Panorama Natuur: een visie op natuur door Young Professionals

Het denken over natuur en landschap in Nederland is aan een opfrisbeurt toe. In Panorama Natuur hebben 9 jongeren hun eigen visie daarop ontwikkeld, en dragen daarmee bij aan een nieuw natuurverhaal

Metachronous peritoneal metastases in patients with pT4b colon cancer: An international multicenter analysis of intraperitoneal versus retroperitoneal tumor invasion

It was hypothesized that colon cancer with only retroperitoneal invasion is associated with a low risk of peritoneal dissemination. This study aimed to compare the risk of metachronous peritoneal metastases (mPM) between intraperitoneal and retroperitoneal invasion

Detection of ice core particles via deep neural networks

Insoluble particles in ice cores record signatures of past climate parameters like vegetation, volcanic activity or aridity. Their analytical detection depends on intensive bench microscopy investigation and requires dedicated sample preparation steps. Both are laborious, require in-depth knowledge and often restrict sampling strategies. To help overcome these limitations, we present a framework based on Flow Imaging Microscopy coupled to a deep neural network for autonomous image classification of ice core particles. We train the network to classify 7 commonly found classes: mineral dust, felsic and basaltic volcanic ash (tephra), three species of pollen (Corylus avellana, Quercus robur, Quercus suber) and contamination particles that may be introduced onto the ice core surface during core handling operations. The trained network achieves 96.8 % classification accuracy at test time. We present the system’s potentials and limitations with respect to the detection of mineral dust, pollen grains and tephra shards, using both controlled materials and real ice core samples. The methodology requires little sample material, is non destructive, fully reproducible and does not require any sample preparation step. The presented framework can bolster research in the field, by cutting down processing time, supporting human-operated microscopy and further unlocking the paleoclimate potential of ice core records by providing the opportunity to identify an array of ice core particles. Suggestions for an improved system to be deployed within a continuous flow analysis workflow are also presented

Detection of ice core particles via deep neural networks

Insoluble particles in ice cores record signatures of past climate parameters like vegetation dynamics, volcanic activity, and aridity. For some of them, the analytical detection relies on intensive bench microscopy investigation and requires dedicated sample preparation steps. Both are laborious, require in-depth knowledge, and often restrict sampling strategies. To help overcome these limitations, we present a framework based on flow imaging microscopy coupled to a deep neural network for autonomous image classification of ice core particles. We train the network to classify seven commonly found classes, namely mineral dust, felsic and mafic (basaltic) volcanic ash grains (tephra), three species of pollen (Corylus avellana, Quercus robur, Quercus suber), and contamination particles that may be introduced onto the ice core surface during core handling operations. The trained network achieves 96.8 % classification accuracy at test time. We present the system's potential and its limitations with respect to the detection of mineral dust, pollen grains, and tephra shards, using both controlled materials and real ice core samples. The methodology requires little sample material, is non-destructive, fully reproducible, and does not require any sample preparation procedures. The presented framework can bolster research in the field by cutting down processing time, supporting human-operated microscopy, and further unlocking the paleoclimate potential of ice core records by providing the opportunity to identify an array of ice core particles. Suggestions for an improved system to be deployed within a continuous flow analysis workflow are also presented

Drug-induced caspase 8 upregulation sensitises cisplatin-resistant ovarian carcinoma cells to rhTRAIL-induced apoptosis

BACKGROUND: Drug resistance is a major problem in ovarian cancer. Triggering apoptosis using death ligands such as tumour necrosis factor-related apoptosis inducing ligand (TRAIL) might overcome chemoresistance. METHODS: We investigated whether acquired cisplatin resistance affects sensitivity to recombinant human (rh) TRAIL alone or in combination with cisplatin in an ovarian cancer cell line model consisting of A2780 and its cisplatin-resistant subline CP70. RESULTS: Combining cisplatin and rhTRAIL strongly enhanced apoptosis in both cell lines. CP70 expressed less caspase 8 protein, whereas mRNA levels were similar compared with A2780. Pre-exposure of particularly CP70 to cisplatin resulted in strongly elevated caspase 8 protein and mRNA levels. Caspase 8 mRNA turnover and protein stability in the presence or absence of cisplatin did not differ between both cell lines. Cisplatin-induced caspase 8 protein levels were essential for the rhTRAIL-sensitising effect as demonstrated using caspase 8 small-interfering RNA (siRNA) and caspase-8 overexpressing constructs. Cellular FLICE-inhibitory protein (c-FLIP) and p53 siRNA experiments showed that neither an altered caspase 8/c-FLIP ratio nor a p53-dependent increase in DR5 membrane expression following cisplatin were involved in rhTRAIL sensitisation. CONCLUSION: Cisplatin enhances rhTRAIL-induced apoptosis in cisplatin-resistant ovarian cancer cells, and induction of caspase 8 protein expression is the key factor of rhTRAIL sensitisation. British Journal of Cancer (2011) 104, 1278-1287. doi:10.1038/bjc.2011.84 www.bjcancer.com (C) 2011 Cancer Research U

Oral processing of hydrogels: Influence of food material properties versus individuals' eating capability

Food material properties play an important role in sensory perception and consumer acceptance of foods. However, the actual oral processing behavior may depend on both the material properties of the food that is being consumed and individuals' oral capabilities. This study aimed to examine the relationships between intrinsic (oral capabilities of healthy participants) and extrinsic (food material properties of a set of hydrogels) variables to the real oral processing behavior. Three κ‐carrageenan hydrogels (κC), differing in fracture mechanics and oral tribology properties, were prepared: native κC, κC with added Na‐alginate, and a κC matrix with added Ca‐alginate beads of 300 μm. A composite score of eating capability (EC) was measured with non‐invasive techniques (maximum bite force and tongue pressure) using a panel of 28 untrained consumers. The oral processing behaviors (number of chews, oral residence time, and chewing rate) were analyzed with the same participants using frame‐by‐frame video analysis. It was found that the EC scores did not correlate with any of the oral processing behaviors. The number of chews and oral residence time showed a strong correlation with the fracture force and friction force at orally relevant speeds (10–100 mm/s), whereas chewing rate did not vary with these properties. The results from this study indicate that oral processing in healthy adults seems mainly motivated by food material properties, and the chewing rate seems to relate more to individual differences and EC than to food properties. Insights from this study, using model hydrogels, have helped to promote knowledge on oral processing behavior in healthy individuals; could bridge the gap between consumer science, psychology, and food science; and may be of interest to product developers in designing foods with pleasant texture properties

Increased masticatory activity and quality of life in elderly persons with dementia-a longitudinal matched cluster randomized single-blind multicenter intervention study.

Background: Worldwide, millions of people are suffering from dementia and this number is rising. An index of quality of life (QoL) can describe the impact a disease or treatment has on a person's wellbeing. QoL comprises many variables, including physical health and function, and mental health and function. QoL is related to masticatory ability and physical activity. Animal studies show that disruption of mastication due to loss of teeth or a soft diet leads to memory loss and learning problems. Since these are common complaints in dementia, it is hypothesized that improvement of masticatory function and normalization of diet consistency can increase QoL in elderly persons suffering from dementia. Therefore, the goal of the present study is to examine whether an increase in masticatory activity, achieved by increased food consistency and enhancement of masticatory function through improved oral health care has a positive effect on QoL, including cognition, mood, activities of daily living (ADL), and circadian rhythm in elderly persons with dementia.Methods and design: The described study is a prospective longitudinal matched cluster randomized single-blind multicenter study. Participants are elderly persons living in the Netherlands, suffering from dementia and receiving psychogeriatric care. An intervention group will receive improved oral health care and a diet of increased consistency. A control group receives care as usual. Participants will be assessed four times; outcome variables besides QoL are cognition, mood, independence, rest-activity rhythm, blood pressure, and masticatory function.Discussion: This research protocol investigates the effect of an intervention executed by daily caregivers. The intervention will increase masticatory activity, which is achieved by three different actions, (providing oral health care, increasing food consistency, or a combination of both). There is a certain amount of variety in the nature of the interventions due to local differences in nursing homes. This might be a scientific weakness in the study design; however, a practical implementation of any findings will be subject to the same factors, making this study design clinically relevant.Trial registration: NTR1561. © 2013 Weijenberg et al.; licensee BioMed Central Ltd

Use of S-100B to Evaluate Therapy Effects during Bevacizumab Induction Treatment in AJCC Stage III Melanoma

To investigate the feasibility of using bevacizumab to improve the survival of American Joint Committee on Cancer (AJCC) stage III melanoma patients, we investigated how a single bevacizumab treatment affected nodal disease and a panel of biomarkers in clinically fluorodeoxyglucose positron emission tomography (FDG-PET)/computed tomography (CT)-staged, stage III melanoma patients, prior to therapeutic lymph node dissection (TLND). Four weeks before TLND, nine patients (median age 50, range 28.8-62.1 years; two male, seven female) with palpable lymph node metastases received 7.5 mg/kg bevacizumab. Before and after this treatment, all patients were assessed by measurements of the maximum standardized uptake value (SUVmax) by FDG-PET scan, and serum S-100B and lactate dehydrogenase (LDH). After TLND, the dissection specimen was analyzed for number of removed lymph nodes, number of metastatic lymph nodes, and tumor necrosis. Median follow-up was 15.5 (2.2-32.9) months. Histopathological analysis revealed tumor necrosis in six patients, of whom five had an S-100B decline and one had an unchanged S-100B level after bevacizumab. The other three patients showed an S-100B increase and no necrosis. Tumor necrosis was correlated with S-100B decrease (P = 0.048). No association was found between necrosis and the markers SUVmax and LDH. No wound healing disturbances were encountered. Tumor necrosis in dissection specimens was associated with declining S-100B levels, while elevated S-100B was only found in cases with no necrosis. Bevacizumab might be useful in treating AJCC stage III melanoma patients prior to TLND, and S100-B appears to be a useful marker for assessment of treatment effects