Glioma-associated mesenchymal stem cells have profound effects on brain tumors

GBMs have proven to be a major pathology with vast infiltration potential and extreme chemo- and radio-resistance leading to devastating outcomes. The GBMs, however, are not only detrimental on the host alone but also they interact with the microenvironment to manifest some of their pathological hallmarks. Within the tumor microenvironment, MSCs have gained a strong attention in the recent years. The role of MSCs within the brain tumor niche has been partially explained including pro- and anti-tumorigenic effects. It was, however, a controversial issue as to what makes MSCs pro- or anti-tumorigenic. Moreover, the contribution of MSCs in the brain tumor histopathology was not yet fully uncovered. Here I investigated the role of MSCs in the brain tumor pathology and the signaling mechanisms. It was shown earlier in our lab that MSCs act as anti-tumorigenic in the presence of serum and anti-tumorigenic in serum-free conditions. Which condition is more relevant to the pathological situation was an open question. When I co-inoculated MSCs with GBMs, they homed the tumor satellites, where they are probably not in contact with blood-borne factors. Therefore, I concluded that serum-free conditions are more relevant to in vivo pathological situation. MSCs promoted viability of many primary GSC lines under serum-free conditions. The induction of survival and proliferation was mediated by the increase in the levels of QKIs in GBMs upon exposure to MSC-derived soluble factors. In turn, QKIs increase the levels of EGFR causing an overresponse to growth factors. Moreover, increased QKI-levels in GBMs mediate the chemoresistance against TMZ. In addition to soluble factors, MSCs signal via exosomes. Those exosomes carry EFNA3 mRNA from MSCs to GBMs. EFNA3 expression in turn induces cellular migration. The inhibition of EFNA3 transfer via genetically engineered antibodies against exosome docking sites on the recipient GBM cells or against EFNA3 (if it is translated and integrated on the surface) as well as EGFR-blockade might prove useful for future therapeutic approaches against GBMs. There are no well-established mouse models to study the interaction between MSCs and GBMs at the tumor satellite. Therefore, I sought to establish such a model by expressing HSV-TK in GBMs and inducing cell death via GCV administration either by osmotic pumps or via systemic injection and established a model where one can study tumor satellites. Additionally, I established a model to study the mRNA transfer from MSCs to GBMs. For this, I expressed Cre-recombinase in MSCs, and flipped- and floxed-GFP in GBMs. The Cre-recombinase mRNA is packed into exosomes and delivered to GBMs, labelling GBMs with GFP for the rest of their lives. This enables us to demonstrate the transfer of mRNA as well as to track individual GBM cells, contacted by the MSCs, in terms of their migratory behaviors in vivo. All in all, I uncovered a previously unknown action of MSCs in GBM pathology defining two targetable systems (EGFR and EFNA3) and established two models to study in vivo interaction of MSCs with GBMs

1D-local binary pattern based feature extraction forclassification of epileptic EEG signals

In this paper, an effective approach for the feature extraction of raw Electroencephalogram (EEG) signals by means of one-dimensional local binary pattern (1D-LBP) was presented. For the importance of making the right decision, the proposed method was performed to be able to get better features of the EEG signals. The proposed method was consisted of two stages: feature extraction by 1D-LBP and classification by classifier algorithms with features extracted. On the classification stage, the several machine learning methods were employed to uniform and non-uniform 1D-LBP features. The proposed method was also compared with other existing techniques in the literature to find out benchmark for an epileptic data set. The implementation results showed that the proposed technique could acquire high accuracy in classification of epileptic EEG signals. Also, the present paper is an attempt to develop a general-purpose feature extraction scheme, which can be utilized to extract features from different categories of EEG signals

Crepis foetida L. subsp rhoeadifolia (Bleb.) Celak. as a source of multifunctional agents: Cytotoxic and phytochemical evaluation

The cytotoxic, anticholinesterase, antityrosinase and antioxidant effects of methanol extract from the flower of C. foetida subsp. rhoeadifolia (CFRME) were evaluated. The cytotoxic effect was investigated using HepG2, Caco-2, MCF-7 and MCF-10A cell lines. Enzyme inhibitory activities were tested by spectrophotometric methods. Different chemical assays were used to determine the antioxidant effects. In addition, phenolic constituents were quantified. High-performance liquid chromatographic (HPLC) analysis revealed that chlorogenic acid was the major phenolic component in the extract. The extract showed a strong antiproliferative, antioxidant, and anticholinesterase and antityrosinase effects. These findings suggest that C. foetida subsp. rhoeadifolia may be considered as a source of ingredients that can be used as food supplements. (C) 2015 Elsevier Ltd. All rights reserved

Comparing Tumor Cell Invasion and Myeloid Cell Composition in Compatible Primary and Relapsing Glioblastoma

Glioblastoma (GBM) recurrence after treatment is almost inevitable but addressing this issue with adequate preclinical models has remained challenging. Here, we introduce a GBM mouse model allowing non-invasive and scalable de-bulking of a tumor mass located deeply in the brain, which can be combined with conventional therapeutic approaches. Strong reduction of the GBM volume is achieved after pharmacologically inducing a tumor-specific cell death mechanism. This is followed by GBM re-growth over a predictable timeframe. Pharmacological de-bulking followed by tumor relapse was accomplished with an orthotopic mouse glioma model. Relapsing experimental tumors recapitulated pathological features often observed in recurrent human GBM, like increased invasiveness or altered immune cell composition. Orthotopic implantation of GBM cells originating from biopsies of one patient at initial or follow-up treatment reproduced these findings. Interestingly, relapsing GBM of both models contained a much higher ratio of monocyte-derived macrophages (MDM) versus microglia than primary GBM. This was not altered when combining pharmacological de-bulking with invasive surgery. We interpret that factors released from viable primary GBM cells preferentially attract microglia whereas relapsing tumors preponderantly release chemoattractants for MDM. All in all, this relapse model has the capacity to provide novel insights into clinically highly relevant aspects of GBM treatment

COVID-19 in Kidney Transplant Recipients: A Multicenter Experience from the First Two Waves of Pandemic

Background Kidney transplant recipients have an increased risk of complications from COVID-19. However, data on the risk of allograft damage or death in kidney transplant recipients recovering from COVID-19 is limited. In addition, the first and second waves of the pandemic occurred at different times all over the world. In Turkey, the Health Minister confirmed the first case in March 2020; after that, the first wave occurred between March and August 2020; afterward, the second wave began in September 2020. This study aims to demonstrate the clinical presentations of kidney transplant recipients in the first two waves of the pandemic in Turkey and explore the impact of COVID-19 on clinical outcomes after the initial episode. Methods Patients with COVID-19 from seven centers were included in this retrospective cohort study. Initially, four hundred and eighty-eight kidney transplant recipients diagnosed with COVID-19 between 1 March 2020 to 28 February 2021 were enrolled. The endpoints were the occurrence of all-cause mortality, acute kidney injury, cytokine storm, and acute respiratory distress syndrome. In addition, longer-term outcomes such as mortality, need for dialysis, and allograft function of the surviving patients was analyzed. Results Four hundred seventy-five patients were followed up for a median of 132 days after COVID-19. Forty-seven patients (9.9%) died after a median length of hospitalization of 15 days. Although the mortality rate (10.1% vs. 9.8%) and intensive care unit admission (14.5% vs. 14.5%) were similar in the first two waves, hospitalization (68.8% vs. 29.7%; p < 0.001), acute kidney injury (44.2% vs. 31.8%; p = 0.009), acute respiratory distress syndrome (18.8% vs. 16%; p = 0.456), and cytokine storm rate (15.9% vs. 10.1%; p = 0.072) were higher in first wave compared to the second wave. These 47 patients died within the first month of COVID-19. Six (1.4%) of the surviving patients lost allografts during treatment. There was no difference in the median serum creatinine clearance of the surviving patients at baseline (52 mL/min [IQR, 47-66]), first- (56 mL/min [IQR, 51-68]), third- (51 mL/min [IQR,48-67]) and sixth-months (52 mL/min [IQR, 48-81]). Development of cytokine storm and posttransplant diabetes mellitus were independent predictors for mortality. Conclusions Mortality remains a problem in COVID-19. All the deaths occur in the first month of COVID-19. Also, acute kidney injury is common in hospitalized patients, and some of the patients suffer from graft loss after the initial episode

Prevalence and predictors of gestational diabetes mellitus: a nationwide multicentre prospective study

Cetinkaya, Esra/0000-0003-2415-1236; Taskiran, Bengur/0000-0003-4842-450X; MELEKOGLU, RAUF/0000-0001-7113-6691; pekkolay, zafer/0000-0002-5323-2257; Ozer, Alev/0000-0002-0934-0226; kilinc, faruk/0000-0002-0198-2558; Aygun, Elif Ganime/0000-0003-3737-7250; KARAKILIC, ERSEN/0000-0003-3590-2656; Aydin, Hasan/0000-0003-4246-0681WOS: 000457530200011PubMed: 30402933Aim Prevalence rates of gestational diabetes mellitus (GDM) show considerable variation among different countries and regions of the world. The primary aim of this study was to determine the nationwide prevalence and predictors of GDM in Turkey. Methods We conducted prospective nationwide screening among pregnant women. Between August 2016 and November 2017, a total of 2643 pregnant women from 51 centres in 12 different regions were enrolled. A two-step screening method and Carpenter and Coustan criteria were used in the diagnosis of GDM. Clinical and biochemical data were obtained using electronic database software. Results The national prevalence of GDM was found to be 16.2% [95% confidence intervals (CI) 15.0% to 17.4%] without a significant difference between urban and rural regions. Women with GDM were older (mean age: 32 +/- 5 vs. 28 +/- 5 years, P < 0.001) and heavier (mean BMI: 27.2 +/- 5.1 vs. 24.7 +/- 4.7 kg/m(2), P < 0.001) than their counterparts without GDM. The prevalence of GDM tended to increase with age (< 25 years, 6.9%; 26-35 years, 15.6%; and 36-45 years, 32.7%; P < 0.001). Maternal age, maternal BMI, history of previous GDM and family history of diabetes mellitus were independent predictors of developing GDM (P < 0.05 for all). Low-risk women (age < 25 years, BMI < 25 kg/m(2), no family history of diabetes) comprised 10.7% of the total population and the prevalence of GDM in these women was 4.5% (95% CI 2.4% to 7.8%). Conclusion The results of this nationwide study indicate that GDM is very common, affecting one in seven pregnancies in Turkey. Implementation of international guidelines on screening and management of this public health problem is required