Splay aligned liquid crystal network photoactuators for integrated microfluidic pumps

As lab-on-a-chip devices aim to incorporate complex and multi-step microfluidic workflows, active fluid control within these platforms is critical. We use a splay aligned liquid crystal network (LCN) photoactuator, capable of deformation upon blue light illumination, as a stimuli responsive material to create integrated fluidic elements. After optimization of the manufacturing parameters, a well-defined actuator material is attained. Illumination with a 455 nm light emitting diode (LED) at 41 mW cm−2 achieves deflection of a 3 × 8 × 0.05 mm LCN film by 380 µm, generating forces of 1.1 mN. The actuator response is stable over time and scalable by light intensity, temperature, and size of the LCN film. By combining with a polydimethylsiloxane (PDMS) membrane, integration into a microfluidic chip is demonstrated and fluid movement of 77 nL in a 2 s stroke is attained. In a pumping setup, the LCN film functions as pumping membrane and two passive PDMS check valves complete the integrated micropump. Constant pumping rates of 0.1 µL min−1 are achieved. An advantage of this micropump setup lies in the non-contact actuation method, which allows for easy integration into microfluidic chips, without the need for chip-to-world connections. Furthermore, with the simple manufacturing procedure and the low operating power, important requirements for application in point-of-care settings are fulfilled.</p

Methyl-binding domain protein-based DNA isolation from human blood serum combines DNA analyses and serum-autoantibody testing

<p>Abstract</p> <p>Background</p> <p>Circulating cell free DNA in serum as well as serum-autoantibodies and the serum proteome have great potential to contribute to early cancer diagnostics via non invasive blood tests. However, most DNA preparation protocols destroy the protein fraction and therefore do not allow subsequent protein analyses. In this study a novel approach based on methyl binding domain protein (MBD) is described to overcome the technical difficulties of combining DNA and protein analysis out of one single serum sample.</p> <p>Methods</p> <p>Serum or plasma samples from 98 control individuals and 54 breast cancer patients were evaluated upon silica membrane- or MBD affinity-based DNA isolation via qPCR targeting potential DNA methylation markers as well as by protein-microarrays for tumor-autoantibody testing.</p> <p>Results</p> <p>In control individuals, an average DNA level of 22.8 ± 25.7 ng/ml was detected applying the silica membrane based protocol and 8.5 ± 7.5 ng/ml using the MBD-approach, both values strongly dependent on the serum sample preparation methods used. In contrast to malignant and benign tumor serum samples, cell free DNA concentrations were significantly elevated in sera of metastasizing breast cancer patients. Technical evaluation revealed that serum upon MBD-based DNA isolation is suitable for protein-array analyses when data are consistent to untreated serum samples.</p> <p>Conclusion</p> <p>MBD affinity purification allows DNA isolations under native conditions retaining the protein function, thus for example enabling combined analyses of DNA methylation and autoantigene-profiles from the same serum sample and thereby improving minimal invasive diagnostics.</p

Influence of Different Lactation Stages on Circadian Rhythmicity of Metabolic Biomarkers in Dairy Cows: A Pilot Study

Currently, subclinical metabolic imbalances at the individual cow and herd level are detected by measuring biomarkers in single blood samples. However, diurnal variations have not been fully described yet but need to be considered when sampling for a robust ad consistent analysis. The study describes the influence of lactation phases on circadian rhythms and diurnal variations for non-esterified fatty acids (NEFA), beta-hydroxybutyrate (BHB), total bilirubin (tBIL) and aspartate aminotransferase (AST) in dairy cows. In an observational pilot study, we used 16 clinically healthy Simmental dairy cows subdivided in four different lactation stages (dry-off, fresh, high and late lactating). Every cow was monitored for 24 h, with blood sampling and assessment of clinical parameters every 2 h. Time and lactation stage influence the concentration of the biomarkers NEFA, BHB and tBIL in serum. Further, circadian rhythmicity was found in high lactating cows for NEFA peaking at 5:39 am and BHB peaking at 4:20 pm. We suggest blood sampling for single-point measurements within three hours after the first feeding until two hours after the last feeding of the day. The results provide a new insight into the physiology of circadian rhythms in dairy cows and enable improved metabolic monitoring

Salivary Biomarkers for Dental Caries Detection and Personalized Monitoring

This study investigated the potential of salivary bacterial and protein markers for evaluating the disease status in healthy individuals or patients with gingivitis or caries. Saliva samples from caries- and gingivitis-free individuals (n = 18), patients with gingivitis (n = 17), or patients with deep caries lesions (n = 38) were collected and analyzed for 44 candidate biomarkers (cytokines, chemokines, growth factors, matrix metalloproteinases, a metallopeptidase inhibitor, proteolytic enzymes, and selected oral bacteria). The resulting data were subjected to principal component analysis and used as a training set for random forest (RF) modeling. This computational analysis revealed four biomarkers (IL-4, IL-13, IL-2-RA, and eotaxin/CCL11) to be of high importance for the correct depiction of caries in 37 of 38 patients. The RF model was then used to classify 10 subjects (five caries-/gingivitis-free and five with caries), who were followed over a period of six months. The results were compared to the clinical assessments of dental specialists, revealing a high correlation between the RF prediction and the clinical classification. Due to the superior sensitivity of the RF model, there was a divergence in the prediction of two caries and four caries-/gingivitis-free subjects. These findings suggest IL-4, IL-13, IL-2-RA, and eotaxin/CCL11 as potential salivary biomarkers for identifying noninvasive caries. Furthermore, we suggest a potential association between JAK/STAT signaling and dental caries onset and progression

Pla2g2a Attenuates Colon Tumorigenesis in Azoxymethane-Treated C57BL/6 Mice; Expression Studies Reveal Pla2g2a Target Genes and Pathways

Background: The group IIA secretory phospholipase A2 gene, Pla2g2a, confers resistance to intestinal tumorigenesis in the ApcMin/+ mouse model. However, it is unclear how Pla2g2a exerts its tumor-suppressive effects and whether its mode of action depends on Apc-germline mutations

Microbial Analysis of Saliva to Identify Oral Diseases Using a Point-of-Care Compatible qPCR Assay

Oral health is maintained by a healthy microbiome, which can be monitored by state-of-the art diagnostics. Therefore, this study evaluated the presence and quantity of ten oral disease-associated taxa (P. gingivalis, T. forsythia, T. denticola, F. nucleatum, C. rectus, P. intermedia, A. actinomycetemcomitans, S. mutans, S. sobrinus, oral associated Lactobacilli) in saliva and their clinical status association in 214 individuals. Upon clinical examination, study subjects were grouped into healthy, caries and periodontitis and their saliva was collected. A highly specific point-of-care compatible dual color qPCR assay was developed and used to study the above-mentioned bacteria of interest in the collected saliva. Assay performance was compared to a commercially available microbial reference test. Eight out of ten taxa that were investigated during this study were strong discriminators between the periodontitis and healthy groups: C. rectus, T. forsythia, P. gingivalis, S. mutans, F. nucleatum, T. denticola, P. intermedia and oral Lactobacilli (p < 0.05). Significant differentiation between the periodontitis and caries group microbiome was only shown for S. mutans (p < 0.05). A clear distinction between oral health and disease was enabled by the analysis of quantitative qPCR data of target taxa levels in saliva

Microbial Analysis of Saliva to Identify Oral Diseases Using a Point-of-Care Compatible qPCR Assay

Oral health is maintained by a healthy microbiome, which can be monitored by state-of-the art diagnostics. Therefore, this study evaluated the presence and quantity of ten oral disease-associated taxa (P. gingivalis, T. forsythia, T. denticola, F. nucleatum, C. rectus, P. intermedia, A. actinomycetemcomitans, S. mutans, S. sobrinus, oral associated Lactobacilli) in saliva and their clinical status association in 214 individuals. Upon clinical examination, study subjects were grouped into healthy, caries and periodontitis and their saliva was collected. A highly specific point-of-care compatible dual color qPCR assay was developed and used to study the above-mentioned bacteria of interest in the collected saliva. Assay performance was compared to a commercially available microbial reference test. Eight out of ten taxa that were investigated during this study were strong discriminators between the periodontitis and healthy groups: C. rectus, T. forsythia, P. gingivalis, S. mutans, F. nucleatum, T. denticola, P. intermedia and oral Lactobacilli (p &lt; 0.05). Significant differentiation between the periodontitis and caries group microbiome was only shown for S. mutans (p &lt; 0.05). A clear distinction between oral health and disease was enabled by the analysis of quantitative qPCR data of target taxa levels in saliva

OralDisk: A Chair-Side Compatible Molecular Platform Using Whole Saliva for Monitoring Oral Health at the Dental Practice

Periodontitis and dental caries are two major bacterially induced, non-communicable diseases that cause the deterioration of oral health, with implications in patients’ general health. Early, precise diagnosis and personalized monitoring are essential for the efficient prevention and management of these diseases. Here, we present a disk-shaped microfluidic platform (OralDisk) compatible with chair-side use that enables analysis of non-invasively collected whole saliva samples and molecular-based detection of ten bacteria: seven periodontitis-associated (Aggregatibacter actinomycetemcomitans, Campylobacter rectus, Fusobacterium nucleatum, Prevotella intermedia, Porphyromonas gingivalis, Tannerella forsythia, Treponema denticola) and three caries-associated (oral Lactobacilli, Streptococcus mutans, Streptococcus sobrinus). Each OralDisk test required 400 µL of homogenized whole saliva. The automated workflow included bacterial DNA extraction, purification and hydrolysis probe real-time PCR detection of the target pathogens. All reagents were pre-stored within the disk and sample-to-answer processing took < 3 h using a compact, customized processing device. A technical feasibility study (25 OralDisks) was conducted using samples from healthy, periodontitis and caries patients. The comparison of the OralDisk with a lab-based reference method revealed a ~90% agreement amongst targets detected as positive and negative. This shows the OralDisk’s potential and suitability for inclusion in larger prospective implementation studies in dental care settings

Salivary Biomarkers for Dental Caries Detection and Personalized Monitoring

This study investigated the potential of salivary bacterial and protein markers for evaluating the disease status in healthy individuals or patients with gingivitis or caries. Saliva samples from caries- and gingivitis-free individuals (n = 18), patients with gingivitis (n = 17), or patients with deep caries lesions (n = 38) were collected and analyzed for 44 candidate biomarkers (cytokines, chemokines, growth factors, matrix metalloproteinases, a metallopeptidase inhibitor, proteolytic enzymes, and selected oral bacteria). The resulting data were subjected to principal component analysis and used as a training set for random forest (RF) modeling. This computational analysis revealed four biomarkers (IL-4, IL-13, IL-2-RA, and eotaxin/CCL11) to be of high importance for the correct depiction of caries in 37 of 38 patients. The RF model was then used to classify 10 subjects (five caries-/gingivitis-free and five with caries), who were followed over a period of six months. The results were compared to the clinical assessments of dental specialists, revealing a high correlation between the RF prediction and the clinical classification. Due to the superior sensitivity of the RF model, there was a divergence in the prediction of two caries and four caries-/gingivitis-free subjects. These findings suggest IL-4, IL-13, IL-2-RA, and eotaxin/CCL11 as potential salivary biomarkers for identifying noninvasive caries. Furthermore, we suggest a potential association between JAK/STAT signaling and dental caries onset and progression

Salivary biomarkers for dental caries detection and personalized monitoring

This study investigated the potential of salivary bacterial and protein markers for evaluating the disease status in healthy individuals or patients with gingivitis or caries. Saliva samples from caries-and gingivitis-free individuals (n = 18), patients with gingivitis (n = 17), or patients with deep caries lesions (n = 38) were collected and analyzed for 44 candidate biomarkers (cytokines, chemokines, growth factors, matrix metalloproteinases, a metallopeptidase inhibitor, proteolytic enzymes, and selected oral bacteria). The resulting data were subjected to principal component analysis and used as a training set for random forest (RF) modeling. This computational analysis revealed four biomarkers (IL-4, IL-13, IL-2-RA, and eotaxin/CCL11) to be of high importance for the correct depiction of caries in 37 of 38 patients. The RF model was then used to classify 10 subjects (five caries-/gingivitis-free and five with caries), who were followed over a period of six months. The results were compared to the clinical assessments of dental specialists, revealing a high correlation between the RF prediction and the clinical classification. Due to the superior sensitivity of the RF model, there was a divergence in the prediction of two caries and four caries-/gingivitis-free subjects. These findings suggest IL-4, IL-13, IL-2-RA, and eotaxin/CCL11 as potential salivary biomarkers for identifying noninvasive caries. Furthermore, we suggest a potential association between JAK/STAT signaling and dental caries onset and progression