in stage I disease had excellent prognosis. In stages II and III, respectively 22.2% and 50.0% of patients developed metastases. Among patients who received chemotherapy with cisplatin and etoposide, 17% achieved partial remission with progression-free survival (PFS) of 8.0 months, and a further 50% achieved stable disease with PFS of 4.0, 4.5, and 4.5 months respectively. In 6 (19.4%) patients MCC coexisted with chronic lymphocytic leukemia (CLL). In all six cases CLL preceded MCC development.
Conclusions: Female gender, tumor-free resection margins, and local disease were found to be independent prognostic factors in MCC progression. Patients with hematological malignancies, immunosuppression, and those with immune deficiencies should be closely followed up as they are predisposed to develop MCC.
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http://dx.doi.org/10.1007/s13555-020-00424-5 | DOI Listing |
Sci Rep
January 2025
Drug Theoretics and Cheminformatics Laboratory, Department of Pharmaceutical Technology, Jadavpur University, Kolkata, 700 032, India.
We have adopted the classification Read-Across Structure-Activity Relationship (c-RASAR) approach in the present study for machine-learning (ML)-based model development from a recently reported curated dataset of nephrotoxicity potential of orally active drugs. We initially developed ML models using nine different algorithms separately on topological descriptors (referred to as simply "descriptors" in the subsequent sections of the manuscript) and MACCS fingerprints (referred to as "fingerprints" in the subsequent sections of the manuscript), thus generating 18 different ML QSAR models. Using the chemical spaces defined by the modeling descriptors and fingerprints, the similarity and error-based RASAR descriptors were computed, and the most discriminating RASAR descriptors were used to develop another set of 18 different ML c-RASAR models.
View Article and Find Full Text PDFInt J Biol Macromol
January 2025
Chemical and Petroleum Engineering Department, College of Engineering, United Arab Emirates University, PO Box 15551, Al Ain, United Arab Emirates. Electronic address:
In this study, the role of a transition metal complex in improving hydrolysis efficiency during nanocellulose production was analysed. Cellulose nanocrystals (CNCs) were extracted from date seeds by incorporating a copper metal complex during HCl hydrolysis. In contrast to traditional HCl hydrolysis at moderate conditions, which yielded only microcrystalline cellulose (MCC), this approach resulted in the extraction of CNCs with a 10 % improved yield compared to MCC.
View Article and Find Full Text PDFInt J Biol Macromol
January 2025
Jiangsu Co-Innovation Center of Efficient Processing and Utilization of Forest, Resources, College of Chemical Engineering, Nanjing Forestry University, Nanjing 210037, PR China. Electronic address:
This study investigates the mixing effects on the enzymatic hydrolysis of microcrystalline cellulose (MCC) and dilute-acid pretreated corncob substrates under high-solid conditions. Enzymatic hydrolysis experiments were conducted to assess cellulose conversion rates under varying mixing conditions (0, 50, 150, and 250 rpm) and solids loadings (5 %, 15 %, 25 %, and 35 %, w/v), and distinct physicochemical properties of the substrates were characterized. Additionally, the role of mixing conditions and solid loadings on cellulose hydrolysis kinetics and enzyme adsorption on both substrates and lignin were elucidated.
View Article and Find Full Text PDFJ Chromatogr A
December 2024
Downstream Processing, Bioprocessing Technology Institute (BTI), Agency for Science, Technology and Research (A*STAR), 20 Biopolis Way, Centros #06-01 138668, Singapore. Electronic address:
Given the complexities of continuous bioprocessing, it is critical to thoroughly investigate the process parameters unique to multi-column chromatography (MCC) and their potential impacts. However, existing studies have focused on either loading densities or residence time at steady states only, and their combined impact on critical quality attributes (CQAs) especially during transient phases were less known. In this study, we investigated the impact of critical process parameters during both steady-state and transient phases (start-up, close-down, and intermediate perturbation) through full factorial design.
View Article and Find Full Text PDFComput Biol Med
January 2025
LMA Laboratory, University of Bejaia, Bejaia 06000, Algeria. Electronic address:
Social networks are increasingly taking over daily life, creating a volume of unsecured data and making it very difficult to capture safe data, especially in times of crisis. This study aims to use a Convolutional Neural Network (CNN)-Long Short-Term Memory (LSTM)-based hybrid model for health monitoring and health crisis forecasting. It consists of efficiently retrieving safe content from multiple social media sources.
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