Noninvasive Prenatal Diagnosis of SEA-Thalassemia by Combining 1000 Genomes Database and Relative Haplotype Dosage.

To explore a noninvasive method for diagnosis of SEA-thalassemia and to investigate whether the regional factors affect the accuracy of this method. The method involved using a public database and bioinformatics software to construct parental haplotypes for proband and predicting fetal genotypes using relative haplotype dosage. We screened and downloaded sequencing data of couples who were both SEA-thalassemia carriers from the China National Genebank public data platform, and matched the sequencing data format with that of the reference panel using Ubuntu system tools. We then used Beagle software to construct parental haplotypes, predicted fetal haplotypes by relative haplotype dosage. Finally, we used Hidden Markov Model and Viterbi algorithm to determine fetal pathogenic haplotypes. All noninvasive fetal genotype diagnosis results were compared with gold standard gap-PCR electrophoresis results. Our method was successful in diagnosing 13 families with SEA-thalassemia carriers. The best diagnostic results were obtained when Southern Chinese Han was used as the reference panel, and 10 families showed full agreement between our noninvasive diagnostic results and the gap-PCR electrophoresis results. The accuracy of our method was higher when using a Chinese Han as the reference panel for haplotype construction in the Southern Chinese Han region as opposed to Beijing Chinese region. The combined use of public databases and relative haplotype dosage for diagnosing SEA-thalassemia is a feasible approach. Our method produces the best noninvasive diagnostic results when the test samples and population reference panel are closely matched in both ethnicity and geography. When constructing parental haplotypes with our method, it is important to consider the effect of region in addition to population background alone.

Ultrasensitive and ultrastretchable metal crack strain sensor based on helical polydimethylsiloxane.

The majority of crack sensors do not offer simultaneously both a significant stretchability and an ultrahigh sensitivity. In this study, we present a straightforward and cost-effective approach to fabricate metal crack sensors that exhibit exceptional performance in terms of ultrahigh sensitivity and ultrahigh stretchability. This is achieved by incorporating a helical structure into the substrate through a modeling process and, subsequently, depositing a thin film of gold onto the polydimethylsiloxane substrate via sputter deposition. The metal thin film is then pre-stretched to generate microcracks. The sensor demonstrates a remarkable stretchability of 300%, an exceptional sensitivity with a maximum gauge factor reaching 107, a rapid response time of 158 ms, minimal hysteresis, and outstanding durability. These impressive attributes are attributed to the deliberate design of geometric structures and careful selection of connection types for the sensing materials, thereby presenting a novel approach to fabricating stretchable and highly sensitive crack-strain sensors. This work offers a universal platform for constructing strain sensors with both high sensitivity and stretchability, showing a far-reaching significance and influence for developing next-generation practically applicable soft electronics.

[Establishment of a quantitative method for GC analysis of polyoxyethylene (35) castor oil in microemulsion extracts].

With the continuous exploration of microemulsions as solvents for traditional Chinese medicine extraction, polyoxyethy-lene(35) castor oil(CrEL), a commonly used surfactant, is being utilized by researchers. However, the problem of detecting residues of this surfactant in microemulsion extracts has greatly hampered the further development of microemulsion solvents. Based on the chemical structures of the components in CrEL and the content determination method of castor oil in the 2020 edition of the Chinese Pharmacopoeia(Vol. Ⅳ), this study employed gas chromatography(GC) and single-factor experiments to optimize the preparation method of methyl ricinoleate from CrEL. The conversion coefficient between the two was validated, and the optimal sample preparation method was used to process microemulsion extracts of Zexie Decoction from three batches. The content of methyl ricinoleate generated was determined, and the content of CrEL in the microemulsion extracts of Zexie Decoction was calculated using the above conversion coefficient. The results showed that the optimal preparation method for CrEL was determined. Specifically, 10 mL of 1 mol·L~(-1) KOH-methanol solution was heated at 60 ℃ for 15 min in a water bath. Subsequently, 10 mL of boron trifluoride etherate-methanol(1∶3) solution was heated at 60 ℃ for 15 min in a water bath, followed by extraction with n-hexane twice. CrEL could stably produce 20.84% methyl ricinoleate. According to this conversion coefficient, the average mass concentration of CrEL in the three batches of Zexie Decoction microemulsion extracts was 11.94 mg·mL~(-1), which was not significantly different from the CrEL mass concentration of 11.57 mg·mL~(-1) during microemulsion formulation, indicating that the established content determination method of this study was highly accurate, sensitive, and repeatable. It can be used for subsequent research on microemulsion extracts of Zexie Decoction and provide a reference for quality control of other drug formulations containing CrEL.

Seismic response analysis of super-high-rise building structures with three-layer isolation systems.

This paper proposes a triple-layer isolation device based on the single-story isolation and double-layer isolation. By establishing dynamic equilibrium equations and conducting earthquake response comparative analyses on the same super-tall building structure using three different forms of isolation: single-story isolation, double-layer isolation, and triple-layer isolation, it is found that the triple-layer isolation device, which adds an isolation layer on the basis of the double-layer isolation device, exhibits many different characteristics in terms of its damping mechanism, seismic response rules, etc., due to the differences in the position and quantity of the isolation layer. Rare earthquakes are equivalent to ASCE maximum considered earthquake or annual occurrence probability of 2%. The research shows that, under rare earthquake conditions, the isolation effect of the triple-layer isolation device in the super-tall frame-shear structure is better than that of the single-story isolation and double-layer isolation devices. Particularly, as the number of floors increases, the triple-layer isolation device can significantly reduce the seismic isolation support tension and compression stresses, inter-story displacement, single-story shear force, overturning moment, and floor acceleration of the high-rise building structure, and concentrate the lateral displacement of the structure on the three isolation layers, dissipating most of the seismic input energy.

Flexible Microstructured Capacitive Pressure Sensors Using Laser Engraving and Graphitization from Natural Wood.

In recent years, laser engraving has received widespread attention as a convenient, efficient, and programmable method which has enabled high-quality porous graphene to be obtained from various precursors. Laser engraving is often used to fabricate the dielectric layer with a microstructure for capacitive pressure sensors; however, the usual choice of electrodes remains poorly flexible metal electrodes, which greatly limit the overall flexibility of the sensors. In this work, we propose a flexible capacitive pressure sensor made entirely of thermoplastic polyurethane (TPU) and laser-induced graphene (LIG) derived from wood. The capacitive pressure sensor consisted of a flexible LIG/TPU electrode (LTE), an LIG/TPU electrode with a microhole array, and a dielectric layer of TPU with microcone array molded from a laser-engraved hole array on wood, which provided high sensitivity (0.11 kPa-1), an ultrawide pressure detection range (20 Pa to 1.4 MPa), a fast response (~300 ms), and good stability (>4000 cycles, at 0-35 kPa). We believe that our research makes a significant contribution to the literature, because the easy availability of the materials derived from wood and the overall consistent flexibility meet the requirements of flexible electronic devices.

Research Progress of Cell-Free Fetal DNA in Non-Invasive Prenatal Diagnosis of Thalassemia.

Thalassemia is a genetic disease that seriously affects the health of the fetus. At present, invasive prenatal diagnosis is the main method of thalassemia screening, but invasive prenatal diagnosis has the risk of fetal abortion. The discovery of cell-free fetal DNA (cffDNA) in the peripheral blood of pregnant women provides the possibility for non-invasive prenatal diagnosis (NIPD). Rapid and efficient capture of mutational information on cffDNA in maternal plasma can help prevent the birth of children with thalassemia major. Currently, strategies for cffDNA-based NIPD of thalassemia include the detection of paternal mutations in maternal plasma, detection of a proportion of wild and mutant alleles in maternal plasma, linkage disequilibrium single nucleotide polymorphism (SNP) based on pedigree probands, and prediction of fetal genotypes by bioinformatics combined with population information. Therefore, this paper will focus on the above aspects, in order to provide an essential reference to the prevention and treatment of thalassemia.

Interpreting the Therapeutic Efficiency of Multifunctional Hybrid Nanostructure against Glioblastoma.

Glioblastoma is considered the most fatal malignant brain tumor that starts from the central nervous system (CNS), where the blood-brain barrier (BBB) remains the biggest challenge for active targeting of drugs in malignant brain tumor. Thereby, we have designed a paclitaxel PTX@ANG/FA-NPs hybrid novel nanodrug delivery system that can overcome the clinical BBB. The structural and morphological characterization of PTX@ANG/FA-NPs confirmed successful synthesis of nanomicelles with the size range of about 160 to 170 nm. The overall repressive effect of PTX@ANG/FA-NPs on human glioblastoma U251 cells was 1.2-times that of PTX alone. In vitro cellular uptake assay also demonstrated that the dual-targeted nanoparticles (NPs) were more easily taken up by glioblastoma U251 cells. Although the antiglioblastoma activity was confirmed by cell migration assay, apoptosis assay, and cellular uptake assay, the absorption was studied by in vivo fluorescence imaging and brain distribution. The synthesized PTX@ANG/FA-NPs probe significantly inhibited the migration of U251 within the cells and promoted the apoptosis process. Moreover, the RhB@ANG/FA-NPs and PTX@ANG/FA-NPs showed higher accumulating potential at sites of tumor BBB disruption. The novel nanodrug delivery system mediated enhanced distribution of drugs at the targeted site for therapeutics efficacies against glioblastomas across the BBB.

Analysis of the Improvement of Engineering Mechanics Experimental Methods Based on IoT and Machine Learning.

With the rapid development of sensor technology, machine learning, and the Internet of Things, wireless sensor networks have gradually become a research hotspot. In order to improve the data fusion performance of wireless sensor networks and ensure network security in the event of external attacks, this paper proposes a wireless sensor optimization algorithm model, involving wireless sensor networks, the Internet of Things, and other related fields. This paper first analyzes the role of the Internet of Things in wireless sensor networks, studies the localization mechanism and hierarchy of the Internet of Things based on wireless sensor networks, and improves the LE-RLPCCA (Position Estimation Robust Local Retention Criteria Correlation Analysis) localization algorithm model based on sensor grids. This paper discusses the problems of machine learning in wireless sensor networks, constructs a sensor-based machine learning model, and designs a data fusion algorithm for a wireless sensor networks' machine learning model. The application of wireless sensors in engineering mechanics experiments is summarized, and the optimization algorithm model of the wireless sensor in engineering mechanics experiments is proposed. The analysis results show that the average accuracy of the DKFCM-FSVM (Density aware Kernel-based Fuzzy C-means Clustering algorithm Fuzzy Support Vector Machine) algorithm in detecting five behaviors is 0.997, 0.992, 0.904, 0.996, and 0.946, respectively, and the accuracy in detecting different behaviors is the best, 0.005, 0.01, 0.003, and 0.006 respectively. It achieves the lowest false positive rate in the detection of different behaviors, and the average false positive rate is 0.004, 0.003, 0.003, 0.008, and 0.005, respectively, which shows that the DKFCM-FSVM algorithm model of wireless sensor networks in engineering mechanics experiments is the optimal solution. The work of this paper has good reference value for the application of wireless sensor networks and the optimization of engineering mechanics experimental methods and is helpful for further research of sensor technology.

UPLC-MS-based plasma metabolomics for identifying energy metabolism biomarkers of maintenance in growing pigs.

The purpose of this study is to explore the potential plasma metabolism biomarkers reflecting the maintenance status of growing pigs. The repeated measurement design was used in this experiment, and six barrows (28.6 ± 0.5 kg BW) were selected and kept in metabolism crates. The feeding level in growing pigs close to ad libitum was 2400 kJ ME/kg BW0.6 ·day-1 during Day 1 to Day 7, while a feeding level of 782 kJ ME/kg BW0.6 ·day-1 was provided as energy requirement for maintenance during Day 8 to Day 14. Plasma samples of each pig were collected from the anterior vena cava on the morning of Day 8 and Day 15. The metabolites of plasma were determined by high-resolution mass spectrometry using a metabolomics approach. Results showed that metabolomics analysis between ad libitum-fed state and maintained status revealed differences in 16 compounds. Identified compounds were enriched in metabolic pathways related to linoleic acid metabolism, tryptophan metabolism, and alanine, aspartate and glutamate metabolism. In conclusion, linoleic acid metabolism, tryptophan metabolism, alanine, aspartate and glutamic acid metabolism pathways played a major regulatory role in the maintenance status of growing pigs. The potential metabolism biomarkers of maintenance in growing pigs were linoleic acid, glutamine and tyrosine.

The Influence of Physical Exercise Frequency and Intensity on Individual Entrepreneurial Behavior: Evidence from China.

Physical exercise can benefit individuals' physical and mental health and also influence individuals' long-term behavioral choices. Doing exercise is particularly important given that physical exercise can impact individuals' cognitive abilities and positive emotional states, which may further impact entrepreneurial behavior. Therefore, understanding the relationship between exercise and entrepreneurial behavior is essential, because it can provide policy suggestions for popularizing athletic activities and boosting entrepreneurship. Consequently, the present study examined whether physical exercise could predict entrepreneurial behavior and the possible psychological mechanisms within this relationship. Based on the 2017 Chinese General Social Survey (CGSS2017), this study tested the hypotheses using the Probit and Tobit models. The results showed that individuals' physical exercise intensity and frequency positively affected their entrepreneurial behavior. In addition, five variables moderated the relationships between physical exercise and individual entrepreneurial behavior: urban-rural differences, education level, marital status, the existence of minor children, and age. Moreover, positive emotions and physical/mental health mediated the influence of physical exercise (exercise frequency and exercise intensity) on individual entrepreneurial behavior. Endogeneity explanations were ruled out by including instrumental variable, copula terms and adopting coarsened exact matching.

The analysis of dynamic emotional contagion in online brand community.

Online brand communities (OBCs) could benefit firms in many usages, ranging from collecting consumers' suggestions or advice to interacting with community members directly and transparently. Creating a positive emotional atmosphere is essential for such communities' healthy development as its boosts the continuous involvement of each member. However, the dynamic cross-influences and evolution of emotions in OBCs have not been fully explored, which was the research gap this paper tried to fill. Based on emotional contagion theory, this study identifies three sources of textual sentiment through machine learning methods in OBCs: member's posts, other members' feedback, and the focal firm's official feedback. This study further tested the dynamic emotional contagion process among these sources on valence (mean) and volatility (dispersion), namely how they affected each other. Data was collected from the MIUI forum, a large forum launched by Xiaomi corporate on August 1, 2011, which contained 17,622 posts and 99,426 feedback. Results showed that: (1) in the emotional contagion process, there existed differences in the influence of emotional valence and volatility from different sources; (2) all emotional interactions were temporary and mostly lasted no more than three days; (3) the most significant contributor of each sources' emotion was itself, which could be explained by lagged effect; (4) the valence of focal firm's emotion (focal firm's official feedback) was the second contributor of the valence of member's emotion (member's posts) and other members' emotion (other members' feedback). Three sources of emotion in OBCs and emotional valence/volatility should be considered when firms try to guide the emotional changes in such communities. Furthermore, firms could proactively influence members' emotions by carefully designing the feedback to members' posts. Besides, since all interactions are temporary, firms need to engage in online communities frequently, like consistently offering feedback.

The influence of firm's feedbacks on user-generated content's linguistic style matching-An explanation based on communication accommodation theory.

In virtual brand communities, users and firms continuously use different or similar linguistic styles to communicate with each other. Existing literature has demonstrated that the linguistic style matching (LSM) between the coming users' posts [user-generated content (UGC)] and existing firms' content will influence users' behavior, like promoting users to release more posts. However, little research has been conducted to analyze how firms' feedbacking behaviors influence LSM. To fill the gap, this paper uses Python to measure the LSM between 69,463 posts from 9,777 users and existing firms' generated content in the MIUI community and examines the impact of firms' feedbacks on this LSM. The results show that the firms' feedbacks frequency increased the LSM, but the firms' feedbacks text length decreased the LSM. In addition, users' textual sentiment and the published text length moderate the impact of firms' feedbacks (e.g., frequency, text length) on LSM. Specifically, the users' textual sentiment valence increases the positive effect of firms' feedbacks frequency and weakens the negative effect of firms' feedbacks text length on LSM. The users' produced content text length reduced the positive effect of firms' feedbacks frequency and offset the negative effect of the firms' feedbacks text length on LSM. Further, the effects above are significant for the relatively active users but not for the inactive ones. Based on communication accommodation theory, this paper investigates the impact of firms' feedbacks frequency and text length on subsequent users' posting behaviors, providing an essential reference for guiding firms' virtual brand community management.

Using Extended Technology Acceptance Model to Assess the Adopt Intention of a Proposed IoT-Based Health Management Tool.

Advancements in IoT technology contribute to the digital progress of health science. This paper proposes a cloud-centric IoT-based health management framework and develops a system prototype that integrates sensors and digital technology. The IoT-based health management tool can collect real-time health data and transmit it to the cloud, thus transforming the signals of various sensors into shared content that users can understand. This study explores whether individuals in need tend to use the proposed IoT-based technology for health management, which may lead to the new development of digital healthcare in the direction of sensors. The novelty of this research lies in extending the research perspective of sensors from the technical level to the user level and explores how individuals understand and adopt sensors based on innovatively applying the IoT to health management systems. By organically combining TAM with MOA theory, we propose a comprehensive model to explain why individuals develop perceptions of usefulness, ease of use, and risk regarding systems based on factors related to motivation, opportunity, and ability. Structural equation modeling was used to analyze the online survey data collected from respondents. The results showed that perceived usefulness and ease of use positively impacted adoption intention, Perceived ease of use positively affected perceived usefulness. Perceived risk had a negative impact on adoption intention. Readiness was only positively related to perceived usefulness, while external benefits were positively related to perceived ease of use and negatively related to perceived risk. Facilitative conditions were positively correlated with perceived ease of use and negatively correlated with perceived risk. Technical efficacy was positively related to perceived ease of use and perceived usefulness. Overall, the research model revealed the cognitive mechanism that affects the intention of individuals to use the system combining sensors and the IoT and guides the digital transformation of health science.

Assessment of the Potential of Sarcandra glabra (Thunb.) Nakai. in Treating Ethanol-Induced Gastric Ulcer in Rats Based on Metabolomics and Network Analysis.

Gastric ulcer (GU) is one of the most commonly diagnosed diseases worldwide, threatening human health and seriously affecting quality of life. Reports have shown that the Chinese herbal medicine Sarcandra glabra (Thunb.) Nakai (SGN) can treat GU. However, its pharmacological effects deserve further validation; in addition, its mechanism of action is unclear. An acute gastric ulcer (AGU) rat model induced by alcohol was used to evaluate the gastroprotective effect of SGN by analysis of the histopathological changes in stomach tissue and related cytokine levels; the potential mechanisms of action of SGN were investigated via serum metabolomics and network pharmacology. Differential metabolites of rat serum were identified by metabolomics and the metabolic pathways of the identified metabolites were enriched via MetaboAnalyst. Furthermore, the critical ingredients and candidate targets of SGN anti-AGU were elucidated. A compound-reaction-enzyme-gene network was established using Cytoscape version 3.8.2 based on integrated analysis of metabolomics and network pharmacology. Finally, molecular docking was applied to verify the acquired key targets. The results showed that SGN exerted a certain gastroprotective effect via multiple pathways and targets. The effects of SGN were mainly caused by the key active ingredients isofraxidin, rosmarinic, and caffeic acid, which regulate hub targets, such as PTGS2, MAPK1, and KDR, which maintain the homeostasis of related metabolites. Signal pathways involved energy metabolism as well as immune and amino acid metabolism. Overall, the multi-omics techniques were proven to be promising tools in illuminating the mechanism of action of SGN in protecting against diseases. This integrated strategy provides a basis for further research and clinical application of SGN.

[Optimization of extraction process of Congrong Shujing Granules based on AHP-CRITIC analysis].

The index weight coefficients were determined by comparing the analytic hierarchy process(AHP), the criteria importance through inter-criteria correlation(CRITIC), and the AHP-CRITIC mixed weighting method. The comprehensive scores of index components(echinacoside, salvianolic acid B, paeoniflorin, and ointment yield) of each group in the orthogonal test were compared to optimize the extraction process of Congrong Shujing Granules. The results showed that the AHP-CRITIC mixed weighting method scientifically optimized the extraction process. To be specific, the decoction pieces should be added with the 6-fold amount of water and extracted twice, 1 h each time. After three verification tests, the average mass fractions of echinacoside, salvianolic acid B, and paeoniflorin were 0.72, 9.34, and 5.92 mg·g~(-1), respectively, and the average ointment yield was 47.18%. As verified by the AHP-CRITIC mixed weighting method and the orthogonal test, the optimized extraction process of Congrong Shujing Granules was stable and feasible and could be applied to industrial production.

The Influence of Psychological Safety on Students' Creativity in Project-Based Learning: The Mediating Role of Psychological Empowerment.

Creative-oriented new educational model will shape the direction and appearance of world development. This study focuses on the role of psychological safety and psychological empowerment in improving students' creativity in the context of project-based learning from the perspective of student empowerment. Based on self-determination theory, we propose that psychological safety positively affects students' creativity through psychological empowerment, and fault-tolerant culture plays a positive role in it. In this study, 238 students who participated in project-based learning were randomly selected to conduct a questionnaire survey. The results show that there is a positive correlation between psychological safety and creativity, and psychological empowerment plays an intermediary role in the relationship between them. The fault-tolerant culture enhances the direct influence of psychological safety on psychological empowerment and the indirect influence of psychological safety on creativity. Theoretical and practical implications were also discussed.

Why Are User-Generated Contents So Varied? An Explanation Based on Variety-Seeking Theory and Topic Modeling.

In online communities, such as Twitter, Facebook, or Reddit, millions of pieces of contents are generated by users every day, and these user-generated contents (UGCs) show a great variety of topics discussed that make the online community vivid and attractive. However, the reasons why UGCs show great variety and how a firm can influence this variety was unknown, which had been an obstacle to understanding and managing UGCs' variety. This study fills these two gaps based on variety-seeking theory and topic modeling, which is a technique in machine learning. We extract, quantitatively, the topic of the UGCs using topic modeling and divide UGCs into two types: single topic and multiple topics. The user's tendency to choose the type of UGC is used to measure variety-seeking behavior. We found that users have an intrinsic preference for variety when producing UGCs; the more single topic UGCs were produced in the past, the higher the probability of producing multiple topics UGC and the lower the probability of producing single topic UGC would be in the next, and vice versa. Furthermore, we discussed the effect of language/linguistic style matching (LSM) between firm feedbacks and UGCs on users' variety-seeking tendencies in UGCs' production. This study makes three contributions: (1) broadening variety-seeking theory to new behavior, that is content production behavior, and the results demonstrated that people would show a variety-seeking behavior in producing UGCs. (2) a new feasible method to measure the variety of UGCs by using topic modeling to extract the topics of UGCs and then measure the variety-seeking behavior in producing UGCs by analyzing the choice between single topic and multiple topics. (3) guidance for the firm to alter LSM of feedbacks to influence the variety of UGCs.

[Preparation of paclitaxel-loaded and folic acid-modified poly (lactic-co-glycolic acid) nano-micelles and in vitro anticancer effect on cervical cancer HeLa cells].

The paclitaxel-loaded and folic acid-modified poly(lactic-co-glycolic acid) nano-micelles(PTX@FA-PLGA-NMs) were prepared by the emulsion solvent evaporation method, and the parameters of paclitaxel-loaded nano-micelles were optimized with the particle size and PDI as evaluation indexes. The morphology of the nano-micelles was observed by transmission electron microscopy(TEM), and the stability, drug loading and encapsulation efficiency were systematically investigated. In vitro experiments were performed to study the cytotoxic effects of nano-micelles, apoptosis, and cellular uptake. Under the optimal parameters, the nano-micelles showed the particle size of(125.3±1.2) nm, the PDI of 0.086±0.026, the zeta potential of(-20.0±3.8) mV, the drug loading of 7.2%±0.75%, and the encapsulation efficiency of 50.7%±1.0%. The nano-micelles were in regular spherical shape as observed by TEM. The blank FA-PLGA-NMs exhibited almost no inhibitory effect on the proliferation and growth of tumor cells, while the drug-loaded nano-micelles and free PTX exhibited significant inhibitory effects. The IC_(50) of PTX@FA-PLGA-NMs and PTX was 0.56 µg·mL~(-1) and 0.66 µg·mL~(-1), respectively. The paclitaxel-loaded nano-micelles were potent in inhibiting cell migration as assessed by the scratch assay. PTX@FA-PLGA-NMs had good pro-apoptotic effect on cervical cancer HeLa cells and significantly promoted the uptake of HeLa cells. The results of in vitro experiments suggested that PTX@FA-PLGA-NMs could target and treat cervical cancer HeLa cells. Therefore, as nanodrug carriers, PTX@FA-PLGA-NMs with anti-cancer activity are a promising nano-system for improving the-rapeutic effects on tumors.