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Osteoporosis is linked to increased bone marrow adipocyte (BMAd) proliferation, which displaces bone-forming cells and alters the local environment. The impact of BMAd lipid droplets on bone health and osteoblast function remains unclear. This study investigates the interplay between BMAd-derived lipid droplets and osteoblast functionality, focusing on ferroptosis pathways. Osteoblast cultures were treated with conditioned media from adipocytes to simulate in vivo conditions. High-throughput mRNA sequencing and Western blot analysis were used to profile changes in gene expression and protein levels related to ferroptosis, oxidative phosphorylation, and osteogenic markers. Cellular assays assessed the direct impact of lipid droplets on osteoblast activity. Results showed that osteoblasts exposed to adipocyte-conditioned media had increased intracellular lipid droplet accumulation, upregulation of ferroptosis-related genes and proteins, and downregulation of oxidative phosphorylation and osteoblast differentiation markers. Treatment with ferroptosis inhibitors reversed the detrimental effects on osteoblasts, indicating the functional relevance of this pathway in osteoporosis. BMAd-derived lipid droplets contribute to osteoblast dysfunction through ferroptosis induction. Inhibiting ferroptosis could preserve osteoblast function and combat osteoporosis-related bone issues, suggesting that modulating lipid metabolism and redox balance in bone cells may be promising for future treatments.

The receptive field (RF) plays a crucial role in convolutional neural networks (CNNs) because it determines the amount of input information that each neuron in a CNN can perceive, which directly affects the feature extraction ability. As the number of convolutional layers in CNNs increases, there is a decay of the RF according to the two-dimensional Gaussian distribution. Thus, an effective receptive field (ERF) can be used to characterize the available part of the RF. The ERF is calculated by the kernel size and layer number within the neural network architecture. Currently, ERF calculation methods are typically applied to single-channel input data that are both independent and identically distributed. However, such methods may result in a loss of effective information if they are applied to more general (i.e., multi-channel) datasets. Therefore, we proposed a multi-channel ERF calculation method. By conducting a series of numerical experiments, we determined the relationship between the ERF and the convolutional kernel size in conjunction with the layer number. To validate the new method, we used the recently published global wave surrogate model for climate simulation (GWSM4C) and its accompanying dataset. According to the newly established relationship, we refined the kernel size and layer number in each neural network of the GWSM4C to produce the same ERF but lower RF attenuation rates than those of the original version. By visualizing the gradient map at several points in West African and East Pacific areas, the high gradient value regions confirmed the known swell sources, which indicated effective feature extraction in these areas. Furthermore, the new version of the GWSM4C yielded better prediction accuracy for significant wave height in global swell pools. The root mean square errors in the West African and East Pacific regions reduced from approximately 0.3 m, in the original model to about 0.15 m, in the new model. Moreover, these improvements were attributed to the higher efficiency of the newly modified neural network structure that allows the inclusion of more historical winds while maintaining acceptable computational consumption.

Phasor Measurement Units (PMUs) are widely used in power system state estimation due to its high sampling rate and real-time estimation of power state in power systems. However, it is also vulnerable to cyberattacks (GPS spoofing attacks) since it uses unencrypted GPS civil signals for synchronization. The GPS spoofing attacks (GSAs) will intentionally manipulate the time reference of PMUs, which is equivalent to falsifying the phase angle of the PMU measurements. In this paper, we consider the secure power state estimation and attacks detection with the unknown GSAs in the power systems. Particularly, we derived the PMU-based GSAs model in the power state estimation problem, which is formulated as a mixed maximum likelihood problem. In the formulated problem, the involved unknown parameters are coupled and the objective function is non-convex, which are of significant challenges in finding optimal solutions. To tackle these challenges, a joint maximum a posteriori and maximum likelihood (JMAP-ML) algorithm is proposed to securely estimate the power state and detect the GSAs in the mixed measurements of PMUs. Different testing scenarios in IEEE 14 bus system are simulated to show the proposed algorithm’ performance on GSAs detection and state estimation. Numerical examples demonstrate the improved accuracy of our algorithm compared with classical algorithms when GSAs are present. And we conclude that when a sufficient number of PMUs are deployed in the system, the impact of GSAs will be largely compensated in the estimation stage.

Predicting nearshore significant wave heights (SWHs) with high accuracy is of great importance for coastal engineering activities, marine and coastal resource studies, and related operations. In recent years, the prediction of SWHs in two-dimensional fields based on deep learning has been gradually emerging. However, predictions for nearshore areas still suffer from insufficient resolution and poor accuracy. This paper develops a NS (NearShore) model based on the GWSM4C model (Global Wave Surrogate Model for Climate simulations). In the training area, the GWSM4C -NS model achieved a correlation coefficient (CC) of 0.977, with a spatial Root Mean Square Error (RMSE), annual mean spatial relative error (MAPE), and annual mean spatial absolute error (MAE) of 0.128 m, 10.7%, and 0.103 m, respectively. Compared to the GWSM4C model’s predictions, the RMSE and MAE decreased by 59% and 60% respectively, demonstrating the model’s effectiveness in enhancing nearshore SWH predictions. Additionally, applying this model to untrained sea areas to further validate its learning capability in wave energy propagation resulted in a CC of 0.951, with RMSE, MAPE, and MAE of 0.161m, 12.9%, and 0.137m, respectively. The RMSE and MAE were 43% and 39% lower than the GWSM4C model’s interpolated predictions. The results shown above suggest that the newly proposed model can effectively improve the performance of GWSM4C in nearshore areas.

Abstract Objective To investigate the association between circulating secretoneurin (SN) and angiographic coronary collateralization in stable angina patients with chronic coronary total occlusion (CTO). Methods SN concentrations in serum were measured in 641 stable angina patients with CTO by radioimmunoassay. The status of coronary collaterals from the contra-lateral vessel was visually estimated using the Rentrop grading system, and was categorized into poor (grade 0 or 1) or good (grade 2 or 3) collateralization. Results Serum SN levels were significantly higher in patients with good coronary collaterals compared to those with poor collaterals (175.23 ± 52.09 pmol/L vs. 143.29 ± 42.01 pmol/L, P

Abnormal crowd behavior recognition is one of the research hotspots in computer vision. Its goal is to use computer vision technology and abnormal behavior detection models to accurately perceive, predict, and intervene in potential abnormal behaviors of the crowd and monitor the status of the crowd system in public places in real time, to effectively prevent and deal with public security risks and ensure public life safety and social order. To this end, focusing on the abnormal crowd behavior recognition technology in the computer vision system, a systematic review study of its theory and cutting-edge technology is conducted. First, the crowd level and abnormal behaviors in public places are defined, and the challenges faced by abnormal crowd behavior recognition are expounded. Then, from the dimensions based on traditional methods and based on deep learning, the mainstream technologies of abnormal behavior recognition are discussed, and the design ideas, advantages, and limitations of various methods are analyzed. Next, the mainstream software tools are introduced to provide a comprehensive reference for the technical framework. Secondly, typical abnormal behavior datasets at home and abroad are sorted out, and the characteristics of these datasets are compared in detail from multiple perspectives such as scale, characteristics, and uses, and the performance indicators of different algorithms on the datasets are compared and analyzed. Finally, the full text is summarized and the future development direction of abnormal crowd behavior recognition technology is prospected.

The large-scale integration of distributed photovoltaics （DPVs） has a profound impact on the secure and stable operation of distribution networks. Analysis and assessment on DPV hosting capacity can effectively assist in its rational planning and utilization. To this end， an method for analyzing the DPV hosting capacity interval is proposed to calculate the maximum DPV integration capacity in distribution networks under uncertainties. Firstly， the DPV output uncertainties are quantified by means of nonparametric kernel density estimation based on the historical data， and the DPV output interval is calculated by Newton-Raphson method. Secondly， a DPV hosting capacity interval analysis model for distribution networks considering safe operation constraints is established， which is then decomposed into an optimistic submodel and a pessimistic submodel based on interval analysis theory. Then， to reduce the difficulty of model solution， the pessimistic sub-model is simplified by the equivalence transformation， and the two sub-models are solved separately to obtain the interval solution. Finally， simulation analysis is carried out in the improved 15-node distribution system and a distribution network in Lishui， Zhejiang Province. The results verify the effectiveness and practicality of the proposed method.

Abstract Data recovery from monolithic storage devices (MSDs) is in high demand for legal or business purposes. However, the conventional data recovery methods are destructive, complicated, and time-consuming. We develop a robotic-arm-assisted optical coherence tomography (robotic-OCT) for non-destructive inspection of MSDs, offering ~7 μm lateral resolution, ~4 μm axial resolution and an adjustable field-of-view to accommodate various MSD sizes. Using a continuous scanning strategy, robotic-OCT achieves automated volumetric imaging of a micro-SD card in ~37 seconds, significantly faster than the traditional stop-and-stare scanning that typically takes tens of minutes. We also demonstrate the robotic-OCT-guided laser ablation as a microsurgical tool for targeted area removal with precision of ±10 μm and accuracy of ~50 μm, eliminating the need to remove the entire insulating layer and operator intervention, thus greatly improving the data recovery efficiency. This work has diverse potential applications in digital forensics, failure analysis, materials testing, and quality control.

The aqueous instability of halide perovskite seriously hinders its direct application in water as a potential photocatalyst. Here, we prepared a new type of polyvinylpyrrolidone (PVP) passivated δ-CsPbI3 (δ-CsPbI3@PVP) microcrystal by a facile method. This material can be uniformly dispersed in water and stably maintain its crystal structure for a long time, breaking through the bottleneck of halide perovskite photocatalysis in water. Under visible light, δ-CsPbI3@PVP can almost completely photodegrade organic dyes (including Rhodamine B, methylene blue, and crystal violet) in only 20 min. The efficient photocatalytic activity is attributed to the enhanced visible light absorption arising from PbI2 defects in δ-CsPbI3@PVP and the intrinsic low photoluminescence quantum yield of δ-CsPbI3, which induces efficient light absorption and photocatalytic activity. We highlight δ-CsPbI3@PVP as an effective aqueous photocatalyst, and this study provides new insights into how to exploit the potential of halide perovskite in photocatalytic applications.

Background: While the protective effects of n-3 polyunsaturated fatty acids (PUFAs) on cardiac ischemia-reperfusion (IR) injury have been previously reported, limited data are available regarding how these fatty acids affect membrane receptors and their downstream signaling following IR injury. We aimed to identify potential receptors activated by n-3 PUFAs in IR hearts to understand the regulatory mechanisms of these receptors.Methods: We used fat-1 mice, which naturally have elevated levels of n-3 PUFAs, and C57BL/6J mice as a control group to create a myocardial IR injury model through Langendorff perfusion. We assessed the impact of endogenous n-3 PUFAs on left ventricular function, myocardial infarct size, myocardial apoptosis, and ATP production. RNA sequencing (RNA-seq) and bioinformatics analysis were conducted to identify molecular targets affected by n-3 PUFAs. Based on these analyses we then treated IR hearts of WT and fat-1 mice with an antagonist (ML221) or an agonist (apelin-13) for the predicted receptor to assess cardiac contractile function and intracellular signaling pathways. An in vitro hypoxia-reoxygenation (HR) model was also used to confirm the effects of n-3 PUFAs on the examined intracellular signaling pathways.Results: Endogenous n-3 PUFAs protected cardiac structure and function in post-IR hearts, and modulated phosphorylation patterns in the PI3K-AKT-mTOR signaling pathways. RNA-seq analysis revealed that n-3 PUFAs affected multiple biological processes as well as levels of the apelin receptor (APLNR). Consistent with a role for the PLNNR, ML221 synchronized the activation of the PI3K-AKT-mTOR signaling axis, suppressed the expression of PKCδ and phosphorylated p38α, upregulated PKCε expression, upregulated or restored the phosphorylation of myofilaments, and prevented myocardial injury and contractile dysfunction in WT IR hearts. By contrast, apelin-13 disrupted the PI3K-AKT-mTOR signaling axis in post-IR fat-1 hearts. The phosphorylation signaling targeted by APLNR inhibition in post-IR fat-1 hearts was also observed after treating HR cells with eicosatetraenoic acid (EPA).Conclusion: Endogenous n-3 PUFAs protect against post-IR injury and preserve cardiac contractile function possibly through APLNR inhibition. This inhibition synchronizes the PI3K-AKT-mTOR axis, suppresses detrimental phosphorylation signaling, and restores or increases myofilament phosphorylation in post-IR hearts. The beneficial effects observed in fat-1 transgenic mouse hearts can be attributed, at least in part, to elevated EPA levels. This study is the first to demonstrate that n-3 PUFAs protect hearts against IR injury through APLNR inhibition.

IntroductionAcute lung injury (ALI) is a severe respiratory tract disorder facilitated by dysregulated inflammation, oxidative stress and intestinal ecosystem. Fecal microbiota transplantation (FMT) is a rapid method for gut microbiota (GM) reconstruction. Furthermore, our previous studies have confirmed that human umbilical cord mesenchymal stromal cells (HUC-MSCs) can alleviate ALI by improving GM composition. Therefore, we aimed to explore the efficacy and mechanism of FMT from HUC-MSCs-treated mice on ALI.MethodsIn brief, fresh feces from HUC-MSCs-treated mice were collected for FMT, and the mice were randomly assigned into NC, FMT, LPS, ABX-LPS, and ABX-LPS-FMT groups (n = 12/group). Subsequently, the mice were administrated with antibiotic mixtures to deplete GM, and given lipopolysaccharide and FMT to induce ALI and rebuild GM. Next, the therapeutic effect was evaluated by bronchoalveolar lavage fluid (BALF) and histopathology. Immune cells in peripheral blood and apoptosis in lung tissues were measured. Furthermore, oxidative stress- and inflammation-related parameter levels were tested in BALF, serum, lung and ileal tissues. The expressions of apoptosis-associated, TLR4/NF-κB pathway-associated, Nrf2/HO-1 pathway related and tightly linked proteins in the lung and ileal tissues were assessed. Moreover, 16S rRNA was conducted to assess GM composition and distribution.ResultsOur results revealed that FMT obviously improved the pathological damage of lung and ileum, recovered the immune system of peripheral blood, decreased the cell apoptosis of lung, and inhibited inflammation and oxidative stress in BALF, serum, lung and ileum tissues. Moreover, FMT also elevated ZO-1, claudin-1, and occludin protein expressions, activating the Nrf2/HO-1 pathway but hindering the TLR4/NF-κB pathway. Of note, the relative abundances of Bacteroides, Christensenella, Coprococcus, and Roseburia were decreased, while the relative abundances of Xenorhabdus, Sutterella, and Acinetobacter were increased in the ABX-LPS-FMT group.ConclusionFMT from HUC-MSCs-treated mice may alleviate ALI by inhibiting inflammation and reconstructing GM, additionally, we also found that the TLR4/NF-κB and Nrf2/HO-1 pathways may involve in the improvement of FMT on ALI, which offers novel insights for the functions and mechanisms of FMT from HUC-MSCs-treated mice on ALI.

BackgroundA substantial portion of heart failure (HF) patients adherent to guideline-directed medical therapies have experienced improved ejection fraction (EF), termed HFimpEF. Glycemic variability (GV) has emerged as a critical cardiometabolic factor. However, the relation between long-term GV and the incidence of HFimpEF is still unclear.MethodsA total of 591 hospitalized HF patients with reduced EF (HFrEF, EF≤ 40%) admitted from January 2013 to December 2020 were consecutively enrolled. Repeat echocardiograms were performed at baseline and after around 12 months. The incidence of HFimpEF, defined as (1) an absolute EF improvement ≥10% and (2) a second EF > 40% and its association with long-term fasting plasma glucose (FPG) variability were analyzed.ResultsDuring a mean follow-up of 12.2 ± 0.6 months, 218 (42.0%) patients developed HFimpEF. Multivariate analysis showed FPG variability was independently associated with the incidence of HFimpEF after adjustment for baseline HbA1c, mean FPG during follow-up and other traditional risk factors (odds ratio [OR] for highest vs. lowest quartile of CV of FPG: 0.487 [95% CI 0.257~0.910]). Evaluation of GV by alternative measures yielded similar results. Subgroup analysis revealed that long-term GV was associated with HFimpEF irrespective of glycemic levels and diabetic conditions.ConclusionsThis study reveals that greater FPG variability is associated with compromised development of HFimpEF. A more stable control of glycemic levels might provide favorable effects on myocardial functional recovery in HF patients even without diabetes.

Abstract Anastomotic leak is still a severe complication in esophageal surgery due to high mortality. This article reviews the updates on the treatment of anastomotic leak after esophagectomy in order to provide reference for clinical treatment and research. The relevant studies published in the Chinese Zhiwang, Wanfang, and MEDLINE databases to December 21, 2021 were retrieved, and esophageal carcinoma, esophagectomy, anastomotic leakage, and fistula selected as the keywords. A total of 78 studies were finally included. The treatments include traditional surgical drainage, new reverse drainage trans‐fistula, stent plugging, endoscopic clamping, biological protein glue injection plugging, endoluminal vacuum therapy (EVT), and reoperation, etc. Early diagnosis, accurate classification and optimal treatment can promote the rapid healing of anastomotic leaks. EVT may be the most valuable approach, simultaneously with good commercial prospects. Reoperation should be considered in patients with complex fistula in which conservative treatment is insufficient or has failed.

State estimation plays a central role in ensuring the secure operation of the smart grid. However, deliberately designed false data injection attacks (FDIAs) can pass by conventional detections to manipulate the process of state estimation by injecting malicious data into measurements. Ultimately, FDIAs make the result of state estimation deviate from secure value and affect the security and stable operation of the power system. In this paper, we consider the different distribution characteristics between normal measurements and false measurements and build a Gaussian mixture model (GMM). Particularly, we focus on achieving joint detection and localization of FDIAs. To tackle these challenges, a model-based algorithm named Joint Maximum a Posteriori - Maximum Likelihood (JMAP-ML) is proposed to estimate the individual parameters of GMM and achieve joint detection and localization of FDIAs with high accuracy. Different testing scenarios in the IEEE-14-bus and IEEE-30-bus power systems are simulated to show the performance of the proposed algorithm on parameters estimation, FDIAs detection and localization. Numerical examples demonstrate the proposed algorithm achieves satisfactory results in detecting and localizing FDIAs compared to the other algorithms.

Power system state estimation is an essential component of the modern power system energy management system (EMS), and accurate state estimation is an indispensable basis for subsequent work. However, the attacker can inject biases into measurements to launch false data injection attacks (FDIAs) in smart grids, which ultimately cause state estimates to deviate from security values. This paper proposed the joint use of static state estimation and dynamic state estimation to detect the FDIA, i.e. the joint use of weighted least squares (WLS) and extended Kalman filter (EKF) with exponential weighting function (WEKF), which improves the robustness of state estimation. Since the WLS estimation considers only the measurements at the current moment, the recursive feature of the WEKF enables the estimation process to involve both historical state and current measurements. Therefore, consistency tests and residual tests were performed using the estimations of WLS and WEKF to effectively detect FDIA. In addition, a cluster partitioning approach with approximate equal redundancy of subsystems is proposed to locate the FDIA. The detection of FDIA triggers the partitioning of the network system, and then the chi-square test is used separately in each sub-network to determine the location of FDIA. Finally, the experimental results in the IEEE-14 bus system and the IEEE-30 bus system demonstrate that the approach can effectively detect and locate FDIAs.

Abstract Objectives To investigate whether intravenous thrombolysis (IVT) with alteplase (a recombinant tissue plasminogen activator, rt-PA) before endovascular treatment (EVT) is beneficial for acute ischemic stroke (AIS) patients in different periods. Methods This study enrolled a total of 140 patients hospitalized between 2019 and 2022 with AIS from large vessel occlusion (LVO) in the anterior circulation. Those patients were divided into the EVT alone group and IVT + EVT group, in which EVT was preceded by intravenous rt-PA. According to the time from onset to femoral artery puncture, the above two groups were divided into the following subgroups: 0.05). After adjusting for confounding factors, a lower incidence of intracerebral hemorrhage was observed in the EVT group (P

Abstract Free space detection is a very important task in road scene understanding. With the continued development of convolutional neural networks, free‐space detection can be seen as a class‐specific semantic segmentation problem. In this paper, a new encoding–decoding network structure‐HRUnet is designed, which always maintains the input of high‐resolution images in both the encoding and decoding phases. It extracts multi‐scale information from RGB images and continuously fuses them, and finally achieves accurate spatial detection. In addition, in order to improve the accuracy of detection, the attention mechanism module‐spin attention is proposed to achieve the interaction between channel and spatial dimensions when calculating channel attention, establish the come relationship between channel and space, reduce the loss of feature information, and further improve the accuracy of spatial detection. Experimental results show that the proposed neural network structure outperforms current popular models in terms of balanced the computational complexity and accuracy.

Under the influence of power grid and economy, the operation optimization of aggregate resources has high practical value and significance. For the problems of the existing aggregate resource operation optimization methods, this paper presents a completely new optimization method, considering the economic factors of power output, grid line transmission, grid stability, transformer capacity, energy storage charging and discharge loss, grid transmission loss, transformer loss and production arrangement of adjustable resource aggregate, and combined with the idea of electric power translation in the operation of the load device. By adopting a mixed-integer linear programming model (Mixed-Integer Linear Programming, MILP), the operation optimization problem of the aggregate resource is transformed into a mathematical planning problem to be solved, which effectively avoids the start-stop delay of the load device, and shortens the time taken to adjust power supply and demand, reduces the construction cost and operation and maintenance cost of the aggregate, and realizes the optimal allocation of electric power resources, improves the sustainable energy utilization rate and the stability of the power system, and provides a new direction for the continuous development and progress of the power system.

Abstract Concerning the difficulty in determining the restart strategy for AC/DC interconnected systems, this paper proposes a method of calculating the optimal restart strategy for AC/DC interconnected systems based on dynamic energy. First, a dynamic energy function that characterises the stability of system is constructed. Then, the analytical expressions of the dynamic energy function are calculated separately for the deionisation stage, the restart stage, and the alpha retard stage of the entire restart process. On this basis, the variation rate of the system dynamic energy is defined as the energy accumulation rate, which quantifies the accumulation or consumption of dynamic energy during the restart process, and facilitates detailed analysis of the effects of the restart time and restart duration on the stability of system. Then, a method to calculate the optimal restart time is proposed with the goal of minimising the dynamic energy accumulated in the system. Finally, hardware‐in‐the‐loop tests are carried out on the RT‐LAB platform for simulation verification. The experimental results show that the dynamic energy function constructed in this paper can reflect the stability of system. Using the proposed optimal restart strategy can reduce the accumulation of dynamic energy and improve the stability of system.

Objective To investigate the current status of social jet lag (SJL) in army helicopter pilots and explore its influencing factors. Methods Objective data, including SJL, sleep time, sleep quality, pressure and number of daily steps in the army aviators were collected by a smart watch from December 14 to 30 in 2021. Subjective data including socio-demographic and results of Pittsburgh sleep quality index scale (PSQI) were collected by self-developed sleep assessment APP. SPSS statistics 25.0 was used for statistical analysis. Descriptive analysis was adopted for measurement data, and frequency analysis was employed for enumerate data. Pearson correlation analysis and stepwise linear regression analysis were performed respectively to analyze the correlation of variables and the influencing factors for SJL. Results Finally, eligible data were collected from 33 male pilots. Their average SJL was 0.45±1.21 h, total PSQI score 6.64±2.70, total sleep duration 7.58±0.64 h, average pressure score 35.45±10.76, and average daily steps (11.0±2.5)×103 steps. The variables correlated with SJL were stress (r=0.45), insomnia severity (r=0.39), fatigue status (r=0.54), sleep efficiency (r=0.43), times of waking (r=0.52), daily steps (r=-0.39), and duration of deep sleep (r=-0.49) (all P < 0.05). The results of stepwise linear regression analysis suggested that fatigue, wakeup time during night, exercise, stress, marriage and smoking were related factors of SJL. Conclusion Helicopter pilots have severe SJL, with 39% of them having SJL longer than 1 h. Fatigue, poor nighttime sleep quality, stress, singleness and smoking can aggravate SJL, while exercise can attenuate SJL. Special attention should be paid to SJL evaluation for pilots in aviation health care.

Inorganic halide perovskite CsPbI3 is highly promising in the photocatalytic field for its strong absorption of UV and visible light. Among the crystal phases of CsPbI3, the δ-phase as the most aqueous stability; however, directly using it in water is still not applicable, thus limiting its dye photodegradation applications in aqueous solutions. Via adopting nitrogen-doped graphene quantum dots (NGQDs) as surfactants to prepare δ-phase CsPbI3 nanocrystals, we obtained a water-stable material, NGQDs-CsPbI3. Such a material can be well dispersed in water for a month without obvious deterioration. High-resolution transmission electron microscopy and X-ray diffractometer characterizations showed that NGQDs-CsPbI3 is also a δ-phase CsPbI3 after NGQD coating. The ultraviolet-visible absorption spectra indicated that compared to δ-CsPbI3, NGQDs-CsPbI3 has an obvious absorption enhancement of visible light, especially near the wavelength around 521 nm. The good dispersity and improved visible-light absorption of NGQDs-CsPbI3 benefit their aqueous photocatalytic applications. NGQDs-CsPbI3 alone can photodegrade 67% rhodamine B (RhB) in water, while after compositing with TiO2, NGQDs-CsPbI3/TiO2 exhibits excellent visible-light photocatalytic ability, namely, it photodegraded 96% RhB in 4 h. The strong absorption of NGQDs-CsPbI3 in the visible region and effective transfer of photogenerated carriers from NGQDs-CsPbI3 to TiO2 play the key roles in dye photodegradation. We highlight NGQDs-CsPbI3 as a water-stable halide perovskite material and effective photocatalytic adjuvant.

Outliers can be generated in the power system due to aging system equipment, faulty sensors, incorrect line connections, etc. The existence of these outliers will pose a threat to the safe operation of the power system, reduce the quality of the data, affect the completeness and accuracy of the data, and thus affect the monitoring analysis and control of the power system. Therefore, timely identification and treatment of outliers are essential to ensure stable and reliable operation of the power system. In this paper, we consider the problem of detecting and localizing outliers in power systems. The paper proposes a Minorization–Maximization (MM) algorithm for outlier detection and localization and an estimation of unknown parameters of the Gaussian mixture model (GMM). To verify the performance of the method, we conduct simulation experiments by simulating different test scenarios in the IEEE 14-bus system. Numerical examples show that in the presence of outliers, the MM algorithm can detect outliers better than the traditional algorithm and can accurately locate outliers with a probability of more than 95%. Therefore, the algorithm provides an effective method for the handling of outliers in the power system, which helps to improve the monitoring analyzing and controlling ability of the power system and to ensure the stable and reliable operation of the power system.

Abstract Background There is currently a lack of effective treatments for non-small cell lung cancer (NSCLC) patients harboring HER2 mutations. We examined the efficacy and safety of, and potential resistance mechanism to, pyrotinib, a pan-HER inhibitor, in advanced NSCLC carrying HER2 mutations. Methods In this multicenter, single-arm, phase II trial, stage IIIB-IV NSCLC patients harboring HER2 mutations, as determined using next-generation sequencing, were enrolled and treated with pyrotinib at a dose of 400 mg/day. The primary endpoint was 6-month progression-free survival (PFS) rate, and secondary endpoints were objective response rate (ORR), PFS, overall survival (OS), disease control rate (DCR), and safety. The impact of different HER2 mutation types on sensitivity to pyrotinib and the potential of utilizing mutational profile derived from circulating tumor DNA (ctDNA) to predict disease progression were also explored. Results Seventy-eight patients were enrolled for efficacy and safety analysis. The 6-month PFS rate was 49.5% (95% confidence interval [CI], 39.2–60.8). Pyrotinib produced an ORR of 19.2% (95% CI, 11.2–30.0), with median PFS of 5.6 months (95% CI, 2.8–8.4), and median OS of 10.5 months (95% CI, 8.7–12.3). The median duration of response was 9.9 months (95% CI, 6.2–13.6). All treatment-related adverse events (TRAEs) were grade 1–3 (all, 91.0%; grade 3, 20.5%), and the most common TRAE was diarrhea (all, 85.9%; grade 3, 16.7%). Patients with exon 20 and non-exon 20 HER2 mutations had ORRs of 17.7% and 25.0%, respectively. Brain metastases at baseline and prior exposure to afatinib were not associated with ORR, PFS, or OS. Loss of HER2 mutations and appearance of amplification in HER2 and EGFR were detected upon disease progression. Conclusions Pyrotinib exhibited promising efficacy and acceptable safety in NSCLC patients carrying exon 20 and non-exon 20 HER2 mutations and is worth further investigation. Trial registration Chinese Clinical Trial Registry Identifier: ChiCTR1800020262

In regions where transmission corridors are badly needed, UHV lines will inevitably be constructed in parallel with other UHV or EHV lines. Hence, the electromagnetic environment characteristics near the corridors are complex and in-depth study should be carried out. In this paper, three models of parallel AC transmission lines are established, and the characteristics of the power frequency electromagnetic field, radio interference and audible noise near the parallel lines are studied. The results show that as the line spacing decreases, the area of strong electromagnetic environment reduces, but the amplitude will increase. The height of the parallel-erected line has more influence on the distribution of the power frequency electromagnetic field than the radio interference and audible noise. Generally, the electromagnetic environment generated by the parallel erection of UHV transmission lines is related to the conductor height and the spacing of parallel lines. When the radio interference and audible noise limits are up to standard, the spacing of parallel erection lines can be appropriately reduced. This study has a certain reference significance for the design and construction of UHV lines in areas being short of corridors.

In the 2021 WHO Classification of Tumors of the Central Nervous System (fifth edition), the term "circumscribed" was used to classify astrocytic gliomas with localized growth characteristics. So far, the descriptions of "diffuse" and "circumscribed", which define the growth mode, have been applied to the classification of gliomas. This paper interprets the content of circumscribed astrocytic gliomas in the new edition tumors classification, introduces the definitions and clinical characteristics of high ⁃ grade astrocytoma with piloid features and astroblastoma, MN1⁃altered, and analyzes the value and significance of molecular markers and gene changes in the diagnosis and treatment of circumscribed astrocytic gliomas.

Background Because of advances in medical treatments, a substantial proportion of patients with heart failure (HF) have experienced recovery of ejection fraction (EF), termed HF with recovered EF (HFrecEF). Insulin resistance (IR) is prevalent in HF and tightly related with prognosis. This study investigates the relationship between IR and the incidence of HFrecEF in patients who are nondiabetic. Methods and Results A total of 262 patients with HF with reduced EF (HFrEF) who were nondiabetic were consecutively enrolled. Patients were classified into HFrecEF (follow‐up EF>40% and ≥10% absolute increase) or otherwise persistent HFrEF based on repeat echocardiograms after 12 months. IR was estimated by an updated homeostasis model assessment for IR (HOMA2‐IR). The median HOMA2‐IR level was 1.05 (interquartile range [IQR], 0.67–1.63) in our cohort of patients with HF who were nondiabetic. During follow‐up, 121 (odds ratio [OR], 46.2% [95% CI 40.2–52.2]) patients developed HFrecEF. Compared with patients with HFrEF, patients with HFrecEF had significantly lower HOMA2‐IR levels (0.92 [IQR, 0.61–1.37] versus 1.14 [IQR, 0.75–1.78], P=0.007), especially in nonischemic HF. Log2‐transformed HOMA2‐IR was inversely correlated to improvements in EF (Pearson's r=−0.25, P

Copper-induced cell death, a form of apoptosis, has been extensively investigated in human diseases. Recent studies on the mechanisms underlying copper-induced cell death have provided innovative insights into copper-related toxicity in cells, and this form of programmed cell death was termed cuproptosis. Herein, we conducted a comprehensive analysis to determine the specific role of cuproptosis in osteosarcoma. Using consensus clustering analysis, patients with osteosarcoma from the TARGET database were classified into subgroups with distinct cuproptosis-based molecular patterns. Accordingly, these patients displayed diverse clinicopathological features, survival outcomes, tumor microenvironment (TME) characteristics, immune-related scores, and therapeutic responses. Furthermore, we constructed a cuproptosis-based risk signature and nomogram, as well as developed a cuproptosis score for improved patient characterization. The prognostic model and cuproptosis score were well validated and confirmed to efficiently distinguish high- and low-risk patients, thereby affording great predictive value. Finally, we verified the abnormal expression of prognostic CUG in OS patients by immunohistochemistry. In conclusion, we suggest that cuproptosis may play an important role in regulating the tumor microenvironment features, tumor progression and the long-term prognosis of osteosarcoma.

The Phasor Measurement Unit (PMU) with a GPS signal receiver is a synchronized sensor widely used for power system state estimation. While the GPS receiver ensures time accuracy, it is vulnerable to network attacks. GPS spoofing attacks can alter the phase angle of PMU measurement signals and manipulate system states. This paper derives a power system state model based on PMUs under GPS spoofing attacks, according to the characteristics of changes in bus voltages and branch currents after GSA. Based on the characteristics of this model, a detection and correction algorithm for attacked data is proposed to detect GSA and correct attacked measurements. The corrected measurements can be used for power system state estimation. Simulation results on the IEEE 14-bus system show that the proposed algorithm improves the accuracy of state estimation under one or multiple GSAs, especially when multiple GSAs are present, compared to classical Weighted Least Squares Estimation (WLSE) and Alternating Minimization (AM) algorithms. Further research indicates that this algorithm is also applicable to large-scale networks.

Coronary collateralization is substantially impaired in patients with type 2 diabetes and occlusive coronary artery disease, which leads to aggravated myocardial ischemia and a more dismal prognosis. In a diabetic setting, altered serum lipid profiles and profound glycoxidative modification of lipoprotein particles induce endothelial dysfunction, blunt endothelial progenitor cell response, and severely hamper growth and maturation of collateral vessels. The impact of dyslipidemia and lipid-lowering treatments on coronary collateral formation has become a topic of heightened interest. In this review, we summarized the association of triglyceride-based integrative indexes, hypercholesterolemia, increased Lp(a) with its glycoxidative modification, as well as quantity and quality abnormalities of high-density lipoprotein with impaired collateral formation. We also analyzed the influence of innovative lipid-modifying strategies on coronary collateral development. Therefore, clinical management of diabetic dyslipidemia should take into account of its effect on coronary collateralization in patients with occlusive coronary artery disease.

ObjectiveTo analyze the familial aggregation of college students′ self-reported food allergy in college students, provide baseline information on the prevalence of food allergy in college students and theoretical basis for preventing, treating and managing food allergy.MethodsIn 2019, cross-sectional study was done through 2 538 college students from 6 universities in Nanchang by multi-stage cluster random sampling. The investigation contents included the food allergy status, main influencing factors and family history of food allergy, etc. Data was analysed statistically with SPSS 17.0 software.Results2 313 valid questionnaires were collected. The incidence of self-reported food allergy was 15.69%(363/2 313). Most of them was rapid food allergy. About half students did not know about food allergy, and more than 70% of them did not pay attention to food labels. The FA had obvious familial aggregation.There was a significant difference between the incidence of food allergy among students with positive family history and those with negative family history (χ2=28.696, P

BackgroundThe murine transverse aortic constriction (TAC) model is frequently used to investigate molecular mechanisms underlying heart failure. However, limited data is available regarding the expression of mRNAs and circRNAs in murine heart failure progression induced by pressure overload.MethodsTransverse aortic constriction was used to induce pressure overload for 2, 4, and 8 weeks in mice. Echocardiographic measurements in B-mode and M-mode, as well as blood flow Doppler data were collected in mice without (sham) and with (2W-, 4W-, and 8W-post-TAC) pressure load. Hearts were excised and morphology, cardiomyocyte size, and fibrosis were determined. RNA sequencing, circRNA microarray, functional mRNA enrichment analysis, hub gene identification, target miRNA interaction, and competitive endogenous RNA (ceRNA) network construction were conducted.ResultsHeart weight, cardiomyocyte hypertrophy, and fibrosis gradually increased over time in the hearts with pressure overload. The 2W-post-TAC hearts displayed concentric hypertrophy, thickened left ventricular walls, and increased EF and FS. The 4W-post-TAC hearts were characterized by preserved EF and FS, dilated atria, and increased left ventricle (LV) systolic volume. The 8W-post-TAC hearts presented with ventricular and atrial dilation, increased LV systolic and diastolic volume, reduced EF and FS, and increased ejection time (MV ET). mRNA expression analysis suggested that cardiac remodeling, immune response dysregulation, and metabolic disorder were the key cellular events in heart failure progression. Depression in chemotaxis and mitochondrial function were predicted in 4W- and 8W-post-TAC myocardia, respectively. A ceRNA network analysis demonstrated that the circRNAs targeted the expression of genes enriched in metabolism dysregulation in the 2W-post-TAC hypertrophic hearts, while they targeted genes enriched in cardiac remodeling in the 4W-post-TAC EF-preserved hearts and in the suppression of oxidative phosphorylation and cardiac contraction in the 8W-post-TAC EF-reduced hearts.ConclusionOur work empirically demonstrates that distinctive features of heart failure, including ventricular hypertrophy, heart failure with preserved EF (HFpEF), and heart failure with reduced EF (HFrEF) are present in the murine pressure overload models. The three stages of heart failure vary in terms of mRNA and circRNA expression, as well as ceRNA regulation in a manner consistent with their structural, functional, and pathological differences.

Abstract Background Patients with type 2 diabetes mellitus (T2DM) are predisposed to poor cardiovascular outcomes after ST-segment elevation myocardial infarction (STEMI). Left ventricular adverse remodeling (LVAR) triggered upon myocardial infarction is recognized as the predominant pathological process in the development of heart failure. In the present study, we sought to investigate whether visit-to-visit fasting plasma glucose (FPG) variability is a potential predictor of LVAR in T2DM patients after STEMI. Methods From January 2014 to December 2018 in Ruijin Hospital, T2DM patients with STEMI who underwent primary percutaneous coronary intervention were consecutively enrolled and followed up for ~ 12 months. The changes in left ventricular geometric and functional parameters between baseline and 12-month follow-up were assessed by echocardiography. The incidence of LVAR, defined as 20% increase in indexed left ventricular end-diastolic volume (LVEDV), and its relationship with visit-to-visit FPG variability were analyzed. Multivariate regression models were constructed to test the predictive value of FPG variability for post-infarction LVAR. Results A total of 437 patients with type 2 diabetes and STEMI were included in the final analysis. During a mean follow-up of 12.4 ± 1.1 months, the incidence of LVAR was 20.6% and mean enlargement of indexed LVEDV was 3.31 ± 14.4 mL/m2, which was significantly increased in patients with higher coefficient variance (CV) of FPG (P = 0.002) irrespective of baseline glycemic levels. In multivariate analysis, FPG variability was independently associated with incidence of post-infarction LVAR after adjustment for traditional risk factors, baseline HbA1c as well as mean FPG during follow-up (OR: 3.021 [95% CI 1.081–8.764] for highest vs. lowest tertile of CV of FPG). Assessing FPG variability by other two measures, including standard deviation (SD) and variability independent of the mean (VIM), yielded similar findings. Conclusions This study suggests that visit-to-visit FPG variability is an independent predictor of incidence of LVAR in T2DM patients with STEMI. Trial registration Trials number, NCT02089360; registered on March 17,2014.

Abstract Background Patients with type 2 diabetes are under substantially higher risk of in-stent restenosis (ISR) after coronary stent implantation. We sought to investigate whether visit-to-visit HbA1c variability is a potential predictor of ISR in diabetic patients after stent implantation. Methods We consecutively enrolled type 2 diabetic patients who underwent successful elective percutaneous coronary intervention and performed follow-up coronary angiography after around 12 months. The incidence of ISR and its relationship with visit-to-visit HbA1c variability, expressed as coefficient of variation (CV), standard deviation (SD) and variability independent of the mean (VIM), were studied. Multivariable Cox proportional hazards models were constructed to analyze the predictive value of HbA1c variability for ISR. Results From September 2014 to July 2018 in Ruijin Hospital, a total of 420 diabetic patients (688 lesions) after stent implantation were included in the final analysis. During a mean follow-up of 12.8 ± 1.3 months, the incidence of ISR was 8.6%, which was significantly increased in patients with higher CV of HbA1c (P = 0.001). The mean diameter stenosis (DS), net luminal loss and net luminal gain were 22.9 ± 16.8%, 0.42 ± 0.88 mm and 1.66 ± 0.83 mm, respectively. Greater DS was observed in subjects with higher tertiles of CV of HbA1c (P

Abstract Background To assess the prognostic role of coronary collaterals in patients with type 2 diabetes mellitus (T2DM) after successful percutaneous coronary intervention (PCI) for chronic total occlusion (CTO). Methods Coronary collateralization was graded according to Rentrop scoring system in 198 type 2 diabetic patients and 335 non-diabetics with stable angina undergoing PCI for at least one CTO lesion. Left ventricular ejection fraction (LVEF) was determined and major adverse cardio-cerebral events (MACCE) were recorded during follow-up. Results Poor collateralization was more common in patients with T2DM than in non-diabetics (40% vs 29%, p = 0.008). At 13.5 ± 4.1 months, the rate of composite MACCE (17.3% vs 27.6%, p = 0.034) and repeat revascularization (15.2% vs 25.5%, p = 0.026) was lower and the increase in LVEF (3.10% vs 1.80%, p = 0.024) was greater in patients with good collaterals than in those with poor collaterals for non-diabetic group. The associations were in the same direction for T2DM group (35% vs 44%; 30% vs 36%; 2.14% vs 1.65%, respectively) with a higher all-cause mortality in diabetic patients with poor collaterals (p = 0.034). Multivariable Cox proportional hazards analysis showed that coronary collateralization was an independent factor for time to MACCE (HR 2.155,95% CI 1.290–3.599, p = 0.003) and repeat revascularization (HR 2.326, 95% CI 1.357–3.986, p = 0.002) in non-diabetic patients, but did not enter the model in those with T2DM. Conclusions T2DM is associated with reduced coronary collateralization. The effects of the status of coronary collateralization on long-term clinical outcomes and left ventricular function appear to be similar in size in type 2 diabetic patients and non-diabetics after successful recanalization of CTO.

Objective To investigate the the timing of the first time of hyperbaric oxygen therapy and its effect on the recovery of neurological function and quality of life in patients with acute moderate to severe carbon monoxide poisoning. Methods A retrospective analysis was carried out in the patients with acute carbon monoxide poisoning admitted to our hyperbaric oxygen treatment center from January 2015 to June 2018. The patients who met the criteria of poisoning within 24 h, did not receive hyperbaric oxygen treatment in other hospitals, and had moderate or severe poisoning were divided into 3 groups according to the first treatment time, that is, ultra-early group (shorter than 6 h after poisoning), early group (within 6~12 h), and ordinary group (in 12~24 h after poisoning). The degree of recovery (complete recovery, partial recovery, no recovery), Glasgow coma index (GCS), simple mental state scale (MMSE), Barthel index (BI) and incidence of delayed encephalopathy after treatment was compared among the 3 groups. Results A total of 136 patients were eligible for admission, including 39 in the ultra-early group, 51 in the early group and 46 in the ordinary group. There were no significant differences in age, sex distribution and total treatment times among the groups. At the end of treatment, the proportions of patients with complete recovery were 43.5%, 31.4%, and 17.4%, respectively in the ultra-early group, early group and ordinary group. The improvement of GCS score was 4.85, 3.87 and 3.01, respectively, that of MMSE score was 19.01, 14.05, and 12.34, respectively, and that of BI was 75.48, 68.24 and 54.58, respectively, in the 3 groups. In 1 year after the treatment, delayed encephalopathy was observed in 2 cases (5.1%) in the ultra-early group, 7 cases (13.7%) in the early group, and 14 cases (30.4%) in the ordinary group. The ultra-early group obtained all better indicators than the ordinary group, and better percentage of complete recovery of symptoms, MMSE score and lower incidence of delayed encephalopathy when compared with the early group (all P < 0.05). Conclusion Implementation of hyperbaric oxygen therapy within 6 h after poisoning can result in a better prognosis for patients with moderate to severe acute carbon monoxide poisoning.

Forensic science standards are specifications and procedures that would greatly help to ensure a scientific, reliable and accurate result of the forensic process. The development of forensic science standards in China has been carried for more than 30 years and has its own development characteristics. Many forensic science standards have been widely used in forensic analysis and interpretation for the purposes of presenting conclusions to the court, effectively improving the performance of forensic science in China. This paper reviews the history and current situation of forensic science standards in China, including the standard development organization, standard supply, standardization system, standard implementation and review. This paper also introduces the characteristics and challenges of forensic science standardization in China and discusses the future trends, which would help to enhance the understanding of China’s forensic science standardization and provide a Chinese reference for the global forensic science community.

Background: Pressure overload can result in dilated cardiomyopathy. The beneficial effects of n-3 polyunsaturated fatty acids (n-3 PUFAs) on heart disorders have been widely recognized. However, the molecular mechanisms underlying their protective effects against cardiomyopathy remain unclear.Methods: Pressure overload in mice induced by 8 weeks of transverse aortic constriction was used to induce dilated cardiomyopathy. A transgenic fat-1 mouse model carrying the n-3 fatty acid desaturase gene fat-1 gene from Caenorhabditis elegans was used to evaluate the mechanism of n-3 PUFAs in this disease. Echocardiography, transmission electron microscopy, and histopathological analyses were used to evaluate the structural integrity and function in pressure overloaded fat-1 hearts. mRNA sequencing, label-free phosphoprotein quantification, lipidomics, Western blotting, RT-qPCR, and ATP detection were performed to examine the effects of n-3 PUFAs in the heart.Results: Compared with wild-type hearts, left ventricular ejection fraction was significantly improved (C57BL/6J [32%] vs. fat-1 [53%]), while the internal diameters of the left ventricle at systole and diastole were reduced in the fat-1 pressure overload hearts. mRNA expression, protein phosphorylation and lipid metabolism were remodeled by pressure overload in wild-type and fat-1 hearts. Specifically, elevation of endogenous n-3 PUFAs maintained the phosphorylation states of proteins in the subcellular compartments of sarcomeres, cytoplasm, membranes, sarcoplasmic reticulum, and mitochondria. Moreover, transcriptomic analysis predicted that endogenous n-3 PUFAs restored mitochondrial respiratory chain function that was lost in the dilated hearts, and this was supported by reductions in detrimental oxylipins and protection of mitochondrial structure, oxidative phosphorylation, and ATP production.Conclusions: Endogenous n-3 PUFAs prevents dilated cardiomyopathy via orchestrating gene expression, protein phosphorylation, and lipid metabolism. This is the first study provides mechanistic insights into the cardioprotective effects of n-3 PUFAs in dilated cardiomyopathy through integrated multi-omics data analysis.

The secure operation of smart grids is closely linked to state estimates that accurately reflect the physical characteristics of the grid. However, well-designed false data injection attacks (FDIAs) can manipulate the process of state estimation by injecting malicious data into the measurement data while bypassing the detection of the security system, ultimately causing the results of state estimation to deviate from secure values. Since FDIAs tampering with the measurement data of some buses will lead to error offset, this paper proposes an attack-detection algorithm based on statistical learning according to the different characteristic parameters of measurement error before and after tampering. In order to detect and classify false data from the measurement data, in this paper, we report the model establishment and estimation of error parameters for the tampered measurement data by combining the the k-means++ algorithm with the expectation maximization (EM) algorithm. At the same time, we located and recorded the bus that the attacker attempted to tamper with. In order to verify the feasibility of the algorithm proposed in this paper, the IEEE 5-bus standard test system and the IEEE 14-bus standard test system were used for simulation analysis. Numerical examples demonstrate that the combined use of the two algorithms can decrease the detection time to less than 0.011883 s and correctly locate the false data with a probability of more than 95%.

Background: Chromogranin B (CgB) is increased in heart failure and proportionate to disease severity. We investigated whether circulating CgB level is associated with left ventricular (LV) functional recovery potential after successful recanalization of chronic total occlusion (CTO).Methods: Serum levels of CgB were assayed in 53 patients with stable angina with LV functional recovery [an absolute increase in LV ejection fraction (EF) of ≥5%] and 53 age- and sex-matched non-recovery controls after successful recanalization of CTO during 12-month follow-up.Results: We found that CgB level was significantly lower in the recovery group than in the non-recovery group (593 [IQR 454–934] vs. 1,108 [IQR 696–2020] pg/ml, P < 0.001), and that it was inversely correlated with changes in LVEF (Spearman's r = −0.31, P = 0.001). Receiver operating characteristic (ROC) analysis showed that the area under the curve of CgB for predicting LVEF improvement was 0.76 (95% CI 0.664–0.856), and that the optimal cutoff value was 972.5 pg/ml. In multivariate analyses, after adjusting for confounding factors, high CgB level remained an independent determinant of impaired LV functional recovery after CTO recanalization. LV functional improvement appeared to be more responsive to CgB in patients with poor than with good coronary collaterals.Conclusions: Elevated circulating CgB level confers an increased risk of impaired LV functional recovery after successful recanalization of CTO in patients with stable coronary artery disease.