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Abstract Background The triglyceride-glucose (TyG) index has been recognized as being an alternative cardiometabolic biomarker for insulin resistance associated with the development and prognosis of cardiovascular disease (CVD). However, the prospective relationship between baseline and long-term trajectories of the TyG index and carotid atherosclerosis (CAS) progression has yet to be investigated. Methods This longitudinal prospective cohort study included 10,380 adults with multiple general health checks at Peking University Third Hospital from January 2011 to December 2020. The TyG index was calculated as ln (fasting triglyceride [mg/dL] × fasting glucose [mg/dL]/2). The latent class trajectory modeling method was used to analyze the TyG index trajectories over the follow-up. Based on univariate and multivariate Cox proportional hazards analyses, hazard ratios (HRs) and 95% confidence intervals (CIs) were calculated for the baseline and trajectory of the TyG index. Results During a median follow-up period of 757 days, 1813 participants developed CAS progression. Each 1-standard deviation (SD) increase in the TyG index was associated with a 7% higher risk of CAS progression after adjusting for traditional CVD risk factors (HR = 1.067, 95% CI 1.006–1.132). Similar results were observed when the TyG index was expressed as quartiles. According to different trajectory patterns, participants were categorized into low-stable, moderate-stable, and high-increasing groups. After multivariate adjustment, the moderate-stable group had a 1.139-fold (95% CI 1.021–1.272) risk of CAS progression. The high-increasing trajectory of the TyG index tended to be associated with CAS progression (HR = 1.206, 95% CI 0.961–1.513). Conclusions Participants with higher baseline and moderate-stable trajectory of the TyG index were associated with CAS progression. Long-term trajectories of the TyG index can help to identify individuals at a higher risk of CAS progression who deserve specific preventive and therapeutic approaches.

Abstract Neuropsychiatric disorders are multifactorial disorders with diverse aetiological factors. Identifying treatment targets is challenging because the diseases are resulting from heterogeneous biological, genetic, and environmental factors. Nevertheless, the increasing understanding of G protein-coupled receptor (GPCR) opens a new possibility in drug discovery. Harnessing our knowledge of molecular mechanisms and structural information of GPCRs will be advantageous for developing effective drugs. This review provides an overview of the role of GPCRs in various neurodegenerative and psychiatric diseases. Besides, we highlight the emerging opportunities of novel GPCR targets and address recent progress in GPCR drug development.

Circulating tumor DNA (ctDNA) has potential as a promising biomarker for molecular residual disease (MRD) detection in lung cancer. As the next‐generation sequencing standardized panel for ctDNA detection emerges, its clinical utility needs to be validated. We prospectively recruited 184 resectable lung cancer patients from four medical centers. Serial postoperative ctDNAs were analyzed by a standardized panel. A total of 427 postoperative plasma samples from 177 eligible patients were enrolled. ctDNA positivity after surgery was an independent predictor for disease recurrence and preceded radiological recurrence by a median of 6.6 months (range, 0.7–27.0 months). ctDNA‐positive or ‐negative patients with tumors of any stage had similar disease‐free survival (DFS). Patients who received targeted therapy had significantly improved DFS than those not receiving adjuvant therapy or receiving chemotherapy, regardless of baseline/preadjuvant ctDNA status. According to whether the ctDNA variants were detected in its matched tissue, they were classified into tissue derived and non‐tissue derived. Patients with detectable postoperative ctDNA with tissue‐derived mutations had comparable DFS with those with non‐tissue‐derived mutations. Collectively, we demonstrated that postoperative ctDNA has the potential to stratify prognosis and optimize tumor stage in resectable lung cancer. ctDNA variants not identified in tissue samples should be considered in MRD test.

Zn–Ag alloys are particularly promising for application as biodegradable implant materials due to their harmless degradation products, suitable degradation rate, and remarkable biocompatibility. Nonetheless, their mechanical properties are generally below the requirements for medical implants. In this work, a bimodal grain structured Zn–0.5Ag–0.2Mg alloy with excellent strength and ductility was achieved through combined equal channel angular pressing (ECAP) and cold rolling (CR), significantly superior to their counterparts obtained through ECAP or CR. Specifically, the ultimate tensile strength (UTS) and elongation (EL) of the alloy are as high as 332 MPa and 63%, respectively, far exceeding the application requirements. In achieving the excellent mechanical properties, a key role is played by hetero-deformation induced (HDI) strengthening. This work may provide practical guidance for developing high-performance Zn alloys.

The endoplasmic reticulum (ER) is indispensable for maintaining normal life activities. Dysregulation of the ER function results in the accumulation of harmful proteins and lipids and the disruption of intracellular signaling pathways, leading to cellular dysfunction and eventual death. Protein misfolding within the ER disrupts its delicate balance, resulting in the accumulation of misfolded or unfolded proteins, a condition known as endoplasmic reticulum stress (ERS). Renal fibrosis, characterized by the aberrant proliferation of fibrotic tissue in the renal interstitium, stands as a grave consequence of numerous kidney disorders, precipitating a gradual decline in renal function. Renal fibrosis is a serious complication of many kidney conditions and is characterized by the overgrowth of fibrotic tissue in the glomerular and tubular interstitium, leading to the progressive failure of renal function. Studies have shown that, during the onset and progression of kidney disease, ERS causes various problems in the kidneys, a process that can lead to kidney fibrosis. This article elucidates the underlying intracellular signaling pathways modulated by ERS, delineating its role in triggering diverse forms of cell death. Additionally, it comprehensively explores a spectrum of potential pharmacological agents and molecular interventions aimed at mitigating ERS, thereby charting novel research avenues and therapeutic advancements in the management of renal fibrosis.

Cadmium (Cd) contamination in agricultural soils has emerged as a significant concern, particularly due to its potential impact on plant-based food. Soil pH reductions can exacerbate Cd mobility, leading to excessive accumulation in crops. While liming has been demonstrated as an effective method to mitigate Cd accumulation in rice grains in acid soils of southern China, its efficacy in remediating acid soils in northern China remains unclear. In this study, a multi-year field experiment was conducted on farmland impacted by zinc ore smelting at coordinates of 33.92° N 112.46° E to investigate the use of limestone for controlling Cd accumulation in wheat and maize grains. The results indicated that applying 7.5 t ha−1 of limestone significantly raised the soil pH from 4.5 to 6.8 as anticipated. Different rates of limestone application (2.25, 4.45, and 7.50 t ha−1) reduced Cd bioavailability in the soil by 20–54%, and Cd accumulation in wheat grains by 5–38% and maize grains by 21–63%, without yield penalty. The remediation effects were sustained for at least 27 months, highlighting limestone as a promising ameliorant for smelting-affected farmland in northern China.

In recent years, with the increase in environmental awareness, people have become more and more concerned about the effectiveness with which coal burns. Laser-induced breakdown spectroscopy (LIBS) has become an important way of coal elemental analysis because of its uncomplicated sample handling, remote sensing capability, and superior sensitivity in identifying a wide range of elements, including both major and minor constituents, down to trace levels. However, the complexity of its mechanism of action, the experimental environmental factors, and the presence of matrix effects in its measurement spectrum have affected the measurement accuracy. In this paper, on the basis of introducing the experimental process and principle of LIBS, we summarize and analyze the influence of each factor on the LIBS detection medium, summarize the mainstream model analysis algorithms, and analyze the advantages and disadvantages of each model. While summarizing the LIBS in media detection in recent years, it aims to provide strong support and guidance for subsequent more in-depth exploration and research.

With the growing adoption of battery energy storage systems in renewable energy sources, electric vehicles (EVs), and portable electronic devices, the effective management of battery systems has become increasingly critical. The advent of wireless battery management systems (wBMSs) represents a significant innovation in battery management technology. Traditional wired battery management systems (BMSs) face challenges, including complexity, increased weight, maintenance difficulties, and a higher chance of connection failure. In contrast, wBMSs offer a robust solution, eliminating physical connections. wBMSs offer enhanced flexibility, reduced packaging complexity, and improved reliability. Given that wBMSs are still in a preliminary stage, this review paper explores their evolution, current state, and future directions. A comprehensive survey of state-of-the-art wBMS technologies, including academic and commercial solutions, is elaborated in this paper. We compare wireless communication technologies like Bluetooth Low Energy (BLE), Zigbee, Near-Field Communication (NFC), Wi-Fi, and cellular networks in the context of wBMSs. We discuss their performance in terms of efficiency, reliability, scalability, and security. Despite its promising outlook, wBMSs still face challenges such as data security, signal interference, regulatory and standardization issues, and competition from the continued advancement of wired BMS technologies, making the advantages of wBMSs less evident. This paper concludes with guidelines for future research and development of wBMSs, aiming to address these challenges and pave the way for a broad adoption of wBMSs across various applications. This paper aims to inspire further research and innovation in the field, contributing to developing an industry-ready wBMS.

This paper proposes a single-phase, transformer-less, seven-level inverter that utilizes eight switches, three capacitors, and two diodes to produce seven voltage levels with triple boosting ability. The availability of the common-ground point eliminates the leakage current in PV applications. The proposed Transformer-Less Triple-Boosting Seven-Level Inverter (TLTB7LI) has the ability to feed different types of loads from non-unity to unity power factors. The voltage balancing of capacitors takes place naturally without the need for auxiliary circuits and complicated control strategies. This paper investigates the appropriateness of the proposed TLTB7LI for grid-connected application. The Peak Current Controller (PCC) is employed to generate the switching pulses and regulate the active/reactive power transfer between the converter and the output, which guarantees the high quality of injected current to the output. Moreover, the operational principles, its control technique, as well as the design procedure of the key components of the proposed inverter have been presented. The superiority of the proposed inverter over existing counterparts has been verified through comparative analysis. The simulation and experimental analysis validated the proper operation of the proposed TLTB7LI.

Charge transport materials constitute a relatively large portion of the cost in the production of perovskite solar cells (PSCs). Therefore, developing cheap and efficient charge transport materials is of great significance for the commercialization of PSCs. In this study, three low-cost hole transport materials (HTMs), specifically 4,4'-(3,3'-bis(4-methoxy-2,6-dimethylphenyl)-[2,2'-bithiophene]-5,5'-diyl)bis(N,N-bis(4-methoxyphenyl)aniline) (TP-H), 4,4'-(3,3'-bis(4-methoxy-2,6-dimethylphenyl)-[2,2'-bithiophene]-5,5'-diyl)bis(3-methoxy-N,N-bis(4-methoxyphenyl)aniline) (TP-OMe), and 4,4'-(3,3'-bis(4-methoxy-2,6-dimethylphenyl)-[2,2'-bithiophene]-5,5'-diyl)bis(3-fluoro-N,N-bis(4-methoxyphenyl)aniline) (TP-F), were designed and synthesized using a bulky group-substituted 2,2'-bithiophene core and methoxy- or F-functionalized triphenylamine derivatives. Compared to the HTMs without F atoms, TP-F using F substitution exhibited enhanced intermolecular packing, a lower highest occupied molecular orbital energy level, and increased hole mobility and conductivity. The PSC incorporating the doped TP-F as the hole transport layer achieved the highest power conversion efficiency (over 24%) among the three devices. The high performance of TP-F can be attributed to the passivation effect of S and F atoms on uncoordinated Pb2+ within the perovskite (PVSK) film, which significantly reduces the density of defect states and the incidence of trap-mediated recombination in PSCs. This study demonstrates the effectiveness of the 3,3'-bis(4-methoxy-2,6-dimethylphenyl)-2,2'-bithiophene building block for constructing cost-effective HTMs and highlights the impact of F substitution on enhancing the photovoltaic performance of PSCs.

The passive estimation of harmonic sound source depth is of great significance for underwater target localization and identification. Passive source depth estimation using a single hydrophone with an unknown seabed geoacoustic property is a crucial challenge. To address this issue, a harmonic sound source depth estimation algorithm, seabed independent depth estimation (SIDE) algorithm, is proposed. This algorithm combines the estimated mode depth functions, modal amplitudes, and the sign of each modal to estimate the sound source depth. The performance of the SIDE algorithm is analyzed by simulations. Results show that the SIDE is insensitive to the initial range of the sound source, the source depth, the hydrophone depth, the source velocity, and the type of the seabed. Finally, the effectiveness of the SIDE algorithm is verified by the SWellEX-96 data.

Hydronephrosis resulting from unilateral ureteral obstruction (UUO) is a common cause of renal injury, often progressing to late-stage renal fibrosis or even potential renal failure. Renal injury and repair processes are accompanied by changes in cellular senescence phenotypes. However, the mechanism is poorly understood. The purpose of this study is to clarify the changes in senescence phenotype at different time points in renal disease caused by UUO and to further investigate whether eliminating senescent cells using the anti-senescence drug ABT263 could attenuate UUO-induced renal disease. Specifically, renal tissues were collected from established UUO rat models on days 1, 2, 7, and 14. The extent of renal tissue injury and fibrosis in rats was assessed using histological examination, serum creatinine, and blood urea nitrogen levels. The apoptotic and proliferative capacities of renal tissues and phenotypic changes in cellular senescence were evaluated. After the intervention of the anti-senescence drug ABT263, the cellular senescence as well as tissue damage changes were re-assessed. We found that before the drug intervention, the UUO rats showed significantly declined renal function, accompanied by renal tubular injury, increased inflammatory response, and oxidative stress, alongside aggravated cellular senescence. Meanwhile, after the treatment with ABT263, the rats had a significantly lower number of senescent cells, attenuated renal tubular injury and apoptosis, enhanced proliferation, reduced oxidative stress and inflammation, improved renal function, and markedly inhibited fibrosis. This suggests that the use of the anti-senescence drug ABT263 to eliminate senescent cells can effectively attenuate UUO-induced renal injury. This highlights the critical role of cellular senescence in the transformation of acute injury into chronic fibrosis.

Geotechnical engineering is civil engineering constructed in rock and soil and includes three main types: underground, foundation, and slope engineering [...]

In scientific computing, neural networks have been widely used to solve partial differential equations (PDEs). In this paper, we propose a novel RBF-assisted hybrid neural network for approximating solutions to PDEs. Inspired by the tendency of physics-informed neural networks (PINNs) to become local approximations after training, the proposed method utilizes a radial basis function (RBF) to provide the normalization and localization properties to the input data. The objective of this strategy is to assist the network in solving PDEs more effectively. During the RBF-assisted processing part, the method selects the center points and collocation points separately to effectively manage data size and computational complexity. Subsequently, the RBF processed data are put into the network for predicting the solutions to PDEs. Finally, a series of experiments are conducted to evaluate the novel method. The numerical results confirm that the proposed method can accelerate the convergence speed of the loss function and improve predictive accuracy.

The substantial data volume within dynamic point clouds representing three-dimensional moving entities necessitates advancements in compression techniques. Motion estimation (ME) is crucial for reducing point cloud temporal redundancy. Standard block-based ME schemes, which typically utilize the previously decoded point clouds as inter-reference frames, often yield inaccurate and translation-only estimates for dynamic point clouds. To overcome this limitation, we propose an advanced patch-based affine ME scheme for dynamic point cloud geometry compression. Our approach employs a forward-backward jointing ME strategy, generating affine motion-compensated frames for improved inter-geometry references. Before the forward ME process, point cloud motion analysis is conducted on previous frames to perceive motion characteristics. Then, a point cloud is segmented into deformable patches based on geometry correlation and motion coherence. During the forward ME process, affine motion models are introduced to depict the deformable patch motions from the reference to the current frame. Later, affine motion-compensated frames are exploited in the backward ME process to obtain refined motions for better coding performance. Experimental results demonstrate the superiority of our proposed scheme, achieving an average 6.28% geometry bitrate gain over the inter codec anchor. Additional results also validate the effectiveness of key modules within the proposed ME scheme.

There is a pressing need across various applications for efficiently compressing point clouds. While the Moving Picture Experts Group introduced the geometry-based point cloud compression (G-PCC) standard, its attribute compression scheme falls short of eliminating signal frequency-domain redundancy. This paper proposes a texture-guided graph transform optimization scheme for point cloud attribute compression. We formulate the attribute transform coding task as a graph optimization problem, considering both the decorrelation capability of the graph transform and the sparsity of the optimized graph within a tailored joint optimization framework. First, the point cloud is reorganized and segmented into local clusters using a Hilbert-based scheme, enhancing spatial correlation preservation. Second, the inter-cluster attribute prediction and intra-cluster prediction are conducted on local clusters to remove spatial redundancy and extract texture priors. Third, the underlying graph structure in each cluster is constructed in a joint rate–distortion–sparsity optimization process, guided by geometry structure and texture priors to achieve optimal coding performance. Finally, point cloud attributes are efficiently compressed with the optimized graph transform. Experimental results show the proposed scheme outperforms the state of the art with significant BD-BR gains, surpassing G-PCC by 31.02%, 30.71%, and 32.14% in BD-BR gains for Y, U, and V components, respectively. Subjective evaluation of the attribute reconstruction quality further validates the superiority of our scheme.

BackgroundThe attention towards the relationship between chronic obstructive pulmonary disease (COPD) and dietary intake is escalating. However, the effects of dietary niacin on COPD in middle and older individuals remains unclear. This study aimed to illuminate the connection between dietary niacin intake and COPD.MethodsThis cross-sectional study analyzed 7,170 participants from the National Health and Nutrition Examination Survey (NHANES) spanning the years 2013 to 2018. Participants were categorized into four groups based on quartiles of dietary niacin intake. To examine the association between covariates, dietary niacin intake, and COPD, we employed univariate analysis and multivariate logistic regression equations. Additionally, restricted cubic splines were utilized to assess linearity. Furthermore, we conducted stratified and interaction analyses to evaluate the stability of the relationship in diverse subgroups.ResultsAmong the 7,170 participants, 11.6% (834/7170) were diagnosed with COPD. The multivariable adjusted odds ratios (ORs) and 95% confidence intervals (CIs) for COPD were 0.96 (95% CI: 0.77-1.19, p = 0.706), 0.78 (95% CI: 0.62-0.99, p = 0.038), and 0.76 (95% CI: 0.57-1.00, p = 0.047), respectively, when comparing the second, third, and fourth quartiles of niacin intake levels to the lowest quartile (p for trend = 0.017). An inverse association was observed between the occurrence of COPD and dietary niacin intake (nonlinear: p = 0.347). Stratified analyses revealed no significant differences or interactions.ConclusionOur findings suggest a potential link between increased dietary niacin intake and a decreased prevalence of COPD.

We conducted a retrospective cohort study to evaluate the transmission risk of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Omicron BA.2 variant and the effectiveness of inactivated COVID-19 vaccine boosters in Shenzhen during a BA.2 outbreak period from 1 February to 21 April 2022. A total of 1,248 individuals were infected with the BA.2 variant, and 7,855 close contacts were carefully investigated. The risk factors for the high secondary attack rate of SARS-CoV-2 infection were household contacts [adjusted odds ratio (aOR): 1.748; 95% confidence interval (CI): 1.448, 2.110], younger individuals aged 0–17 years (aOR: 2.730; 95% CI: 2.118, 3.518), older persons aged ≥60 years (aOR: 1.342; 95% CI: 1.135, 1.588), women (aOR: 1.442; 95% CI: 1.210, 1.718), and the subjects exposed to the post-onset index cases (aOR: 8.546; 95% CI: 6.610, 11.050), respectively. Compared with the unvaccinated and partially vaccinated individuals, a relatively low risk of secondary attack was found for the individuals who received booster vaccination (aOR: 0.871; 95% CI: 0.761, 0.997). Moreover, a high transmission risk was found for the index cases aged ≥60 years (aOR: 1.359; 95% CI: 1.132, 1.632), whereas a relatively low transmission risk was observed for the index cases who received full vaccination (aOR: 0.642; 95% CI: 0.490, 0.841) and booster vaccination (aOR: 0.676; 95% CI: 0.594, 0.770). Compared with full vaccination, booster vaccination of inactivated COVID-19 vaccine showed an effectiveness of 24.0% (95% CI: 7.0%, 37.9%) against BA.2 transmission for the adults ≥18 years and 93.7% (95% CI: 72.4%, 98.6%) for the adults ≥60 years, whereas the effectiveness was 51.0% (95% CI: 21.9%, 69.3%) for the individuals of 14 days to 179 days after booster vaccination and 51.2% (95% CI: 37.5%, 61.9%) for the non-household contacts. The estimated mean values of the generation interval, serial interval, incubation period, latent period, and viral shedding period were 2.7 days, 3.2 days, 2.4 days, 2.1 days, and 17.9 days, respectively. In summary, our results confirmed that the main transmission route of Omicron BA.2 subvariant was household contact, and booster vaccination of the inactivated vaccines was relatively effective against BA.2 subvariant transmission in older people.

Abstract In recent years, 2D reconfigurable phototransistors (RPTs) have been applied in broadband convolutional processing, retinomorphic hardware devices, and non‐volatile memorizers. However, there has been a lack of investigation into all‐2D Schottky junctions used in RPT with polarity control behavior. Herein, a vertically stacked multilayered WS2/WTe2 Schottky RPT is reported. The semimetal characteristics of 1T’‐WTe2 is designed to form a built‐in electric field of 69 meV across the heterojunction and WS2 exhibits gate‐tunable characteristics. Therefore, reconfigurable rectifying behavior and self‐driven bidirectional photo response can be achieved. The phototransistor possesses a gate‐tunable rectification ratio ranging from 10−2 to 105, and the corresponding logic half‐wave rectifier shows excellent switchable rectifying states. Under 635 nm illumination, the responsivity can be adjusted from −1325 to 430 mA W−1 with reversed signs. Meanwhile, the maximum power conversion efficiency is 2.84%, and the specific detectivity is 1.47 × 1012 Jones. The device shows both negative and positive responsivity with linear gate dependence within a voltage window of 10 V. Impressively, nonvolatile photovoltaic performance can be demonstrated by reversing short‐circuit current and open‐circuit voltage by applying and releasing pulsed gate voltage. Finally, reconfigurable polarization behavior, single‐pixel imaging, and the optical logic circuit are applicable to the heterostructure.

Lutein possesses various physiological activities but is susceptible to light degradation, thermal degradation, and oxidative degradation. As such, protecting the activity of lutein-based products using natural extracts has become a current research. In this study, lutein was protected by complexing inulin-type fructan (ITF), soybean protein isolate (SPI), and epicatechin (EC), and the protection mechanism of epicatechin-fructan glycosylated soybean protein isolate (EC-GSPI) toward lutein was elucidated comprehensively. The results showed that the addition of EC delayed the degradation of lutein. The results of light stability experiments showed that increased EC significantly enhanced the storage time of the GSPI-Lutein system from 4 to 13 days. Additionally, the effect of EC on glycosylated soybean 7S globulin (G7S) and glycosylated soybean 11S globulin (G11S) was assessed. The light stability of G11S-Lutein and G7S-Lutein after the addition of EC was from G11S > G7S → G7S > G11S. Furthermore, the proteins purified from SPI interacted differently with EC and ITF, with soybean 7S globulin (7S) mainly interacting with EC and soybean 11S globulin (11S) mainly interacting with ITF. EC-GSPI-Lutein exhibited a good protective effect, probably due to the occurrence of hygrothermal Maillard between ITF and 11S, providing a porous structure for lutein storage. At the same time, the binding of EC to 7S significantly enhanced the antioxidant property of the solution and the stability of the protein secondary structure, thereby prolonging the storage time of lutein.

With the development of smart grids, the introduction of intermittent energy and the increase in dynamic loads have led to more and more dynamic characteristics of electricity loads in the grid. Intelligent energy meters that passed calibration under steady-state load may not necessarily meet the measurement error requirements under the excitation of dynamic load test signals, and some may even produce significant errors. At present, research on dynamic error testing of intelligent energy meters mainly focuses on establishing models of dynamic error testing signals, and the reasons for the generation of dynamic errors are still unclear. In order to analyze the sources of dynamic errors in intelligent energy meters, this article adopts a mechanism modeling method to establish a full system model of intelligent energy meters, in order to analyze the influence of model parameters of each unit on the dynamic errors of active energy, and provide important theoretical reference for further improving the dynamic error characteristics of energy meters. In addition, identifying the sources of errors has important application value for improving the algorithm of energy metering chips, optimizing the overall design of energy meters, and selecting energy meters in dynamic load scenarios for the power sector.

Immunotherapy, specifically immune checkpoint inhibitors, has emerged as a promising approach for treating malignant tumors. The gut, housing approximately 70 % of the body's immune cells, is abundantly populated with gut bacteria that actively interact with the host's immune system. Different bacterial species within the intestinal flora are in a delicate equilibrium and mutually regulate each other. However, when this balance is disrupted, pathogenic microorganisms can dominate, adversely affecting the host's metabolism and immunity, ultimately promoting the development of disease. Emerging researches highlight the potential of interventions such as fecal microflora transplantation (FMT) to improve antitumor immune response and reduce the toxicity of immunotherapy. These remarkable findings suggest the major role of intestinal flora in the development of cancer immunotherapy and led us to the hypothesis that intestinal flora transplantation may be a new breakthrough in modifying immunotherapy side effects.

ObjectiveTemporal lobe epilepsy (TLE) predominantly originates from the anteromedial basal region of the temporal lobe, and its prognosis is generally favorable following surgical intervention. However, TLE often appears negative in magnetic resonance imaging (MRI), making it difficult to quantitatively diagnose the condition solely based on clinical symptoms. There is a pressing need for a quantitative, automated method for detecting TLE.MethodsThis study employed MRI scans and clinical data from 51 retrospective epilepsy cases, dividing them into two groups: 34 patients in TLE group and 17 patients in non-TLE group. The criteria for defining the TLE group were successful surgical removal of the epileptogenic zone in the temporal lobe and a favorable postoperative prognosis. A standard procedure was used for normalization, brain extraction, tissue segmentation, regional brain partitioning, and cortical reconstruction of T1 structural MRI images. Morphometric features such as gray matter volume, cortical thickness, and surface area were extracted from a total of 20 temporal lobe regions in both hemispheres. Support vector machine (SVM), extreme learning machine (ELM), and cmcRVFL+ classifiers were employed for model training and validated using 10-fold cross-validation.ResultsThe results demonstrated that employing ELM classifiers in conjunction with specific temporal lobe gray matter volume features led to a better identification of TLE. The classification accuracy was 92.79%, with an area under the curve (AUC) value of 0.8019.ConclusionThe method proposed in this study can significantly assist in the preoperative identification of TLE patients. By employing this method, TLE can be included in surgical criteria, which could alleviate patient symptoms and improve prognosis, thereby bearing substantial clinical significance.

Background: Circulating tumor DNA (ctDNA) has emerged as a biomarker that can define the risk of recurrence after curative-intent surgery for patients with colorectal cancer (CRC). However, beyond the predictive power of postoperative ctDNA detection, the efficacy and potential limitations of ctDNA detection urgently need to be fully elucidated in a large cohort of CRC. Objectives: To define potentially cured CRC patients through ctDNA monitoring following surgery. Design: A prospective, multicenter, observational study. Methods: We enrolled 309 patients with stages I–IV CRC who underwent definitive surgery. Tumor tissues were sequenced by a custom-designed next-generation sequencing panel to identify somatic mutations. Plasma was analyzed using a ctDNA-based molecular residual disease (MRD) assay which integrated tumor-genotype-informed and tumor-genotype-naïve ctDNA analysis. The turnaround time of the assay was 10–14 days. Results: Postoperative ctDNA was detected in 5.4%, 13.8%, 15%, and 30% of patients with stage I, II, III, and IV disease, respectively, and in 17.5% of all longitudinal samples. Patients with positive postsurgery MRD had a higher recurrence rate than those with negative postsurgery MRD [hazard ratio (HR), 13.17; p < 0.0001], producing a sensitivity of 64.6%, a specificity of 94.8%, a positive predictive value (PPV) of 75.6%, and a negative predictive value (NPV) of 91.5%. Furthermore, patients with positive longitudinal MRD also had a significantly higher recurrence rate (HR, 14.44; p < 0.0001), with increased sensitivity (75.0%), specificity (94.9%), PPV (79.6%), and NPV (93.4%). Subgroup analyses revealed that adjuvant therapy did not confer superior survival for patients with undetectable or detectable MRD. In addition, MRD detection was less effective in identifying lung-only and peritoneal metastases. Conclusion: Postoperative ctDNA status is a strong predictor of recurrence independent of stage and microsatellite instability status. Longitudinal undetectable MRD could be used to define the potentially cured population in CRC patients undergoing curative-intent surgery.

In this study, thermoplastic starch (TPS) was prepared by melt extrusion process, in which glycerol and/or D-mannitol were used as plasticizers, and the effect of different glycerol/D-mannitol ratios (4:0, 3:1, 2:2, 1:3, and 0:4) on the physicochemical properties of the extruded starch samples was investigated. The short-range molecular order, crystallization, gelatinization, thermal stability, and thermal properties of the TPS samples were analyzed through attenuated total reflection-Fourier transform infrared (ATR-FTIR) spectroscopy, X-ray diffraction (XRD), rapid visco analysis (RVA), differential scanning calorimetry (DSC), and thermogravimetric analysis (TGA). The results showed that the crystallinity and short-range molecular order of the TPS samples increased with increasing glycerol content. Conversely, the water absorption index (WAI) and water solubility index (WSI) of the TPS samples decreased with increasing glycerol content. In addition, the TPS samples with higher glycerol content exhibited higher gel and thermal stabilities. This study provides a theoretical basis for starch extrusion and plasticization in the preparation of TPS-based materials with specific properties.

ABSTRACT: In the present study, we aimed to elucidate the effects of stevia extract on production performance, serum immune indexes, intestinal structure, and cecum microbial structure. We randomly divided eight hundred 46-wk-old Roman hens into 5 groups, with 8 replicates in each group and 20 chickens in each replicate. The control group was fed a basal diet, whereas the 4 experimental groups were fed 50, 100, 200, and 400 mg/kg stevia extracts. The study period was 24 wk. The addition of different concentrations of the stevia extract to the diet resulted in significant secondary changes in the egg production rate at 1 to 12 wk (P < 0.05). Furthermore, the addition of 50 and 100 mg/kg stevia extract to the diet significantly increased serum IgM and IgG levels in laying hens (P < 0.05) but linearly decreased serum IL-1β levels (P < 0.05). Serum T-SOD activity linearly increased (P = 0.057); however, serum biochemical indexes showed no significant differences. Stevia extract tended to increase the ratio of the duodenal villi height to the depth of the crypt (P = 0.067), with no obvious lesions in the duodenum, jejunum, and ileum. In addition, stevia extract increased the relative abundance of species at the phylum level, with the abundance of Bacteroides and Firmicutes exhibiting significant secondary changes (P < 0.05). The ACE and Chao1 indexes suggested that stevia extract addition significantly increased the alpha diversity of cecum microorganisms in laying hens. Furthermore, NMDS analysis based on operational taxonomic units revealed that stevia extract addition increased the beta diversity of cecum microorganisms in laying hens. Adding a certain amount of stevia extract to feed can improve the production performance, immune ability, and intestinal health of laying hens to some extent, and we recommend an effective level of 200mg/kg of stevia extract for laying hen diets.

Recurrent complete atrioventricular block induced by coronary spasm is rare. We present a case of a 47-year-old woman who suffered from two episodes of out-of-hospital cardiac arrest within one year due to complete atrioventricular block caused by coronary vasospasm. No implantable cardioverter defibrillator was implanted after her first episode. As for the second episode, permanent brain injury was left behind despite successful cardiopulmonary resuscitation. She underwent a challenging rehabilitation process and an implantable cardioverter defibrillator was implanted before discharge. We captured the dynamic changes of the electrocardiogram during the episode with high temporal resolution. This case illustrates the importance of recognizing coronary spasm as a potential cause of complete atrioventricular block and highlights the need for implantable cardioverter defibrillator in such patients to improve survival and quality of life.

Executives' carbon cognition (ECC) is an important driving factor for enterprises to achieve carbon performance (CP) through low-carbon actions, but the existing research has not explored the mechanism between them. Based on the data of 440 Chinese listed companies from 2012 to 2021, we used text mining method to construct the index of ECC, and obtained noteworthy results through regression analysis. The results indicated that ECC has a significant positive impact on corporate low-carbon actions (CLA); CLA has a significant positive impact on CP; CLA plays a mediating role in the relationship between ECC and CP; in addition, firm size negatively moderates the positive impact of ECC on CLA; firm size negatively moderates the mediating effect of CLA on the relationship between ECC and CP. The research conclusions deepen the understanding of the relationship between ECC and CP in the context of carbon neutrality era, and provide theoretical guidance for guiding companies to actively implement low-carbon actions. At the same time, this study introduces the text mining method into the research of ECC, which provides a reference for future research in this field.

In metal-wall EAST superconducting tokamak, H-mode operation with plasma density close to the Greenwald density limit nGW has been achieved with radio frequency and NBI heating for the first time. Both gas puffing from horizontal plane and HFS pellet fueling were used for density ramp-up during the experiment. The confinement of H-mode gradually deteriorates with plasma density increasing. And the H-L transition can be observed after heating power dropping or pellet injection. In the density range of (0.6–1)×nGW, the divertor detachment occurs and causes an obvious confinement degradation. The maximum accessible density ne, max in H-mode phase deviates from the Greenwald scaling. It has been observed that the fraction ne, max/nGW is almost independent of the total heating power, but a high heating power is helpful to extend the duration of high density H-mode. And ne,max/nGW has an increase relation with the safety factor q95 varied by changing plasma current. Besides, it is also found that the discharges with low plasma current have a higher ne, max/nGW than those with high plasma current. All these findings will provide a good reference to the high density plasma operation for future metal-wall fusion devices.

Hydrogels have been recognized for their versatile in regenerative medicine; however, their inadequate mechanical and osteogenic properties have limited their applicability in bone tissue engineering (BTE). Hence, we present a novel approach to address this issue by developing sulfated methacrylate hyaluronic acid hydrogels (SMeHA@CM) doped with alendronate (ALN), calcium ions (Ca2+), and magnesium ions (Mg2+). This hydrogel system incorporates sequential physical and chemical crosslinking to facilitate the treatment of bone defects. Physical crosslinks form between the SO32−, ALN, and Ca2+/Mg2+ ions, resulting in nanocluster crosslinking and complete filling of irregular bone defects. Subsequently, the methacrylate groups within the polymer chain undergo polymerization under ultraviolet light irradiation, forming the second stage of chemical crosslinking in the SMeHA@CM hydrogel. These chemical crosslinks contribute strong chemical bonds, enhancing biomechanical strength, and stable support for bone regeneration. The SMeHA@CM hydrogel exhibits remarkable osteogenic capacity, primarily attributed to the cooperative action of SO32− and Mg2+ ions, which promote the recruitment of bone marrow stem cells and angiogenesis. Furthermore, the sustained release of SO32−-ALN-Ca2+/Mg2+ nanoclusters from the hydrogel system offers additional benefits for bone regeneration. Moreover, both in-vitro and in-vivo assessments confirm the significant potential of the newly developed SMeHA@CM hydrogel for applications in BTE.

Background: Shedding of glycocalyx is relevant to worse prognosis in surgical patients, and elevated levels of serum matrix metalloproteinase-9 (MMP-9) are associated with this phenomenon. This study aimed to investigate the dynamic alterations of serum glycocalyx components and MMP-9 during cardiopulmonary bypass (CPB), and evaluate their predictive capacities for prolonged intensive care unit (ICU) stay, as well as their correlation with coagulation dysfunction. Methods: This retrospective study analyzed serum levels of syndecan-1, heparan sulfate (HS), and MMP-9 at different time points during CPB, and assessed their association with prolonged ICU stay and coagulation dysfunction. Results: Syndecan-1, HS, and MMP-9 exhibited divergent changes during CPB. Serum levels of syndecan-1 (AUC = 78.0 %) and MMP-9 (AUC = 78.4 %) were validated as reliable predictors for prolonged ICU stay, surpassing the predictive value of creatinine (AUC = 70.0 %). Syndecan-1 (rho = 0.566, P

Carbon dots (CDs) have photoconversion performance and have a wide range of applications in agriculture. However, the solution of CDs is susceptible to quench under evaporation of sunlight and is easy to run-off when influenced by the external environment. Here, PVA-coated CDs were used to overcome the solid-state quenching and to prepare CDs microcapsules-polyurethane Film for plant cultivation. In this work, CDs microcapsules which can convert ultraviolet light into blue light for plant growth, were prepared by the “water/oil/water” method, and light-converting CDs microcapsules polyurethane film (CMPF) was prepared by doping CDs microcapsules with polyurethane. The study showed that polyurethane film has good mechanical properties and self-healing ability, the CMPF was able to effectively promote the growth of lettuce, and the effect was most significant at the CDs microcapsules concentration of 4000 mg/L. Compared with the blank group, the fresh and dry weights were increased by 177 % and 143.5 %, respectively, and the content of chlorophyll a, chlorophyll b, carotenoids, and soluble protein were increased by 14.5 %, 188.5 %, 43.3 %, and 17.9 %, respectively. Application of CDs to modulate plant lighting growth regulators for efficient use of ultraviolet (UV) light.

Remote sensing is a promising technology for global water eutrophication monitoring, and the quantity and representativeness of the observed samples influence its accuracy. Due to limitations in high costs in situ monitoring, current remote sensing of lakes often relies on models trained with water quality samples from a single season. However, the generalization ability of these single-season trained models to other seasons has not been extensively studied. In this study, focusing on 38 major lakes in the Yangtze River Basin, we utilized monthly chlorophyll-a (Chla) monitoring data and Sentinel-2 image datasets from 2016 to 2021 to assess the impact of different seasonal data-trained models on the performance of Chla concentration retrieval in lakes. The results indicate that: (a) The sampling time for lake Chla significantly affects the performance of the retrieval model. Based on the seasonal data, the trained models show an R2 range of 0.523 to 0.699, with a Bias ranging from −7.06 % to 7.74 %, while the models trained with full-season samples perform between the various seasonal models. (b) When models built with seasonal data are applied to full-season data retrieval, there is a noticeable decrease in performance. The R2 of the spring-winter data trained model drops by 18.2 %, with RMSL and MAPE increasing by 11.4 % and 4.2 %, respectively. Similarly, the model trained from summer-autumn data shows a 4.02 % decrease in R2, with RMSLE and MAPE rising by 2.76 % and 13.56 %, respectively. This suggests that using models established from seasonal samples to infer full-season Chla concentrations can amplify errors. (c) Compared to seasonal models, full-season models based on different seasonal sampling exhibit better performance (R2 = 0.585, RMSLE = 0.337, Bias = -3.12 %, MAPE = 34.71 %). R2, RMSLE, and MAPE are all superior to seasonal models. Therefore, when performing full-time and long-term retrieval of Chla concentrations in water bodies, it is necessary to use data sampled in different seasons to reduce the errors introduced by seasonal sampling. (d) Chla retrieval models were established for 38 typical lakes and reservoirs in the Yangtze River Basin using the full-time dataset, revealing that 25 % (7/28) of the lakes and 20 % (2/10) of the reservoirs showed significant alteration trends. The number of lakes with increasing Chla concentrations exceeded those with decreasing concentrations, indicating that there is still a substantial risk of eutrophication in the lakes and reservoirs of the Yangtze River Basin.

Abstract Since the four working groups of the Chinese Society of Cardiology issued first expert consensus on coronary microvascular diseases (CMVD) in 2017, international consensus documents on CMVD have increased rapidly. Although some of these documents made preliminary recommendations for the diagnosis and treatment of CMVD, they did not provide classification of recommendations and levels of evidence. In order to summarize recent progress in the field of CMVD, standardize the methods and procedures of diagnosis and treatment, and identify the scientific questions for future research, the four working groups of the Chinese Society of Cardiology updated the 2017 version of the Chinese expert consensus on CMVD and adopted a series of measures to ensure the quality of this document. The current consensus has raised a new classification of CMVD, summarized new epidemiological findings for different types of CMVD, analyzed key pathological and molecular mechanisms, evaluated classical and novel diagnostic technologies, recommended diagnostic pathways and criteria, and therapeutic strategies and medications, for patients with CMVD. In view of the current progress and knowledge gaps of CMVD, future directions were proposed. It is hoped that this expert consensus will further expedite the research progress of CMVD in both basic and clinical scenarios.

ABSTRACT Central nervous system infections (CNSIs) are common complications after neurosurgery with a poor prognosis. The traditional microbiological culture methodology has a low detection rate and time consuming. Metagenomic next-generation sequencing (mNGS) has demonstrated the advantages of being faster, more accurate, and more comprehensive in clinical microbiology. Previous studies had suggested that mNGS had a high sensitivity in the diagnosis of CNSIs. Whether the application of mNGS has health economic value in clinical applications remains to be studied. We designed a prospective, single-center, superiority randomized controlled trial to compare the cost-effectiveness of mNGS with traditional methods for diagnosing CNSIs using a decision tree model. A total of 204 patients will be enrolled and randomly assigned to either the mNGS group or the traditional method group. The two groups of patients entered different decision points according to different clinical manifestations and examination results. They will be then given treatment decisions by a panel of specialists at the corresponding decision point. The primary outcome is the incremental cost-effectiveness ratio, which is the increased cost for every 1% increase in recovery rate. The secondary outcomes are a comparison of time cost, detection cost, and costs associated with antibiotics treatment between the two groups.IMPORTANCEDiagnosing and treating postoperative central nervous system infections (PCNSIs) remains challenging due to the low detection rate and time-consuming nature of traditional methods for identifying microorganisms in cerebrospinal fluid. Metagenomic next-generation sequencing (mNGS) technology provides a rapid and comprehensive understanding of microbial composition in PCNSIs by swiftly sequencing and analyzing the microbial genome. The current study aimed to assess the economic impact of using mNGS versus traditional bacterial culture-directed PCNSIs diagnosis and therapy in post-neurosurgical patients from Beijing Tiantan Hospital. mNGS is a relatively expensive test item, and whether it has the corresponding health-economic significance in the clinical application of diagnosing intracranial infection has not been studied clearly. Therefore, the investigators hope to explore the clinical application value of mNGS detection in PCNSIs after neurosurgery.

Microglia are immune cells within the central nervous system (CNS) closely linked to brain health and neurodegenerative diseases such as Alzheimer’s disease and Parkinson’s disease. In response to changes in the surrounding environment, microglia activate and change their state and function. Several factors, example for circadian rhythm disruption and the development of neurodegenerative diseases, influence microglia activation. In this review, we explore microglia’s function and the associated neural mechanisms. We elucidate that circadian rhythms are essential factors influencing microglia activation and function. Circadian rhythm disruption affects microglia activation and, consequently, neurodegenerative diseases. In addition, we found that abnormal microglia activation is a common feature of neurodegenerative diseases and an essential factor of disease development. Here we highlight the importance of microglia activation in neurodegenerative diseases. Targeting microglia for neurodegenerative disease treatment is a promising direction. We introduce the progress of methods targeting microglia for the treatment of neurodegenerative diseases and summarize the progress of drugs developed with microglia as targets, hoping to provide new ideas for treating neurodegenerative diseases.

ABSTRACT H6 influenza A viruses are enzootic and genetically diverse in both domestic poultry and wild birds, occasionally causing spillovers to mammals, including humans, posing threat to public health. However, the antigenic sites of the hemagglutinin (HA) of H6 are poorly understood. In this study, a panel of murine monoclonal antibodies (MAbs) with different reactivity spectra against HA of H6 was generated and nine key residues of antigenic epitopes in H6 were identified through escape mutants of these MAbs. Of these, residues 139 and 140 belonged to antigenic Sa, residue 89 belonged to antigenic Cb, residue 149 belonged to Ca2, while residue 221 belonged to Ca1 regarding the H1 antigenic sites. However, the other four residues 69, 120, 124, and 246 were not located in the identified antigenic regions of H1. Although most HA variants of the escape mutants had the preference for avian-like receptor, whereas escape mutants m3B9 and m4C2 increased the binding affinity for both avian and human-like receptors, and m1A5 and m6D11 decreased the binding affinity for avian-like receptors. Moreover, a single dose of MAbs 4C2 or 6E3 could fully protect mice against lethal challenge of mouse-adapted A/Eurasian teal/Jiangxi/2018WB0417(H6N2) (MA E-Teal/417) in the prophylactic treatment and also could provide partial protection in the therapeutic treatment. Overall, the generated MAbs and the identified key residues of antigenic epitopes not only provide novel insights into the key markers for monitoring the antigenic variation of H6 but also demonstrate the potential for developing MAb-based passitive treatments for H6. IMPORTANCE Since the escape immunity of influenza A viruses (IAVs) is mainly caused by the continuous antigenic variations in HA, the identification of key antigenic epitopes is crucial for better understanding of the escape immunity and vaccine development for IAVs. The antigenic sites of several HA subtypes, including H1, H3, H5, and H9, have been well characterized, whereas those of H6 subtype are poorly understood. Here, we mapped nine key residues of antigenic epitopes in H6 through escape mutants using a panel of MAbs. Moreover, MAbs 4C2 and 6E3, targeting 140 and 89 residues, respectively, could protect mice against lethal challenge of MA E-Teal/417. These key residues of antigenic epitopes identified here provide the molecular targets for further elucidating the antigenic evolution of H6 and better preparing the vaccine against H6 IAV.

Abstract A statistical inversion method of estimating normal mode interference spectral parameters (including waveguide invariance and interference frequency) from one‐dimensional broadband sound intensity spectrum (1D BSIS) is presented. First, the interference phase of 1D BSIS is compensated by a non‐linear factor for each pair of unknown parameters in a prior parameter space. Second, the singular value decomposition is performed for a data matrix, which is constructed by the phase‐compensated BSIS. Then, a misfit function is defined based on both the maximum singular value and the corresponding singular vector of the data matrix. Finally, the posterior probability distributions of unknown parameters are analysed based on statistical inversion theory. This method is suitable for the situation using a single receiver and without any environmental information. Numerical simulations illustrate the validity of the presented method.

BackgroundUsing statistical methods to analyze and summarize the research data of the inclusion criteria, to provide a quantitative average effect size to interpret the influence of mindfulness yoga exercise on patients with different depressive symptoms, explain the therapeutic effect of mindfulness yoga therapy on depression and its possible mechanism of action, and provide new ideas for the clinical treatment of patients with depression.MethodReview Manage 5.4 software was used to comprehensively evaluate the effect of yoga exercise on depression interventions to provide a reference for improving mental health. CNKI, PubMed, Web of science, EBSCO were searched for all case–control research articles on yoga for depression from 2000 to 2022. After screening, data extraction and quality evaluation of randomized controlled trials (RCTs) by inclusion and exclusion criteria, a total of 22 studies with 2,216 patients were included, including 1,101 in the yoga intervention group and 1,115 in the control group.ResultsThe results showed a large heterogeneity in the literature on the effect of yoga exercise on depression, with a combined total effect size [SMD = −1.53, 95%CI (−1.96, −1.10), p

This paper investigates the issue of disturbance observer-based fuzzy adaptive optimal finite-time control in light of the backstepping approach for strict-feedback nonlinear systems with bias fault term and full state constraints. Considering that external disturbance and bias fault signal can affect the stability of control and control quality, a disturbance observer is constructed to track the external disturbances and bias fault online. A disturbance observer-based finite-time control strategy is proposed to achieve optimized control by utilizing the fuzzy logic system approximation-based adaptive dynamic programming method under the critic-actor framework. The purpose of the critic is to evaluate control performance and the role of the actor is to execute control behaviour. In addition, it is proved that the proposed fuzzy adaptive optimal finite-time scheme not only realizes all signals in closed-loop system are bounded, but also ensures that system states are restricted within specific sets. Finally, simulation results are shown to demonstrate the effectiveness of the proposed control strategy.

The motivation of this work is to analyse the nonlinear models and their complex nature with generalized tools associated with material and history-based properties. With the help of well-known and widely used numerical scheme, we study the stimulating behaviours of the financial system in this work. The impact of parameters on price index, rate of interest, investment demand, influence changes and investment cost with respect to saving amount, and the elasticity of commercial markets demand are discussed. The consequences of generalizing the model within the arbitrary order are derived. The existence of the solution for the considered system is presented. This study helps beginner researchers to investigate complex real-world problems and predict the corresponding consequences.

There is strong evidence that the functional connectome is highly related to the white matter connectome in older children and adults, though little is known about structure-function relationships in early childhood. We investigated the development of cortical structure-function coupling in children longitudinally scanned at 1, 2, 4, and 6 years of age (N = 360) and in a comparison sample of adults (N = 89). We also applied a novel graph convolutional neural network-based deep learning model with a new loss function to better capture inter-subject heterogeneity and predict an individual’s functional connectivity from the corresponding structural connectivity. We found regional patterns of structure-function coupling in early childhood that were consistent with adult patterns. In addition, our deep learning model improved the prediction of individual functional connectivity from its structural counterpart compared to existing models.

Garlic oil is a liquid extracted from garlic that has various natural antibacterial and anti-inflammatory properties and is believed to be used to prevent and treat many diseases. However, the main functional components of garlic oil are unstable. Therefore, in this study, encapsulating garlic oil with cyclodextrin using the saturated co-precipitation method can effectively improve its chemical stability and water solubility and reduce its characteristic odor and taste. After preparation, the microcapsules of garlic oil cyclodextrin were characterized, which proved that the encapsulation was successful. Finally, the results showed that the encapsulated garlic oil still had antioxidant ability and slow-release properties. The final addition to plant-based meat gives them a delicious flavor and adds texture and mouthfeel. Provided a new reference for the flavor application of garlic cyclodextrin micro-capsules in plant-based meat patties.

Developing highly efficient earth‐abundant alternatives to traditional noble metal catalysts is essential for clean and sustainable energy‐conversion and energy‐storage technologies, yet still challenging in limited active sites and weak resistance to electrochemical corrosion. Herein, density‐functional theory calculations demonstrate that hexagonal boron nitride (h‐BN), albeit often being considered inert, can generate boron‐active radicals at defective sites by forming heterogeneous structures with graphene‐containing point vacancies, leading to a substantial electron delocalization and charge transfer, indicating a superior catalytic activity. Experimentally, the van der Waals heterostructure is rationally designed with h‐BN nanosheets (BNNs) anchored on reduced graphene oxide (rGO) as strongly coupled composite catalysts. Despite the poor conductivity in BN and lower catalytic activity in rGO, the created heterostructures demonstrate unexpected, improved oxygen evolution reaction (OER) activity with excellent stability in alkaline electrolyte. Qualitative analysis of the valence band offset and theoretical calculation reveal that the formation of heterostructures can significantly drive the electron transfer between C and B atoms near the vacancies across the interface and cause a half‐metallic property of BN, decreasing the free energy barrier of four‐electron OER kinetics. Herein, the synthetic schemes of h‐BNNs are guided as highly active metal‐free OER electrocatalysts.

Abstract Aim The aim of this study was to investigate the lived experience of people with diabetic retinopathy and to understand the impact of the disease on them including the practical problems faced in the day‐to‐day life. Design Descriptive qualitative research. Methods A convenience sample of 11 patients with diabetic retinopathy who were hospitalized in a tertiary hospitals in Shandong province of China were enrolled. Data were collected using semi‐structured in‐depth interviews. The six‐stage thematic analysis of Braun and Clarke was used for data analysis. Results Three themes and 12 sub‐themes were extracted, namely: countdown to darkness (lack of disease knowledge, bystander's perspective, distrust of grassroots hospitals); Endless abyss (action restrictions, social isolation, stigma, lost of meaning in life, catastrophizing explanations, a heavy burden); Light chaser (craving for light, turning points in behaviour, self‐adjustment).

Abstract Background Mitochondrial dysfunction induced by excessive mitochondrial reactive oxygen species (ROS) damages embryonic development and leads to growth arrest. Objective The purpose of this study is to elucidate whether maternal zinc (Zn) exert protective effect on oxidative stress targeting mitochondrial function using an avian model. Result In ovo injected tert-butyl hydroperoxide (BHP) increases (P

Lagerstroemia L. (Lythraceae) is a widely distributed genus of trees and shrubs native to tropical and subtropical environments from Southeast Asia to Australia, with numerous species highly valued as ornamentals. Although the plastomes of many species in this genus have been sequenced, the rates of functional gene evolution and their effect on phylogenetic analyses have not been thoroughly examined. We compared three plastome sequence matrices to elucidate how differences in these datasets affected phylogenetic analyses. Robust phylogenetic relationships for Lagerstroemia species were reconstructed based on different plastome sequence partitions and multiple phylogenetic methods. Identification of single-nucleotide variants within different genes also provides basic data on the patterns of functional gene evolution in Lagerstroemia and may provide insights into how those mutations affect protein structure and potentially drive divergence via cytonuclear incompatibility. These results as well as analyses of non-synonymous and synonymous mutations, indicate that heterotachic modes of evolution are present in functional plastome genes and should be accounted for in the analyses of molecular evolution. In addition, divergence events within the Lagerstroemia were dated for the first time. Several of the divergence estimates corresponded to well-known Earth history events, such as the reduction in global temperatures at the Eocene/Oligocene boundary. Our analyses conducted in Lagerstroemia here dissects the various patterns in the divergence of Lagerstroemia and may provide a useful guide to help plant breeders, as well as the necessity of using plastomic data and as possible as to combine evidence from morphological characteristics to investigate the complicated interspecies relationship and the evolutionary dynamics of species.