Utility investigation of automated techniques in hematopoietic progenitor cell count and viability assessment in the Good Manufacturing Practice (GMP) settingg

Aim: To compare our parameters as regards: i) cell count via two different automated cell count techniques, and ii) viability via automated trypan blue exclusion and 7-aminoactinomycin D (7-AAD) staining. Method: We used the trypan blue exclusion technique and an automated cell counter and for viability testing, and the trypan blue exclusion technique and the 7-AAD evaluation by flow cytometry. The trypan blue exclusion and the radio frequency techniques were used for automated cell counting. Flow cytometric analysis was performed by evaluating the yielded cellular products for 7-AAD uptake during the cell count of CD34+ cells. Results: The mean values for cell count were estimated as 3.44±1.22x106/ml (range, 2.48-5.71x106/ml) and 4.14±1.94x106/ml (range, 1.77-7.43x106/ml) for the trypan blue exclusion and radio frequency techniques, respectively. Additionally, the mean values for viability analyses via the automated trypan blue exclusion and 7-AAD were 93.38±6.09% (range, 79.00-98.00%) and 99.49±0.60% (range, 98.40-100.00%), respectively. Conclusions: Our study has responded to two fundamental questions: whether the results of both of the automated techniques for cell count correspond with each other, and whether the results of the automated viability assessment conform those of the 7-AAD technique during the manufacturing processes of cellular therapy products intended for clinical use. Even though we have the opportunity to use the hemocytometer in our laboratory setting, the automated trypan blue exclusion technique gives cell count results in concordance within the range of the expectations of our Quality Management System (QMS)

Classification of brain hemorrhage computed tomography images using OzNet hybrid algorithm

Classification of brain hemorrhage computed tomography (CT) images provides a better diagnostic implementation for emergency patients. Attentively, each brain CT image must be examined by doctors. This situation is time-consuming, exhausting, and sometimes leads to making errors. Hence, we aim to find the best algorithm owing to a requirement for automatic classification of CT images to detect brain hemorrhage. In this study, we developed OzNet hybrid algorithm, which is a novel convolution neural networks (CNN) algorithm. Although OzNet achieves high classification performance, we combine it with Neighborhood Component Analysis (NCA) and many classifiers: Artificial neural networks (ANN), Adaboost, Bagging, Decision Tree, K-Nearest Neighbor (K-NN), Linear Discriminant Analysis (LDA), Naive Bayes and Support Vector Machines (SVM). In addition, Oznet is utilized for feature extraction, where 4096 features are extracted from the fully connected layer. These features are reduced to have significant and informative features with minimum loss by NCA. Eventually, we use these classifiers to classify these significant features. Finally, experimental results display that OzNet-NCA-ANN excellent classifier model and achieves 100% accuracy with created Dataset 2 from Brain Hemorrhage CT images

From RNA isolation to microarray analysis: Comparison of methods in FFPE tissues

Background: Genome-wide gene expression profiling analysis of FFPE tissue samples is indispensable for cancer research and provides the opportunity to evaluate links between molecular and clinical information, however, working with FFPE samples is challenging due to extensive cross-linking, fragmentation and limited quantities of nucleic acid. Thus, processing of FFPE tissue samples from RNA extraction to microarray analysis still needs optimization

Clinical and pathological characteristics of gastrointestinal stromal tumor (GIST) metastatic to bone

Our aim in this study was to describe the clinical, morphological, and molecular profile of gastrointestinal stromal tumor (GIST) metastatic to bone. We analyzed the morphological, phenotypic, and molecular characteristics of seven cases, and in addition reviewed 17 cases from literature. Sequence analysis of KIT and PDGFRA genes was possible for six cases. For the GIST cases with bone metastasis, the most common primaries were small intestine (29%), stomach (25%), and rectum (21%). Sites of bone metastases were vertebrae (11), pelvis (8), femur (8), ribs (6), humerus (5), skull (3), scapula (1), and mandible (1). The size ranged from 1.5 to 13 cm (median, 3.8 cm). Bone metastases without involvement of any other organ were seen in 17% of the cases and were solitary in 14 (58%). Adjacent soft tissue involvement was present in nearly half of the patients. Bone metastasis was either manifest at the time of diagnosis (28%) or occurred after a mean period of 4.7 years (3 months-20 years). Morphologically, neoplastic cells were spindle in 67%, epithelioid in 13%, and mixed epithelioid and spindle in 20%. CD117, DOG1, and CD34 were positive in 88, 86, and 85% of the cases, respectively. KIT Exon 11 mutations were the most frequent gene alteration (78%), followed by KIT Exon 13 mutations. Of 17 of the cases with available follow-up information, 7 (41%) patients developed bone metastasis under imatinib therapy. Five patients (29%) died of disease within a mean of 17 months. Bone metastases from GIST are usually found in patients with advanced disease and typically present as lytic masses with occasional soft tissue involvement. We could not identify any KIT or PDGFRA alterations predisposing to bone metastasis

Serum procalcitonin and C-reactive protein kinetics as indicators of treatment outcome in hospitalized patients with community-acquired pneumonia

WOS: 000389053000023PubMed ID: 27966308Background/aim: There has been growing interest in the use of serum procalcitonin (PCT) and C-reactive protein (CRP) in patients with community-acquired pneumonia (CAP). The aim of this study was to investigate whether an assessment of fever, leukocyte count, and serum CRP and PCT levels on admission and during follow-up (day 3) provides any information about the clinical outcome in hospitalized patients with CAP. Materials and methods: Patients with a diagnosis of CAP who were admitted to and followed at four university hospitals were evaluated retrospectively using the Turkish Thoracic Society Pneumonia Database. Results: A total of 103 hospitalized CAP patients (57 males, mean age: 61.5 +/- 16.7 years) were enrolled in the study. Treatment failure (TF) was observed in 20 patients (19.4%). Pneumonia Severity Index scores, serum CRP levels, and PCT levels on admission were significantly higher in the TF group. There were significant decreases in CRP and PCT levels between admission day and day 3 in the treatment success group. Conclusion: In patients with CAP, the body temperature and leukocyte count on admission do not predict outcome. Monitoring levels of CRP and PCT may be useful as a predictor of treatment outcome

Factors affecting treatment success in community acquired pneumonia (CAP)

WOS: 00020937040245

Antibiotic treatment outcomes in community-acquired pneumonia

WOS: 000441766000006PubMed ID: 30119147Background/aim: The optimal empiric antibiotic regimen for patients with community-acquired pneumonia (CAP) remains unclear. This study aimed to evaluate the clinical cure rate, mortality, and length of stay among patients hospitalized with community-acquired pneumonia in nonintensive care unit (ICU) wards and treated with a beta-lactam, beta-lactam and macrolide combination, or a fluoroquinolone. Materials and methods: This prospective cohort study was perfbrined using standardized web-based database sheets from January 2009 to September 2013 in nine tertiary care hospitals in Turkey. Results: Six hundred and twenty-one consecutive patients were enrolled. A pathogen was identified in 78 (12.6%) patients. The most frequently isolated bacteria were S. pneumoniae (21.8%) and P. aeruginosa (19.2%). The clinical cure rate and length of stay were not different among patients treated with beta-lactam, beta-lactam and macrolide combination, and fluoroquinolone. Forty-seven patients (9.2%) died during the hospitalization period. There was no difference in survival among the three treatment groups. Conclusion: In patients admitted to non-ICU hospital wards for CAP, there was no difference in clinical outcomes between beta-lactam, beta-lactam and macrolide combination, and fluoroquinolone regimens.Turk Toraks DernegiThis study was supported by a grant from the Turk Toraks Dernegi. We thank the TURCAP Study Group (Kokturk N, Filiz A, Edis EC, Uzaslan E, Yalcinsoy M, Gunduz C, Dikensoy O, Cetinkaya C, Durmaz F) for their valuable contributions

Nine-week trastuzumab treatment versus 52-week trastuzumab treatment for HER2-positive early-stage breast cancer

Purposes Trastuzumab is known to be effective for early and advanced stages of breast cancer but optimal duration for early-stage breast cancer (EBC) is not well known. We evaluated the efficacy and toxicity of 9- and 52-week trastuzumab therapy for EBC retrospectively

Prognostic Factors for Recurrence-Free Survival in Patients with HER2-Positive Early-Stage Breast Cancer Treated with Adjuvant Trastuzumab

Background: The objective of this study was to identify prognostic factors affecting the recurrence-free survival (RFS) in patients who received a 52-week trastuzumab therapy for HER2-positive early stage breast cancer (EBC). Patients and Methods: The medical records of all patients with EBC from 10 centers were analyzed. Pathologic and clinical tumor characteristics were evaluated in 424 female patients who received 52 weeks of adjuvant trastuzumab for HER2-positive EBC. Survival was estimated using the Kaplan-Meier method. Univariate analyses of RFS were performed with the log-rank test. Independent prognostic and predictive factors affecting RFS were assessed by Cox regression analysis. Results: Median follow-up time was 33.1 months (range 9.2-75.9 months). 3-year RFS and overall survival were 87 and 97%, respectively. In multivariate analysis, patients aged 70 years or over (p = 0.017, relative risk (RR) 2.7, 95% confidence interval (CI) 1.19-6.13), patients with > 9 positive lymph nodes (p = 0.001, RR 2.52, 95% CI 1.42-4.46), and those with progesterone receptor-negative tumors (p = 0.006, RR 2.33, 95% CI 1.27-4.27) had worse RFS. Conclusion: In spite of a 52-week adjuvant trastuzumab treatment, classic poor prognostic factors for invasive EBC remained as such in patients with HER2-positive EBC

Risk factors for brain metastasis as a first site of disease recurrence in patients with HER2 positive early stage breast cancer treated with adjuvant trastuzumab

Purpose: The aim of this study was to determine risk factors for brain metastasis as the first site of disease recurrence in patients with HER2-positive early-stage breast cancer (EBC) who received adjuvant trastuzumab