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Background Primary pancreatic paragangliomas are extremely rare tumors. Limited by the diagnostic efficacy of histopathological examination, their malignant behavior is thought to be associated with local invasion or metastasis, with only four malignant cases reported in the literature to date. As pancreatic paragangliomas share similar imaging features with other types of pancreatic neuroendocrine neoplasms, they are difficult to diagnose accurately without the support of pathological evidence. As primary pancreatic paragangliomas are rare, especially those accompanied by lymph node metastasis, there is currently no consensus on treatment. Herein, we report a case of primary pancreatic paraganglioma with lymph node metastasis. Case summary A mass located in the pancreatic body was incidentally discovered on computed tomography in a 41-year-old Tibetan man. Distal pancreatectomy was subsequently performed and a 4.1 cm × 4.2 cm tumor was found embedded in the body of the pancreas during surgery. Histological examination confirmed the characteristics of paraganglioma in which the neoplastic chief cells were arranged in a classic Zellballen pattern under hematoxylin-eosin staining. Further, immunohistochemistry demonstrated that the sustentacular cells in the tumor tissue were positive for S-100 protein, and neoplastic cells and pancreatic draining lymph nodes were positive for chromogranin A and synaptophysin; thus, the presence of lymph node metastasis (two of the eight resected pancreatic draining lymph nodes) was also confirmed. A diagnosis of primary pancreatic paraganglioma with lymph node metastasis was finally established. The patient remained disease-free for 1 year after the surgery. Conclusion A definite diagnosis of pancreatic paraganglioma mainly depends on postoperative histopathological and immunohistochemical examinations. Surgical resection may be the first treatment of choice for patients with primary pancreatic paraganglioma that has metastasized to the lymph nodes.

Objectives This study aims to explore a novel intraoperative trajectory-determined strategy of grouped patient-specific drill templates (PDTs) for transoral C2 pedicle screw insertion (C2 TOPI) for atlantoaxial dislocation (AAD) with incomplete reduction and to evaluate its efficiency and accuracy. Methods Ten cadaveric C2 specimens were scanned by computed tomography (CT) and randomly divided into two groups (the PDT and freehand groups). A novel intraoperative trajectory-determined strategy of grouped PDTs was created for AAD with incomplete reduction. C2 TOPI was performed by use of the PDT technique and the fluoroscopy-guided freehand technique. After surgery, the screw deviations from the centroid of the cross-section at the midpoint of the pedicle and screw position grades were assessed in both groups. Results Compared to the freehand group, the PDT group had a significantly shorter surgery time than the freehand group (47.7 vs 61.9 min, P 0.05). Conclusion The novel intraoperative trajectory-determined strategy of grouped PDTs can be used as an accurate and feasible method for C2 TOPI for AAD with incomplete reduction.

Because of global warming, global sea levels have risen, the frequency of drought in Taiwan is much more frequent in winter and spring, and rainfall tends to concentrate in summer. The probability of disaster-type weather has also increased significantly. Estimating precipitable water vapor (PWV) through GPS signals, related studies and analyses of weather conditions, and the effective use of meteorological forecasts have been valued by many meteorological research organizations and officials. In this study, PWV data from 2006 to 2017 and rainfall data were used for long-term harmonic analysis. PWV data calculated by ECMWF (ECMWF-PWV) and PWV data calculated by GPS (GPS-PWV) were subjected to regression analysis to verify the reliability of the GPS-PWV data. The research results show that GPS-PWV and ECMWF-PWV have extremely high correlations; however, the climatic characteristics of some regions and the high spatial resolution of GPS-PWV are able to accurately calculate the high topographic relief of small areas. It is judged that the GPS-PWV is more accurate than the ECMWF-PWV. It is worth noting that the PWV trend of the regions during the 6-year-before period has not changed very much, but the rainfall trend has changed obviously. Except for the eastern region, most of the regions show a decreasing trend year by year. More long-term observations are still needed to prove whether this phenomenon relates to global warming. Long-term rainfall analysis showed that the topography blocked water vapor to the western, southern, and mountainous regions, making them distinctly wet or dry. The harmonic curve showed great consistency with the peaks of PWV and rainfall. However, in the northern and eastern parts of the windward side, the time when maximum rainfall occurred each year may be one month later than the time when the maximum PWV value occurred each year. The reason for this difference is likely to be a decrease in the number of autumn typhoons, resulting in a nearly one-month difference in PWV peaks and rainfall peaks. Finally, we analyzed the linear trend of GPS-PWV and temperature for all regions in Taiwan, and found that annual increasing rate of GPS-PWV and temperature of all regions are within 0.4–0.5 mm/year and 0.04–0.11 C°/year, respectively.

Diabetic neuropathic pain (DNP) is a common complication of diabetes characterized by persistent pain. Emerging evidence links astrocytes to mechanical nociceptive processing, and the motor cortex (MCx) is a cerebral cortex region that is known to play a key role in pain regulation. However, the association between MCx astrocytes and DNP pathogenesis remains largely unexplored. Here, we studied this association using designer receptors exclusively activated by designer drugs to specifically manipulate MCx astrocytes. We proved that the selective inhibition of MCx astrocytes reduced DNP in streptozocin (STZ)-induced DNP models and discovered a potential mechanism by which astrocytes release cytokines, including TNF-α and IL-1β, to increase neuronal activation in the MCx, thereby regulating pain. Together, these results demonstrate a pivotal role for MCx astrocytes in DNP pathogenesis and provide new insight into DNP treatment strategies.

BACKGROUND We investigated the influence of dexmedetomidine on the emergence agitation of pediatric patients after ophthalmologic operation under general anesthesia using sevoflurane. METHODS We selected 90 patients that were administered pediatric ophthalmologic operation for the study. The patients were randomly divided into 3 groups according to the administration way of drugs, i.e. the normal saline group (Group S, n = 30), the midazolam group (Group M, n = 30) and the dexmedetomidine group (Group D, n = 30). For all patients, anesthesia induction was performed using sevoflurane before anesthesia, and the anesthesia was maintained in the operation with a combination of sevoflurane and remifentanil; laryngeal mask airway (LMA) was used for assisted ventilation. 10 minutes before the end of operation, 15mL of 0.9% normal saline, 0.05mg/kg of midazolam and 0.5μg/kg of dexmedetomidine were administered to Group S, Group M and Group D, respectively. After the operation, we observed the awakening time, time of the LMA removal as well as the recovery time in the post anesthesia care unit (PACU) of patients in all three groups. We evaluated the postoperative condition of sedation and agitation of the patients using Ramsay sedation scale, 5-point scale and pediatric anesthesia emergence deliriums scale (PAED) and performed statistical analysis. RESULTS In the comparisons of awakening time, time of the LMA removal as well as the recovery time, we found that Group M was the longest sequentially followed by Group D and Group S with statistically significant differences (P < 0.05). While the comparison of the scores of Ramsay sedation scale revealed that Group D scored highest followed by Group M and Group S with statistically significant differences (P < 0.05), both of the comparisons of the scores of 5-point scale and PAED scale showed that Group D scored the lowest, followed by Group M and Group S in sequence with statistically significant differences (P < 0.05). CONCLUSIONS Dexmedetomidine can significantly lower the incidence of emergence agitation of pediatric patients after the ophthalmologic operation under sevoflurane anesthesia.

Although corticosteroids and alcohol are two major risk factors for nontraumatic osteonecrosis of the femoral head (NONFH), the effects of other factors have rarely been studied, thereby making early diagnosis and treatment of NONFH difficult. This study aimed to develop and validate a nomogram to NONFH, but patients with alcohol- and steroid-related NONFH are not at all taken into account in this study. A training cohort of 790 patients (n = 434, NONFH; n = 356, femoral neck fractures [non-NONFH]) diagnosed in our hospital from January 2011 to December 2016 was used for model development. A least absolute shrinkage and selection operator (lasso) regression model was used for date dimension reduction and optimal predictor selection. A predictive model was developed from univariate and multivariate logistic regression analyses. Performance characterisation of the resulting nomogram included calibration, discriminatory ability, and clinical usefulness. After internal validation, the nomogram was further evaluated in a separate cohort of 300 consecutive patients included between January 2017 and December 2018. The simple prediction nomogram included five predictors from univariate and multivariate analyses, including gender, total cholesterol levels, triglyceride levels, white blood cell count, and platelet count. Internal validation showed that the model had good discrimination [area under the receiver operating characteristic curve (AUC) = 0.80] and calibration. Good discrimination (AUC = 0.81) and calibration were preserved in the validation cohort. Decision curve analysis showed that the predictive nomogram was clinically useful. The simple diagnostic nomogram, which combines demographic data and laboratory blood test results, was able to quantify the probability of NONFH in cases of early screening and diagnosis.

HCC (hepatocellular carcinoma) is a major health threat for the Chinese population and has poor prognosis because of strong resistance to chemotherapy in patients. For instance, a considerable challenge for the treatment of HCC is sorafenib resistance. The aberrant glucose metabolism in cancer cells aerobic glycolysis is associated with resistance to chemotherapeutic agents. Drug-resistance cells and tumors were exposed to sorafenib to establish sorafenib-resistance cell lines and tumors. Western blotting and real-time PCR or IHC staining were used to analyze the level of CLCF1 in the sorafenib resistance cell lines or tumors. The aerobic glycolysis was analyzed by ECAR assay. The mechanism mediating the high expression of CLCF1 in sorafenib-resistant cells and its relationships with miR-130-5p was determined by bioinformatic analysis, dual luciferase reporter assays, real-time PCR, and western blotting. The in vivo effect was evaluated by xenografted with nude mice. The relation of CLCF1 and miR-30a-5p was determined in patients’ samples. In this study, we report the relationship between sorafenib resistance and increased glycolysis in HCC cells. We also show the vital role of CLCF1 in promoting glycolysis by activating PI3K/AKT signaling and its downstream genes, thus participating in glycolysis in sorafenib-resistant HCC cells. Furthermore, we also show that miR-30a-5p directly targets CLCF1 and that sorafenib-mediated suppression of miR-30a-5p results in the upregulation of CLCF1 in HCC cells resistant to sorafenib. We also found that when a cholesterol modified agomiR-30a-5p was delivered systemically to mice harboring sorafenib-resistant HCC tumors, tumor growth decreased significantly. There is an uncharacterized mechanism of biochemical resistance to hormone therapies orchestrated by the miR-30a-5p/CLCF1 axis to mediate sorafenib resistance and aerobic glycolysis in HCC. Therefore, this study indicates that targeting the miR-30a-5p/CLCF1 axis may hold promise for therapeutic intervention in HCC sorafenib resistance patients.

Background Sentinel lymph node biopsy (SLNB) plays a vital role in breast cancer surgery, and the identified number of sentinel nodes determines its accuracy for representing the status of the axillae. There are two types of tumor biopsies in breast cancer: preoperative and intraoperative biopsies. We compared the effects of the two different biopsies on the results of SLNB. Methods Patients with clinical stages T1–3, N0 (cT1-3 N0) tumors were enrolled in this study. A total of 53% of patients received preoperative tumor biopsy, and 47% received intraoperative excisional biopsy. To identify the sentinel lymph nodes, patients received dual tracer injection. The number of SLNs detected and the false-negative rate were compared between groups. Results A total of 204 patients were enrolled, 108 received preoperative tumor biopsy, and 96 received intraoperative excisional biopsy. Among all the patients, 160 received axillary lymph node dissection (ALND) following SLNB. Preoperative tumor biopsy detected more SLNs than intraoperative biopsy (mean rank 113.87 vs. 90.9, p = 0.004). The false-negative rates in the preoperative and intraoperative tumor biopsy groups were 3% and 18%, respectively. Conclusions Patients in the preoperative tumor biopsy group had more SLNs identified than intraoperative biopsy patients. The false-negative rate was also lower in the preoperative biopsy group.

Accurate classification of electrocardiogram (ECG) signals is of significant importance for automatic diagnosis of heart diseases. In order to enable intelligent classification of arrhythmias with high accuracy, an accurate classification method based intelligent ECG classifier using the fast compression residual convolutional neural networks (FCResNet) is proposed. In the proposed method, the maximal overlap wavelet packet transform (MOWPT), which provides a comprehensive time-scale paving pattern and possesses the time-invariance property, was utilized for decomposing the original ECG signals into sub-signal samples of different scales. Subsequently, the samples of the five arrhythmia types were utilized as input to the FCResNet such that the ECG arrhythmia types were identified and classified. In the proposed FCResNet model, a fast down-sampling module and several residual block structural units were incorporated. The proposed deep learning classifier can substantially alleviate the problems of low computational efficiency, difficult convergence and model degradation. Parameter optimizations of the FCResNet were investigated via single-factor experiments. The datasets from MIT-BIH arrhythmia database were employed to test the performance of the proposed deep learning classifier. An averaged accuracy of 98.79% was achieved when the number of the wide-stride convolution in fast down-sampling module was set as 2, the batch size parameter was set as 20 and wavelet subspaces of low frequency bands in MOWPT were selected as input of the classifier. These analysis results were compared with those generated by some comparison methods to validate the superiorities and enhancements of the proposed method.

Background Esophageal adenocarcinoma is often associated with late diagnoses, poor prognoses, significant morbidities, and high mortality rates. Aberrant expression of Wnt/β-catenin signal pathways were observed in the tumorigenesis and metastasis of esophageal adenocarcinoma. Sorting nexins 3 has been shown to participate in Wnt protein sorting and regulate Wnt/β-catenin signal transduction. Thus, we studied the role and molecular mechanism of sorting nexins 3 in esophageal adenocarcinoma. Methods Tissue microassay were used to analyze the expression of sorting nexins 3 in esophageal adenocarcinoma tissue and its relationship with survival rate. Using in vivo and in vitro models, we further investigated the effect of sorting nexins 3 on tumor growth and metastasis and underling mechanism. Results Immunohistochemical staining of human esophageal adenocarcinoma tissue microassay revealed an increased sorting nexins 3 level in esophageal adenocarcinoma tissue and high expression of sorting nexins 3 correlated with the poor prognosis. In vitro study showed that sorting nexins 3 knockdown suppressed esophageal adenocarcinoma cell invasion, metastasis, and epithelial-mesenchymal translation (EMT) process, and this result was confirmed by in vivo tumor metastasis assays. Moreover, we further proved that sorting nexins 3 affected cell invasion and EMT through Wnt/β-catenin signal pathway. Conclusion Our data provided strong evidence that sorting nexins 3 played a critical role in esophageal adenocarcinoma metastasis through Wnt/β-catenin signal pathway.

Objective: To explore the relationship between cerebrospinal fluid-contacting neurons (CSF-cNs) and endogenous neural progenitor cells (ENPCs) and whether CSF-cNs are involved in nerve repair after spinal cord injury (SCI).Methods: Cholera toxin B-horseradish peroxidase complex (CB-HRP) and cholera toxin B conjugated with saporin (CB-SAP) were injected into the lateral ventricles of spinal cord injured rats to mark and destroy the CSF-cNs. Then the rats in the experimental group were injured by SCI. Observe the content and co-expression of CSF-cNs and ENPCs in rats of each group, and observe the recovery of motor function after SCI in each group.Results: After the destruction of CSF-cNs, the number of ENPCs decreased significantly in the long term after the surgery, and the recovery of motor function also deteriorated as compared to the group with intact CSF-cNs. Meanwhile some cells in the spinal cord express both the biological marker of CSF-cNs and ENPCs.Conclusion: This study shows that the population of ENPCs and motor function recovery in SCI rats declined after the destruction of CSF-cNs, suggesting that CSF-cNs affect the ENPCs population and may be involved in the recovery of neural function after SCI.

Purpose To characterize the relationship between mean and sectoral variation of anterior chamber angle (ACA) width using anterior segment (AS)-OCT. Design Cross-sectional study with sectoral variation of anterior chamber angle width as the main outcome measure. Participants Participants 50 years of age or older were identified from the Chinese American Eye Study (CHES), a population-based epidemiologic study in Los Angeles, California. Methods Participants underwent a complete ocular examination including gonioscopy and AS-OCT imaging. Primary angle-closure disease (PACD) was defined as inability to visualize pigmented trabecular meshwork in 3 or more quadrants. Four AS-OCT images from 1 eye per participant were analyzed, and parameters describing ACA width were measured at 500 and 750 μm from the scleral spur: angle opening distance (AOD500 and AOD750), trabecular iris space area (TISA500 and TISA750), and scleral spur angle (SSA500 andSSA750). The relationship between mean and sectoral variation of ACA width was assessed using locally weighted scatterplot smoothing (LOWESS) regression, change-point analyses, and Spearman correlation coefficients. Results Six hundred seventy-four eyes (337 with PACD, 337 without PACD) from 674 participants were analyzed. Overall, sectoral variation of ACA width decreased as mean ACA width decreased. This relationship was divided into 2 phases based on the change-point analysis. Sectoral variation of ACA width was correlated strongly and significantly (P Conclusions Correlations between mean and sectoral variation of ACA width strengthen as the severity of angle narrowing worsens. This relationship likely reflects anatomic changes related to chronic angle closure and may be relevant for refining current definitions and management of PACD.

Parkinson’s disease (PD) is a multi-system neurodegenerative disorder. Patients with PD often suffer chronic pain. In the present study, we investigated motor, sensory and emotional changes in three different PD mice models. We found that 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP)-treatment caused significant changes in all measurements. Mechanical hypersensitivity of PD model induced by MPTP peaked at 3 days and persisted for at least 14 days. Using Fos transgenic mice, we found that neurons in the anterior cingulate cortex (ACC) were activated after MPTP treatment. Inhibiting ACC by bilateral microinjection of muscimol significantly reduced mechanical hypersensitivity and anxiety-like responses. By contrast, MPTP induced motor deficit was not affected, indicating ACC activity is mostly responsible for sensory and emotional changes. We also investigated excitatory synaptic transmission and plasticity using brain slices of MPTP treated animals. While L-LTP was blocked or significantly reduced. E-LTP was not significantly affected in slices of MPTP treated animals. LTD induced by repetitive stimulation was not affected. Furthermore, we found that paired-pulse facilitation and spontaneous release of glutamate were also altered in MPTP treated animals, suggesting presynaptic enhancement of excitatory transmission in PD. Our results suggest that ACC synaptic transmission is enhanced in the animal model of PD, and cortical excitation may play important roles in PD related pain and anxiety.

The classification of electroencephalogram (EEG) signals is of significant importance in brain computer interface (BCI) systems. Aiming to achieve intelligent classification of motor imagery EEG types with high accuracy, a classification methodology using the wavelet packet decomposition and the proposed deep residual convolutional networks (DRes-CNN) is proposed. Firstly, EEG waveforms are segmented into sub-signals. Then the EEG signal features are obtained through the wavelet packet decomposition algorithm, and some selected wavelet coefficients are retained and reconstructed into EEG signals in their respective frequency bands. Subsequently, the reconstructed EEG signals were utilized as input of the proposed deep residual convolutional networks to classify EEG signals. Finally, EEG types of motor imagination are classified by the DRes-CNN classifier intelligently. The datasets from BCI Competition were used to test the performance of the proposed deep learning classifier. Classification experiments show that the average recognition accuracy of this method reaches 98.76%. The proposed method can be further applied to the BCI system of motor imagination control.

Indoxyl sulphate (IS), a protein-bound uremic toxin that dramatically increases in the sera of patients with end-stage renal disease (ESRD), is poorly removed by conventional haemodialysis (HD). The purpose of this study was to explore whether the addition of water-soluble sorbent poly-β-cyclodextrins (PCDs) to dialysate can increase the clearance of IS in uremic rats in vivo.Male SD rats (450-550 g, n = 18) with nephrectomy plus IS injection (10-mg/kg) were randomly divided into three groups: 1. The HD group (n = 6): conventional HD for 4 h; 2. the 2% PCD group: 2% PCD added to the dialysate, HD for 4 h; and 3. the 4% PCD group: 4% PCD added to the dialysate, HD for 4 h. The serum IS levels in model rats were similar to those of ESRD patients. A stable and safe rat HD treatment mode was established by adjusting the vascular access, blood flow rate, dialysate flow rate, dialysis pipe, dialysate configuration, temperature, treatment environment, and other aspects.Our study found that adding 2% PCD to dialysate significantly improved the clearance of IS approximately twofold compared with conventional HD. Further increasing the PCD concentration to 4% did not increase IS clearance.Therefore, our study showed that adding water-soluble sorbent PCDs to dialysate significantly improved the clearance of IS in uremic rats in vivo.

Background: The performance of chest radiography-based age and sex prediction has not been well validated. We used a deep learning model to predict the age and sex of healthy adults based on chest radiographs (CXRs). Methods: In this retrospective study, 66,643 CXRs of 47,060 healthy adults were used for model training and testing. In total, 47,060 individuals (mean age ± standard deviation, 38.7 ± 11.9 years, 22,144 males) were included. By using chronological ages as references, mean absolute error (MAE), root mean square error (RMSE), and Pearson’s correlation coefficient were used to assess the model performance. Summarized class activation maps were used to highlight the activated anatomical regions. The area under the curve (AUC) was used to examine the validity for sex prediction. Results: When model predictions were compared with the chronological ages, the MAE was 2.1 years, RMSE was 2.8 years, and Pearson’s correlation coefficient was 0.97 (p &lt, 0.001). Cervical, thoracic spines, first ribs, aortic arch, heart, rib cage, and soft tissue of thorax and flank seemed to be the most crucial activated regions in the age prediction model. The sex prediction model demonstrated an AUC of &gt, 0.99. Conclusion: Deep learning can accurately estimate age and sex based on CXRs.

Background One of the surgical treatments for necrotising enterocolitis (NEC) is to resect the necrotic bowel and defunction the gut by stoma, which can come with severe complications impacting infant growth. Human breastmilk feeding has been proved to prevent NEC, world-widely. This study is to identify whether human breastmilk could reduce the incidence of stoma related complications in NEC patients after primary surgery.MethodsA retrospective chart review was done on patients who had intestine resection and stoma for NEC in the period from 2015-1-1 to 2021-4-30 at Anhui Provincial Children’s Hospital (APCH). Demographics, feeding methods (human milk feeding versus formula milk feeding) and stoma related complications were collected, and the factors, potentially associated with stoma related complications, were analysed. ResultsA total of 58 patients, including 35 males and 23 females, had stoma for NEC. The mean gestational age was 34 weeks (28 to 40). The mean body weight at surgery was 2.83kg (1.03 to 4.80). Before surgery, 38 patients had perforation. Additionally, 46 patients had ileostomy; 12 had colostomy. After primary operation, 40 of them were fed with human breastmilk while 18 of them were fed with formula milk. 26 of 58 patients had stoma related complications, including fluid/electronic imbalance, stoma prolapse, and stoma stenosis. Feeding methods and gestational age were found significantly related to stoma related complications via a binary logistical multivariable analysis.ConclusionsIn this study, the most frequent stoma related complication was fluid/electronic imbalance. Younger gestational age was identified as a risk factor associated with stoma related complications; human breastmilk feeding can benefit patients against these complications.

Background Multiple acyl-CoA dehydrogenase deficiency (MADD) is a riboflavin-responsive lipid-storage myopathy caused by mutations in the EFTA, EFTB or ETFDH genes. We report a Chinese family of Southern Min origin with two affected siblings with late-onset riboflavin-responsive MADD due to a homozygous c.250G > A EFTDH mutation and review the genetic epidemiology of the c.250G > A mutation. Case presentation Both siblings presented with exercise-induced myalgia, progressive proximal muscle weakness and high levels of serum muscle enzymes and were initially diagnosed as polymyositis after a muscle biopsy. A repeat biopsy in one sibling subsequently showed features of lipid storage myopathy and genetic analysis identified a homozygous mutation (c.250G > A) in the ETFDH gene in both siblings and carriage of the same mutation by both parents. Glucocorticoid therapy led to improvement in muscle enzyme levels, but little change in muscle symptoms, and only after treatment with riboflavin was there marked improvement in exercise tolerance and muscle strength. The frequency and geographic distribution of the c.250G > A mutation were determined from a literature search for all previously reported cases of MADD with documented mutations. Our study found the c.250G > A mutation is the most common EFTDH mutation in riboflavin-responsive MADD (RR-MADD) and is most prevalent in China and South-East Asia where its epidemiology correlates with the distribution and migration patterns of the southern Min population in Southern China and neighbouring countries. Conclusions Mutations in ETFDH should be screened for in individuals with lipid-storage myopathy to identify patients who are responsive to riboflavin. The c.250G > A mutation should be suspected particularly in individuals of southern Min Chinese background.

Bionic design of flying robots based on natural models has become a hot topic in mechanical engineering. The research going on in this direction considers that there is a lot to learn from flying animals such as birds, insects, and bats, from walking on the ground to getting enough power to be airborne. To get an efficient design of flying robots, we must better understand the origin of flight. This paper focuses on the review of avian flight and its possible application in the design of flying robots. Different hypotheses have been proposed to tackle the origin and evolution of avian flight from cursorial dinosaurs to modern birds, including the famous ground-up and tree-down theories. During the past decade, discoveries of feathered and winged dinosaurs from Liaoning, China, strongly supported the theory that birds originated from theropod dinosaurs. The transition from running on the ground to maneuver in the sky involves various stages of flights and plumages, which can be now illustrated by several representative paravian dinosaurs from Liaoning. Those fossils provide good research bases for the design of flying robots. Microraptor is one of those important transitional stages in the evolution of flight. This paravian dinosaur is characterized by the presence of pennaceous feathers along both its arms and its legs, but how it could actually fly is still debated. It is of course difficult to evaluate the flight performances of an extinct animal, but aerodynamics of a four-wing robot can be developed to get some knowledge about its flying capacity. Fossil and living flying animals with different morphologies, stability, and control mechanism can be a source of inspiration for designing socially relevant products.

Among the different arterial accesses, the femoral access is the main approach for intraoperative angiography (IOA) performed in a prone position. Without a standardized protocol, however, the application of prone IOAs in intracranial arteriovenous malformation (AVM) or arteriovenous fistula (AVF) surgery remains limited by its procedural complexity. This study describes the detailed protocol for prone IOA through a transfemoral approach and highlights several refinements in preparing this procedure. This study retrospectively reviewed the intracranial or high cervical AVM/AVF surgical cases in which both resection and IOA were performed in the prone or three-quarter prone position. Extended femoral sheath approaches and radiolucent head clamps were used in all cases. An aneurysm clip, serving as a localization landmark in IOA, was routinely placed within the surgical field. The IOA imaging, clinical impact of IOA, and complications related to the procedure were recorded. A total of six AVM and three AVF cases, operated on in the prone (n = 7) or three-quarter prone (n = 2) positions, were included. Multiple vessel injections were required in 66.7% of cases, and IOA was successfully performed in every intended vessel. All IOA images were adequate for interpretation, except for two cases in which the non-radiolucent component of the head clamp obscured the region of interest in the lateral views. Incomplete occlusion was identified in two patients, and the aneurysm clip provided precise guidance in localizing the residual nidus. Final IOA confirmed complete lesion removal in all cases, and there were no IOA-related complications. Three key steps in setting-up a prone IOA procedure for intracranial AVM/AVF surgery are proposed: (1) utilize an extended femoral sheath approach, (2) establish a localization landmark with an aneurysm clip and (3) avoid possible image interference from the non-radiolucent component of the head clamp.

This paper proposes a novel planar type lightweight current collector for proton exchange membrane fuel cells (PEMFC) designed for low power portable applications. The proposed lightweight current collector, which is composed of a substrate, electrical conduction layer and corrosion resistance layer, combines the conventional metal sheet/mesh for current collecting and substrate together to reduce the possible distortion during operation caused by the mismatch due to large different mechanical properties between components. The current collector adopts FR-4 as the substrate material. The electrical conduction layer is made via coating a copper thin film using a thermo-evaporation layer. The corrosion resistance layer is made via coating a graphene thin film using spin coating and a vacuum oven process. Fabricated current collector sheet resistance measurements are conducted. The complete current collectors are assembled into a single cell PEMFC with both forced convection air-breathing cathode and self-air-breathing cathode. The related performance and stability experiments were conducted to investigate the feasibility for further applications.

Itch contagion has been reported in human when people watch someone scratching in a video. The basic mechanism of contagious itch induced by scratching video is still being investigated. A recent study has reported that adult mice showed itch like responses after watching itch-like video or mice showing itching responses. However, such contagious itch behaviors failed to be reproduced by another study by repeating the same experiments of viewing itching mice. It is unclear if contagious itch induced by seeing itching video may be reproducible. In the present study, we used a four-iPad paradigm to repeat these experiments, and found that mice showed no significant itch-like responses after watching itching video of mice. To test if mice actually can see the video, we placed mirrors at the same location. Interestingly, mice showed altered activities in the open field with the mirrors. Finally, in healthy subjects, we found that viewing human itch video did cause itch sensation or responses. Our results indicate that the mouse model may not appropriate for studying contagious itch in humans.

It is the first mission for a landing gear retraction system to extend the structure during the phases of take-off and landing of the flight. Besides, the structure should be available to improve the reliability, strength and stability of the system while reducing the influence of the landing gear on the total drag. However, a large number of airplane accidents are due to the malfunctions or failures of the landing gear retraction system. In this paper, a novel design of retraction system is proposed. Instead of having only one side-stay to execute the desired motion, this new design proposed an over-constrained mechanism with four side-stays, which augments the structural strength and stability of the landing gear system with six over constraints. With such configuration, a second actuating motor to retract the landing gear can be inserted regardless of the first actuator to augment the reliability on the execution of the mechanism. Analyses on the properties of the landing gear retraction system with four side-stays show that the landing gear strut has a vertical motion, which decreases the working and storage spaces used for the system. Finally, this paper examines the statics and the stiffness coefficients of the retraction system with respect to its structure parameters. This provides the optimum structure for the landing gear system in terms of strength and reliability.

Text classification is one of the most important and typical tasks in Natural Language Processing (NLP) which can be applied for many applications. Recently, deep learning approaches has shown their advantages in solving text classification problem, in which Convolutional Neural Network (CNN) is one of the most successful model in the field. In this paper, we propose a novel deep learning approach for categorizing text documents by using scope-based convolutional neural network. Different from window-based CNN, scope does not require the words that construct a local feature have to be contiguous. It can represent deeper local information of text data. We propose a large-scale scope-based convolutional neural network (LSS-CNN), which is based on scope convolution, aggregation optimization, and max pooling operation. Based on these techniques, we can gradually extract the most valuable local information of the text document. This paper also discusses how to effectively calculate the scope-based information and parallel training for large-scale datasets. Extensive experiments have been conducted on real datasets to compare our model with several state-of-the-art approaches. The experimental results show that LSS-CNN can achieve both effectiveness and good scalability on big text data.

The classification of electrocardiogram (ECG) signals is very important for the automatic diagnosis of heart disease. Traditionally, it is divided into two steps, including the step of feature extraction and the step of pattern classification. Owing to recent advances in artificial intelligence, it has been demonstrated that deep neural network, which trained on a huge amount of data, can carry out the task of feature extraction directly from the data and recognize cardiac arrhythmias better than professional cardiologists. This paper proposes an ECG arrhythmia classification method using two-dimensional (2D) deep convolutional neural network (CNN). The time domain signals of ECG, belonging to five heart beat types including normal beat (NOR), left bundle branch block beat (LBB), right bundle branch block beat (RBB), premature ventricular contraction beat (PVC), and atrial premature contraction beat (APC), were first transformed into time-frequency spectrograms by short-time Fourier transform. Subsequently, the spectrograms of the five arrhythmia types were utilized as input to the 2D-CNN such that the ECG arrhythmia types were identified and classified finally. Using ECG recordings from the MIT-BIH arrhythmia database as the training and testing data, the classification results show that the proposed 2D-CNN model can reach an averaged accuracy of 99.00%. On the other hand, in order to achieve optimal classification performances, the model parameter optimization was investigated. It was found when the learning rate is 0.001 and the batch size parameter is 2500, the classifier achieved the highest accuracy and the lowest loss. We also compared the proposed 2D-CNN model with a conventional one-dimensional CNN model. Comparison results show that the 1D-CNN classifier can achieve an averaged accuracy of 90.93%. Therefore, it is validated that the proposed CNN classifier using ECG spectrograms as input can achieve improved classification accuracy without additional manual pre-processing of the ECG signals.

The flight of bats is comparatively less documented and understood than birds and insects and may provide novel inspiration for the design of flapping flight robots. This study captured the natural flight of short-nosed fruit bats (Cynopterus sphinx) by an optical motion capture system, “OptiTrack”, with pasted markers on the wings and body to reconstruct the flight parameters. Due to the self-occlusion at some moments, points on the membrane wings cannot be captured by any cameras. To draw a smooth trajectory, it is desired to reconstruct all missing data. Therefore, an algorithm is proposed by using numerical techniques, accompanied by modern mathematical and computational tools, to envisage the missing data from the captured flight. The least-square fitted polynomial engendered the parameter equations for x-, y-, and z-coordinates of marked points which were used to reconstruct the trajectory of the flight. The parameter equations of position coordinates were also used to compute the morphological and aerodynamic characteristics of the flight. The most outstanding contribution of the work is that not only the trajectory, velocity, and velocity field but also the morphing areas of the membrane wings were recreated using the reconstructed data. These data and reconstructed curves of trajectory and velocity field will be used for the further aerodynamic analysis and mechanism design of the flapping robot. This method can also be generalized to reconstruct the performance parameters of any other animals for bionic design.

With the widespread occurrence of aquaculture diseases and the broad application of antibiotics, drug-resistant pathogens have increasingly affected aquatic animals’ health. Marine probiotics, which live under high pressure in a saltwater environment, show high potential as a substitute for antibiotics in the field of aquatic disease control. In this study, twenty strains of non-hemolytic bacteria were isolated from the intestine of wild oysters and perch, and a model of Caenorhabditis elegans infected by Vibrio anguillarum was established. Based on the model, ML1206, which showed a 99% similarity of 16S rRNA sequence to Planococcus maritimus, was selected as a potential marine probiotic, with strong antibacterial capabilities and great acid and bile salt tolerance, to protect Caenorhabditis elegans from being damaged by Vibrio anguillarum. Combined with plate counting and transmission electron microscopy, it was found that strain ML1206 could significantly inhibit Vibrio anguillarum colonization in the intestinal tract of Caenorhabditis elegans. Acute oral toxicity tests in mice showed that ML1206 was safe and non-toxic. The real-time qPCR results showed a higher expression level of genes related to the antibacterial peptide (ilys-3) and detoxification (ugt-22, cyp-35A3, and cyp-14A3) in the group of Caenorhabditis elegans protected by ML1206 compared to the control group. It is speculated that ML1206, as a potential probiotic, may inhibit the infection caused by Vibrio anguillarum through stimulating Caenorhabditis elegans to secrete antibacterial effectors and detoxification proteins. This paper provides a new direction for screening marine probiotics and an experimental basis to support the potential application of ML1206 as a marine probiotic in aquaculture.

Background Respiratory syncytial virus (RSV) is a leading cause of acute lower respiratory infection globally. There are vaccine candidates in development, but a systematic review on immunogenicity and safety of vaccine is lacking. Methods This systematic review of RSV vaccine clinical trials was undertaken using four databases. Searches were conducted using both controlled vocabulary terms such as “Respiratory Syncytial Virus, Human,” “Respiratory Syncytial Virus Infections,” “Respiratory Syncytial Virus Vaccines,” “Immunization,” “Immunization Programs” and “Vaccines” and corresponding text word terms. The included studies were limited to clinical trials published from January 2000 to 31 December 2020. RSV infection case was defined as RSV‐associated medically attended acute respiratory illness (MAARI) or RSV infection by serologically confirmed test (Western blot) during the RSV surveillance period. We calculated the relative risk of each vaccine trial with RSV infection case. Results Of 6306 publications, 38 were included and data were extracted covering four major types of RSV vaccine candidates, these being live‐attenuated/chimeric (n = 14), recombinant‐vector (n = 6), subunit (n = 12) and nanoparticle vaccines (n = 6). For RSV infection cases, nine trials were involved and none of them showed a vaccine‐related increased MAARI during RSV surveillance season. Conclusion LID ∆M2‐2, MEDI M2‐2, RSVcps2 and LID/∆M2‐2 /1030s (live‐attenuated) were considered the most promising vaccine candidates in infant and children. In the elderly, a nanoparticle F vaccine candidate and Ad26.RSV.preF were considered as two potential effective vaccines. A promising maternal vaccine candidate is still lacking.

Gas sensor technology is widely utilized in various areas ranging from home security, environment and air pollution, to industrial production. It also hold great promise in non-invasive exhaled breath detection and an essential device in future internet of things. The past decade has witnessed giant advance in both fundamental research and industrial development of gas sensors, yet current efforts are being explored to achieve better selectivity, higher sensitivity and lower power consumption. The sensing layer in gas sensors have attracted dominant attention in the past research. In addition to the conventional metal oxide semiconductors, emerging nanocomposites and graphene-like two-dimensional materials also have drawn considerable research interest. This inspires us to organize this comprehensive 2020 gas sensing materials roadmap to discuss the current status, state-of-the-art progress, and present and future challenges in various materials that is potentially useful for gas sensors.

In recent years, with the increasing importance of education and the development of technology such as the internet and big data, more and more researchers have applied big data research to the field of education. Although big data contains high value, it can easily lead to information overload. Therefore, researchers have developed an education recommendation system that combines education with big data to find valuable information from massive data. Based on the user's historical behavior, the recommendation system can find out the user's interest characteristics, analyze the user's needs and interests, and thereby recommend content that the user is interested in. But when it comes to new users or new products, the recommendation system can not find information about their preferences, which can easily cause data sparseness and cold start problem. In this paper, we propose a cold-start recommendation model for interests, which can enhance the usability of user-related data. The model first uses the Pearson coefficient to calculate the learning interest perception relationship between users with temporal context. Second, based on this model, we use neural network to analyze the semantics of relevant data. In order to find suitable relevant data for recommendation, we use the KNN algorithm by reducing the number of neural network outputs. Finally, the experimental results are proved from the real data of Douban book, experiments show that cold-start recommendation model for learning interests solves the problem of data sparseness and cold start to a certain extent that is compared with the traditional recommendation model based on collaborative filtering algorithm.

ObjectivesThe NCCN guidelines recommend that the addition of bevacizumab should be considered in metastatic breast cancers in some circumstances, but there are no recommendations for the similar antiangiogenic drug apatinib. The aim of this study was to evaluate the safety and efficacy of apatinib in metastatic breast cancer patients pretreated with multiline treatment in a real-world setting.Materials and MethodsMetastatic breast cancer patients pretreated with multiline treatment who had apatinib treatment initiated from September 2015 to August 2019 at Shandong Cancer Hospital and Institute were included. The primary endpoints included PFS and OS, and the secondary endpoint was treatment-related toxicity.ResultsA total of 66 patients with metastatic breast cancer received apatinib treatment after failure of multiline chemotherapy in this study. The median PFS and OS of all 66 patients were 6.0 months and 10.0 months, respectively. The clinical beneficial rate was 40.9%. All patients tolerated treatment well, and no patients died of toxicity. The common toxicities of apatinib were hand and foot syndrome, secondary hypertension and fatigue events. The number of prior chemotherapy regimens was significantly associated with DFS and OS. Capecitabine may be a better choice for combination with a longer median OS of 19 months, while apatinib combined with other drugs was 9 months, and the apatinib monotherapy was 10 months.ConclusionApatinib produced moderate efficacy in metastatic breast cancer patients pretreated with multiline treatment with no significant treatment-related adverse events. Apatinib might be a choice for women as a maintenance salvage therapy following multiline chemotherapy failure.

Community driven social media sites are rich sources of knowledge and entertainment and at the same vulnerable to the flames or toxic content that can be dangerous to various users of these platforms as well as to the society. Therefore, it is crucial to identify and remove such content to have a better and safe online experience. Manually eliminating flames is tedious and hence many research works focus on machine learning or deep learning models for automated methods. In this paper, we primarily focus on detecting the insincere content using neural network-based learning methods. We also integrated the profanity features as profanity is correlated with honesty according to psychology research. We tested our model on the questions datasets from CQA platform to detect the insincere content. Our integrated neural network model enabled us to achieve a high performance of F1-score, 94.01%, compared to the standard machine learning algorithms.

Background: Split-dose (SPD) regimen has been proved more effective than a single-dose (SID) regimen for various drug preparations; however, limited data have focused on morning colonoscopy. We implemented this study to compare the bowel cleanliness and tolerability of a same-day SID versus SPD 2 L polyethylene glycol electrolyte solution (PEG) for morning colonoscopy. Methods: Patients undergoing morning colonoscopy were randomized into two groups, SID or SPD. In the SID group, patients had to complete 2 L PEG between 4 and 6 am on the day of colonoscopy. In the SPD group, patients had to complete 1 L PEG between 8 and 9 pm on the day before followed by another 1 L PEG between 5 and 6 am on the day of colonoscopy. Colonoscopy was performed between 8 and 12 am under anesthesia. Investigators and endoscopists were blinded to the allocation. The primary end point was the effectiveness of bowel cleansing according to the Boston Bowel Preparation Scale (BBPS). The secondary outcomes were polyp detection rate, compliance, tolerability, and patient satisfaction. Results: Overall, there were 147 and 148 patients in the SID and SPD group, respectively. The SPD group had a better quality of bowel preparation than the SID group with a total BBPS score of 7.25 ± 1.53 versus 6.71 ± 1.65 (P = 0.005). No difference in the polyp detection rate was noted, although more polyps were detected in the SPD group. More patients felt acceptable with the bowel preparation regimen in the SPD group compared to the SID group (76% vs. 65%, P = 0.03). The adverse events were more commonly observed in the SID group, presented as nausea and vomiting. Conclusion: For morning colonoscopy, split-dose 2 L PEG is superior to single-dose 2 L PEG by improved bowel preparation, better tolerability, and patient satisfaction.

Endometriosis (EM) in reproductive females has an incidence of 6–10% and greatly affects female fertility, quality of life, and long-term health. The gut microbiota can affect the physiological and pathological processes of humans through various pathways, such as those involving the nervous and endocrine systems and immunity, and it plays important roles in endocrine and inflammatory diseases. Whether the gut microbiota plays a role in EM has gradually attracted researchers’ attention. In the present study, fecal and blood samples were collected from 12 patients with stage 3/4 EM and 12 healthy controls. We performed 16S rRNA high-throughput sequencing to compare the gut microbiota between the EM and control groups. Serum levels of hormones and inflammatory cytokines were measured. We found that compared with the control group, the EM group had a lower α diversity of gut microbiota and a higher Firmicutes/Bacteroidetes ratio. The abundances of various taxa (such as Actinobacteria, Tenericutes, Blautia, Bifidobacterium, Dorea, and Streptococcus) were significantly different between the two groups. The taxon with the highest abundance in the EM group was Prevotella_7, and that in the control group was Coprococcus_2. The serum levels of E2 and IL-8 were significantly higher in the EM group than in the control group (E2: EM group 74.7 ± 22.5 pg/L vs CON group 47.9 ± 12.5 pg/L; IL-8: EM group 6.39 ± 1.59 pg/mL vs CON group 4.14 ± 0.73 pg/mL). Additionally, the gut microbiota of the EM group was enriched for the microbial function categories environmental information processing, endocrine system, and immune system. Correlations were detected between each of Blautia and Dorea abundance and estradiol level and between Subdoligranulum abundance and IL-8 level. This study elucidated the associations between the gut microbiota and both serum hormones and inflammatory factors in EM. However, the findings need to be verified in future studies.

Background: PIK3CA mutations are common genomic alterations in estrogen receptor (ER)-positive breast cancers, currently, the development of selective PI3Kα (phosphatidylinositol 3-kinase α) inhibitors is ongoing. The mechanisms contributing to the anticancer activity of alpelisib in PIK3CA-mutant breast cancer cells and the mechanism of acquired resistance to alpelisib remain elusive. Methods: Drug-sensitive cell lines were exposed to alpelisib to establish alpelisib-resistant cell lines. Western blotting was used to assess changes in protein expression. Apoptosis was evaluated by flow cytometry. In vivo with mouse xenograft models and in vitro colony formation and MTS and assay were carried out to determine the growth inhibitory effects of the tested drugs. Protein half-lives were examined and proteasome inhibitors were used to estimate protein degradation. Gene knockdown was carried out using shRNA or siRNA. Results: In the present study, we report the potent induction of apoptosis by alpelisib in PIK3CA-mutant breast cancer cell lines. AKT phosphorylation suppression, AKT/Foxo3a-dependent Bim induction, and AKT/GSK-3β-dependent Mcl-1 degradation were observed. Apoptosis induced by alpelisib was attenuated by Mcl-1 (4A) overexpression or Bim suppression. Furthermore, alpelisib could not modulate Mcl-1 or Bim levels in cell lines that were resistant to alpelisib. AKT inhibitor and alpelisib combination restored the sensitivity of alpelisib-resistant cells to growth inhibition and apoptosis in vitro and in vivo. Conclusions: Therefore, modulation of Mcl-1 degradation and AKT-dependent Bim induction are crucial for mediating the resistance and sensitivity of PIK3CA-mutant breast tumor cells to alpelisib, thus making it a productive strategy for overcoming acquired resistance to alpelisib.

In recent years, with the increasing proportion of renewable energy, some system problems have gradually emerged. To reduce the economic cost of system operations and improve power system reliability, renewable power forecasting is an indispensable part. Compared with the deterministic prediction, the probabilistic forecast considers the uncertainty, which helps manage risks and make decisions for power grids. This study proposes a novel probabilistic forecasting method for wind power generation, which includes data preprocessing, adaptive neuro fuzzy inference system (ANFIS) training model with fuzzy c-means clustering algorithm, and post processing of predicted-interval. The input data of the proposed probabilistic forecasting model include the numerical weather prediction (NWP) ensemble wind speeds, NWP spot wind-speed forecasts, and historical wind power measurements. For practical applications, measured data of power generation at actual wind farms were used to compare different forecasting models. The research results demonstrate that the proposed model supports better performance and prediction stability. Furthermore, this work reveals the importance of both data preprocessing and post processing of predicted interval on wind power forecasting. These essential processes greatly improve the performance of the probabilistic wind power forecasts.

Background: Respiratory syncytial virus (RSV) is a leading cause of acute lower respiratory infection globally. There are vaccines in pipeline to prevent it but a systematic review on immunogenicity and safety of vaccine is lacking. Methods: This systematic review of RSV vaccine clinical trials was undertaken using 4 databases. Searches were conducted using both controlled vocabulary terms such as ‘Respiratory Syncytial Virus, Human’, ‘Respiratory Syncytial Virus Infections’, ‘Respiratory Syncytial Virus Vaccines’, ‘Immunization’, ‘Immunization Programs’ and ‘Vaccines’ and corresponding text word terms. The searches for published papers were limited to clinical trials published from January 2000 to August 6th, 2018. RSV infection case was defined as RSV associated medically attended acute respiratory illness (MAARI) or RSV infection by serologically-confirmed test (Western Blot) during the RSV surveillance period. We calculated the relative risk of each vaccine trial with RSV infection case. Results: Of 4395 publications, 24 were included and data were extracted covering 4 major types of RSV vaccine candidates, these being live-attenuated/chimeric (n=9), recombinant-vector (n=10), subunit (n=1) and nanoparticle vaccines (n=4). For RSV infection cases, 7 trials were involved and none of them showed a vaccine-related increased MAARI during RSV surveillance season. Conclusion: LID ∆M2-2, MEDI M2-2, and RSVcps2 (live-attenuated) were considered the most promising vaccine candidates in infant and children. In the elderly, a nanoparticle F vaccine candidate was considered as a potential effective vaccine. Although no promising vaccine was identified from pregnant-women test, RSV F-024 subunit vaccine candidate and an RSV F nanoparticle vaccine showed encouraging results in healthy non-pregnant women.

The classification of electroencephalogram (EEG) signals is of significant importance in brain-computer interface (BCI) systems. Aiming to achieve intelligent classification of EEG types with high accuracy, a classification methodology using sparse representation (SR) and fast compression residual convolutional neural networks (FCRes-CNNs) is proposed. In the proposed methodology, EEG waveforms of classes 1 and 2 are segmented into subsignals, and 140 experimental samples were achieved for each type of EEG signal. The common spatial patterns algorithm is used to obtain the features of the EEG signal. Subsequently, the redundant dictionary with sparse representation is constructed based on these features. Finally, the samples of the EEG types were imported into the FCRes-CNN model having fast down-sampling module and residual block structural units to be identified and classified. The datasets from BCI Competition 2005 (dataset IVa) and BCI Competition 2003 (dataset III) were used to test the performance of the proposed deep learning classifier. The classification experiments show that the recognition averaged accuracy of the proposed method is 98.82%. The experimental results show that the classification method provides better classification performance compared with sparse representation classification (SRC) method. The method can be applied successfully to BCI systems where the amount of data is large due to daily recording.

This paper constructs planar-type graphene thin film current collectors for proton exchange membrane fuel cells (PEMFCs). The present planar-type current collector adopts FR-4 as the substrate and coats a copper thin film using thermal evaporation for the electric-conduction layer. A graphene thin film is then coated onto the current collector to prevent corrosion due to electrochemical reactions. Three different coating techniques are conducted and compared: Spin coating, RF magnetron sputtering, and screen printing. The corrosion rates and surface resistances are tested and compared for the different coating techniques. Single cell PEMFCs with the developed current collectors are assembled and tested. A PEMFC module with two cells is also designed and constructed. The cell performances are measured to investigate the device feasibility.

At present, the overall sensitivity and specificity of blood biomarkers are insufficient for a diagnosis of colorectal cancer (CRC).We analyzed the serum synaptophysin like 1 (sSYPL1) in controls, adenoma patients, CRC patients, pre- and postoperative CRC patients by ELISA.The upregulation of SYPL1 was confirmed in CRC tissues at both mRNA and protein levels. Consistently, sSYPL1 was significantly higher in CRC patients than in either controls (t = 14.50, P 0.0001) or adenoma patients (t = 10.56, P 0.0001) and was associated with lymph node invasion (χsSYPL1 might be an outstanding marker for CRC diagnosis, especially for patients with low CEA levels.

Neurodegenerative diseases, including Alzheimer’s disease (AD) and Parkinson’s disease (PD), are generally featured by neuroinflammation and procedural loss of selectively vulnerable...

Objective. This study aimed at investigating the therapeutic effect and mechanism of pioglitazone metformin complex preparation (PM) in polycystic ovary syndrome (PCOS) comorbid psychological distress. Methods. Seventy-five patients with PCOS comorbid psychological distress were randomly allocated into the PM, metformin, and placebo groups. The primary efficacy measure was the change from baseline to week 12 on the Symptom Checklist 90-R (SCL-90-R) scores. NLRP3 inflammasome, IL-1β, IL-6, TNF-α, and biochemical parameters were determined at baseline and at week 12. The participants were required to meet the criteria for PCOS (Rotterdam, NIH) and psychological distress (any factor scores of SCL−90−R>2). Results. The participants had significantly high scores on the SCL-90-R scales of anxiety and depression. PM significantly decreased anxiety and depression symptom severity (from 2.31±0.75 to 1.65±0.38, p<0.001, and from 2.08±0.74 to 1.61±0.46, p=0.010, at week 12, respectively). PM significantly decreased the expression of NRPL3 and caspase-1. Patients in the PM group experienced a significant reduction in IL-1β (from 98.42±14.38 to 71.76±13.66, p=0.02), IL-6 (from 87.51±8.74 to 71.98±15.87, p=0.02), and TNF-α (from 395.33±88.55 to 281.98±85.69, p=0.04). PM was superior to metformin in reducing total testosterone (2.24±0.74 versus 3.06±0.83, p=0.024, at week 12).Conclusions. This study is the first to reveal that PM alleviates psychological distress via inhibiting NLRP3 inflammasome and improves several markers, including total testosterone.

Anterior segment optical coherence tomography (AS-OCT) is a noncontact in vivo imaging method that provides qualitative and quantitative assessments of the anterior segment and its anatomical structures, including the iridocorneal angle and aqueous outflow pathways. Advances in optical coherence tomography (OCT) technology revolutionized ophthalmology, and AS-OCT imaging has rapidly matured into a versatile tool for clinical examinations and scientific research. AS-OCT imaging provides a complement to gonioscopy and ultrasound biomicroscopy in assessments of the iridocorneal angle, an important anatomical site for evaluation in patients with elevated intraocular pressure. Modern AS-OCT devices can also characterize aqueous outflow structures within the scleral wall, such as the trabecular meshwork, Schlemm’s canal, and collector channels. AS-OCT imaging is of particular interest to glaucoma specialists for its use to assess biometric risk factors for gonioscopic angle closure and primary angle closure disease. It has also been used to evaluate and quantify patient response to laser or surgical treatment. Despite these technological advances and clinical applications, widespread adoption of AS-OCT imaging among eye care providers has been slowed by a variety of factors that limit its method and implementation. However, ongoing research is focused on resolving these limitations, which would greatly enhance the clinical utility of AS-OCT imaging in the future. This chapter discusses these topics and provides an introduction to qualitative and quantitative interpretation of AS-OCT images.

The etiology of oral lichen planus (OLP) is still not clear. The purpose of this study was to explore the role of CXC chemokine receptor 3(CXCR3) and its ligand CXC motif chemokine 10(CXCL10) in the pathogenesis of OLP. We examined the expression of CXCR3 and CXCL10 in OLP patients and healthy controls by quantitative real-time PCR, Western blotting, ELISAs, and immunohistochemistry, respectively. Moreover, we detected the effects of CXCL10/CXCR3 axis on T lymphocyte migration, proliferation and apoptosis by Transwell assays, CCK8 assays, and flow cytometry. We found that the expression of CXCR3 and CXCL10 was significantly increased in OLP patients. In addition, T lymphocyte migration rate of CXCL10 stimulation group was significantly higher than that of control and CXCR3 antagonist groups. After antagonizing CXCR3, the migration ability of T lymphocytes was significantly decreased, and regardless of whether CXCL10 was added in the upper chamber culture medium, the number of migrating cells was similar. The addition of CXCL10 stimulant could stimulate the proliferation of T lymphocytes, but there was no significant difference compared with control group. After antagonizing CXCR3, the proliferation rate of T lymphocytes was significantly reduced. However, there were no significant differences in the apoptosis rates of T lymphocytes between CXCL10 stimulation group, antagonist CXCR3 group, and control group. Due to the change of expression in CXCR3 and CXCL10, and its interaction in mediating the directional migration of peripheral blood T lymphocytes, affecting the proliferation of T lymphocytes, it suggests that CXCL10/CXCR3 axis may be related to the immune mechanism of OLP.

During the past one to two decades, the probabilistic forecasting of a wind-power generation has been regarded as a necessary input to decisions made for the purpose of reliable and economic power systems operations, especially since the penetration of the renewable energy has begun to grow rapidly. Probabilistic forecasting differs from traditional deterministic forecasting in which it takes uncertainty into account. This paper proposes a modified nonparametric method for constructing reliable prediction intervals (PIs). The lower upper bound estimation (LUBE) method is adapted to construct PIs for the wind-power generation, based on the ensemble wind-speed data from the numerical weather prediction system of the Central Weather Bureau of Taiwan. The charged system search (CSS) is used to adjust parameters in LUBE. The performance of the proposed method is examined using datasets from several wind farms in Taiwan. Simulation results demonstrate that the quality of PIs output by the proposed model significantly exceeded that of those constructed using the persistence model with a 1-h-ahead time horizon.

Objectives Our aim was to identify and prevalidate a set of salivary proteins that can distinguish oral squamous cell carcinomas (OSCC) patients from healthy individuals and patients with oral potentially malignant disorders (OPMD). Subjects and methods Proteomes of 60 saliva samples from healthy individuals, OPMD patients, and OSCC patients were assayed using the isobaric tags for relative and absolute quantitation (iTRAQ) method. Enzyme-linked immunosorbent assay (ELISA) was used to prevalidate the candidate biomarkers in an independent sample set (n = 90). Results In total, 246 differentially expressed proteins were identified by comparing each two groups, and 21 proteins were differentially expressed when OSCC was compared with both OPMD and Control. Three proteins, namely, solute carrier family 3 member 2 (SLC3A2), S100 calcium-binding protein A2 (S100A2), and interleukin-1 receptor antagonist protein (IL1RN), were selected as candidate biomarkers. Comparing the OSCC group with the healthy group, the area under curve (AUC) of the three combined biomarkers was 0.89, with a sensitivity of 83.33% and a specificity of 83.33%. Comparing the OSCC group with the OPMD group, the AUC value was 0.87, with a sensitivity of 93.33% and a specificity of 70.00%. Conclusion Our study indicates that salivary proteomics is promising for the discovery of OSCC biomarkers.

BACKGROUND The pathogenesis of oral lichen planus (OLP) may be related to mental factors. In this study, we investigated the molecular mechanism of mental factors in the development of OLP. METHODS The normal control group and OLP patients were tested and evaluated by Zung self-rating anxiety scale and self-rating depression scale. Secondly, Agilent human LncRNA chip technology was used to detect differential genes in the total RNA of the normal control group and OLP patients, and to screen out the differentially expressed genes related to anxiety and depression. Thirdly, we verified the genes at gene level and protein level, respectively. RESULTS Zung self-rating anxiety scale and self-rating depression scale showed that tendency of anxiety and depression in OLP patients is significantly higher than that in normal controls, but there was no significant difference between the erosion form group and the reticular form group; the duration of OLP showed significant negative correlations between degree of anxiety and depression. Microarray analysis showed there were four differential genes (PDE4B, RGS2, SYNGR1, and SYNE1) related to anxiety and depression in OLP patients; real-time qPCR confirmed the expression of PDE4B mRNA was lower in the peripheral blood of normal control group (P < 0.001). The expression of RGS2, SYNGR1, and SYNE1 mRNA was higher in the normal control group (P < 0.05, P < 0.05, P < 0.05). Wes automatic western blot confirmed that the expression of PDE4B protein was lower in the peripheral blood of the normal control group (P < 0.01). CONCLUSION PDE4B gene may play a role in the pathogenesis of OLP.