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Both deep understanding and reliable prediction of postoperative soft tissue changes are crucial for planning orthognathic surgery. Instead of estimating soft tissue responses by measuring individual landmark changes, this study aimed to investigate the relationship (ratio) between soft and hard tissue movements in different facial regions through three-dimensional cone-beam computed tomography (CBCT). Preoperative and postoperative CBCT images were superimposed using the surface registration method on the basis of the cranial base, and 10 facial regions of interest were defined. Region-based volumetric subtractions between the preoperative and postoperative segments were performed. The volumetric differences and surface of each region were used to estimate the average movement. Correlation and regression analyses were performed to examine the relationships between the corresponding soft and hard tissue movements. An overall pattern of facial soft tissue movement was observed in patients with prognathism who underwent orthognathic surgery. The experiment results have shown that mean ratios for the average soft-to-hard tissue movements in the facial regions varied, which may not exactly be similar to the published reports because of the population biocharacteristics and study methods, but the trend is in agreement with the previous studies. Additionally, the prediction capability of the regression model was significantly high, ranging from 0.786 to 0.857, in upper lip, upper vermilion, and chin regions, thus demonstrating that the skin outline changes in these critical regions could be reliably predicted from the underlying bone movements. These results could likely be applied in future soft tissue simulation in orthognathic surgery.

A nonlinear hysteresis model of magneto-mechanical-thermo coupling for Terfenol-D materials is presented according to Wiss ferromagnetic theory, thermodynamics relations and Jiles–Atherton model. Numerical calculation and experimental results show that the mode well reflects the magnetostrictive characteristics of Terfenol-D rod under the coupling of stress, temperature and magnetic field. A fiber Bragg grating current transformer based on Terfenol-D material is designed according to the strain sensing mechanism of fiber Bragg grating and the demodulation principle of unbalanced M–Z interferometer. The theoretical analysis and research on the working characteristics of the fiber current transformer under the influence of different prestressing force and bias current are carried out. The results are important for the design and application of the current transformer with the Terfenol-D material.

PI fiber insulation paper has excellent insulation and heat resistance, which can replace traditional insulation paper to provide a new high-performance material. In this paper, we adopt a two-step method to synthesize PI, that is, firstly synthesize polyamic acid, and then perform electrospinning and thermal imidization to prepare PI porous fiber membrane. The test results show that the breakdown field strength of the PI porous film is 50 kV/mm. Further research shows that the insulation structure has the characteristics of continuous multiple breakdown. When the fiber film is repeatedly broken down to 25 times at the same point, the field strength of each breakdown of the fiber film changes between 40 and 55 kV/mm, and the average breakdown field strength is 53 kV/mm. Nano-Al 2 O 3 was introduced into the fiber membrane by in situ polymerization. The breakdown field strength of the composite fiber film can reach 74.89 kV/mm after doping 2 wt% nano-Al 2 O 3 , which is higher than that of the pure film. At the same time, this kind of fiber paper also has repeatable breakdown characteristics, and the breakdown voltage distribution width of multiple breakdown is reduced. This characteristic provides the maintenance free characteristic of DC over-voltage for the insulation structure composed of this fiber paper, and can improve the service life of transformer under DC over-voltage such as lightning stroke.

Pulse measurements made using wearable devices can aid the monitoring of human physiological condition. Accurate estimation of waveforms is often difficult for nonexperts; motion artifacts may occur during tonometry measurements when the skin–sensor contact pressure is insufficient. An alternative approach is to extract only high-quality pulses for use in index calculations. The present study aimed to determine the effectiveness of using machine-learning analysis in discriminating between high-quality and low-quality pulse waveforms induced by applying different contact pressures. Radial blood pressure waveform (BPW) signals were measured noninvasively in healthy young subjects using a strain-gauge transducer. One-minute-long trains of pulse data were measured when applying the appropriate contact pressure (67.80 ± 1.55 mmHg) and a higher contact pressure (151.80 ± 3.19 mmHg). Eight machine-learning algorithms were employed to evaluate the following 40 harmonic pulse indices: amplitude proportions and their coefficients of variation and phase angles and their standard deviations. Significant differences were noted in BPW indices between applying appropriate and higher skin–surface contact pressures. The present appropriate contact pressure could not only provide a suitable holding force for the wearable device but also helped to maintain the physiological stability of the underlying tissues. Machine-learning analysis provides an effective method for distinguishing between the high-quality and low-quality pulses with excellent discrimination performance (leave-one-subject-out test: random-forest AUC = 0.96). This approach will aid the development of an automatic screening method for waveform quality and thereby improve the noninvasive acquisition reliability. Other possible interfering factors in practical applications can also be systematically studied using a similar procedure.

Early identification of cognitive impairment would allow affected patients to receive care at earlier stage. Changes in the arterial stiffness have been identified as a prominent pathological feature of dementia. This study aimed to verify if applying machine-learning analysis to spectral indices of the arterial pulse waveform can be used to discriminate different cognitive conditions of community subjects. 3-min Radial arterial blood pressure waveform (BPW) signals were measured noninvasively in 123 subjects. Eight machine-learning algorithms were used to evaluate the following 4 pulse indices for 10 harmonics (total 40 BPW spectral indices): amplitude proportion and its coefficient of variation; phase angle and its standard deviation. Significant differences were noted in the spectral pulse indices between Alzheimer’s-disease patients and control subjects. Using them as training data (AUC = 70.32% by threefold cross-validation), a significant correlation (R2 = 0.36) was found between the prediction probability of the test data (comprising community subjects at two sites) and the Mini-Mental-State-Examination score. This finding illustrates possible physiological connection between arterial pulse transmission and cognitive function. The present findings from pulse-wave and machine-learning analyses may be useful for discriminating cognitive condition, and hence in the development of a user-friendly, noninvasive, and rapid method for the early screening of dementia.

Background Empathy is one of the fundamental factors enhancing the therapeutic effects of physician–patient relationships, but there has been no relevant research in China on the pediatric resident physicians’ capacity for empathy or the influencing factors. Methods A mixed-methods study was undertaken. The student version of the Jefferson Scale of Empathy was used to assess 181 postgraduate residents at Shanghai Children’s Medical Center and Shanghai Children’s Hospital. Differences in empathy ability among pediatric resident physicians of different genders and specialties were analyzed using independent sample t-tests and Mann–Whitney U tests. A one-way analysis of variance was used to analyze the differences in empathy ability at different educational levels and years of medical residency training. Seven third-year postgraduate pediatric residents from Shanghai Children’s Medical Center participated in semi-structured interviews exploring the influencing factors. We analyzed the interview transcripts using thematic analysis. Results The scale was completed by 154 pediatric residents. No statistically significant differences in empathy were found between educational level, postgraduate year, gender, or specialty. The factors influencing empathy in doctor–patient communication included the person who accompanied the child to see the doctor, how the children cooperated with doctors for medical treatment, the volume of pediatric outpatient and emergency visits, and the physician’s ability to withstand pressure. All interviewed resident physicians regarded learning empathy as important but rarely spent extra time learning it. Conclusions The evaluation results of resident physicians on changes in empathy after improving clinical abilities vary according to their understanding of empathy, and the work environment has an important impact on pediatricians’ empathy ability. Their empathy score is relatively low, and this requires exploration and intervention.

Clinically, activated EGFR mutation associated chemo-drugs resistance has severely threaten NSCLC patients. Nanoparticle based small interfering RNA (siRNA) therapy representing another promising alternative by silencing specific gene while still suffered from charge associated toxicity, strong immunogenicity and poor targetability. Herein, we reported a novel EGFR-mutant NSCLC therapy relying on edible and cation-free kiwi-derived extracellular vesicles (KEVs), which showed sevenfold enhancement of safe dosage compared with widely used cationic liposomes and could be further loaded with Signal Transducer and Activator of Transcription 3 interfering RNA (siSTAT3). siSTAT3 loaded KEVs (STAT3/KEVs) could be easily endowed with EGFR targeting ability (STAT3/EKEVs) and fluorescence by surface modification with tailor-making aptamer through hydrophobic interaction. STAT3/EKEVs with a controlled size of 186 nm displayed excellent stability, high specificity and good cytotoxicity towards EGFR over-expressing and mutant PC9-GR4-AZD1 cells. Intriguingly, the systemic administration of STAT3/EKEVs significantly suppressed subcutaneous PC9-GR4-AZD1 tumor xenografts in nude mice by STAT3 mediated apoptosis. This safe and robust KEVs has emerged as the next generation of gene delivery platform for NSCLC therapy after multiple drug-resistance. Graphical Abstract

Sinulariolide (SC-1) is a natural product extracted from the cultured-type soft coral Sinularia flexibilis and possesses anti-inflammation, anti-proliferative, and anti-migratory in several types of cancer cells. However, the molecular pathway behind its effects on inflammation remains poorly understood. Since inflammatory cytokines such as TGFβ, TNFα, IL-1, IL-6, and IL-8 activate transcription factors such as Smads, NF-κB, STAT3, Snail, Twist, and Zeb that drive the epithelial-to-mesenchymal transition (EMT), in this study, we focus on the investigation in effects of SC-1 on TGFβ-induced interleukin-6 (IL-6) releases in an in vitro cell culture model. We showed that both intracellular IL-6 expression and secretion were stimulated by TGFβ and associated with strong upregulation of IL-6 mRNA and increased transcription in A549 cells. SC-1 blocked TGFβ-induced secretion of IL-6 while showing no effect on the induction of fibronectin and plasminogen activator inhibitor-1 genes, indicating that SC-1 interferes with only a subset of TGFβ activities. In addition, SC-1 inhibits TGFβ-induced IL-6 by suppressing p38 MAPK signaling and subsequently inhibits NF-κB and its nuclear translocation without affecting the canonical Smad pathway and receptor turnover. Overall, these data suggest that p38 may involve in the inhibition of SC-1 in IL-6 release, thus illustrating an inhibitory effect for SC-1 in the suppression of inflammation, EMT phenotype, and tumorigenesis.

The sensor that simultaneously perceives bending strain and magnetic field has the potential to detect the finger bending state and hand position of the human and robot. Based on unique magneto-mechanical coupling effect of magnetostrictive materials, the proposed a bi-perceptive flexible sensor, consisting of the Co–Fe film and magnetic sensing plane coils, can realize dual information perception of strain/magnetic field through the change of magnetization state. The sensor structure and interface circuit of the sensing system are designed to provide high sensitivity and fast response, based on the input–output characteristics of the simulation model. An asynchronous multi-task deep learning method is proposed, which takes the output of the position task as the partial input of the bending state task to analyze the output information of the sensor quickly and accurately. The sensing system, integrating with the proposed model, can better predict the bending state and approach distance of human or robot hand.

Three-dimensional computed tomographic imaging has become popular in clinical evaluation, treatment planning, surgical simulation, and outcome assessment for maxillofacial intervention. The purposes of this study were to investigate whether there is any correlation among landmark-based horizontal reference planes and to validate the reproducibility and reliability of landmark identification. Preoperative and postoperative cone-beam computed tomographic images of patients who had undergone orthognathic surgery were collected. Landmark-oriented reference planes including the Frankfort horizontal plane (FHP) and the lateral semicircular canal plane (LSP) were established. Four FHPs were defined by selecting 3 points from the orbitale, porion, or midpoint of paired points. The LSP passed through both the lateral semicircular canal points and nasion. The distances between the maxillary or mandibular teeth and the reference planes were measured, and the differences between the 2 sides were calculated and compared. The precision in locating the landmarks was evaluated by performing repeated tests, and the intraobserver reproducibility and interobserver reliability were assessed. A total of 30 patients with facial deformity and malocclusion--10 patients with facial symmetry, 10 patients with facial asymmetry, and 10 patients with cleft lip and palate--were recruited. Comparing the differences among the 5 reference planes showed no statistically significant difference among all patient groups. Regarding intraobserver reproducibility, the mean differences in the 3 coordinates varied from 0 to 0.35 mm, with correlation coefficients between 0.96 and 1.0, showing high correlation between repeated tests. Regarding interobserver reliability, the mean differences among the 3 coordinates varied from 0 to 0.47 mm, with correlation coefficients between 0.88 and 1.0, exhibiting high correlation between the different examiners. The 5 horizontal reference planes were reliable and comparable for 3D craniomaxillofacial analysis. These reference planes were useful in standardizing the orientation of 3D skull models.