PIN1 Attenuation Improves Midface Hypoplasia in a Mouse Model of Apert Syndrome

Premature fusion of the cranial suture and midface hypoplasia are common features of syndromic craniosynostosis caused by mutations in the FGFR2 gene. The only treatment for this condition involves a series of risky surgical procedures designed to correct defects in the craniofacial bones, which must be performed until brain growth has been completed. Several pharmacologic interventions directed at FGFR2 downstream signaling have been tested as potential treatments for premature coronal suture fusion in a mouse model of Apert syndrome. However, there are no published studies that have targeted for the pharmacologic treatment of midface hypoplasia. We used Fgfr2^S252W/+ knock-in mice as a model of Apert syndrome and morphometric analyses to identify causal hypoplastic sites in the midface region. Three-dimensional geometric and linear analyses of Fgfr2^S252W/+ mice at postnatal day 0 demonstrated distinct morphologic variance. The premature fusion of anterior facial bones, such as the maxilla, nasal, and frontal bones, rather than the cranium or cranial base, is the main contributing factor toward the anterior-posterior skull length shortening. The cranial base of the mouse model had a noticeable downward slant around the intersphenoid synchondrosis, which is related to distortion of the airway. Within a skull, the facial shape variance was highly correlated with the cranial base angle change along Fgfr2 S252W mutation-induced craniofacial anomalies. The inhibition of an FGFR2 downstream signaling enzyme, PIN1, via genetic knockdown or use of a PIN1 inhibitor, juglone, attenuated the aforementioned deformities in a mouse model of Apert syndrome. Overall, these results indicate that FGFR2 signaling is a key contributor toward abnormal anterior-posterior dimensional growth in the midface region. Our study suggests a novel therapeutic option for the prevention of craniofacial malformations induced by mutations in the FGFR2 gene.

Dynamic predictive model for postoperative nausea and vomiting for intravenous fentanyl patient-controlled analgesia

Postoperative nausea and vomiting is the most common side-effect of opioid-based intravenous patient-controlled analgesia. Apfel's simplified risk score is popular but it has some limitations. We developed and validated a dynamic predictive model for nausea or vomiting up to 48 postoperative hours, available as an online web application. Fentanyl was used by 22,144 adult patients for analgesia after non-cardiac surgery under general anaesthesia: we randomly divided them into development (80%) and validation (20%) cohorts, repeated 100 times. We used linear discriminant analysis to select variables for multivariate logistic regression. The incidences of postoperative nausea or vomiting were: 0-48 h, 5691/22,144 (26%); 0-6 h, 2749/22,144 (12%); 6-12 h, 2687/22,144 (12%); 12-18 h, 2624/22,144 (12%); 18-24 h, 1884/22,144 (9%); and 24-48 h, 1082/22,144 (5%). The median (95%CI) area under the receiver operating characteristic curve was 0.72 (0.71-0.73) up to 48 postoperative hours compared with 0.65 (0.64-0.66) for the Apfel model, p < 0.001. The equivalent areas for 0-6 h, 6-12 h, 12-18 h, 18-24 h and 24-48 h were: 0.70 (0.69-0.72); 0.71 (0.69-0.73); 0.69 (0.68-0.71); 0.70 (0.67-0.72); and 0.69 (0.66-0.71), respectively. Our web application allows clinicians to calculate incidences of nausea and vomiting in patients receiving intravenous fentanyl for patient-controlled analgesia.

Stretchable Electroluminescent Display Enabled by Graphene-Based Hybrid Electrode

Stretchable alternating-current electroluminescent (ACEL) devices are required due to their potential in wearable, biomedical, e-skin, robotic, lighting, and display applications; however, one of the main hurdles is to achieve uniform electroluminescence with an optimal combination of transparency, conductivity, and stretchability in electrodes. We therefore propose a fabrication scheme involving strategically combining two-dimensional graphene layers with a silver nanowire (Ag NW)-embedded PEDOT:PSS film. The developed hybrid electrode overcomes the limitations of commonly known metallic NWs and ionic conductor-based electrodes for ACEL applications. Furthermore, the potential of the hybrid electrode is realized in demonstrating large-area stretchable ACEL devices composed of an 8 × 8 passive array. The prototype ACEL passive array demonstrates efficient and uniform electroluminescence under high levels of mechanical deformation such as bending, rolling, twisting, and stretching.

The Detection of UHECRs with the EUSO-TA Telescope

EUSO-TA is a cosmic ray detector developed by the JEM-EUSO (Joint Experiment Missions for Extreme Universe Space Observatory) Collaboration, observing during nighttime the fluorescence light emitted along the path of extensive air showers in the atmosphere. It is installed at the Telescope Array site in Utah, USA, in front of the fluorescence detector station at Black Rock Mesa. It serves as a ground-based pathfinder experiment for future space-based missions. EUSO-TA has an optical system with two Fresnel lenses and a focal surface with 6 × 6 multi-anode photomultiplier tubes with 64 channels each, for a total of 2304 channels. The overall field of view is ∼10.6°× 10.6°. This detector technology allows the detection of cosmic ray events with high spatial resolution, having each channel a field of view of about ∼0.2° × 0.2° and a temporal resolution of 2.5 µs. First observations of ultra-high energy cosmic rays revealed the cosmic ray detection capability of EUSO-TA. The foreseen upgrade of EUSO-TA will improve the efficiency of the detector and will increase the statistics of detected events. In this work we present recent results of the detection capability of EUSO-TA and its limits. Moreover, other results about the analysis of laser pulses, stars and meteors will be discussed.

Development of a new analgesic index using nasal photoplethysmography

Although surrogate measures to quantify pain intensity have been commercialised, there is a need to develop a new index with improved accuracy. The aim of this study was to develop a new analgesic index using nasal photoplethysmography data. The specially designed sensor was placed between the columella and the nasal septum to acquire nasal photoplethysmography in surgical patients. Nasal photoplethysmography and Surgical Pleth Index^® (GE Healthcare) data were obtained for 14 min both in the absence (pre-operatively) or presence (postoperatively) of pain in a group of surgical patients, each patient acting as their own control. Various dynamic photoplethysmography variables were extracted to quantify pain intensity; the most accurate index was selected using logistic regression as a classifier. The area under the curve of the receiver-operating characteristic curve was measured to evaluate the accuracy of final model predictions. In total, 12,012 heart beats from 89 patients were used to develop a new Nasal Photoplethysmography Index for analgesic depth quantification. The two-variable model (a combination of diastolic peak point variation and heart beat interval variation) was most accurate in discriminating between the presence and absence of pain (numerical rating scale (NRS) ≥ 3). The accuracy and area under the curve of the receiver-operating characteristic curve for the Nasal Photoplethysmography Index were 75.3% and 0.8018, respectively, and 64.8% and 0.7034, respectively, for the Surgical Pleth Index. The Nasal Photoplethysmography Index clearly distinguished pain (NRS ≥ 3) in awake surgical patients with postoperative pain. The Nasal Photoplethysmography Index performed better than the Surgical Pleth Index. Further validation studies are needed to evaluate its feasibility to quantify pain intensity during general anaesthesia.

Utilization of biopsy-based genomic classifier to predict distant metastasis after definitive radiation and short-course ADT for intermediate and high-risk prostate cancer

BACKGROUND

We examined the ability of a biopsy-based 22-marker genomic classifier (GC) to predict for distant metastases after radiation and a median of 6 months of androgen deprivation therapy (ADT).

METHODS

We studied 100 patients with intermediate-risk (55%) and high-risk (45%) prostate cancer who received definitive radiation plus a median of 6 months of ADT (range 3-39 months) from 2001-2013 at a single center and had available biopsy tissue. Six to ten 4 micron sections of the needle biopsy core with the highest Gleason score and percentage of tumor involvement were macrodissected for RNA extraction. GC scores (range, 0.04-0.92) were determined. The primary end point of the study was time to distant metastasis. Median follow-up was 5.1 years. There were 18 metastases during the study period.

RESULTS

On univariable analysis (UVA), each 0.1 unit increase in GC score was significantly associated with time to distant metastasis (hazard ratio: 1.40 (1.10-1.84), P=0.006) and remained significant after adjusting for clinical variables on multivariable analysis (MVA) (adjusted hazard ratio: 1.36 (1.04-1.83), P=0.024). The c-index for 5-year distant metastasis was 0.45 (95% confidence interval: 0.27-0.64) for Cancer of the Prostate Risk Assessment score, 0.63 (0.40-0.78) for National Comprehensive Cancer Network (NCCN) risk groups, and 0.76 (0.57-0.89) for the GC score. Using pre-specified GC risk categories, the cumulative incidence of metastasis for GC>0.6 reached 20% at 5 years after radiation (P=0.02).

CONCLUSIONS

We believe this is the first demonstration of the ability of the biopsy-based GC score to predict for distant metastases after definitive radiation and ADT for intermediate- and high-risk prostate cancer. Patients with the highest GC risk (GC>0.6) had high rates of metastasis despite multi-modal therapy suggesting that they could potentially be candidates for treatment intensification and/or enrollment in clinical trials of novel therapy.

RNA in Salivary Extracellular Vesicles as a Possible Tool for Systemic Disease Diagnosis

Saliva contains biological information as blood and is recognized as a valuable diagnostic medium for their noninvasiveness. Although "-omics" researches have tried to investigate saliva, the origin and significance of its contents are not clear, and its usage is largely confined to oral disease in the diagnostic and prognostic field. In an attempt to broaden the applicability of saliva and to find systemic disease-derived RNA in saliva, we made mouse models that had human melanoma and isolated extracellular vesicles (EVs) from their saliva by an aqueous 2-phase system (ATPS), then identified and evaluated their expression of human melan-A RNA, which is associated with melanoma on skin. With ATPS, EVs were isolated efficiently and stably while taking less time compared to isolation by ultracentrifugation. When ATPS was used to isolate EVs from saliva, the mean ± SD percentage of EVs recovered from initial EVs was 38.22% ± 18.55% by the number of particles, and the mean ± SD percentage of RNA recovered from the initial amount was 60.33% ± 5.34%. RNAs within isolated EVs were analyzed subsequently by reverse transcription quantitative polymerase chain reaction and polymerase chain reaction from saliva and plasma. In melanoma mice, amplification of human melan-A was identified from saliva and plasma, even though a relative amount of normalized melan-A was lower than that of plasma. These results present a possibility that RNAs derived from systemic disease are transferred into saliva from blood in EVs. Also, they suggest that saliva could be exploited in obtaining information about systemic disease, not only about oral disease, by examining RNAs in EVs from saliva instead of blood.

Photoplethysmography sampling frequency: pilot assessment of how low can we go to analyze pulse rate variability with reliability?

Pulse rate variability (PRV) analysis appears as the first alternative to heart rate variability analysis for wearable devices; however, there is a constraint on computational load and energy consumption for the limited system resources available to the devices. Considering that adjustment of the sampling frequency is one of the strategies for reducing computational load and power consumption, this study aimed to investigate the influence of sampling frequency (f _s) on PRV analysis and to find the minimum sampling frequency while maintaining reliability. We generated 5000, 2500, 1000, 500, 250, 100, 50, 25, 20, 15, 10, 5 Hz down-sampled photoplethysmograms from 10 kHz-sampled PPGs and derived time- and frequency-domain variables of the PRV. These included AVNN, SDNN, SDSD, RMSSD, NN50, pNN50, total power, VLF, LF, HF, LF/HF, nLF and nHF for each down-sampled signal. Derived variables were compared with heart rate variability of the 10 kHz-sampled electrocardiograms, and then statistically investigated using one-way ANOVA test and Bland-Altman analysis. As a result, significant differences (P  <  0.05) were found for SDNN, SDSD, RMSSD, NN50, pNN50, TP, HF, LF/HF, nLF and nHF, but not for AVNN, VLF and LF. Based on the post hoc tests, it was found that the NN50 and pNN50, SDSD and RMSSD, LF/HF and nHF, SDNN, TP and nLF analysis had significant differences at f _s  ⩽  20 Hz, f _s  ⩽  15 Hz, f _s  ⩽10 Hz; f _s  =  5 Hz, respectively. In other words, a significant difference was not seen for any variable if the f _s was greater than 25 Hz. Consequently, our pilot study suggests that analysis of variability in the time and frequency domain from pulse rate obtained through PPG may be potentially as reliable as that derived from the analysis of the electrocardiogram, provided that f _s  ⩾25 Hz sampling frequency is used.