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Abstract Digital technology serves as a new industrial driving force, playing a crucial role in promoting the efficiency of regional tourism. To explore the inherent logic between digital technology and tourism development, the study employed the DEA-BCC model and the entropy-weighted TOPSIS method to measure the tourism efficiency and digital technology development level of 31 provinces (municipalities and districts) in China from 2011 to 2022. The evolutionary characteristics of the relationship between digital technology and tourism efficiency were analyzed from the spatio-temporal dimension, and empirical tests were carried out using the spatial error model (SEM) and the spatial lag model (SLM) to explore the mechanism of the impact of digital technology on tourism efficiency. The results show that: during the study period, the overall trend of digital technology development and tourism efficiency is upward, but there is a certain degree of spatial mismatch between the two; digital technology is not only conducive to the improvement of tourism efficiency in the province, but also acts on neighboring provinces through spatial spillover effects, mechanism of action tests show that digital technology can positively moderate the effects of tourism economic growth and tourism industry structure on tourism efficiency; in western and northeast China, the positive effect of digital technology on tourism efficiency is more obvious. The conclusions provide a new perspective for understanding and analyzing the development of provincial tourism in China, as well as a reference for the rational use of digital technology to promote tourism development.

Abstract Alkaline metal sulfur (AMS) batteries offer a promising solution for grid-level energy storage due to their low cost and long cycle life. However, the formation of solid compounds such as M2S2 and M2S (M = Na, K) during cycling limits their performance. Here we unveil intermediate-temperature K-Na/S batteries utilizing advanced electrolytes that dissolve all polysulfides and sulfides (K2Sx, x = 1–8), significantly enhancing reaction kinetics, specific capacity, and energy density. These batteries achieve near-theoretical capacity (1655 mAh g−1 sulfur) at 75 °C with a 1 M sulfur concentration. At a 4 M sulfur concentration, they deliver 830 mAh g−1 at 2 mA cm−2, retaining 71% capacity after 1000 cycles. This new K-Na/S battery with specific energy of 150-250 Wh kg−1 only employs earth-abundant elements, making it attractive for long-duration energy storage.

Disperse ferrite is generally embedded in lightweight steel, yet exhibits decent performance, thereby prompting a question: can heterogeneous design optimize it? Here, two representative structures, featured with discontinuous fibrous and dispersed ferrite separately embedded in the austenite matrix, were constructed as examples to address the issue. A heterostructure with fibrous ferrite shows a remarkable product (49 GPa·%) of ultimate strength and total elongation, standing out among other lightweight steels. Superior strength-ductility synergy is primarily attributed to hetero-deformation-induced strengthening and hardening. Abundant hetero-interactions imparted by phase boundaries, dense slip bands in austenite and dislocation networks inside ferrite serve as underlying physical mechanisms.

Abstract Background Echinocandins belong to the fourth generation of antifungals, and there are no systematic studies on their risk in coagulation dysfunction; this study will predict the risk of coagulation dysfunction of echinocandins using the US Food and Drug Administration Adverse Event Reporting System (FAERS) database. Method Data from January 2004 to March 2024 were obtained from FAERS. We examined the clinical characteristics of the coagulation dysfunction events and conducted disproportionality analysis by using reporting odds ratios (ROR) to compare echinocandins with the full database. Results There were 313 reports of coagulation dysfunction related to echinocandins as the primary suspect (PS) drug. The median time to incident for coagulation dysfunction was 3 (interquartile range [IQR] 1–9) days. Compared to triazoles and polyenes, echinocandins have a stronger signal (ROR 3.18, 95%CI 2.81–3.51, p

Abstract Pathogenic allele silencing is a promising treatment for genetic hereditary diseases. Here, we develop an RNA-cleaving tool, TaqTth-hpRNA, consisting of a small, chimeric TaqTth, and a hairpin RNA guiding probe. With a minimal flanking sequence-motif requirement, in vitro and in vivo studies show TaqTth-hpRNA cleaves RNA efficiently and specifically. In an Alzheimer’s disease model, we demonstrate silencing of mutant APP swe mRNA without altering the wild-type APP mRNA. Notably, due to the compact size of TaqTth, we are able to combine with APOE2 overexpression in a single AAV vector, which results in stronger inhibition of pathologies.

PurposeThis research intends to investigate the treatment of non-small cell lung cancer (NSCLC) using Toripalimab, focusing on its effectiveness and safety profile. Efficacy refers to the survival prognosis, while safety pertains to the occurrence of adverse events in our study. It also aims to provide reference information for neoadjuvant and postoperative therapies.MethodsUp to March 20, 2024, studies on randomized controlled trials and single-arm trials involving Toripalimab for NSCLC were sourced from the Cochrane Library, Embase, PubMed, and Web of Science databases. Data extraction and analysis were independently conducted by two researchers utilizing Stata 15.0 and R software.ResultsA total of 8 studies were analyzed, including 6 single-arm studies and 2 randomized controlled trials (RCTs). Toripalimab treatment in the RCTs showed an overall survival (OS) of [HR=0.67, 95% CI (0.53, 0.85); p=0.71]. The objective response rate (ORR) from single-arm studies was reported as [ES=0.59, 95% CI (0.36, 0.81); p

The battery thermal management system (BTMS) is a necessary consideration to ensure the efficiency, safety, and reliability of battery energy storage systems (BESS). Immersion cooling, with its high heat transfer efficiency and uniform heat distribution, is emerging as the trend in BTMS. This study investigated a 372 kW/372 kWh BESS utilizing the immersion cooling technique, where the entire cluster of batteries is immersed in a coolant. The large-full-scale simulation model is established to analyze the flow and temperature performance. 3 types of immersion coolant are compared, which are 10# transformer oil (DF1), silicone oil-5cSt (DF2), and natural ester RAPO (DF3). The conclusion shows that DF2 is the optimal immersion liquid for the battery cluster, for the lowest average temperatures, which are 26.30 °C and 36.91 °C during 0.5 P and 1 P discharge, respectively. Based on the temperature uniformity index (UTave,s), DF1 represents the best temperature uniformity, with the value of 0.034 and 0.047 during 0.5P and 1P discharge, respectively. Because of the high viscosity of DF3, it achieves the highest system pressure drop and the worst temperature uniformity, which shows that DF3 are not suitable to be selected as immersion coolant.

Abstract Ultra‐thin 2D materials have great potential as electrodes for micro‐supercapacitors (MSCs) because of their facile ion transport channels. Here, a high‐precision controllable photonic‐synthesis strategy that provided 1 inch wafer‐scale ultra‐thin film arrays of alloyed WxMo2xSy with sulfur vacancies and expanded interlayer (13.2 Å, twice of 2H MoS2) is reported. This strategy regulates the nucleation and growth of transition metal dichalcogenides (TMDs) on the picosecond or even femtosecond scale, which induces Mo–W alloying, interlayer expansion, and sulfur loss. Therefore, the diffusion barrier of WxMo2xSy is reduced, with charge transfer and ion diffusion enhancing. The as‐prepared symmetric MSCs with the size of 100 × 100 µm2 achieve ultrahigh specific capacitance (242.57 mF cm−2 and 242567.83 F cm−3), and energy density (21.56 Wh cm−3 with power density of 485.13 W cm3). The established synthesis strategy fits numerous materials, which provides a universal method for the flexible synthesis of electrodes in microenergy devices.

IntroductionCrop height and above-ground biomass (AGB) serve as crucial indicators for monitoring crop growth and estimating grain yield. Timely and accurate acquisition of wheat crop height and AGB data is paramount for guiding agricultural production. However, traditional data acquisition methods suffer from drawbacks such as time-consuming, laborious and destructive sampling.MethodsThe current approach to estimating AGB using unmanned aerial vehicles (UAVs) remote sensing relies solely on spectral data, resulting in low accuracy in estimation. This method fails to address the ill-posed inverse problem of mapping from two-dimensional to three-dimensional and issues related to spectral saturation. To overcome these challenges, RGB and multispectral sensors mounted on UAVs were employed to acquire spectral image data. The five-directional oblique photography technique was utilized to construct the three-dimensional point cloud for extracting crop height.Results and DiscussionThis study comparatively analyzed the potential of the mean method and the Accumulated Incremental Height (AIH) method in crop height extraction. Utilizing Vegetation Indices (VIs), AIH and their feature combinations, models including Random Forest Regression (RFR), eXtreme Gradient Boosting (XGBoost), Gradient Boosting Regression Trees (GBRT), Support Vector Regression (SVR) and Ridge Regression (RR) were constructed to estimate winter wheat AGB. The research results indicated that the AIH method performed well in crop height extraction, with minimal differences between 95% AIH and measured crop height values were observed across various growth stages of wheat, yielding R2 ranging from 0.768 to 0.784. Compared to individual features, the combination of multiple features significantly improved the model’s estimate accuracy. The incorporation of AIH features helps alleviate the effects of spectral saturation. Coupling VIs with AIH features, the model’s R2 increases from 0.694-0.885 with only VIs features to 0.728-0.925. In comparing the performance of five machine learning algorithms, it was discovered that models constructed based on decision trees were superior to other machine learning algorithms. Among them, the RFR algorithm performed optimally, with R2 ranging from 0.9 to 0.93.ConclusionIn conclusion, leveraging multi-source remote sensing data from UAVs with machine learning algorithms overcomes the limitations of traditional crop monitoring methods, offering a technological reference for precision agriculture management and decision-making.

Background/objectives: The race-sex differences in emergency department (ED) disposition decisions have been reported widely. Our objective is to identify demographic and clinical subgroups for which this difference is most pronounced, which will facilitate future targeted research on potential disparities and interventions. Methods: We performed a retrospective analysis of 93 987 White and African-American adults assigned an Emergency Severity Index of 3 at 3 large EDs from January 2019 to February 2020. Using random forests, we identified the Elixhauser comorbidity score, age, and insurance status as important variables to divide data into subpopulations. Logistic regression models were then fitted to test race-sex differences within each subpopulation while controlling for other patient characteristics and ED conditions. Results: In each subpopulation, African-American women were less likely to be admitted than White men with odds ratios as low as 0.304 (95% confidence interval (CI): [0.229, 0.404]). African-American men had smaller admission odds compared to White men in subpopulations of 41+ years of age or with very low/high Elixhauser scores, odds ratios being as low as 0.652 (CI: [0.590, 0.747]). White women were less likely to be admitted than White men in subpopulations of 18 to 40 or 41 to 64 years of age, with low Elixhauser scores, or with Self-Pay or Medicaid insurance status with odds ratios as low as 0.574 (CI: [0.421, 0.784]). Conclusions: While differences in likelihood of admission were lessened by younger age for African-American men, and by older age, higher Elixhauser score, and Medicare or Commercial insurance for White women, they persisted in all subgroups for African-American women. In general, patients of age 64 years or younger, with low comorbidity scores, or with Medicaid or no insurance appeared most prone to potential disparities in admissions.

Abstract Materials following Murray’s law are of significant interest due to their unique porous structure and optimal mass transfer ability. However, it is challenging to construct such biomimetic hierarchical channels with perfectly cylindrical pores in synthetic systems following the existing theory. Achieving superior mass transport capacity revealed by Murray’s law in nanostructured materials has thus far remained out of reach. We propose a Universal Murray’s law applicable to a wide range of hierarchical structures, shapes and generalised transfer processes. We experimentally demonstrate optimal flow of various fluids in hierarchically planar and tubular graphene aerogel structures to validate the proposed law. By adjusting the macroscopic pores in such aerogel-based gas sensors, we also show a significantly improved sensor response dynamics. In this work, we provide a solid framework for designing synthetic Murray materials with arbitrarily shaped channels for superior mass transfer capabilities, with future implications in catalysis, sensing and energy applications.

Abstract This study aimed to investigate the risk factors for the onset of subsequent primary breast cancer (SPBC) in women with a previous diagnosis of early‐stage breast cancer (BC) and to construct a prognostic prediction model for patients with SPBC. Using the Surveillance, Epidemiology, and End Results‐17 (SEER‐17) database, we conducted a retrospective cohort analysis on women with initial primary early‐stage BC from 2004 to 2015. Standardized incidence ratio (SIR) was calculated to determine the risk of subsequent primary cancer (SPC). A competing risk model was built to identify the risk factors for the onset of SPBC. And risk factors associated with breast cancer‐specific mortality in SPBC patients were evaluated and presented in the form of nomogram. Compared with the general population, the overall risk of SPC for all sites was significantly elevated in women with early‐stage BC (SIR = 1.21, 95% CI: 1.20–1.23), and breast is the most frequent site. Age, race and ethnicity, year of diagnosis, history of other tumors, histological type, surgery, radiation, chemotherapy, tumor size, positive lymph nodes numbers and ER status were independent risk factors (p

[Introduction] The purpose of this paper is to research and analyze the influence of water resources on the development of the green hydrogen industry in China, reveal the contradiction between water resources and the development of green hydrogen industry, analyze the future development trend of the green hydrogen industry and to provide useful reference for the development layout of renewable energy hydrogen production projects in China. [Method] In order to prove that water resources could limit the development of the green hydrogen industry in "Northeast China, North China, Northwest China" and other areas, the analysis and the demonstration were made based on the field investigations and the documentary materials, considering water resources policies, water usage in traditional chemical industries, and hydrogen production technologies. [Result] The analysis results show that under the restriction of China's water resources-related policies, the layout of green hydrogen industry should consider the constraints of water resources, and the large-scale production of green hydrogen and its substitution for fossil energy hydrogen production cannot effectively save water. Instead, it may lead to an increase in water consumption by the chemical industry. Under the constraint of water resources, the development of China's green hydrogen industry must consider the layout from a holistic perspective, fully integrate the development trend of the existing chemical industry, and consider the abundant resources available such as seawater. [Conclusion] The development of the green hydrogen industry in China should not ignore the problems of existing policy framework, technology level, industrial layout and characteristics of existing resources. When arranging the layout of the green hydrogen projects, the current situation and future trends should be fully considered, and the problems posed by water resources on the green hydrogen industry should be solved from the perspective of the overall planning, the coordinated industrial development and the effective utilization of resources.

The hetero-zone boundary affected region (HBAR), with a high strain gradient, plays a crucial role in the synergistic deformation of layered materials. Our previous experimental study demonstrated that a decreasing interfacial spacing leads to a higher fraction of HBAR and an enhanced combination of strength and ductility. In this work, a conventional mechanism-based strain gradient (CMSG) plasticity model is adopted to simulate the tensile behavior of Cu–Fe layered materials with three different interfacial spacings. The simulation results indicated that strain/stress partitioning and strain banding are the main factors for the synergistic deformation behavior. Strain bands are more likely to be activated in the Cu–Fe layered materials with smaller interfacial spacing. In addition, the formation of HBAR near the layer boundary can be observed, consistent with the previous experiments. During deformation, the HBAR induces back stress and forward stress to strengthen the Cu layer and weaken the Fe layer, respectively. The simulation results indicate the stress transfer between the Cu and Fe layers, which benefits the strain hardening and enhances synergistic deformation. This study provides a valuable insight into the strength-ductility synergy of layered materials. It demonstrates that increasing the HBAR fraction is a viable approach to enhance the mechanical properties of hetero-structured materials.

This study combines experiments with finite element simulations to investigate the effects of different forging ratios on the properties and microstructure of high strength steel 40CrNi2Si2MoV. The results indicate that under high forging ratios, the peak of the austenite phase is significantly reduced, while the peak of the martensite phase becomes dominant, accompanied by an increase in dislocation density, strength, and hardness. The uniform distribution of newly formed small-angle martensite grains enhances both strength and plasticity. The excellent strength and toughness of high-strength steel under high forging ratios mainly depend on tempered martensite and retained austenite. The impact toughness of under a high forging ratio increases by nearly 1.23 times compared to the lower forging ratio. Additionally, the ultimate tensile strength increases by 1.02 times, the microhardness rises by 2.25 %, while the elongation decreases by 0.65 %. Fracture morphology analysis reveals that heightened forging ratios not only ensure a more uniform dispersion of carbides within the matrix but also significantly boost crack propagation resistance, thus enhancing the impact toughness of the experimental steel. The study utilizes finite element software to assess the influence of equivalent stress, equivalent strain, temperature fluctuations, and damage progression on the mechanical properties during the forging process. This comprehensive analysis establishes a robust theoretical framework aimed at optimizing both the forging process and subsequent heat treatment structures and properties of high strength steel 40CrNi2Si2MoV.

With the growing concern about climate issues and the urgent need to reduce carbon emissions, hydrogen has attracted increasing attention as a clean and renewable vehicle energy source. However, the storage of flammable hydrogen gas is a major challenge, and it restricts the commercialisation of fuel cell electric vehicles (FCEVs). This paper provides a comprehensive review of common on-board hydrogen storage tanks, possible failure mechanisms and typical manufacturing methods as well as their future development trends. There are generally five types of hydrogen tanks according to different materials used, with only Type III (metallic liner wrapped with composite) and Type IV (polymeric liner wrapped with composite) tanks being used for vehicles. The metallic liner of Type III tank is generally made from aluminium alloys and the associated common manufacturing methods such as roll forming, deep drawing and ironing, and backward extrusion are reviewed and compared. In particular, backward extrusion is a method that can produce near net-shape cylindrical liners without the requirement of welding, and its tool designs and the microstructural evolution of aluminium alloys during the process are analysed. With the improvement and innovation on extrusion tool designs, the extrusion force, which is one of the most demanding issues in the process, can be reduced significantly. As a result, larger liners can be produced using currently available equipment at a lower cost.

Background: Prolonged or excessive use of acid suppressants may increase the risk of Clostridioides difficile infection (CDI) by altering the intestinal microecosystem. Vonoprazan, a novel potassium-competitive acid blocker, exhibits a faster and more sustained acid-suppressive effect than proton pump inhibitors (PPIs). Therefore, vonoprazan may have a greater impact on the gut microbiota, potentially resulting in CDI. Objectives: This study aimed to explore the potential relationship between acid suppressants and CDI by the Japan Adverse Drug Event Report (JADER) and the FDA Adverse Event Reporting System (FAERS) databases. Design: A retrospective analysis of the JADER and FAERS databases was examined by disproportionality analysis. Methods: We performed signal detection analyses of CDI induced by vonoprazan and PPIs using the JADER and FAERS databases. The association between acid suppressants and CDI was calculated using the reporting odds ratio (ROR) and corresponding 95% confidence interval (95% CI). When the lower limit of the 95% CI is exceeded by 1, the association is considered statistically significant. Results: In the JADER database, the ROR (95% CI) for vonoprazan and PPIs based on suspect drug reports was 15.84 (12.23–20.50) and 2.51 (1.92–3.28), respectively. In the FAERS database, the ROR (95% CI) for vonoprazan and PPIs based on primary and secondary suspect drug reports was 11.50 (6.36–20.82) and 1.42 (1.34–1.51), respectively. Subgroup analysis showed that elderly patients aged 60 years and older were more strongly associated with CDI. The ROR (95% CI) for vonoprazan and PPIs in patients aged 60 years and older in the JADER database was 15.35 (11.59–20.33) and 1.65 (1.14–2.39), respectively. Similarly, the ROR (95% CI) for vonoprazan and PPIs in the FAERS database was 12.56 (6.26–25.20) and 1.43 (1.31–1.57), respectively. Excluding the effect of Helicobacter pylori ( H. pylori ) infection, the use of acid suppressants was still associated with CDI. Conclusion: While signal detection analysis based on the JADER and FAERS databases could not establish causality, our study demonstrated that both vonoprazan and PPIs were significantly associated with CDI. Vonoprazan showed a stronger association with CDI in both databases.

Honeycomb‐layered oxides are a class of cathode materials for sodium‐ion batteries with great potential due to their high voltage and high capacity. However, the structural instability and voltage fading during cycling limit their practical application. Herein, it is revealed that Te substitution into Na3Ni2SbO6 induces a new dual‐honeycomb structure, which can elevate the average discharge voltage of the cathode materials from 3.2 to 3.8 V with improved cycle stability and alleviated voltage decay. Synchrotron operando X‐ray diffraction demonstrates that Te substitution can suppress the O3−P3−O1‐phase transition during charge and discharge processes effectively, benefited from the strong TeO covalent bonds. The resulted Na2.2Ni2Sb0.2Te0.8O6 cathode exhibits a high capacity retention of 70.9% after 1000 cycles at 1C, with an elevated operating voltage of ≈3.8 V. Theoretical calculations reveal that the introduced TeO bonds break the symmetric distribution of charge in Ni/Sb honeycomb structure and elevate the operation voltage by increased valence band width. Proper Te substitution can promote the rate and cycle capability of the cathode by suppressing phase transition and decreasing the bandgap.

BackgroundGonadotrophin-releasing hormone analogs (GnRHas) play a significant role in addressing gynecological diseases, central precocious puberty, and cancer. However, ensuring the safety of GnRHas in real-world applications requires continuous vigilance. In light of this, we undertook a disproportionality analysis focused on adverse events (AEs) associated with GnRHas using data from both the FDA Adverse Event Reporting System (FAERS) and the Japanese Adverse Drug Event Report (JADER). We evaluated GnRHas-associated AEs and characterized the clinical priority of unlisted AEs caused by each GnRHa from the different databases.MethodsIn the disproportionality analysis, we applied two adjusted algorithms to identify signals related to GnRHas in the FAERS and JADER databases from 2004 to 2023. Additionally, we utilized the Statistical Analysis System (SAS, 9.4) to examine potential and high-aROR (adjusted reporting odds ratio) signals associated with GnRHas. We performed clinical priority assessment for suspicious PTs and an analysis of serious/non-serious outcomes. We also gathered information on the onset times of AEs linked with GnRHas from both databases.ResultsFrom January 2004 to September 2023, FAERS and JADER recorded a total of 50,360,413 and 1,440,200 AEs, respectively. Employing two algorithms, the suspicious preferred terms (PTs) related to leuprolide (Leu) were 562 potential PTs (44 unlisted in specifications), followed by goserelin (Gos) with 189 PTs (28 unlisted), triptorelin (Tri) with 172 PTs (28 unlisted), and Leu-JADER with 85 PTs (10 unlisted). At the same PT level, the differences in GnRHas between the two databases were observed, such as cardiac failure, diabetes mellitus, liver disorder, dementia, suicidal ideation, interstitial lung disease, urinary disorders, and hypertensive crisis. In an analysis of serious vs. non-serious outcomes, a total of 43 AEs of Leu were more likely to be reported as serious AEs with p < 0.05 (such as asthenia, urinary retention, diabetes mellitus, interstitial lung disease, gait disturbance, and so on), following by Tri (6 AEs), and Gos (4 AEs). Based on the clinical priority score, 41 PTs of Leu, 26 PTs of Tri, 24 PTs of Gos, and 8 PTs of Leu-JADER were graded as weak. There were 3 PTs of Leu, 2 PTs of Tri, 4 PTs of Gos, and 2 PTs of Leu-JADER that were graded as moderate. Notably, in the assessment of the relevant evidence, 2 PTs (loss of libido and urinary tract toxicity caused by Leu), 1 PT (electrolyte imbalance caused by Tri), and 2 PTs (anorexia and suicidal ideation caused by Gos) showed a strong level of evidence with “++.” The differences in the signal strength of the same PTs from two databases were also worth noting. Moreover, the median onset time for GnRHas (Leu, Tri, and Gos) was 23 days (0, 298), 22 days (0, 181), and 217 days (29, 706), respectively, as median (Q1, Q3).ConclusionAn examination of two databases revealed suspicious AEs associated with GnRHas. Our study found potential new AE signals of GnRHas and supported continuous clinical monitoring, pharmacovigilance, regional differences, and further studies of GnRHas.

Abstract For the performance optimization strategies of hard carbon, heteroatom doping is an effective way to enhance the intrinsic transfer properties of sodium ions and electrons for accelerating the reaction kinetics. However, the previous work focuses mainly on the intrinsic physicochemical property changes of the material, but little attention has been paid to the resulting interfacial regulation of the electrode surface, namely the formation of solid electrolyte interphase (SEI) film. In this work, element F, which has the highest electronegativity, was chosen as the doping source to, more effectively, tune the electronic structure of the hard carbon. The effect of F‐doping on the physicochemical properties of hard carbon was not only systematically analyzed but also investigated with spectroscopy, optics, and in situ characterization techniques to further verify that appropriate F‐doping plays a positive role in constructing a homogenous and inorganic‐rich SEI film. The experimentally demonstrated link between the electronic structure of the electrode and the SEI film properties can reframe the doping optimization strategy as well as provide a new idea for the design of electrode materials with low reduction kinetics to the electrolyte. As a result, the optimized sample with the appropriate F‐doping content exhibits the best electrochemical performance with high capacity (434.53 mA h g−1 at 20 mA g−1) and excellent rate capability (141 mA h g−1 at 400 mA g−1).

Abstract Traumatic brain injuries (TBI) and stroke are major causes of morbidity and mortality in both developing and developed countries. The complex and heterogeneous pathophysiology of TBI and cerebral ischemia‐reperfusion injury (CIRI), in addition to the blood‐brain barrier (BBB) resistance, is a major barrier to the advancement of diagnostics and therapeutics. Clinical data showed that the severity of TBI and stroke is positively correlated with the number of neutrophils in peripheral blood and brain injury sites. Furthermore, neutrophil extracellular traps (NETs) released by neutrophils correlate with worse TBI and stroke outcomes by impairing revascularization and vascular remodeling. Therefore, targeting neutrophils to deliver NETs inhibitors to brain injury sites and reduce the formation of NETs can be an optimal strategy for TBI and stroke therapy. Herein, the study designs and synthesizes a reactive oxygen species (ROS)‐responsive neutrophil‐targeting delivery system loaded with peptidyl arginine deiminase 4 (PAD4) inhibitor, GSK484, to prevent the formation of NETs in brain injury sites, which significantly inhibited neuroinflammation and improved neurological deficits, and improved the survival rate of TBI and CIRI. This strategy may provide a groundwork for the development of targeted theranostics of TBI and stroke.

Using stereo synthetic aperture radar (SAR) to extract 3-D information has become an important means of continuously improving the spatial resolution and geometric positioning accuracy of spaceborne SAR. However, owing to the large differences in a stereo configuration, such as intersection angle (ITA), it is difficult to guarantee localisation accuracy. This study proposed a method for analysing the stereoscopic intersection capability and verifying the accuracy of spaceborne SAR images. The method is improved from three aspects. First, it considers the complexity of the OPSS and SASS modes and discusses the two cases separately in the theoretical modeling and experimental analysis. Secondly, in the theoretical modeling stage, the error is no longer simplified as originating from only one image, but all images have errors. Finally, the validity of the modeling conclusions is verified using multiple sets of simulated experiments and real SAR experiments. Experiments show that stereo SAR has more potential than single SAR. In the opposite-side stereo (OPSS) mode, the planimetric positioning accuracy of 35.028 m (single SAR) can be improved to 3.132 m (stereo SAR, optimal 1.641 m). By designing a reasonable stereo configuration, the geometric positioning accuracy of the original data can be significantly reduced by 31.896 m. In addition, the results show that, (1) for the symmetric OPSS mode, the planimetric accuracy can be improved, and an increase in the ITA will decrease the vertical accuracy. (2) For the same-side stereo (SASS) mode, the smaller the ITA, the higher the planimetric accuracy (except for a weak ITA). In addition, if the incidence angle (ICA) is fixed, an increase in the ITA increases the vertical accuracy. (3) The base-to-height ratio is not the only prerequisite for the stereo configuration. The recommended ITA value for symmetric OPSS mode is 52–80°, and the suggested ITA threshold for SASS mode is 10–21°. The theoretical results are generally compatible with the previous achievements, which can guide applications such as ground control point production, DSM generation, and 3-D information extraction.

The rapid development of micro synthetic aperture radar (SAR) satellites provides a new means of all-day, all-weather, and high-frequency Earth observation. However, the geometric stability of micro SAR satellites is weak, and the geometric positioning error of SAR images is large. The traditional method improves the geometric positioning accuracy (GPA) of satellite images by adding well-distributed ground control points (GCPs), but it is time-consuming and laborious. This study proposed a method for improving the GPA of micro SAR satellites with large positioning errors. The proposed method designs a multilevel and multiscale SAR image matching framework, utilizes high-precision spaceborne SAR digital orthophoto image (DOM), and realizes high-precision virtual GCPs (VGCPs) extraction between micro SAR satellite images and DOM through image matching. Finally, using the matched VGCPs directly participate in the geometric correction to improve the GPA of the micro SAR images. The experiment adopted Gaofen-3 (GF-3) 10-m resolution DOM product as the control data. VGCPs were extracted and GPA was evaluated for five Luojia-2 (LJ-2) SAR images (3-m resolution, stripmap mode). The results show that the GPA of the LJ-2 image is at the kilometer level, and it can be improved to better than 5 m (relative to GF-3 DOM) after processing, which proves the validity and reliability of the proposed method. The proposed method can provide support for the cooperative processing of multisource SAR satellite images.

With the rapid advancements in sequencing technology, an increasing number of genome sequences for medicinal plants have become available. In 2021, TCMPG was introduced as a comprehensive database dedicated to traditional Chinese medicine (TCM) plant genomes, capturing significant attention within the scientific community. To offer invaluable resources to researchers, this database received an upgrade to its latest version, named TCMPG 2.0, accessible at http://cbcb.cdutcm.edu.cn/TCMPG2/. TCMPG 2.0 surpasses its predecessor by adding 114 medicinal plants, 129 genomes, and 159 related herbs. Recognizing the critical role of ingredients in assessing the pharmacological effects of Chinese medicines, TCMPG 2.0 has also amassed data on 13,868 herbal ingredients. Additionally, four practical analytical tools, including Heatmap, Primer3, PlantiSMASH, and CRISPRCasFinder, have been integrated into the toolbox. These valuable enhancements significantly enhance the database's utility for researchers in the field.

Remote sensing sensor platforms are typically located at a significant distance from the ground, ranging from several hundred meters to hundreds of kilometers. This means that, compared to natural images, remote sensing images (RSI) have larger coverage areas and more complex information. The larger size and data volume of RSI presents challenges for computer vision matching algorithms (MAs), making it difficult to apply them directly to RSI matching. Moreover, a matching framework for multisource RSIs capable of large-scale processing by integrating multiple MAs with the entire RSI as input is presently lacking. This study proposes a tie points (TPs) matching framework of multisource remote sensing images based on the geometric and radiation characteristics of RSI. First, RSI is divided into different grids and undergoes local geometry correction. Next, matching between slice images is performed by MAs. Finally, TPs are generated by mapping matched points in multiple slice images to the whole RSI using a geometric processing model. Six representative MAs including artificial feature MAs and deep learning algorithms are integrated into the framework to match TPs from different RSI. Results demonstrate the extraction of TPs for multisource RSI, validating the framework's efficacy. In addition, a large-scale TPs matching test for deep learning MA is performed by using 13 synthetic aperture radar images (10-m resolution) with TPs root mean square error of 0.368 pixels, further confirming the framework's reliability.

The Ti/Al laminated metal components have attracted considerable attention due to their impressive strength and lightweight properties, positioning them as promising materials for aerospace and automotive applications. Although experimental evidence has highlighted their exceptional elongation and formability at elevated temperatures, there is still limited understanding of the underlying atomic-level mechanisms governing high-temperature plastic deformation, particularly with regards to the titanium aluminide (TiAl3) layer. This study utilized molecular dynamics (MD) simulations to investigate the tensile deformation of Ti/Al laminates, emphasizing the effects of temperature and TiAl3 layer thickness on atomic structural evolutions and mechanical properties. The MD simulations confirmed the decreases in the elastic modulus and peak stress at elevated temperatures, consistent with the experimental findings. The total dislocation length displayed an increasing trend with temperature, reaching a maximum at 600 K, before decreasing at 900 K due to amorphization. Moreover, the coordinated deformation among the Ti, Al and TiAl3 layers at elevated temperatures contributed to enhanced plasticity of the Ti/Al laminates. Furthermore, the TiAl3 layer thickness positively influenced the total dislocation length. However, increasing the layer thickness also leads to more high-strain bands in the TiAl3 layer, resulting in crack nucleation and decreased ductility of the Ti/Al laminate. This study provides valuable insights into the plastic deformation of Ti/Al laminates at elevated temperatures from the molecular dynamics perspective, benefitting further improvement in their plastic forming technique and engineering applications.

Abstract Background and Aim To evaluate the efficacy and safety of minocycline, vonoprazan, amoxicillin, and bismuth quadruple therapy for Helicobacter pylori (H. pylori) treatment. Methods From August 2022 to May 2023, clinical data were collected from patients who received H. pylori eradication treatment at West China Fourth Hospital, Sichuan University. One group received the MVAB regimen (amoxicillin, minocycline, vonoprazan, and colloidal bismuth pectin), while another group received the FOAB regimen (amoxicillin, furazolidone, omeprazole, and colloidal bismuth pectin), both administered for 14 days. Follow‐up assessments of safety and compliance were conducted within 1 week after treatment completion. One and a half months after treatment, the success of eradication was evaluated using the urea breath test. Results For the MVAB regimen as a first‐line treatment, the eradication rate was 90.1% (127/141, 95% CI: 85.1–95.1%) in the ITT analysis and 93.4% (127/136, 95% CI: 89.2–97.6%) in the PP analysis as a first‐line treatment. As a second‐line treatment, the eradication rate was 91.3% (21/23, 95% CI: 78.8–103.8%) in both analyses. For the FOAB regimen as a first‐line treatment, the eradication rate was 98.0% (50/51, 95% CI: 94.1–101.2%) in the ITT analysis and 100% (50/50, 95% CI: 100%) in the PP analysis. As a second‐line treatment, the eradication rate was 100% (6/6, 95% CI: 100%) in both analyses. Moreover, there was no significant difference in the incidence of adverse events between the two groups (MVAB regimen: 5.5% and FOAB regimen: 8.8%; P > 0.05). Conclusions The MVAB regimen could indeed be a viable alternative treatment option to conventional therapies.

As a new type of agricultural waste block substrate utilization, the initial wet base state of the substrate culture block needs to be dried. Therefore, studying the drying mechanism of substrate culture block is critical. In this study, the substrate culture block in a dry state was taken as the research object. Based on physical and chemical properties, the internal section of the substrate culture block was characterized by scanning electron microscopy and the pore condition of the particles was quantified. The results showed that the internal pore structure was uniform and favorable for plant root growth. Based on the pore structure, pore channel modeling was constructed to investigate the distribution of the internal multiphase medium and to distinguish between channels and pore-blind channels. The applicability of the modeling was verified and discussed. By measuring the drying rate of the substrate culture block and classifying its drying stages as fast speed, constant speed, and slow speed, it is clarified that the forms of moisture existence are bound-state water and free-state water, and the moisture migration is prioritized as surface adsorption water, interparticle water, particle attached water, and capillary water. Innovate a method to quantify the change of pore space in the drying process by pore coefficient ratio to evaluate the drying quality. The results show that when the pore coefficient ratio is about 40 %, its moisture content is 20 %∼30 %, and the drying effect is best at this time. The physical drying test further confirmed the correctness of the conclusion of the drying stage division and water loss law. This study can provide a theoretical reference for the modeling study of the pore structure of the block matrix and the exploration of its drying mechanism.

Among the post-transcriptional modifications, m6A RNA methylation has gained significant research interest due to its critical role in regulating transcriptional expression. This modification affects RNA metabolism in several ways, including processing, nuclear export, translation, and decay, making it one of the most abundant transcriptional modifications and a crucial regulator of gene expression. The dysregulation of m6A RNA methylation-related proteins in many tumors has been shown to lead to the upregulation of oncoprotein expression, tumor initiation, proliferation, cancer cell progression, and metastasis.Although the impact of m6A RNA methylation on cancer cell growth and proliferation has been extensively studied, its role in DNA repair processes, which are crucial to the pathogenesis of various diseases, including cancer, remains unclear. However, recent studies have shown accumulating evidence that m6A RNA methylation significantly affects DNA repair processes and may play a role in cancer drug resistance. Therefore, a comprehensive literature review is necessary to explore the potential biological role of m6A-modified DNA repair processes in human cancer and cancer drug resistance.In conclusion, m6A RNA methylation is a crucial regulator of gene expression and a potential player in cancer development and drug resistance. Its dysregulation in many tumors leads to the upregulation of oncoprotein expression and tumor progression. Furthermore, the impact of m6A RNA methylation on DNA repair processes, although unclear, may play a crucial role in cancer drug resistance. Therefore, further studies are warranted to better understand the potential biological role of m6A-modified DNA repair processes in human cancer and cancer drug resistance.

IntroductionSeasonal human coronavirus NL63 (HCoV-NL63) is a frequently encountered virus linked to mild upper respiratory infections. However, its potential to cause more severe or widespread disease remains an area of concern. This study aimed to investigate a rare localized epidemic of HCoV-NL63-induced respiratory infections among pediatric patients in Guilin, China, and to understand the viral subtype distribution and genetic characteristics.MethodsIn this study, 83 pediatric patients hospitalized with acute respiratory infections and positive for HCoV-NL63 were enrolled. Molecular analysis was conducted to identify the viral subgenotypes and to assess genetic variations in the receptor-binding domain of the spiking protein.ResultsAmong the 83 HCoV-NL63-positive children, three subgenotypes were identified: C4, C3, and B. Notably, 21 cases exhibited a previously unreported subtype, C4. Analysis of the C4 subtype revealed a unique amino acid mutation (I507L) in the receptor-binding domain of the spiking protein, which was also observed in the previously reported C3 genotype. This mutation may suggest potential increases in viral transmissibility and pathogenicity.DiscussionThe findings of this study highlight the rapid mutation dynamics of HCoV-NL63 and its potential for increased virulence and epidemic transmission. The presence of a unique mutation in the C4 subtype, shared with the C3 genotype, raises concerns about the virus’s evolving nature and its potential public health implications. This research contributes valuable insights into the understanding of HCoV-NL63’s epidemiology and pathogenesis, which is crucial for effective disease prevention and control strategies. Future studies are needed to further investigate the biological significance of the observed mutation and its potential impact on the virus’s transmissibility and pathogenicity.

Summary: The tumor microenvironment (TME) is restricted in metabolic nutrients including the semi-essential amino acid arginine. While complete arginine deprivation causes T cell dysfunction, it remains unclear how arginine levels fluctuate in the TME to shape T cell fates. Here, we find that the 20-μM low arginine condition, representing the levels found in the plasma of patients with cancers, confers Treg-like immunosuppressive capacities upon activated T cells. In vivo mouse tumor models and human single-cell RNA-sequencing datasets reveal positive correlations between low arginine condition and intratumoral Treg accumulation. Mechanistically, low arginine-activated T cells engage in metabolic and transcriptional reprogramming, using the ATF4-SLC7A11-GSH axis, to preserve their suppressive function. These findings improve our understanding of the role of arginine in human T cell biology with potential applications for immunotherapy strategies.

In this article, a modified immersed boundary method (IBM) with a ghost-cells strategy is introduced to study a kind of vertical-axis wind turbine (VAWT). In order to improve the accuracy of the numerical calculation and enhance its adaptability, some treatments on the IBM for the VAWT especially are carried out. The method is testified by the numerical simulation of an Eppler387 airfoil. With the help of the method, some flowing characteristics of the wind turbine have been thoroughly observed and understood. Furthermore, the effects of blade shape, tip vortex and secondary flowing on the turbine performance are discussed in detail based on the numerical results.

Abstract Obese people with acute pancreatitis (AP) have an increased risk of developing severe acute pancreatitis (SAP), which prolongs the length of hospital stay and increases mortality. Thus, elucidation of the mechanisms through which SAP occurs in obese individuals will provide clues for possible treatment targets. Differences in early events in obese or lean patients with AP have not been conclusively reported. We selected C57BL/6 mice as lean mice models, ob/ob mice or diet induced obese (DIO) mice as obese mice models and then induced experimental AP in mice via injections of caerulein. There were suppressed p-AMPK expressions in the pancreas of obese mice, compared with same-age lean C57BL/6 mice, which were further reduced in AP mice models. Obese AP mice were treated using AICAR, a direct AMPK agonist, which prevented pancreatic damage and cell death, suppressed pancreatic enzyme levels in serum, reduced the areas of fat saponification in the peritoneal cavity, prevented injury in other organs and decreased mice mortality rate. Further assays showed that AICAR activates p-AMPK to stabilize pro-caspase-8. Pro-caspase-8 enhances RIPK3 degradation, inhibits pancreatic acinar cell necroptosis, and downregulates the release of pancreatic enzymes. Thus, activation of AMPK by AICAR alleviates pancreatic acinar cell necroptosis and converts SAP to mild acute pancreatitis in obese mice.

Abstract Mass spectrometry technology can realize dynamic detection of many complex matrix samples in a simple, rapid, compassionate, precise, and high-throughput manner and has become an indispensable tool in accurate diagnosis. The mass spectrometry data analysis is mainly to analyze all metabolites in the organism quantitatively and to find the relative relationship between metabolites and physiological and pathological changes. A feature construction of mass spectrometry data (MSFS) method is proposed to construct the features of the original mass spectrometry data, so as to reduce the noise in the mass spectrometry data, reduce the redundancy of the original data and improve the information content of the data. Chi-square test is used to select the optimal non-redundant feature subset from high-dimensional features. And the optimal feature subset is visually analyzed and corresponds to the original mass spectrum interval. Training in 10 kinds of supervised learning models, and evaluating the classification effect of the models through various evaluation indexes. Taking two public mass spectrometry datasets as examples, the feasibility of the method proposed in this paper is verified. In the coronary heart disease dataset, during the identification process of mixed batch samples, the classification accuracy on the test set reached 1.000; During the recognition process, the classification accuracy on the test set advanced to 0.979. On the colorectal liver metastases data set, the classification accuracy on the test set reached 1.000. This paper attempts to use a new raw mass spectrometry data preprocessing method to realize the alignment operation of the raw mass spectrometry data, which significantly improves the classification accuracy and provides another new idea for mass spectrometry data analysis. Compared with MetaboAnalyst software and existing experimental results, the method proposed in this paper has obtained better classification results.

Abstract Background To examine the relationships between polyunsaturated fatty acids (PUFAs) dietary intake and asthma in children. Methods In this cross-sectional study, a total of 14,727 participants from the United States National Health and Nutrition Examination Survey (NHANES) database in 1999–2018 were included, and the baseline characteristics of all participants were gathered. The description analysis was used to explore the possible covariates. Weighted multivariate logistic regression models were adopted to assessed the association between PUFAs dietary intake and asthma in children. In addition, we also performed subgroup analysis based on gender, age, and maternal smoking during pregnancy to investigate this relationship. Results The prevalence of asthma approximately was 15.38% in the present study. The result of weighted multivariate logistic regression indicated that, docosahexaenoic [weighted odds ratio (OR) = 0.37, 95% confidence interval (CI) 0.19–0.74], total n − 3 PUFAs (weighted OR = 0.63, 95%CI 0.43–0.91), and eicosapentaenoic (weighted OR = 0.35, 95%CI 0.13–0.95) dietary intake were negatively associated with asthma in children. The subgroup analysis described that when children were male (weighted OR = 0.28, 95%CI 0.10–0.84), or were 5–7 years (weighted OR = 0.04, 95%CI 0.01–0.37), were 7–12 years (weighted OR = 0.46, 95%CI 0.24–0.90), or their maternal smoking during pregnancy (weighted OR = 0.16, 95%CI 0.03–0.90), docosahexaenoic dietary intake was negatively related to childhood asthma. Conclusion Docosahexaenoic dietary intake was negatively associated with the asthma in children, especially if children were male, or were 5–12 years, or their maternal smoking during pregnancy.

Accurately assessing maize crop height (CH) and aboveground biomass (AGB) is crucial for understanding crop growth and light-use efficiency. Unmanned aerial vehicle (UAV) remote sensing, with its flexibility and high spatiotemporal resolution, has been widely applied in crop phenotyping studies. Traditional canopy height models (CHMs) are significantly influenced by image resolution and meteorological factors. In contrast, the accumulated incremental height (AIH) extracted from point cloud data offers a more accurate estimation of CH. In this study, vegetation indices and structural features were extracted from optical imagery, nadir and oblique photography, and LiDAR point cloud data. Optuna-optimized models, including random forest regression (RFR), light gradient boosting machine (LightGBM), gradient boosting decision tree (GBDT), and support vector regression (SVR), were employed to estimate maize AGB. Results show that AIH99 has higher accuracy in estimating CH. LiDAR demonstrated the highest accuracy, while oblique photography and nadir photography point clouds were slightly less accurate. Fusion of multi-source data achieved higher estimation accuracy than single-sensor data. Embedding structural features can mitigate spectral saturation, with R2 ranging from 0.704 to 0.939 and RMSE ranging from 0.338 to 1.899 t/hm2. During the entire growth cycle, the R2 for LightGBM and RFR were 0.887 and 0.878, with an RMSE of 1.75 and 1.76 t/hm2. LightGBM and RFR also performed well across different growth stages, while SVR showed the poorest performance. As the amount of nitrogen application gradually decreases, the accumulation and accumulation rate of AGB also gradually decrease. This high-throughput crop-phenotyping analysis method offers advantages, such as speed and high accuracy, providing valuable references for precision agriculture management in maize fields.

Winter wheat is an important grain that plays a crucial role in agricultural production and ensuring food security. Its yield directly impacts the stability and security of the global food supply. The accurate monitoring of grain yield is imperative for precise agricultural management. This study aimed to enhance winter wheat yield predictions with UAV remote sensing and investigate its predictive capability across diverse environments. In this study, RGB and multispectral (MS) data were collected on 6 May 2020 and 10 May 2022 during the grain filling stage of winter wheat. Using the Pearson correlation coefficient method, we identified 34 MS features strongly correlated with yield. Additionally, we identified 24 texture features constructed from three bands of RGB images and a plant height feature, making a total of 59 features. We used seven machine learning algorithms (Cubist, Gaussian process (GP), Gradient Boosting Machine (GBM), Generalized Linear Model (GLM), K-Nearest Neighbors algorithm (KNN), Support Vector Machine (SVM), Random Forest (RF)) and applied recursive feature elimination (RFE) to nine feature types. These included single-sensor features, fused sensor features, single-year data, and fused year data. This process yielded diverse feature combinations, leading to the creation of seven distinct yield prediction models. These individual machine learning models were then amalgamated to formulate a Bayesian Model Averaging (BMA) model. The findings revealed that the Cubist model, based on the 2020 and 2022 dataset, achieved the highest R2 at 0.715. Notably, models incorporating both RGB and MS features outperformed those relying solely on either RGB or MS features. The BMA model surpassed individual machine learning models, exhibiting the highest accuracy (R2 = 0.725, RMSE = 0.814 t·ha−1, MSE = 0.663 t·ha−1). Additionally, models were developed using one year’s data for training and another year’s data for validation. Cubist and GLM stood out among the seven individual models, delivering strong predictive performance. The BMA model, combining these models, achieved the highest R2 of 0.673. This highlights the BMA model’s ability to generalize for multi-year data prediction.

The excessive reactive oxygen species (ROS) is a hallmark associated with the initiation and progression of inflammatory bowel disease (IBD), which execrably form a vicious cycle of ROS and inflammation to continually promote disease progression. Here, the gold nanoparticles-embedded ceria nanoparticles (Au/CeO2) with enhanced antioxidant activities are designed to block this cycle reaction for treating IBD by scavenging overproduced ROS. The Au/CeO2 with core-shell and porous structure exhibits significantly higher enzymatic catalytic activities compared with commercial ceria nanoparticles, likely due to the effective exposure of catalytic sites, higher content of Ce (III) and oxygen vacancy, and accelerated reduction from Ce (IV) to Ce (III). Being coated with negatively-charged hyaluronic acid, the Au/CeO2@HA facilitates accumulation in inflamed colon tissues via oral administration, reduces pro-inflammatory cytokines, and effectively alleviates colon injury in colitis mice. Overall, the Au/CeO2@HA with good biocompatibility is a promising nano-therapeutic for treating IBD.

CD19-targeted chimeric antigen receptor T lymphocytes (CAR-T) has demonstrated a high proportion of complete remission in the treatment of relapsed refractory acute B cell lymphoblastic leukemia (r/r B-ALL). It is of great clinical significance to explore which factors will impact long-term disease-free survival of patients with r/r B-ALL after CAR-T therapy without bridging bone marrow transplantation. Our study found that, in patients with r/r B-ALL without bridging transplantation, the patients’ age; infusion dosage; whether they had undergone allo-stem cell transplantation before CAR-T therapy, using CD-19-targeted or CD19/CD22-dual-targeted CAR-T; whether there is fusion gene; tumor burden before therapy; and comorbidity had no significant relationship with their long-term disease-free survival. We found only that CAR-T persistence was highly correlated with patients’ long-term disease-free survival. So, we further profiled CAR-T cells using single-cell sequencing and found that there is a specific T cell subset that may be associated with the long-term persistence of CAR-T. Finally, according to the single-cell sequencing results, we established cell production process named PrimeCAR, which shared common signaling pathways with the T cell subset identified. In the preliminary clinical study, prime CAR-Ts yield good persistence in peripheral blood of patients with B-ALL and lymphoma, without observing grade 2 or higher cytokine release syndrome.

Abstract Hydrogen is a kind of clean and sustainable energy source and arises wide attention in industrial and commercial scenarios. The utilization of hydrogen in safety is eternal theme, thereby it is important to detect hydrogen quickly and accurately in production, use and storage stage. This review focuses on the fiber grating hydrogen sensor, which depicts a great promising for industrial application, introduces the up‐to‐date progress and provides new insight for scale use. Starting with an overview of the sensing mechanism of hydrogen‐sensitive material, then this paper briefly introduces the working principle of fiber grating hydrogen sensor. After that, design and optimization methods for fiber grating hydrogen sensor are emphatically summarizes from viewpoints of sensor structure, hydrogen‐sensitive material, and sensor durability. Last, the challenges of fiber grating hydrogen sensor for practical applications are demonstrated and the future prospects are also put forward, namely the depth investigation in structure, material, key fabrication technology and environmental adaptability of sensor.

Objective: A remarkably sensitive, accurate, and efficient ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) approach was developed as a facile and expeditious method for measuring cilofexor concentration in beagle dogs, the herb-drug interactions between silybinin and cilofexor was explored based on pharmacokinetics.Methods: The plasma sample protein of the beagles were rapidly sedimented with acetonitrile, and cilofexor and tropifexor (internal standard, ISTD) were separated by gradient elution using a 0.1% formic acid aqueous solution and acetonitrile as the mobile phase. The concentrations were detected using positive ion multiple reaction monitoring (MRM) mode. Mass transfer pairs were m/z 587.91→267.91 for cilofexor and m/z 604.08→228.03 for ISTD, respectively. A two-period self-controlled experimental design was adopted for the HDIs experiment. In the first period (Group A), six beagle dogs were orally administered cilofexor at a dose of 1 mg/kg. In the second period (Group B), silybinin (3 mg/kg) was orally administered to the six beagle dogs twice a day for seven consecutive days, after which cilofexor was orally administered. The cilofexor concentration in beagle dogs was determined, and HDIs were evaluated based on their pharmacokinetics.Results: The accuracy and precision of cilofexor were both less than 15%, and the recoveries, matrix effects, and stability met the relevant requirements. The Cmax of cilofexor in group B was 49.62% higher than that in group A, whereas the AUC(0-t) and AUC(0−∞) of cilofexor in group B were 47.85% and 48.52% higher, respectively, than those in group A. Meanwhile, the t1/2 extended from 7.84 h to 9.45 h, CL and Vz decreased in Group B.Conclusion: A novel UPLC-MS/MS approach was successfully applied for the measurement of cilofexor in beagle dog plasma. Silybinin can alter the pharmacokinetics of cilofexor in beagle dogs, thereby increasing plasma exposure to cilofexor.

Abstract A major pathological basis for low back pain is intervertebral disk degeneration, which is primarily caused by the degeneration of nucleus pulposus cells due to imbalances in extracellular matrix (ECM) anabolism and catabolism. The phenotype of macrophages in the local immune microenvironment greatly influences the balance of ECM metabolism. Therefore, the control over the macrophage phenotype of the ECM is promising to repair intervertebral disk degeneration. Herein, the preparation of an injectable nanocomposite hydrogel is reported by embedding epigallocatechin‐3‐gallate‐coated hydroxyapatite nanorods in O‐carboxymethyl chitosan cross‐linked with aldehyde hyaluronic acid that is capable of modulating the phenotype of macrophages. The bioactive components play a primary role in repairing the nucleus pulposus, where the hydroxyapatite nanorods can promote anabolism in the ECM through the nucleopulpogenic differentiation of mesenchymal stem cells. In addition, epigallocatechin‐3‐gallate can decrease catabolism in the ECM in nucleus pulposus by inducing M2 macrophage polarization, which exists in normal intervertebral disks and can alleviate degeneration. The nanocomposite hydrogel system shows promise for the minimally invasive and effective treatment of intervertebral disk degeneration by controlling anabolism and catabolism in the ECM and inhibiting the IL17 signaling pathway (M1‐related pathway) in vitro and in vivo.

Abstract Increasing numbers of studies have shown that tumor cells prefer fermentative glycolysis over oxidative phosphorylation to provide a vast amount of energy for fast proliferation even under oxygen‐sufficient conditions. This metabolic alteration not only favors tumor cell progression and metastasis but also increases lactate accumulation in solid tumors. In addition to serving as a byproduct of glycolytic tumor cells, lactate also plays a central role in the construction of acidic and immunosuppressive tumor microenvironment, resulting in therapeutic tolerance. Recently, targeted drug delivery and inherent therapeutic properties of nanomaterials have attracted great attention, and research on modulating lactate metabolism based on nanomaterials to enhance antitumor therapy has exploded. In this review, the advanced tumor therapy strategies based on nanomaterials that interfere with lactate metabolism are discussed, including inhibiting lactate anabolism, promoting lactate catabolism, and disrupting the “lactate shuttle”. Furthermore, recent advances in combining lactate metabolism modulation with other therapies, including chemotherapy, immunotherapy, photothermal therapy, and reactive oxygen species‐related therapies, etc., which have achieved cooperatively enhanced therapeutic outcomes, are summarized. Finally, foreseeable challenges and prospective developments are also reviewed for the future development of this field.

Background: Vonoprazan has been reported to exert more potent and long-lasting gastric acid inhibition than proton pump inhibitors, potentially leading to a greater impact on the gut microbiota. This study aimed to clarify changes in microbial diversity and bacterial composition after VPZ treatments.Methods: We searched from PubMed, Embase, WOS, Scopus, Cochrane Library, and ClinicalTrials.gov (all years up to May 2023). The primary outcomes were alpha and beta diversity, as well as differences in gut microbiota composition between before and after VPZ treatments. We performed a meta-analysis to uncover the potential changes in human gut microbiota among VPZ users by pooled mean difference (MD) with a 95% confidence interval (CI). The risk of bias was assessed using the ROBINS-I tool.Results: A total of 12 studies were included to compare differences before and after VPZ treatments. Compared with baseline, alpha diversity was significantly reduced after VPZ treatments and gradually returned to baseline with longer follow-up. At the phylum level, there was a decrease in the relative abundance of Firmicutes and Actinobacteria, while Bacteroidetes increased compared with baseline. At the genus level, we found a significant decrease in the relative abundance of Coprococcus and Bifidobacterium and a significant increase in the relative abundance of Bacteroides compared with those before treatment. In subgroup analyses according to country and participants, we found differences in microbial changes after VPZ treatments.Conclusion: Vonoprazan can affect the changes of gut microbiota, which may be potentially associated with its strong ability of acid inhibition. However, due to the large heterogeneity, further studies are required to validate these findings.Systematic Review Registration:https://www.crd.york.ac.uk/prospero/, identifier CRD42023412265.

IntroductionArtificial intelligence (AI) technology has made rapid progress for disease diagnosis and triage. In the field of ophthalmic diseases, image-based diagnosis has achieved high accuracy but still encounters limitations due to the lack of medical history. The emergence of ChatGPT enables human-computer interaction, allowing for the development of a multimodal AI system that integrates interactive text and image information.ObjectiveTo develop a multimodal AI system using ChatGPT and anterior segment images for diagnosing and triaging ophthalmic diseases. To assess the AI system's performance through a two-stage cross-sectional study, starting with silent evaluation and followed by early clinical evaluation in outpatient clinics.Methods and analysisOur study will be conducted across three distinct centers in Shanghai, Nanjing, and Suqian. The development of the smartphone-based multimodal AI system will take place in Shanghai with the goal of achieving ≥90% sensitivity and ≥95% specificity for diagnosing and triaging ophthalmic diseases. The first stage of the cross-sectional study will explore the system's performance in Shanghai's outpatient clinics. Medical histories will be collected without patient interaction, and anterior segment images will be captured using slit lamp equipment. This stage aims for ≥85% sensitivity and ≥95% specificity with a sample size of 100 patients. The second stage will take place at three locations, with Shanghai serving as the internal validation dataset, and Nanjing and Suqian as the external validation dataset. Medical history will be collected through patient interviews, and anterior segment images will be captured via smartphone devices. An expert panel will establish reference standards and assess AI accuracy for diagnosis and triage throughout all stages. A one-vs.-rest strategy will be used for data analysis, and a post-hoc power calculation will be performed to evaluate the impact of disease types on AI performance.DiscussionOur study may provide a user-friendly smartphone-based multimodal AI system for diagnosis and triage of ophthalmic diseases. This innovative system may support early detection of ocular abnormalities, facilitate establishment of a tiered healthcare system, and reduce the burdens on tertiary facilities.Trial registrationThe study was registered in ClinicalTrials.gov on June 25th, 2023 (NCT 05930444).

The timely and precise prediction of winter wheat yield plays a critical role in understanding food supply dynamics and ensuring global food security. In recent years, the application of unmanned aerial remote sensing has significantly advanced agricultural yield prediction research. This has led to the emergence of numerous vegetation indices that are sensitive to yield variations. However, not all of these vegetation indices are universally suitable for predicting yields across different environments and crop types. Consequently, the process of feature selection for vegetation index sets becomes essential to enhance the performance of yield prediction models. This study aims to develop an integrated feature selection method known as PCRF-RFE, with a focus on vegetation index feature selection. Initially, building upon prior research, we acquired multispectral images during the flowering and grain filling stages and identified 35 yield-sensitive multispectral indices. We then applied the Pearson correlation coefficient (PC) and random forest importance (RF) methods to select relevant features for the vegetation index set. Feature filtering thresholds were set at 0.53 and 1.9 for the respective methods. The union set of features selected by both methods was used for recursive feature elimination (RFE), ultimately yielding the optimal subset of features for constructing Cubist and Recurrent Neural Network (RNN) yield prediction models. The results of this study demonstrate that the Cubist model, constructed using the optimal subset of features obtained through the integrated feature selection method (PCRF-RFE), consistently outperformed the RNN model. It exhibited the highest accuracy during both the flowering and grain filling stages, surpassing models constructed using all features or subsets derived from a single feature selection method. This confirms the efficacy of the PCRF-RFE method and offers valuable insights and references for future research in the realms of feature selection and yield prediction studies.

The model was used to predict and analyze the future changes in the total ecological water demand of the Panjin wetland, with a view to providing some scientific reference for the optimal allocation of regional water resources and the sustainable development of wetlands. The results showed that (1) the quality of the habitat environment in the Panjin wetland has a great influence on the change of the total water demand, and the total ecological water demand in the Panjin wetland will continue to decrease in the future. (2) There is a clear correlation between landscape pattern and ecological water demand. (3) The distribution characteristics of the landscape pattern are greatly influenced by political factors, thus affecting the total ecological water demand of the Panjin wetland. HIGHLIGHTS The landscape pattern changes in the Panjin wetland from 1989 to 2017 were investigated.; The ecological water demand of the Panjin wetland was calculated.; The important factor affecting the ecological water demand security of the Panjin wetland was habitat quality.; The ecological water demand of the Panjin wetland was predicted and assessed to provide a basis for scientific wetland management.;

Abstract Background Mesenchymal stem cell (MSC) transplantation therapy is highly investigated for the regenerative repair of cartilage defects. Low-intensity pulsed ultrasound (LIPUS) has the potential to promote chondrogenic differentiation of MSCs. However, its underlying mechanism remains unclear. Here, we investigated the promoting effects and mechanisms underlying LIPUS stimulation on the chondrogenic differentiation of human umbilical cord mesenchymal stem cells (hUC-MSCs) and further evaluated its regenerative application value in articular cartilage defects in rats. Methods LIPUS was applied to stimulate cultured hUC-MSCs and C28/I2 cells in vitro. Immunofluorescence staining, qPCR analysis, and transcriptome sequencing were used to detect mature cartilage-related markers of gene and protein expression for a comprehensive evaluation of differentiation. Injured articular cartilage rat models were established for further hUC-MSC transplantation and LIPUS stimulation in vivo. Histopathology and H&E staining were used to evaluate the repair effects of the injured articular cartilage with LIPUS stimulation. Results The results showed that LIPUS stimulation with specific parameters effectively promoted the expression of mature cartilage-related genes and proteins, inhibited TNF-α gene expression in hUC-MSCs, and exhibited anti-inflammation in C28/I2 cells. In addition, the articular cartilage defects of rats were significantly repaired after hUC-MSC transplantation and LIPUS stimulation. Conclusions Taken together, LIPUS stimulation could realize articular cartilage regeneration based on hUC-MSC transplantation due to the inhibition of the TNF signaling pathway, which is of clinical value for the relief of osteoarthritis.