Miracle-dz/UniFAR-FTUs huggingface dataset:
Development of an Inactivated H7N9 Subtype Avian Influenza Serological DIVA Vaccine Using the Chimeric HA Epitope Approach

DIVA vaccine is a useful tool for eradicating avian influenza, especially for highly pathogenic avian influenza. Several different DIVA strategies have been proposed for avian influenza inactivated whole-virus vaccine, involving the neuraminidase (NA), nonstructural protein 1 (NS1), matrix protein 2 ectodomain (M2e), or HA2 gene. ABSTRACT H7N9 avian influenza virus (AIV) is an emerging zoonotic pathogen, and it is necessary to develop a differentiating infected from vaccinated animals (DIVA) vaccine for the purpose of eradication. H7N9 subtype AIV hemagglutinin subunit 2 glycoprotein (HA2) peptide chips and antisera of different AIV subtypes were used to screen H7N9 AIV-specific epitopes. A selected specific epitope in the HA2 protein of H7N9 AIV strain A/Chicken/Huadong/JD/17 (JD/17) was replaced with an epitope from an H3N2 subtype AIV strain by reverse genetics. The protection and serological DIVA characteristics of the recombinant H7N9 AIV strain were evaluated. The results showed that a specific epitope on the HA2 protein of H7N9 AIV, named the H7-12 peptide, was successfully screened. The recombinant H7N9 AIV with a modified epitope in the HA2 protein was rescued and named A/Chicken/Huadong/JD-cHA/17 (JD-cHA/17). The HA titer of JD-cHA/17 was 10 log2, and the 50% egg infective dose (EID50) titer was 9.67 log10 EID50/ml. Inactivated JD-cHA/17 induced a hemagglutination inhibition (HI) antibody titer similar that of the parent strain and provided 100% protection against high-pathogenicity or low-pathogenicity H7N9 AIV challenge. A peptide chip coated with H7-12 peptide was successfully applied to detect the seroconversion of chickens infected or vaccinated with JD/17, while there was no reactivity with antisera of chickens vaccinated with JD-cHA/17. Therefore, the marked vaccine candidate JD-cHA/17 can be used as a DIVA vaccine against H7N9 avian influenza when combined with an H7-12 peptide chip, making it a useful tool for stamping out the H7N9 AIV. IMPORTANCE DIVA vaccine is a useful tool for eradicating avian influenza, especially for highly pathogenic avian influenza. Several different DIVA strategies have been proposed for avian influenza inactivated whole-virus vaccine, involving the neuraminidase (NA), nonstructural protein 1 (NS1), matrix protein 2 ectodomain (M2e), or HA2 gene. However, virus reassortment, residual protein in a vaccine component, or reduced vaccine protection may limit the application of these DIVA strategies. Here, we constructed a novel chimeric H7N9 AIV, JD-cHA/17, that expressed the entire HA protein with substitution of an H3 AIV epitope in HA2. The chimeric H7N9 recombinant vaccine provides full clinical protection against high-pathogenicity or low-pathogenicity H7N9 AIV challenge. Combined with a short-peptide-based microarray chip containing the H7N9 AIV epitope in HA2, our finding is expected to be useful as a marker vaccine designed for avian influenza.
Overexpression of cyclin‐dependent kinase 1 in esophageal squamous cell carcinoma and its clinical significance

Cyclin‐dependent kinase 1 (CDK1) plays a significant role in certain malignancies. However, it remains unclear whether CDK1 plays a role in esophageal squamous cell carcinoma (ESCC). The aim of this study was to analyze the expression and clinical value of CDK1 in ESCC. CDK1 protein in 151 ESCC tissues and 138 normal esophageal tissues was detected by immunohistochemistry. RNA‐seq of eight pairs of ESCC and adjacent esophageal specimens was performed to evaluate the levels of CDK1 mRNA. Microarray and external RNA‐seq data from 664 cases of ESCC and 1733 cases of control tissues were used to verify the difference in CDK1 expression between the two groups. A comprehensive analysis of all data was performed to evaluate the difference in CDK1 between ESCC tissues and control tissues. Further, functional enrichment analyses were performed based on differentially expressed genes (DEGs) of ESCC and co‐expressed genes (CEGs) of CDK1. In addition, a lncRNA‐miRNA‐CDK1 network was constructed. The expression of CDK1 protein was obviously increased in ESCC tissues (3.540 ± 2.923 vs. 1.040 ± 1.632, P < 0.001). RNA‐seq indicated that the mRNA level of CDK1 was also highly expressed in ESCC tissues (5.261 ± 0.703 vs. 2.229 ± 1.161, P < 0.0001). Comprehensive analysis revealed consistent up‐regulation of CDK1 (SMD = 1.41; 95% CI 1.00–1.83). Further, functional enrichment analyses revealed that the functions of these genes were mainly concentrated in the cell cycle. A triple regulatory network of PVT1‐hsa‐miR‐145‐5p/hsa‐miR‐30c‐5p‐CDK1 was constructed using in silico analysis. In summary, overexpression of CDK1 is closely related to ESCC tumorigenesis.
Flow visualization and force measurement of the clapping effect in bio-inspired flying robots

In this paper, we perform experimental investigations of the aerodynamic characteristics due to wing clapping in bio-inspired flying robots; i.e., micro-air-vehicles (MAVs) that fly by flapping their wings. For this purpose, four flapping MAV models with different levels of clapping (from no clapping at all to full clapping) are developed. The aerodynamic performance of each model is then tested in terms of the average thrust and power consumption at various flapping frequencies. The results show that clapping enhance both thrust and efficiency. To gain some physical insight into the underlying physics behind this clapping-thrust-enhancement, we perform a smoke flow visualization over the wings of the four models at different instants during the flapping cycle.
Sub‐second transient activated patterns to sad expressions in major depressive disorders discovered via hidden Markov model

The pathological mechanisms of major depressive disorders (MDDs) is associated with the overexpression of negative emotions, and the fast transient‐activated patterns underlying overrepresentation in depression still remain to be revealed to date. We hypothesized that the aberrant spatiotemporal attributes of the process of sad expressions are related to the neuropathology of MDD and help to detect the depression severity. We enrolled a total of 96 subjects including 47 patients with MDD and 49 healthy controls (HCs), and recorded their magnetoencephalography data under a sad expression recognition task. A hidden Markov model (HMM) was applied to separate the whole neural activity into several brain states, then to characterize the dynamics. To find the disrupted temporal–spatial characteristics, power estimations and fractional occupancy (FO) of each state were estimated and contrasted between MDDs and HCs. Three states were found over the period of emotional stimuli processing procedure. The early visual stage (0–270 ms) was mainly manifested by state 1, and the emotional information processing stage (270–600 ms) was manifested by state 2, while the state 3 remained a steady proportion across the whole period. MDDs activated statistically more in limbic system during state 2 (p = 0.0045) and less in frontoparietal control network during state 3 (p = 5.38 × 10–5) relative to HCs. Hamilton Depression Rating Scale scores were significantly correlated with the predicted disorder severity using FO values (p = 0.0062, r = 0.3933). Relative to HCs, MDDs perceived the sad contents quickly and spent more time overexpressing the negative emotions. These phenomena indicated MDD patients might easily indulge in negative emotion and neglect other things. Furthermore, temporal descriptors built by HMM could be potential biomarkers for identifying the severity of depression disorders.
Gradient Architecture-Enabled Capacitive Tactile Sensor with High Sensitivity and Ultrabroad Linearity Range.

The sensitivity and linearity are critical parameters that can preserve the high pressure-resolution across a wide range and simplify the signal processing process of flexible tactile sensors. Although extensive micro-structured dielectrics have been explored to improve the sensitivity of capacitive sensors, the attenuation of sensitivity with increasing pressure is yet to be fully resolved. Herein, a novel dielectric layer based on the gradient micro-dome architecture (GDA) is presented to simultaneously realize the high sensitivity and ultrabroad linearity range of capacitive sensors. The gradient micro-dome pixels with rationally collocated amount and height can effectively regulate the contact area and hence enable the linear variation in effective dielectric constant of the GDA dielectric layer under varying pressures. With systematical optimization, the sensor exhibits the high sensitivity of 0.065 kPa-1 in an ultrabroad linearity range up to 1700 kPa, which is first reported. Based on the excellent sensitivity and linearity, the high pressure-resolution can be preserved across the full scale of pressure spectrum. Therefore, potential applications such as all-round physiological signal detection in diverse scenarios, control instruction transmission with combinatorial force inputs, and convenient Morse code communication with non-overlapping capacitance signals are successfully demonstrated through a single sensor device.
Job strain and effort–reward imbalance as risk factors for type 2 diabetes mellitus: A systematic review and meta-analysis of prospective studies

Objectives This systematic review and meta-analysis aimed to synthesize the available data on prospective associations between work-related stressors and the risk of type 2 diabetes mellitus (T2DM) among adult workers, according to the demand–control–support (DCS) and the effort–reward imbalance (ERI) models. Method We searched for prospective studies in PubMed, EMBASE, Web of Science, Scopus, CINHAL and PsychInfo. After screening and extraction, quality of evidence was assessed using the ROBINS-I tool adapted for observational studies. The effect estimates extracted for each cohort were synthesized using random effect models. Results We included 18 studies (reporting data on 25 cohorts) in meta-analyses for job strain, job demands, job control, social support at work and ERI. Workers exposed to job strain had a higher risk of developing T2DM when compared to unexposed workers [pooled rate ratio (RR) 1.16, 95% confidence interval (CI) 1.07–1.26]. This association was robust in several supplementary analyses. For exposed women relative to unexposed women, the RR was 1.35 (95% CI 1.12–1.64). The RR of workers exposed to ERI was 1.24 (95% CI 1.08–1.42) compared to unexposed workers. Conclusions This is the first meta-analysis to find an effect of ERI on the onset of T2DM incidence. It also confirms that job strain increases the incidence of T2DM, especially among women.
Bioinspired solution to finding passageways in foliage with sonar

Finding narrow gaps in foliage is an important component skill for autonomous navigation in densely vegetated environments. Traditional approaches are based on collecting large amounts of data with high spatial resolution. However, the biosonar systems of bats that live in dense habitats demonstrate that finding gaps is possible based on sensors with angular resolutions that are poor compared to technologies such as man-made sonar and lidar. To investigate these capabilities, we have used a biomimetic sonar head to ensonify artificial hedges in the laboratory. We found that a conventional approach based on echo energy performed poorly on detecting gaps with the area under the receiver operating characteristic (ROC) curve ranging from 0.69 to 0.75 depending on the distance to the hedge and gap width. A deep-learning approach based on a convolutional neural network (CNN) operating on the echo spectrograms achieved area under the ROC curve (AUC) values between 0.94 and 0.97. Class activation mapping indicated that the rising flank of the echoes was critical for detecting the gaps. As a consequence, a simple code consisting of first threshold-crossing times was able to almost reproduce the performance of the CNN classifier (AUC 0.9 to 0.95). This demonstrates that the echo waveforms contained patterns that were indicative of a gap in the foliage but did not suffer from the comparatively large beamwidth used.
Design a Novel BCI for Neurorehabilitation Using Concurrent LFP and EEG Features: A Case Study

Objective: Brain-computer interfaces (BCI) that enables people with severe motor disabilities to use their brain signals for direct control of objects have attracted increased interest in rehabilitation. To date, no study has investigated feasibility of the BCI framework incorporating both intracortical and scalp signals. Methods: Concurrent local field potential (LFP) from the hand-knob area and scalp EEG were recorded in a paraplegic patient undergoing a spike-based close-loop neurorehabilitation training. Based upon multimodal spatio-spectral feature extraction and Naïve Bayes classification, we developed, for the first time, a novel LFP-EEG-BCI for motor intention decoding. A transfer learning (TL) approach was employed to further improve the feasibility. The performance of the proposed LFP-EEG-BCI for four-class upper-limb motor intention decoding was assessed. Results: Using a decision fusion strategy, we showed that the LFP-EEG-BCI significantly (p $< $ 0.05) outperformed single modal BCI (LFP-BCI and EEG-BCI) in terms of decoding accuracy with the best performance achieved using regularized common spatial pattern features. Interrogation of feature characteristics revealed discriminative spatial and spectral patterns, which may lead to new insights for better understanding of brain dynamics during different motor imagery tasks and promote development of efficient decoding algorithms. Moreover, we showed that similar classification performance could be obtained with few training trials, therefore highlighting the efficacy of TL. Conclusion: The present findings demonstrated the superiority of the novel LFP-EEG-BCI in motor intention decoding. Significance: This work introduced a novel LFP-EEG-BCI that may lead to new directions for developing practical neurorehabilitation systems with high detection accuracy and multi-paradigm feasibility in clinical applications.
Hope for Ostomates: A Carbon and Zeolite Impregnated Polyester Fabric Inhibits Urine Odor in Cancer Patients: A Randomized Experimental Study

Objective: Many individuals with bladder cancer have undergone a surgical urostomy and often complain of being self-conscious of the unpleasant smell of their own urine. The focus of this study was to test the efficacy of a pouch cover made of a carbon and zeolite containing polyester material to inhibit the smell of urine by comparing two trained dogs’ response time in detecting volatile organic compounds (VOCs) in urine, with and without the fabric covering the samples. Methods: This study used a randomized, blinded experimental design to evaluate the efficacy of a fabric to interfere with two highly trained dogs’ ability to detect specific VOCs present in the urine of prostate cancer patient. Ninety urine samples were analyzed in this study. Results: Prior to the experiment, both dogs accurately detected VOCs in the uncovered test urine samples of men with prostate cancer with a sensitivity and specificity of nearly 100%. Both dogs recognized the “uncovered” urine samples of men with prostate cancer within two seconds. When the test sample was covered with the study fabric, the test urine samples were detected within 30-40 seconds and in some instances the dogs were not able to identify the covered samples, whatsoever. Conclusion: The findings of this study demonstrate that the carbon and zeolite containing polyester fabric did significantly interfere with the ability of the dogs to detect VOCs in urine of men with prostate cancer. The fabric may show promise as a pouch cover in controlling offensive urine odor which many ostomates experience.
General or regional anaesthesia for postpartum haemorrhage—A national population‐based cohort study

Anaesthesia is required to assist the treatment of postpartum haemorrhage (PPH) when manual removal of the placenta or emptying of the uterine cavity is required. The choice between general or regional anaesthesia may depend upon factors such as existing epidural, airway, hypovolaemia, and tradition.
Enhanced Dissolution and In-Vivo Biavailability of Itraconazole Cyclodextrin Complex.

Oral route is the most preferred for administration of drugs owing to its known advantage of better patient compliance. Drugs administered by oral route should dissolve in gastric and intestinal fluid before they permeate through the membrane of GI tract and enter into systemic circulation. So solubility is a prerequisite for absorption of drugs. Co-precipitation of 1:4 (drug: CD) showed higher dissolution as compared to co-precipitation 1:2 (drug: CD) physical mixture (1:2,1:4) ( drug: CD) andpure Itraconazole. Dissolution amounts of co-precipitate increased as the pH of acidic environment increased. Solubility of Itraconazole was improved with higher concentrations of CD. Inclusion complex formation was detected in co-precipite’s as observed in the DSC thermograms. Physical mixture did not show interaction between Itraconazole and CD as supported by the results of FTIR spectra and DSC analysis. The enhanced dissolution of Itraconazole from co-precipitate of 1:4 (drug: CD) was reflected in improved pharmacokinetics of co-precipitate. The results of the study proposes that the dissolution and bio-availability of Itraconazole can be improved by using cyclodextrin, how ever bioavailability of Itraconazole can be influenced by the pH conditions of the gastric environment as evident from dissolution study. Further studies are warranted to examine the effect of food on the bio availability of Itraconazole cyclodextrin complex.
Impact of data visualization on decision-making and its implications for public health practice: a systematic literature review

ABSTRACT Data visualization tools have the potential to support decision-making for public health professionals. This review summarizes the science and evidence regarding data visualization and its impact on decision-making behavior as informed by cognitive processes such as understanding, attitude, or perception. An electronic literature search was conducted using six databases, including reference list reviews. Search terms were pre-defined based on research questions. Sixteen studies were included in the final analysis. Data visualization interventions in this review were found to impact attitude, perception, and decision-making compared to controls. These relationships between the interventions and outcomes appear to be explained by mediating factors such as perceived trustworthiness and quality, domain-specific knowledge, basic beliefs shared by social groups, and political beliefs. Visualization appears to bring advantages by increasing the amount of information delivered and decreasing the cognitive and intellectual burden to interpret information for decision-making. However, understanding data visualization interventions specific to public health leaders’ decision-making is lacking, and there is little guidance for understanding a participant’s characteristics and tasks. The evidence from this review suggests positive effects of data visualization can be identified, depending on the control of confounding factors on attitude, perception, and decision-making.
PGRMC1 Exerts Its Function of Anti-Influenza Virus in the Central Nervous System

Central nervous system (CNS) disease is one of the most common extra-respiratory tract complications of influenza A virus (IAV) infections. However, there is still little knowledge about IAV regulating host responses in brain. ABSTRACT The influenza A virus (IAV) infection is usually restricted to the respiratory tract and only rarely enters the central nervous system (CNS) and causes neurological symptoms. However, the roles of host factors involved in IAV infection in the CNS remain largely undetermined. Therefore, we aimed to characterize the host responses to IAV infection in the brain. We isolated a strain of IAV H5N6, which is neurotoxic and highly pathogenic to mice. High-throughput RNA sequencing (RNA-seq) revealed 240 differentially expressed genes in IAV-infected brains. Among the significantly downregulated genes, we focused on the gene encoding progesterone receptor membrane component-1 (PGRMC1) and observed that IAV H5N6 infection clearly inhibited PGRMC1 in both neuroblastoma and glioma cells. Furthermore, treatment with AG205, a PGRMC1-specific inhibitor, or PGRMC1 knockout promoted H5N6 multiplication in vitro, while overexpression of PGRMC1 resulted in opposite effects. Furthermore, AG205 treatment or PGRMC1 knockout significantly inhibited the retinoic acid-inducible gene I (RIG-I)-mediated interferon beta (IFN-β) signaling pathway and reduced the levels of several antiviral proteins (Mx1 and ISG15). In addition, PGRMC1-mediated regulation of IFN signaling relied on inhibition of the expression and ubiquitination of RIG-I. The loss of PGRMC1 leads to an increased susceptibility of mice (brain and lung) to influenza A virus infection. Conclusively, our results show for the first time that IAV H5N6 downregulates PGRMC1 expression to contribute to virus proliferation by inhibiting RIG-I-mediated IFN-β production in the brain. These findings may offer new insights regarding the interplay between IAV and host factors that may impact IAV pathogenicity in the brain. IMPORTANCE Central nervous system (CNS) disease is one of the most common extra-respiratory tract complications of influenza A virus (IAV) infections. However, there is still little knowledge about IAV regulating host responses in brain. In this study, we identified progesterone receptor membrane component-1 (PGRMC1) as a novel host factor involved in the replication and propagation of IAV H5N6 in the host brain. We also observed that PGRMC1 antagonism was required for viral evasion from the host immune response during IAV infection via inhibition of the retinoic acid-inducible gene I (RIG-I)-mediated interferon beta (IFN-β) signaling pathway and downstream antiviral gene expression. This study revealed a newly identified regulatory mechanism used by IAV H5N6 to ensure its life cycle in the CNS.
Selective 1Hα NMR Methods Reveal Functionally Relevant Proline cis/trans Isomers in Intrinsically Disordered Proteins: Characterization of Minor Forms, Effects of Phosphorylation, and Occurrence in Proteome

Abstract It is important to identify proline cis/trans isomers that appear in several regulatory mechanisms of proteins, and to characterize minor species that are present due to the conformational heterogeneity in intrinsically disordered proteins (IDPs). To obtain residue level information on these mobile systems we introduce two 1Hα‐detected, proline selective, real‐time homodecoupled NMR experiments and analyze the proline abundant transactivation domain of p53. The measurements are sensitive enough to identify minor conformers present in 4–15 % amounts; moreover, we show the consequences of CK2 phosphorylation on the cis/trans‐proline equilibrium. Using our results and available literature data we perform a statistical analysis on how the amino acid type effects the cis/trans‐proline distribution. The methods are applicable under physiological conditions, they can contribute to find key proline isomers in proteins, and statistical analysis results may help in amino acid sequence optimization for biotechnological purposes.