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IntroductionCervicogenic headache (CEH) is a secondary headache characterized by chronic, unilateral headache. Ultrasound-guided injections of the greater occipital nerve (GON) and the third occipital nerve (TON) are effective in the treatment of CEH, as is meridian sinew tuina for the treatment of CEH, but the evidence of clinical efficacy of combining these two therapies is valid. Therefore, we have designed a randomized controlled trial with the aim of investigating the efficacy and safety of ultrasound localization meridian sinew tuina combined with GON and TON injections for the treatment of CEH.Methods and analysisIn this study, we enroll 60 patients experiencing CEH. The control group receives ultrasound-guided injections of GON and TON. The intervention group is treated with ultrasound localization meridian sinew tuina combined with the injection of GON and TON. Meridian sinew tuina is performed once a day for 30 min for 3 days. The primary observational index includes the Short-Form of McGill Pain Questionnaire (SF-MPQ). The Secondary outcomes include Cervical Range of Motion (ROM) and Medical Infrared Thermography (MIT). MIT is used to measure the change in skin temperature in the area of the patient’s meridian sinew tuina treatment of GON and TON before and after the intervention. There are 5 time points assessed as baseline, day 3, day 15, day 30, and day 60.DiscussionThis study proposes to combine ultrasound-guided injections of GON and TON for the treatment of CEH after identifying the treatment area of meridian sinew tuina under ultrasound localization. Meanwhile, MIT is utilized to provide objective evidence of the efficacy of CEH.Clinical trial registrationChiCTR2300076128.

Capsaicinoids are produced uniquely in pepper fruits, and its level determines the commercial quality and health-promoting properties of pepper. So, it is particularly important to increase capsaicinoids content in pepper. Rhizosphere microbiota is critical to plant growth and performance, and affected by plant varieties. However, the impact of pepper varieties with different capsaicinoids yields on the rhizosphere microbiota is poorly understood. Using high-throughput sequencing of the 16S rRNA and internal transcribed spacer (ITS) region, we investigated the rhizosphere microbial community among five pepper varieties containing different capsaicinoids. Our results demonstrated that pepper variety significantly influenced the diversity and structure of rhizosphere microbial community. Bacterial diversity in varieties with high capsaicinoids content was significantly higher than in varieties with low capsaicinoids content, while fungal diversity was opposite to bacterial diversity. The correlation analysis revealed that 19 dominant bacterial genera (e.g., Chujaibacter, Rhodanobacter, and Gemmatimonas) were significantly correlated with capsaicinoids content, and nine of them were also significantly associated with soil nutrients, whereas only one fungal genus (Podospora) was significantly correlated with capsaicinoids content. Additionally, almost all genera which significantly correlated to capsaicinoids content were biomarkers of the five pepper varieties and the correlation was well corresponding to the capsaicinoids content. Overall, our results confirmed that the variety of pepper significantly affected the rhizosphere microbial community in the fields, and bacteria and fungi responded differently to capsaicinoids, which may affect the biosynthesis of capsaicinoids and contribute to further improvement of capsaicinoids production in pepper fruits.

Fermented chopped chili pepper (FCCP) is the most important fermented and processed chili pepper product, and most pepper varieties can be processed with obvious flavor differences. Many studies have tried to explain these differences using the results of component analysis, processing technology, the microbes involved, etc., but few have examined the characteristics of these varieties along with the flavor of products. We conducted a physiochemical characteristic analysis of 35 kinds of fresh chili peppers with different genotypes and made fermented products from 17 varieties, using principal component analysis (PCA) and cluster analysis (CA) to correlate their components with FCCP products. The results were as follows: (1) Protein, total acids, a* (representation of the object’s red and green color), protopectin, and fruit thickness are the five key indexes that affect the quality of fresh chili peppers the most. (2) Protein, total acids, a*, protopectin, and fruit thickness are also the key indexes that affect the quality of FCCP. (3) Suitable ranges of fresh chili pepper to manufacture FCCP are 1.3–2.0 g/100 g for protein, 2.5–4.0 g/kg for total acids, 10–15 g/100 g for protopectin, 30–39 for a*, and 1.2–2.0 mm for fruit thickness. (4) Sensory appraisal shows crispness is the most important mouthfeel sensation and can decrease during the process. The varieties with the top three scores were A12 (21G675), A13 (20Z663), and A14 (21Z698) with scores of 87.92, 74.08, and 74.15, respectively. The varieties in the top three scores are pod peppers. The PCA and CA showed that pod peppers were the most suitable materials for making FCCP. Our results will benefit others in selecting fresh chili peppers for making FCCP and provide data support for directing processable variety breeding.

From connected sensors in soils, on animals or crops, and on drones, to various software and services that are available, “smart” technologies are changing the way farming is carried out. These technologies allow producers to look beyond what the eye can see by collecting non-traditional data and then using analytics tools to improve both food sustainability and profitability. “Smart Agriculture/farming” (SA) or “Digital Agriculture” (DA), often used interchangeably, refer to precision agriculture that is thus connected in a network of sensing and acting. It is a concept that employs modern information technologies, precision climate information, and crop/livestock developmental information to connect production variables to increase the quantity and quality of agricultural and food products. This is achieved by measuring and analyzing variables accurately, feeding the information into the cloud from edge devices, extracting trends from the various data, and subsequently providing information back to the producer in a timely manner. Smart agriculture covers many disciplines, including biology, mechanical engineering, automation, machine learning, artificial intelligence, and information technology-digital platforms. Minimum standards have been proposed for stakeholders with the aim to move toward this highly anticipated and ever-changing revolution. These foundational standards encompass the following general categories, including precise articulation of objectives, and baseline standards for the Internet of Things (IoT), including network infrastructure (e.g., stable 4G or 5G networks or a wireless local area network (WLAN) are available to end users). To sum up, SA aims to improve production efficiency, enhance the quality and quantity of agricultural products, reduce costs, and improve the environmental footprint of the industry. SA’s ecosystem should be industry self-governed and collaboratively financed. SA stakeholders and end-users’ facilities should meet standard equipment requirements, such as sensor accuracy, end data collectors, relevant industry compliant software, and trusted data analytics. The SA user is willing to be part of the SA ecosystem. This short perspective aims to summarize digital/smart agriculture concept in plain language.

Abstract Proximity barcoding assay, a high-throughput method for single-exosome analysis, was employed to profile surface proteins on individual exosomes of SCZ patients. This analysis identified five differentially expressed proteins (DEPs) between SCZ patients and healthy controls (HC) and six DEPs between antipsychotic responders and non-responders. Furthermore, two exosome clusters were found to be associated with SCZ, and certain DEPs were correlated with cognitive functions.

Abstract Background The effect of childhood trauma on Internet gaming disorder remains unclear. In this study, we examined this association in Chinese students and explored the possible associated roles of psychological resilience and depression. Methods In total, 8,579 students from Hunan Province, China, provided information regarding their sociodemographic factors, history of childhood trauma, any symptoms of depression, psychological resilience, and characteristics of Internet gaming disorder for this cross-sectional study. The impact of childhood trauma on Internet gaming disorder, as well as the extent to which it was mediated by depression and moderated by psychological resilience was evaluated. Results The influence of childhood trauma on Internet gaming disorder was partially mediated by depression (B = 0.07, 95% CI [0.04, 0.05], p

This paper presents an analytical study of the dynamic responses in the vehicle–pavement–foundation system, where the vehicle is simplified to a two-degree-of-freedom system, the pavement is modeled using both Euler–Bernoulli (E-B) beam and Timoshenko beam with consideration of pavement roughness, and the subgrade is simulated with a Winkler foundation model featuring cubic nonlinear stiffness. The focus is on using approximate analytical solutions of pavement response to discuss the impact of nonlinear stiffness under various parameter conditions. In previous analytical studies of vehicle–pavement–foundation systems, vehicles were typically simplified to a constant moving force, leading to the conclusion that when the applied force is small, the impact of nonlinear stiffness on the pavement’s dynamic response is minimal; whereas when the force is large, the pavement response increases with the increase in nonlinear stiffness. In this study, the force exerted by the vehicle on the pavement is harmonic, and the impact of nonlinear stiffness on the pavement response is different and much more complex. The research finds that there is a critical value for nonlinear stiffness under the given vehicle parameter conditions: when the nonlinear stiffness is less than the critical value, it has almost no effect on the pavement response; when it exceeds the critical value, the pavement’s response first decreases and then increases with the increase in nonlinear stiffness. The critical value of nonlinear stiffness is not fixed and increases as the vehicle velocity and foundation damping. Moreover, an increase in nonlinear stiffness also causes an increase in the offset between the wheel position and the position of maximum pavement deformation. Under the same parameter conditions, the offset in the E-B beam is significantly greater than that in the Timoshenko beam. Our study’s results enhance the understanding of the nonlinear dynamics within the vehicle–pavement interaction.

Cracks, common indicators of deterioration in bridge frameworks, frequently stem from wear and rust, leading to increased local flexibility and changes in the structure’s dynamic behavior. This study examines how these cracks affect the dynamics of footbridges when subjected to loads generated by walking individuals. The pedestrian is modeled as a linear oscillator, while the cracked bridge is represented by a simply supported beam following Euler–Bernoulli’s theory. The use of the Dirac delta function allows for the precise representation of the localized stiffness reduction at the crack location, facilitating the calculation of analytical expressions for the beam’s vibration modes. The research suggests that the presence of cracks minimally affects the bridge’s mid-span displacement. However, with a limited depth of cracks, the appearance of cracks notably amplifies the mid-span acceleration amplitude of the bridge, leading to a pronounced concentration of energy at the third natural frequency of the bridge in the acceleration spectrum. As the depth and number of cracks increase, the acceleration amplitude continues to decrease, but the corresponding spectrum remains almost unchanged. The study’s outcomes enhance the comprehension of how cracks affect the performance of bridge structures when subjected to loads from pedestrians, offering insights for the monitoring and evaluation of the condition of cracked footbridges.