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Abstract To compare the predictive value of mortality between left ventricular hypertrophy (LVH) defined by Chinese thresholds and defined by international guidelines in hypertension individuals and investigate better indexation methods for LVH in Chinese population. We included 2454 community hypertensive patients with Left ventricular mass (LVM) and relative wall thickness. LVM was indexed to body surface area (BSA), height2 7 and height 1 7. The outcomes were all‐cause and cardiovascular mortality. Cox proportional hazards models were used to explore the association between LVH and the outcomes. C‐statistics and time‐dependent receiver operating characteristic curve (ROC) was used to evaluate the value of those indicators. During a median follow‐up of 49 months (interquartile range 2–54 months), 174 participants (7.1%) died from any cause (n = 174), with 71 died of cardiovascular disease. LVM/BSA defined by the Chinese thresholds was significantly associated with cardiovascular mortality (HR: 1.63; 95%CI: 1.00‐2.64). LVM/BSA was significantly associated with all‐cause mortality using Chinese thresholds (HR: 1.56; 95%CI: 1.14‐2.14) and using Guideline thresholds (HR: 1.52; 95%CI: 1.08‐2.15). LVM/Height1.7 was significantly associated with all‐cause mortality using Chinese thresholds (HR: 1.60; 95%CI: 1.17‐2.20) and using Guideline thresholds (HR: 1.54; 95%CI: 1.04‐2.27). LVM/Height2.7 was not significantly associated with all‐cause mortality. C‐statistics indicated that LVM/BSA and LVM/Height1.7 by Chinese thresholds had better predictive ability for mortality. Time‐ROC indicated that only LVM/Height1.7 defined by Chinese threshold had incremental value for predicting mortality. We found that in community hypertensive populations, race‐specific thresholds should be used to classify LV hypertrophy related to mortality risk stratification. LVM/BSA and LVM/Height1.7 are acceptable normalization method in Chinese hypertension.

Abstract Left ventricular diastolic dysfunction (LVDD) is common in hypertension and is a predictor of increased cardiovascular risk, however the effect of LVDD, detected by new guideline, on major adverse cardiac events (MACE) is unknown in hypertensive patients without known cardiovascular disease. The present study aims to evaluate LVDD in a community hypertension cohort study and assess the effect of LVDD on MACE. we studied 283 asymptomatic nonischemic patients with hypertension who had baseline echocardiogram between 2012 and 2014. Patients were followed for MACE (myocardial infarction, coronary revascularization procedures, heart failure, stroke, all-cause mortality) with mean follow-up of 5.4 years. A Cox proportional hazards model was used to assess the association of LVDD with MACE. At baseline, 35 of the 283 hypertensions were diagnosed with LVDD (12.3%) and 25 patients were women (15.5%). Women had higher frequency of LVDD than men (8%). During follow-up, there were 26.6% patients occurring MACE in the LVDD group at baseline, 9.9% patients occurring MACE in the group with normal diastolic function. In multivariable Cox regression analyses, LVDD was a stronger predictor of MACE (HR: 2.5; 95% CI: 1.20 to 5.25; c- statistics 0.805) than E/e′ ratio (HR: 1.13; 95% CI: 1.04 to 1.22). LVDD was strongly associated with MACE in hypertension patients.

Background Left ventricular mass index (LVMI) has been extensively studied for its relationship with mortality but has been typically assessed at a single time point. We, therefore, describe the trajectory of LVMI in a population with hypertension over 6 years to study the subsequent risk of mortality. Methods and Results We assessed LVMI that was collected during annual health examinations in round 1 (2010–2012), round 2 (2013–2014), and round 3 (2015–2016) with 2 allometric scalings, height2.7, and body surface area, in a cohort of participants with hypertension to identify 6‐year trajectories of LVMI by latent class trajectory modeling. We followed up with participants for mortality by latent trajectory from the last echocardiographic examination (September 17, 2014–December 8, 2016) to December 31, 2018. We calculated mortality hazard ratios by assigned trajectory using Cox proportional hazards models. We obtained data for LVMI from 2453 participants (mean age, 61.80 [SD, 12.14] years, 1428 [58.2%] female). We identified 3 trajectories of LVM/H2.7, characterized by maintained low stable (1298 [52.9%]); moderate stable (935 [38.1%]); high stable (220 [9.0%]), as well as 3 trajectories by LVM/body surface area. During a median follow‐up of 2.15 years, 167 participants developed all‐cause mortality, and 71 were cardiovascular mortality. Only the high stable trajectory was associated with a higher risk of all‐cause mortality compared with the low stable trajectory by LVM/H2.7 or LVM/body surface area (all P

Wearing masks has become the norm during the Coronavirus disease pandemic. Masks can reportedly interface with air pollutants and release microplastics and plastic additives such as phthalates. In this study, an experimental device was set up to simulate the impact of five kinds of masks (activated-carbon, N95, surgical, cotton, and fashion masks) on the risk of humans inhaling microplastics and phthalates during wearing. The residual concentrations of seven major phthalates ranged from 296 to 72,049 ng/g (median: 1242 ng/g), with the lowest and the highest concentrations detected in surgical (median: 367 ng/g) and fashion masks (median: 37,386 ng/g), respectively. During the whole inhalation simulation process, fragmented and 20–100 μm microplastics accounted for the largest, with a rapid release during the first six hours. After one day’s wearing, that of 6 h, while wearing different masks, 25–135 and 65–298 microplastics were inhaled indoors and outdoors, respectively. The total estimated daily intake of phthalates with indoor and outdoor conditions by inhalation and skin exposure ranged from 1.2 to 13 and 0.43 to 14 ng/kg bw/d, respectively. Overall, surgical masks yield a protective effect, while cotton and fashion masks increase human exposure to microplastics and phthalates both indoors and outdoors compared to no mask wearing. This study observed possible risks from common facemasks and provided suggestions to consumers for selecting suitable masks to reduce exposure risks from microplastics and phthalate acid.

Abstract Background Although great progress has been made in recent years in identifying novel genes or natural alleles for rice yield improvement, the molecular mechanisms of how these genes/natural alleles regulate yield-associated traits, such as grain length and 1000-grain weight, remain largely unclear. An in-depth understanding of the roles of these genes/natural alleles in controlling yield traits become a necessity to ultimately increase rice yield via novel molecular techniques, such as gene editing. Results In this study, the roles of IGL1, which was previously identified through a map-based cloning approach, in the regulation of grain length were investigated by overexpressing and knocking out it in the Nipponbare genetic background. Overexpression and knockout of IGL1 (the resulting transgenic lines were hereafter designated IGL1-OE and IGL1-CR lines, respectively) led to elongation and shortening of grains, respectively. To further elucidate the molecular mechanisms behind the IGL1 action, young panicles from IGL1-OE and IGL1-CR lines were subjected to mRNA sequencing. The results showed that both overexpression and knockout of IGL1 all resulted in a large number of upregulated and downregulated differentially expression genes (DEGs) relative to wild-type NPB control lines. A total of 984 DEGs overlapped between upregulated DEGs from IGL1-OE and downregulated DEGs from IGL1-CR; 1146 DEGs were common to downregulated DEGs from IGL1-OE and upregulated DEGs from IGL1-CR. GO term and KEGG pathway analysis revealed that IGL1-upregulated DEGs were associated with extracellular region, protein ubiquitination, cell-wall modification, BR signaling, cell cycle, etc.; by comparison, the IGL1-downregulated DEGs were connected with extracellular region, response to wounding, flavonoid biosynthesis, jasmonic-acid signaling, glucose/sucrose metabolism, etc. Some phytohormone-associated genes (like OsYUCCA4, OsPIN10b, OsBAK1, and OsDLT), TF genes (like OsMADS1 and OsGASR9), grain length-regulating genes (like An-1, GS9, OsIQD14, and TGW2) showed significant upregulation or downregulation in IGL1-OE or IGL1-CR. Conclusion Our result clearly demonstrated that IGL1 is an important regulator of grain length, and has profound impacts on genome-wide gene expression, suggesting that it may work together with certain TFs. Overexpression or knockout of IGL1 appears to cause complex expression changes of genes associated with phytohormones, TFs, grain length-regulating factors, which ultimately brings about the grain elongation.

In the operational forecasting of tropical cyclones (TCs), decoding TC warning messages from global centers, along with extracting, organizing, and storing useful track observations and forecasts, are fundamental tasks. The technical core lies in accurately identifying distinct TC individuals through automated programming methods. Based on the statistical characteristics of historical distances between TC individuals, this study designs a novel method for automatic identification of TC individuals and establishes a database of TC track observations and forecasts by integrating the persistent features from various elements in TC warning messages. This method accurately identifies each TC individual and assigns it a unique database number through a two-step process: initially, through the 'Same Center same Number Comparison(SCNC)' identification method, followed by the 'Spatio-Temeporal Distance Comparison(STDC)' identification method.On this basis, we obtain a well-organized and comprehensive dataset that covers entire TC life time. Over the past decade,the operational practice has demonstrated that this method is accurate and efficient, providing solid data support for the TC forecasting operation, the assessment of TC forecasting accuracy, the compilation of TC yearbook, and TC-related research.

Abstract Background Gastric cancer (GC) is a deadly malignancy with an ever-increasing incidence worldwide. The cellular communication network (CCN) family serves as matricellular proteins and exerts their various functions via regulating cell proliferation and differentiation. This study aimed to perform an integrated analysis of CCNs to predict the prognosis in GC. Methods The microarray datasets were obtained from Gene Expression Omnibus database to identify the differentially expressed genes between GC and non-tumor tissues. Functional enrichment and genetic alteration analysis revealed the biological functions and alteration status associated with CCNs. We analyzed the mRNA and protein expressions of CCN family in GC patients. Furthermore, the prognostic value of distinct CCN family members were analyzed using the Kaplan–Meier plotter database. Finally, the human gastric cancer cell lines were used for in vitro experiments to further validate the role of WISP1. Results 26 genes were firstly identified to be significantly highly expressed in gastric tumor tissues. CCN family genes were identified to predict the prognosis in GC. Among the six CCNs, WISP1 is upregulated in GC tissues and its highly expression is associated with poor survival in GC patients. Moreover, a significant correlation is found between the expression of WISP1 and the pathological stage of patients with GC. Additionally, in vitro experiments demonstrated that WISP1 promotes the proliferation and invasive potential of GC cells, suggesting it may be a potential therapeutic target for GC. Conclusions A comprehensive bioinformatic analysis of CCN genes provides new insights into the potential roles of this family in GC. Importantly, WISP1 may be a good prognostic predictor and a potential therapeutic target for GC.

Abstract Massive multiple‐input multiple‐output and non‐orthogonal multiple access (MIMO‐NOMA) with low‐resolution analog‐to‐digital converters (ADCs) have been widely considered for the next‐generation wireless communication systems. However, the performance of the system including power‐scaling law has not been well investigated for the practical low complexity receivers. Employing the additive quantization noise model, we derive asymptotic approximate expressions of the spectrum efficiency for the system with group successive interference cancellation (GSIC) receivers over Rician fading channels. Based on these approximations, we conduct a unified asymptotic analysis for the system with linear, SIC, and GSIC receivers. The analysis reveals the transmission power can be scaled by the number of antennas for the system with GSIC receivers and shows the effects of crucial parameters including the number of groups, resolution bits, and antennas on the performance. Given a quality of service, the minimum data transmission power is also calculated for each user and the corresponding approximate power allocation is derived. The asymptotic analysis and the accuracy of the power allocation approximation are then verified by simulation results. Numerical results also demonstrate that high spectrum efficiency and energy efficiency can be achieved by the system with medium‐resolution ADCs and low complexity maximum ratio combining‐GSIC receivers with a small number of groups.

IntroductionThe factors that significantly and negatively impact carbon dioxide (CO2) emissions and coastal water quality (CWQ) must be continuously monitored and thoroughly evaluated. Among these, tourism (TR) volume stands out as one of the primary contributors to such effects. In contrast, green fiscal policy (GFP) and fintech (FT) can be considered proactive and modern efforts contributing to the improvement of these environmental indicators. Exploring whether the impacts of these factors exhibit uniformity across quantiles will greatly benefit strategic solutions aimed at avoiding resource waste.MethodsThis paper aims to calibrate procedures to apply the method of moment quantile regression (MMQR) model to address this issue. Firstly, cross-sectional dependence (CSD) among the variables is examined. Next, a stable long-term relationship between the variables is assessed using stationarity analysis. Finally, the MMQR estimation is conducted to thoroughly investigate the impact of independent variables on CWQ and CO2 across different quantiles.ResultsThe results from both the fixed effects (FE-OLS) and dynamic ordinary least squares (D-OLS) models reveal stable and significant correlations between the regressors and response variables. The research findings indicate that GFP and FT exert a significant impact on improving both CWQ and reducing CO2. In contrast, the favorable growth of the TR sector contributes negatively to CWQ and CO2.DiscussionThe paper recommends that the government increase spending and investment in green projects utilizing renewable energy, green transportation, blockchain technology, and advanced techniques. It also advocates for a strategic approach to controlling TR, focusing on enhanced waste management, in order to improve CWQ and CO2 indicators across most quantiles.

Bionic flapping-wing air vehicles present notable advantages, including high maneuverability, concealment, and efficiency. They hold promising applications in military reconnaissance and exploration search and rescue, rooted in a comprehensive exploration of biological flight mechanisms. Advanced motion observation and experimental techniques have facilitated more convenient and precise recording and analysis of insect flight behavior. Research indicates that common insects exhibit a high flapping frequency, ranging from 25 to 400 Hz, while butterflies, characterized by a lower flapping frequency of approximately 10 Hz, stand out. Despite the unique attributes of butterfly flight, aerodynamic research remains scarce compared to other flying organisms, resulting in an insufficient understanding of their intricate flying skills. Butterflies, distinguished by large forewings and hindwings that flap nearly synchronously on the same side of the body, spanning a substantial range of up to 180°, display substantial pitch swing during flight, with highly coupled wing and body movements. Remarkably, despite these complexities, butterflies demonstrate agile flight capabilities, enabling them to embark on long-distance migrations spanning thousands of kilometers. This exceptional characteristic renders them exemplary subjects for bionics research, capturing the attention of scholars globally. In contrast to other insects, butterflies have a uniquely intricate flight mechanism, complicating the development of butterfly-inspired flapping-wing air vehicles. Current endeavors in this field often simplify the mechanism of butterfly wing–body motion coupling, with only a few achieving controlled and stable flight. Simultaneously, the ongoing advancements in microelectromechanical system technology, aerodynamics, and precision processing are insufficient to support the development of practical insect-scale flapping-wing air vehicles fully. Accordingly, researchers have adopted a bionic perspective, observing butterflies’ free flight to understand their flapping-wing flight mechanism via experimental and numerical analysis methods. By the similarity principle of fluid mechanics, adjusting the scale, lowering the flapping frequency, and emulating butterflies’ distinctive flight motion in engineering, a butterfly-inspired flapping-wing air vehicle with a small aspect ratio and ultra-low frequency flapping was conceptualized and fabricated. Although current prototypes can achieve remote-controlled flight, a considerable disparity persists when compared to the flight behavior and capabilities of actual butterflies. Furthermore, most prototypes suffer from subpar battery life due to energy limitations. In comparison to flapping aircraft mimicking birds or larger insects with a high aspect ratio, butterflies have more intricate flapping movement and tailless posture control. Their unique maneuvering flight control, involving coupled and cooperative wing–body movements, demands further comprehensive exploration. Thus, achieving prolonged, controllable, and agile flight in a butterfly-inspired flapping-wing air vehicle poses a considerable challenge. Consequently, this paper synthesizes the distinctive flight behavior and mechanisms observed in living butterflies, elucidating key technologies for developing butterfly-inspired flapping-wing air vehicles. It also delineates the future trajectory for advancing this aircraft category.

Super Typhoon Doksuri is a significant meteorological challenge for China this year due to its strong intensity and wide influence range, as well as significant and prolonged hazards. In this work, we studied Doksuri's main characteristics and assessed its forecast accuracy meticulously based on official forecasts, global models and regional models with lead times varying from 1 to 5 days. The results indicate that Typhoon Doksuri underwent rapid intensification and made landfall at 09:55 BJT on July 28 with a powerful intensity of 50 m s−1 confirmed by the real-time operational warnings issued by China Meteorological Administration (CMA). The typhoon also caused significant wind and rainfall impacts, with precipitation at several stations reaching historical extremes, ranking eighth in terms of total rainfall impact during the event. The evaluation of forecast accuracy for Doksuri suggests that Shanghai Multi-model Ensemble Method (SSTC) and Fengwu Model are the most effective for short-term track forecasts. Meanwhile, the forecasts from the European Centre for Medium-Range Weather Forecasts (ECMWF) and United Kingdom Meteorological Office (UKMO) are optimal for long-term predictions. It is worth noting that objective forecasts systematically underestimate the typhoon maximum intensity. The objective forecast is terribly poor when there is a sudden change in intensity. CMA-National Digital Forecast System (CMA-NDFS) provides a better reference value for typhoon accumulated rainfall forecasts, and regional models perform well in forecasting extreme rainfall. The analyses above assist forecasters in pinpointing challenges within typhoon predictions and gaining a comprehensive insight into the performance of each model. This improves the effective application of model products.

Polycyclic aromatic hydrocarbons (PAHs), including the Group 1 human carcinogen benzo[a]pyrene (BaP), are produced by the incomplete combustion of organic matter and thus are present in tobacco smoke, charbroiled food and diesel exhaust. The nematode Caenorhabditis elegans is an established model organism, however it lacks the genetic components of the classical mammalian cytochrome P450 (CYP)-mediated BaP-diol-epoxide metabolism pathway. We therefore introduced human CYP1A1 or CYP1A2 together with human epoxide hydrolase (EPHX) into the worm genome by Mos1-mediated Single Copy Insertion (MosSCI) and evaluated their response to BaP exposure via toxicological endpoints. Compared to wild-type control, CYP-humanised worms were characterised by an increase in pharyngeal pumping rate and a decrease in volumetric surface area. Furthermore, BaP exposure reduced reproductive performance, as reflected in smaller brood size, which coincided with the downregulation of the nematode-specific major sperm protein as determined by transcriptomics (RNAseq). BaP-mediated reproductive toxicity was exacerbated in CYP-humanised worms at higher exposure levels. Collagen-related genes were downregulated in BaP-exposed animals, which correlate with the reduction in volumetric size. Whole genome DNA sequencing revealed a higher frequency of T > G (A > C) base substitution mutations in worms expressing human CYP1A1;EPHX which aligned with an increase in DNA adducts identified via an ELISA method (but not classical 32P-postlabelling). Overall, the CYP-humanised worms provided new insights into the value of genome-optimised invertebrate models by identifying the benefits and limitations within the context of the (3Rs) concept which aims to replace, reduce and refine the use of animals in research.

Abstract The three-dimensional (3D) organization of genome is fundamental to cell biology. To explore 3D genome, emerging high-throughput approaches have produced billions of sequencing reads, which is challenging and time-consuming to analyze. Here we present Microcket, a package for mapping and extracting interacting pairs from 3D genomics data, including Hi-C, Micro-C, and derivant protocols. Microcket utilizes a unique read-stitch strategy that takes advantage of the long read cycles in modern DNA sequencers; benchmark evaluations reveal that Microcket runs much faster than the current tools along with improved mapping efficiency, and thus shows high potential in accelerating and enhancing the biological investigations into 3D genome. Microcket is freely available at https://github.com/hellosunking/Microcket .

Abstract In cancer treatment, therapeutic strategies that integrate tumor-specific characteristics (i.e., precision oncology) are widely implemented to provide clinical benefits for cancer patients. Here, through in-depth integration of tumor transcriptome and patients’ prognoses across cancers, we investigated dysregulated and prognosis-associated genes and catalogued such important genes in a cancer type-dependent manner. Utilizing the expression matrices of these genes, we built models to quantitatively evaluate the malignant levels of tumors across cancers, which could add value to the clinical staging system for improved prediction of patients’ survival. Furthermore, we performed a transcriptome-based molecular subtyping on hepatocellular carcinoma, which revealed three subtypes with significantly diversified clinical outcomes, mutation landscapes, immune microenvironment, and dysregulated pathways. As tumor transcriptome was commonly profiled in clinical practice with low experimental complexity and cost, this work proposed easy-to-perform approaches for practical clinical promotion towards better healthcare and precision oncology of cancer patients.

The ability to survive starvation is a critical evolutionary adaptation, yet the molecular mechanisms underlying this capability remain incompletely understood. Pore-forming proteins (PFPs) are typically associated with immune defense, where they disturb the membranes of target cells. However, the role of PFPs in non-immune functions, particularly in metabolic and structural adaptations to starvation, is less explored. Here, we investigate the aerolysin-like PFP LIN-24 in Caenorhabditis elegans and uncover its novel function in enhancing starvation resistance. We found that LIN-24 expression is upregulated during starvation, leading to increased expression of the lipase-encoding gene lipl-3. This upregulation accelerates the mobilization and degradation of lipid stores, thereby sustaining energy levels. Additionally, LIN-24 overexpression significantly preserves muscle integrity, as evidenced by the maintenance of muscle structure compared to wild-type worms. Furthermore, we demonstrate that LIN-24 induces the formation of donut-shaped mitochondria, a structural change likely aimed at reducing ATP production to conserve energy during prolonged nutrient deprivation. This mitochondrial remodeling depends on genes involved in mitochondrial dynamics, including mff-1, mff-2, drp-1, and clk-1. Collectively, these findings expand our understanding of PFPs, demonstrating their multifaceted role in stress resistance beyond immune defense. LIN-24’s involvement in regulating metabolism, preserving muscle structure, and remodeling mitochondria highlights its crucial role in the adaptive response to starvation, offering novel insights into the evolution of stress resistance mechanisms and potential therapeutic targets for conditions related to muscle preservation and metabolic regulation.

Since the survival of lymphoma patients who experience disease progression or relapse remains very poor, new therapeutic approaches and effective drugs are urgently needed. Here we show that auranofin (AF), an anti-rheumatoid drug thought to inhibit thioredoxin reductases (TXNRDs) as its mechanism of action, exhibited potent activity against multiple cancer types, especially effective against B cell lymphoma. Surprisingly, a knockdown of TXNRD1 and TXNRD2 did not cause significant cytotoxicity, suggesting that abrogation of TXNRD enzyme per se was insufficient to cause cancer cell death. Further mechanistic study showed that the interaction of AF with TXNRD could convert this antioxidant enzyme to a ROS-generating molecule via disrupting its electron transport, leading to a leak of electrons that interact with molecular oxygen to form superoxide. AF also suppressed energy metabolism by inhibiting both mitochondria complex II and the glycolytic enzyme GAPDH, leading to a significant depletion of ATP and inhibition of cancer growth in vitro and in vivo. Importantly, we found that the AF-mediated ROS stress could induce PD-L1 expression, revealing an unwanted effect of AF in causing immune suppression. We further showed that a combination of AF with anti-PD-1 antibody could enhance the anticancer activity in a syngeneic immune-competent mouse B-cell lymphoma model. Our study suggests that AF could be a potential drug for lymphoma treatment, and its combination with immune checkpoint inhibitors would be a logical strategy to increase the therapeutic activity.

BackgroundFor medical diagnosis, clinicians typically begin with a patient’s chief concerns, followed by questions about symptoms and medical history, physical examinations, and requests for necessary auxiliary examinations to gather comprehensive medical information. This complex medical investigation process has yet to be modeled by existing artificial intelligence (AI) methodologies. ObjectiveThe aim of this study was to develop an AI-driven medical inquiry assistant for clinical diagnosis that provides inquiry recommendations by simulating clinicians’ medical investigating logic via reinforcement learning. MethodsWe compiled multicenter, deidentified outpatient electronic health records from 76 hospitals in Shenzhen, China, spanning the period from July to November 2021. These records consisted of both unstructured textual information and structured laboratory test results. We first performed feature extraction and standardization using natural language processing techniques and then used a reinforcement learning actor-critic framework to explore the rational and effective inquiry logic. To align the inquiry process with actual clinical practice, we segmented the inquiry into 4 stages: inquiring about symptoms and medical history, conducting physical examinations, requesting auxiliary examinations, and terminating the inquiry with a diagnosis. External validation was conducted to validate the inquiry logic of the AI model. ResultsThis study focused on 2 retrospective inquiry-and-diagnosis tasks in the emergency and pediatrics departments. The emergency departments provided records of 339,020 consultations including mainly children (median age 5.2, IQR 2.6-26.1 years) with various types of upper respiratory tract infections (250,638/339,020, 73.93%). The pediatrics department provided records of 561,659 consultations, mainly of children (median age 3.8, IQR 2.0-5.7 years) with various types of upper respiratory tract infections (498,408/561,659, 88.73%). When conducting its own inquiries in both scenarios, the AI model demonstrated high diagnostic performance, with areas under the receiver operating characteristic curve of 0.955 (95% CI 0.953-0.956) and 0.943 (95% CI 0.941-0.944), respectively. When the AI model was used in a simulated collaboration with physicians, it notably reduced the average number of physicians’ inquiries to 46% (6.037/13.26; 95% CI 6.009-6.064) and 43% (6.245/14.364; 95% CI 6.225-6.269) while achieving areas under the receiver operating characteristic curve of 0.972 (95% CI 0.970-0.973) and 0.968 (95% CI 0.967-0.969) in the scenarios. External validation revealed a normalized Kendall τ distance of 0.323 (95% CI 0.301-0.346), indicating the inquiry consistency of the AI model with physicians. ConclusionsThis retrospective analysis of predominantly respiratory pediatric presentations in emergency and pediatrics departments demonstrated that an AI-driven diagnostic assistant had high diagnostic performance both in stand-alone use and in simulated collaboration with clinicians. Its investigation process was found to be consistent with the clinicians’ medical investigation logic. These findings highlight the diagnostic assistant’s promise in assisting the decision-making processes of health care professionals.

Irrigation practice, tillage method, and nitrogen (N) management are the three most important agronomic measures for wheat (Triticum aestivum L.) production, but the combined effects on grain yield and wheat physiological characteristics are still poorly understood. We conducted a three-year split–split field experiment at the junction of the Loess Plateau and Huang-Huai-Hai Plain in China. The two irrigation practices (I0: non-irrigation and I1: one-off irrigation), three tillage methods (RT: rotary tillage, PT: plowing, and ST: subsoiling), and four N managements (N0, N120, N180, and N240) were assigned to the main plots, subplots, and sub-subplots, respectively. Irrigation practice, tillage method, N management, and most of their two-factor and three-factor interactions could significantly affect grain yield and the physiological characteristics of the leaves of winter wheat. One-off irrigation increased the grain yield by 46.9% by optimizing the activities of superoxide dismutase (SOD), peroxidase (POD) and catalase (CAT), the contents of proline (Pro) and soluble sugar (SS), and the net photosynthesis rate (Pn) in leaves during most growth stages of wheat. The improvement of grain yield and physiological characteristics under one-off irrigation was considerably affected by the tillage method and N management, and the effectiveness of one-off irrigation was improved under subsoiling and N180 or N240. One-off irrigation combining subsoiling and N180 had no significant difference relative to one-off irrigation combining subsoiling and N240, while it significantly increased grain yield by 47.1% over the three years, as well as increasing the activities of SOD, POD, and CAT, and Pn in wheat leaves by 23.2%, 41.2%, 26.1%, and 53.0%, respectively, and decreasing the contents of malondialdehyde (MDA), Pro, and SS by 29.2%, 65.4%, and 18.2% compared to non-irrigation rotary tillage combined with N240 across the two years and three stages. The wheat grain yield was significantly associated with the physiological characteristics in flag leaves, and the coefficient was greatest for POD activity, followed by SOD activity and Pn. Therefore, one-off irrigation combining subsoiling and N180 is an optimal strategy for the high-yield production of wheat in dryland regions where the one-off irrigation is assured.

A novel tailless X-type flapping-wing micro air vehicle with two pairs of independent drive wings is designed and fabricated in this paper. Due to the complexity and unsteady of the flapping wing mechanism, the geometric and kinematic parameters of flapping wings significantly influence the aerodynamic characteristics of the bio-inspired flying robot. The wings of the vehicle are vector-controlled independently on both sides, enhancing the maneuverability and robustness of the system. Unique flight control strategy enables the aircraft to have multiple flight modes such as fast forward flight, sharp turn and hovering. The aerodynamics of the prototype is analyzed via the lattice Boltzmann method of computational fluid dynamics. The chordwise flexible deformation of the wing is implemented via designing a segmented rigid model. The clap-and-peel mechanism to improve the aerodynamic lift is revealed, and two air jets in one cycle are shown. Moreover, the dynamics experiment for the novel vehicle is implemented to investigate the kinematic parameters that affect the generation of thrust and maneuver moment via a 6-axis load cell. Optimized parameters of the flapping wing motion and structure are obtained to improve flight dynamics. Finally, the prototype realizes controllable take-off and flight from the ground.

In recent years, contamination of mineral oil hydrocarbons (MOH) in milk powder, especially infant formula, has become a public concern, and related international regulation has gradually escalated. However, there is no standard method for the determination of MOH in milk powder. In this paper, the sample pretreatment method based on the EU limits and analytical requirements were improved and optimized, and the saponification method, hexane extraction, silica gel clean-up, epoxidation reaction method in order were used, and a highly sensitive method for the determination of mineral oils of saturated hydrocarbons (MOSH) and mineral oils of aromatic hydrocarbons (MOAH) in milk powder by on-line high performance liquid chromatography-gas chromatography (HPLC-GC) were established. Results showed that, the method achieved a limit of quantification (LOQ) of 0.5 mg/kg and recoveries of 81.1%~112.0% (RSD=0.3%~3.8%), meeting the method requirements of the European Joint Research Center (JRC). The method was applied to analyze the international proficiency testing samples, and the results showed the detection results of MOSH and MOAH from C16 to C25 and C25 to C35 were close to the true values, and the absolute values of their z'-scores were less than 2. This indicated that the method passed the validation, and the method could be referred to as the standard for the determination of MOSH and MOAH in milk powder.

Abstract The interaction between cerebral endothelial cells (CEC) and brain parenchymal cells is critical to maintain neurovascular homeostasis, whereas extracellular vesicles (EVs) are essential to mediate the cell–cell communication. Previous researches demonstrated that CEC-derived EVs (CEC-EVs) confer neuroprotective actions. However, the molecular mechanisms remain unknown. In this study, we isolated EVs from CEC and assessed their immune-regulatory actions in microglial cells and mice following lipopolysaccharide (LPS) exposure. We found that CEC-EVs treatment significantly ameliorated LPS-induced inflammatory activation, shifting microglial polarization from pro-inflammatory phenotype to anti-inflammatory phenotype. Meanwhile, microglial cells can effectively internalize CEC-EVs and this process was further enhanced by immune activation. Next, the miRNA microarray analysis revealed that CEC-EVs increased expression of miR-672-5p, which was demonstrated to be the cargo of CEC-EVs. TGFβ-activated kinase 1 (TAK1)-binding proteins 2 (TAB2) was identified to be the target of miR-672-5p. Through inhibiting TAB2, miR-672-5p derived from CEC-EVs suppressed TAK1-TAB signaling and thereby mitigating the downstream NF-κB activation. Furthermore, we found that by delivering miR-672-5p, CEC-EVs promoted autophagy and hence stimulating autophagic degradation of NLRP3 inflammasome. Our work firstly revealed the neuroimmune-modulating actions of CEC-EVs and further demonstrated that miR-672-5p secreted from CEC-EVs inhibits microglial pro-inflammatory polarization and facilitates autophagic process via targeting TAB2.

Abstract This study explored the potential links between Chinese industrial policy and cross-border mergers and acquisitions by Chinese firms from 2009 to 2019. Based on describing China's industrial strategy and evaluating the then-current situation of Chinese enterprises' cross-border mergers and acquisitions, this empirical study constructed a two-way fixed-effect panel model and an intermediate effect model to assess the mechanism of industrial policy's influence on Chinese enterprises' cross-border mergers and acquisitions decisions. The findings were as follows: (1) Industrial policy could promote the implementation of cross-border mergers and acquisitions of Chinese enterprises; (2) By easing financial restrictions, industrial policy could improve firms' access to capital and encourage cross-border mergers and acquisitions. (3) Industrial policies could promote the high political relevance of state-owned enterprises, thus promoting the success of transnational mergers and acquisitions of enterprises. Therefore, it was significant to promote the transformation of industrial policy from subsidy-oriented to performance-oriented and rationally evaluate the risks and benefits of M&A for enterprises to complete cross-border M&A.

The impact of global warming is increasing and thus exacerbating environmental stresses that affect plant yield and distribution, including the Eriobotrya japonica Lindl (Loquat tree). Eriobotrya japonica, a member of the Rosaceae family, is valued not only for its nutritious fruit but also for its medicinal purposes, landscape uses, and other pharmacological benefits. Nonetheless, the productivity of Eriobotrya japonica has raised a lot of concern in the wake of adverse environmental conditions. Understanding the characteristics of the LRR-RLK gene family in loquat is crucial, as these genes play vital roles in plant stress responses. In this study, 283 LRR-RLK genes were identified in the genome of E. japonica that were randomly positioned on 17 chromosomes and 24 contigs. The 283 EjLRR-RLK proteins clustered into 21 classes and subclasses in the phylogenetic analysis based on domain and protein arrangements. Further explorations in the promoter regions of the EjLRR-RLK genes showed an abundance of cis-regulatory elements that functioned in growth and development, phytohormone, and biotic and abiotic responses. Most cis-elements were present in the biotic and abiotic responses suggesting that the EjLRR-RLK genes are invested in regulating both biotic and abiotic stresses. Additional investigations into the responses of EjLRR-RLK genes to abiotic stress using the RT-qPCR revealed that EjLRR-RLK genes respond to abiotic stress, especially heat and salt stresses. Particularly, EjapXI-1.6 and EjapI-2.5 exhibited constant upregulation in all stresses analyzed, indicating that these may take an active role in regulating abiotic stresses. Our findings suggest the pivotal functions of EjLRR-RLK genes although additional research is still required. This research aims to provide useful information relating to the characterization of EjLRR-RLK genes and their responses to environmental stresses, establishing a concrete base for the following research.