Unlocking the therapeutic potential of P2X7 receptor: a comprehensive review of its role in neurodegenerative disorders

The P2X7 receptor (P2X7R), an ATP-gated ion channel, has emerged as a crucial player in neuroinflammation and a promising therapeutic target for neurodegenerative disorders. This review explores the current understanding of P2X7R’s structure, activation, and physiological roles, focusing on its expression and function in microglial cells. The article examines the receptor’s involvement in calcium signaling, microglial activation, and polarization, as well as its role in the pathogenesis of Alzheimer’s disease, Parkinson’s disease, multiple sclerosis, and amyotrophic lateral sclerosis. The review highlights the complex nature of P2X7R signaling, discussing its potential neuroprotective and neurotoxic effects depending on the disease stage and context. It also addresses the development of P2X7R antagonists and their progress in clinical trials, identifying key research gaps and future perspectives for P2X7R-targeted therapy development. By providing a comprehensive overview of the current state of knowledge and future directions, this review serves as a valuable resource for researchers and clinicians interested in exploring the therapeutic potential of targeting P2X7R for the treatment of neurodegenerative disorders

Large-scale sub-5-nm vertical transistors by van der Waals integration.

Vertical field effect transistor (VFET), in which the semiconductor is sandwiched between source/drain electrodes and the channel length is simply determined by the semiconductor thickness, has demonstrated promising potential for short channel devices. However, despite extensive efforts over the past decade, scalable methods to fabricate ultra-short channel VFETs remain challenging. Here, we demonstrate a layer-by-layer transfer process of large-scale indium gallium zinc oxide (IGZO) semiconductor arrays and metal electrodes, and realize large-scale VFETs with ultra-short channel length and high device performance. Within this process, the oxide semiconductor could be pre-deposited on a sacrificial wafer, and then physically released and sandwiched between metals, maintaining the intrinsic properties of ultra-scaled vertical channel. Based on this lamination process, we realize 2 inch-scale VFETs with channel length down to 4 nm, on-current over 800 A/cm2, and highest on-off ratio up to 2 × 105, which is over two orders of magnitude higher compared to control samples without laminating process. Our study not only represents the optimization of VFETs performance and scalability at the same time, but also offers a method of transfer large-scale oxide arrays, providing interesting implication for ultra-thin vertical devices

Osmotic Stress Induced Cell Death in Wheat Is Alleviated by Tauroursodeoxycholic Acid and Involves Endoplasmic Reticulum Stress–Related Gene Expression

Although, tauroursodeoxycholic acid (TUDCA) has been widely studied in mammalian cells because of its role in inhibiting apoptosis, its effects on plants remain almost unknown, especially in the case of crops such as wheat. In this study, we conducted a series of experiments to explore the effects and mechanisms of action of TUDCA on wheat growth and cell death induced by osmotic stress. Our results show that TUDCA: (1) ameliorates the impact of osmotic stress on wheat height, fresh weight, and water content; (2) alleviates the decrease in chlorophyll content as well as membrane damage caused by osmotic stress; (3) decreases the accumulation of reactive oxygen species (ROS) by increasing the activity of antioxidant enzymes under osmotic stress; and (4) to some extent alleviates osmotic stress–induced cell death probably by regulating endoplasmic reticulum (ER) stress–related gene expression, for example expression of the basic leucine zipper genes bZIP60B and bZIP60D, the binding proteins BiP1 and BiP2, the protein disulfide isomerase PDIL8-1, and the glucose-regulated protein GRP94. We also propose a model that illustrates how TUDCA alleviates osmotic stress–related wheat cell death, which provides an important theoretical basis for improving plant stress adaptation and elucidates the mechanisms of ER stress–related plant osmotic stress resistance

Expert consensus on digital intraoral scanning technology

Digital intraoral scanning is a hot topic in the field of oral digital technology. In recent years, digital intraoral scanning has gradually become the mainstream technology in orthodontics, prosthodontics, and implant dentistry. The precision of digital intraoral scanning and the accuracy and stitching of data collection are the keys to the success of the impression. However, the operators are less familiar with the intraoral scanning characteristics, imaging processing, operator scanning method, oral tissue specificity of the scanned object, and restoration design. Thus far, no unified standard and consensus on digital intraoral scanning technology has been achieved at home or abroad. To deal with the problems encountered in oral scanning and improve the quality of digital scanning, we collected common expert opinions and sought to expound the causes of scanning errors and countermeasures by summarizing the existing evidence. We also describe the scanning strategies under different oral impression requirements. The expert consensus is that due to various factors affecting the accuracy of digital intraoral scanning and the reproducibility of scanned images, adopting the correct scanning trajectory can shorten clinical operation time and improve scanning accuracy. The scanning trajectories mainly include the E-shaped, segmented, and S-shaped methods. When performing fixed denture restoration, it is recommended to first scan the abutment and adjacent teeth. When performing fixed denture restoration, it is recommended to scan the abutment and adjacent teeth first. Then the cavity in the abutment area is excavated. Lastly, the cavity gap was scanned after completing the abutment preparation. This method not only meets clinical needs but also achieves the most reliable accuracy. When performing full denture restoration in edentulous jaws, setting markers on the mucosal tissue at the bottom of the alveolar ridge, simultaneously capturing images of the vestibular area, using different types of scanning paths such as Z-shaped, S-shaped, buccal-palatal and palatal-buccal pathways, segmented scanning of dental arches, and other strategies can reduce scanning errors and improve image stitching and overlap. For implant restoration, when a single crown restoration is supported by implants and a small span upper structure restoration, it is recommended to first pre-scan the required dental arch. Then the cavity in the abutment area is excavated. Lastly, scanning the cavity gap after installing the implant scanning rod. When repairing a bone level implant crown, an improved indirect scanning method can be used. The scanning process includes three steps: First, the temporary restoration, adjacent teeth, and gingival tissue in the mouth are scanned; second, the entire dental arch is scanned after installing a standard scanning rod on the implant; and third, the temporary restoration outside the mouth is scanned to obtain the three-dimensional shape of the gingival contour of the implant neck, thereby increasing the stability of soft tissue scanning around the implant and improving scanning restoration. For dental implant fixed bridge repair with missing teeth, the mobility of the mucosa increases the difficulty of scanning, making it difficult for scanners to distinguish scanning rods of the same shape and size, which can easily cause image stacking errors. Higher accuracy of digital implant impressions can be achieved by changing the geometric shape of the scanning rods to change the optical curvature radius. The consensus confirms that as the range of scanned dental arches and the number of data concatenations increases, the scanning accuracy decreases accordingly, especially when performing full mouth implant restoration impressions. The difficulty of image stitching processing can easily be increased by the presence of unstable and uneven mucosal morphology inside the mouth and the lack of relatively obvious and fixed reference objects, which results in insufficient accuracy. When designing restorations of this type, it is advisable to carefully choose digital intraoral scanning methods to obtain model data. It is not recommended to use digital impressions when there are more than five missing teeth

Search for eccentric black hole coalescences during the third observing run of LIGO and Virgo

Despite the growing number of confident binary black hole coalescences observed through gravitational waves so far, the astrophysical origin of these binaries remains uncertain. Orbital eccentricity is one of the clearest tracers of binary formation channels. Identifying binary eccentricity, however, remains challenging due to the limited availability of gravitational waveforms that include effects of eccentricity. Here, we present observational results for a waveform-independent search sensitive to eccentric black hole coalescences, covering the third observing run (O3) of the LIGO and Virgo detectors. We identified no new high-significance candidates beyond those that were already identified with searches focusing on quasi-circular binaries. We determine the sensitivity of our search to high-mass (total mass M>70 M⊙) binaries covering eccentricities up to 0.3 at 15 Hz orbital frequency, and use this to compare model predictions to search results. Assuming all detections are indeed quasi-circular, for our fiducial population model, we place an upper limit for the merger rate density of high-mass binaries with eccentricities 0<e≤0.3 at 0.33 Gpc−3 yr−1 at 90\% confidence level

Ultralight vector dark matter search using data from the KAGRA O3GK run

Among the various candidates for dark matter (DM), ultralight vector DM can be probed by laser interferometric gravitational wave detectors through the measurement of oscillating length changes in the arm cavities. In this context, KAGRA has a unique feature due to differing compositions of its mirrors, enhancing the signal of vector DM in the length change in the auxiliary channels. Here we present the result of a search for U(1)B−L gauge boson DM using the KAGRA data from auxiliary length channels during the first joint observation run together with GEO600. By applying our search pipeline, which takes into account the stochastic nature of ultralight DM, upper bounds on the coupling strength between the U(1)B−L gauge boson and ordinary matter are obtained for a range of DM masses. While our constraints are less stringent than those derived from previous experiments, this study demonstrates the applicability of our method to the lower-mass vector DM search, which is made difficult in this measurement by the short observation time compared to the auto-correlation time scale of DM

Hyperspectral Estimation of Nitrogen Content in Different Leaf Positions of Wheat Using Machine Learning Models

Remote sensing estimation of crop nitrogen content allows real-time monitoring of growth to develop scientific methods. However, most of the current remote sensing estimates of crop nitrogen contents have limitations in accurately reflecting the vertical distribution of nutrients in plants. Firstly, the original hyperspectrum is first-order differential (FD), second-order differential (SD), and continuous removal (CR), and the corresponding sensitive bands were screened by correlation analysis in this paper. Then, the spectral reflectance, vegetation indices, and wavelet coefficients were used as input features to construct models for estimating nitrogen content of flag leaf, upper 1 leaf, upper 2 leaf, upper 3 leaf, and upper 4 leaf based on partial least squares regression (PLSR), support vector machine (SVM), random forest (RF), and multiple linear regression (MLR), respectively. The results showed that the accuracy of nitrogen content prediction based on wavelet coefficients was the highest. The combination of MLR and SVM with wavelet coefficients had high accuracy and robustness in the prediction of nitrogen content at different leaf positions. Additionally, the prediction accuracy of nitrogen gradually increased as the leaf position of winter wheat increased. The study can provide technical support for remote sensing estimation of nutrient elements at vertical leaf position of crops. The study can provide a reference for prediction of other crops

Hyperspectral Estimation of Nitrogen Content in Different Leaf Positions of Wheat Using Machine Learning Models

Remote sensing estimation of crop nitrogen content allows real-time monitoring of growth to develop scientific methods. However, most of the current remote sensing estimates of crop nitrogen contents have limitations in accurately reflecting the vertical distribution of nutrients in plants. Firstly, the original hyperspectrum is first-order differential (FD), second-order differential (SD), and continuous removal (CR), and the corresponding sensitive bands were screened by correlation analysis in this paper. Then, the spectral reflectance, vegetation indices, and wavelet coefficients were used as input features to construct models for estimating nitrogen content of flag leaf, upper 1 leaf, upper 2 leaf, upper 3 leaf, and upper 4 leaf based on partial least squares regression (PLSR), support vector machine (SVM), random forest (RF), and multiple linear regression (MLR), respectively. The results showed that the accuracy of nitrogen content prediction based on wavelet coefficients was the highest. The combination of MLR and SVM with wavelet coefficients had high accuracy and robustness in the prediction of nitrogen content at different leaf positions. Additionally, the prediction accuracy of nitrogen gradually increased as the leaf position of winter wheat increased. The study can provide technical support for remote sensing estimation of nutrient elements at vertical leaf position of crops. The study can provide a reference for prediction of other crops

Electric Conductivity and Piezoresistivity of Carbon Nanotube Artificial Skin Based on the Design of Mesh Structure

This paper introduces a new method of sensing pressure by using carbon nanotube yarns which are embedded in artificial skin, based on the design of the mesh structure. With the sensing technology, a kind of mesh model has been established for piezoresistive effect detection of carbon nanotube yarns in artificial skin. By analyzing the sensing characteristics of carbon nanotube yarns, we can conclude that the artificial skin embedded with yarns in a mesh model could be used for sensing pressure. It may cover the surface of the robot and has significant theoretical as well as practical value for intelligent robot research in the future