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Abstract In recent years, A series of environmental problems caused by air pollution have attracted widespread attention. Air quality forecasting has become an indispensable part of people’s daily life. However, the traditional air quality prediction (AQP) model WRF-CMAQ simulation system faces several challenges: (1) the fuzziness of pollutant formation mechanism; (2) the hardness of integrating the features of meteorological conditions; (3) the difficulty of cooperating among monitoring stations. To deal with these challenges, we propose a multi-task station cooperative air quality prediction (MTSC-AQP) system for sustainable development. The MTSC-AQP system contains three modules: air quality analysis, a WRF-LSTM module for initial pollutant prediction, and multi-station cooperative AQP. Through air quality analysis, it can calculate the air quality index (AQI) and analyze the correlation between pollutants and meteorological conditions. Then, the WRF-LSTM module integrates spatio-temporal multi-source data to forecast the initial concentration of pollutants. Finally, the system incorporates the gravity model to predict the final AQI. Extensive experiments conducted on real-world datasets show the effectiveness of forecasting the AQI by using the MTSC-AQP system.

Abstract Objectives To develop and validate a radiomics nomogram combining radiomics features and clinical factors for preoperative evaluation of Ki-67 expression status and prognostic prediction in clear cell renal cell carcinoma (ccRCC). Methods Two medical centers of 185 ccRCC patients were included, and each of them formed a training group (n = 130) and a validation group (n = 55). The independent predictor of Ki-67 expression status was identified by univariate and multivariate regression, and radiomics features were extracted from the preoperative CT images. The maximum relevance minimum redundancy (mRMR) and the least absolute shrinkage and selection operator algorithm (LASSO) were used to identify the radiomics features that were most relevant for high Ki-67 expression. Subsequently, clinical model, radiomics signature (RS), and radiomics nomogram were established. The performance for prediction of Ki-67 expression status was validated using area under curve (AUC), calibration curve, Delong test, decision curve analysis (DCA). Prognostic prediction was assessed by survival curve and concordance index (C-index). Results Tumour size was the only independent predictor of Ki-67 expression status. Five radiomics features were finally identified to construct the RS (AUC: training group, 0.821; validation group, 0.799). The radiomics nomogram achieved a higher AUC (training group, 0.841; validation group, 0.814) and clinical net benefit. Besides, the radiomics nomogram provided a highest C-index (training group, 0.841; validation group, 0.820) in predicting prognosis for ccRCC patients. Conclusions The radiomics nomogram can accurately predict the Ki-67 expression status and exhibit a great capacity for prognostic prediction in patients with ccRCC and may provide value for tailoring personalized treatment strategies and facilitating comprehensive clinical monitoring for ccRCC patients.

Background Transfemoral carotid artery stenting (TFCAS) carries important perioperative risks. Outcome prediction tools may help guide clinical decision‐making but remain limited. We developed machine learning algorithms that predict 1‐year stroke or death following TFCAS. Methods and Results The VQI (Vascular Quality Initiative) database was used to identify patients who underwent TFCAS for carotid artery stenosis between 2005 and 2024. We identified 112 features from the index hospitalization (82 preoperative [demographic/clinical], 13 intraoperative [procedural], and 17 postoperative [in‐hospital course/complications]). The primary outcome was 1‐year postprocedural stroke or death. The data were divided into training (70%) and test (30%) sets. Six machine learning models were trained using preoperative features with 10‐fold cross‐validation. The primary model evaluation metric was area under the receiver operating characteristic curve. The algorithm with the best performance was further trained using intra‐ and postoperative features. Model robustness was assessed using calibration plots and Brier scores. Overall, 35 214 patients underwent TFCAS during the study period and 3257 (9.2%) developed 1‐year stroke or death. The best preoperative prediction model was extreme gradient boosting, achieving an area under the receiver operating characteristic curve of 0.94 (95% CI, 0.93–0.95). In comparison, logistic regression had an AUROC of 0.65 (95% CI, 0.63–0.67). The extreme gradient boosting model maintained excellent performance at the intra‐ and postoperative stages, with area under the receiver operating characteristic curve values of 0.94 (95% CI, 0.93–0.95) and 0.98 (95% CI, 0.97–0.99), respectively. Calibration plots showed good agreement between predicted/observed event probabilities with Brier scores of 0.11 (preoperative), 0.11 (intraoperative), and 0.09 (postoperative). Conclusions Machine learning can accurately predict 1‐year stroke or death following TFCAS, performing better than logistic regression.

Abstract Lower extremity open revascularization is a treatment option for peripheral artery disease that carries significant peri-operative risks; however, outcome prediction tools remain limited. Using machine learning (ML), we developed automated algorithms that predict 30-day outcomes following lower extremity open revascularization. The National Surgical Quality Improvement Program targeted vascular database was used to identify patients who underwent lower extremity open revascularization for chronic atherosclerotic disease between 2011 and 2021. Input features included 37 pre-operative demographic/clinical variables. The primary outcome was 30-day major adverse limb event (MALE; composite of untreated loss of patency, major reintervention, or major amputation) or death. Our data were split into training (70%) and test (30%) sets. Using tenfold cross-validation, we trained 6 ML models. Overall, 24,309 patients were included. The primary outcome of 30-day MALE or death occurred in 2349 (9.3%) patients. Our best performing prediction model was XGBoost, achieving an area under the receiver operating characteristic curve (95% CI) of 0.93 (0.92–0.94). The calibration plot showed good agreement between predicted and observed event probabilities with a Brier score of 0.08. Our ML algorithm has potential for important utility in guiding risk mitigation strategies for patients being considered for lower extremity open revascularization to improve outcomes.

Abstract The electron-phonon (el-ph) and phonon-phonon interactions play crucial roles in determining the electronic and thermal transport properties of materials. Using the group theory and ab-initio calculations, we have derived the full-landscape selection rules for intravalley and intervalley scattering for carriers in 2D silicon and germanium allotropes with low buckled (LB) and large honeycomb dumbbell (LHD) structures, showing dominant role of optical modes in total el-ph coupling in LHD Si/Ge due to most el-ph scattering channels via acoustic modes blocked by symmetries. Remarkably, we show that due to the relatively large optical phonon bandwidth and “bunching effect" of acoustic phonon bands, the selection rules of three-phonon interactions reveal the dominant ooo and aoo channels in LHD and LB Si/Ge, respectively, and the temprature-induced effects significantly increase the ratio between mode-resolved four-phonon interactions and three-phonon interactions in most of the phonon-frequency region, finally leading to the low thermal conductivities in both LB and LHD Si/Ge. Furthermore, we observe the anomalous temperature-dependent thermal conductivities in LHD Ge, resulted from the vanishing quasi-acoustic-optical phonon gap under the temperature-induced effects. By considering full el-ph coupling and higher-order anharmonic phonon-phonon interactions, the maximal thermoelectric figures of merits in LHD Si and LB Ge are found to reach 1.06 and 0.66 at 700 K, respectively, significantly surpassing their bulk counterparts. Our work is poised to stimulate wide-ranging exploration into phonon transport across diverse materials, and benefits both fundamental knowledge and advanced technologies of 2D Si/Ge allotropes.

Wireless capsule endoscopy (WCE) systems are used to capture images of the human digestive tract for medical applications, especially the noninvasive diagnostics and treatments of small intestinal diseases. As an important part of the WCE system, the antenna plays a crucial role in transmitting and receiving data. To transmit diagnostic real-time images from the inside body with high resolution at a high data transmission speed, ultra-wideband (UWB) antenna designs for the WCE system have been proposed by researchers in recent years. However, to the best of our knowledge, there are few papers to systematically review the UWB antennas used in the WCE system. In this paper, a comprehensive review of different UWB antenna designs for WCE system is presented. In-body and on-body UWB antennas are classified according to the radiative performances and structure. Particular attention is also paid to the models used in simulation and experiment, as well as some key performance parameters and technologies in the process of antenna design. This extensive summary of UWB antennas for WCE systems will help to understand the prospects and challenges in this field.

With the development of modern technology, the construction industry, and navigation technology, the metal Cu alloy has become an important metal material in mainstream industrial applications. As an indispensable basic metal material in the field of science and technology, its problem with corrosion is still a long-term problem that scientists have been working to solve. In this paper, air spraying technology is used to prepare an Al2O3-PDMS composite coating. By adjusting the content of Al2O3, the surface of the Cu alloy can reach different wetting states. The results show that the corrosion potential of the as-prepared superhydrophobic Al2O3-PDMS coating increases by 70 mV compared with the substrate, the corrosion current density decreases by one order of magnitude, and the impedance modulus increases from 2000 to 12,000 Ω⋅cm2, indicating a significantly enhanced corrosion resistance. It also possesses excellent anti-pollution and anti-icing behaviors, thereby allowing them to work in harsh industrial conditions.

Interface dislocation networks have a great influence on the mechanical properties of the new Ni-based single-crystal alloy (NSC) containing Re, but it is difficult to find out the structural evolution behaviors at the micro-level. Thus, molecular dynamics (MD) simulation is used to analyze the atomic potential energy change and dislocation evolution mechanism, and non-linear characteristic parameters are used to analyze the microstructure evolution of NSC. First, a new model of Ni-Al-Re that is closer to the real properties of the material is established using the MD method according to the optimal volume ratio of matrix phase to precipitate phase. Then, the MD models of NSC with different contents of Re are calculated and analyzed under compressive and tensile loads. The results show that with an increase in Re atoms, the atomic potential energy at the interface dislocation networks is reduced; thus, the stability of the system is enhanced, and the hindrance of the interface dislocation networks to the dislocation movement of the matrix phase is strengthened. At the same time, the number of HCP structures and OISs formed by the destruction of the intact FCC structures also decreases. In the non-linear ultrasonic experiment, with the increase in Re atoms, the non-linear enhancement of the microstructure of the NSC leads to an increase in the corresponding non-linear characteristic parameters. Accordingly, the microstructural evolution behaviors of the phase interface of the new NSC can be effectively explored using the combination of MD simulation and non-linear ultrasonic experimentation. The results of this study lay a foundation for the subsequent research of the microscopic defects of NSCs by using ultrasonic phased-array technology.

Abstract The 2D semiconductors are an ideal platform for exploration of bosonic fluids composed of coupled photons and collective excitations of atoms or excitons, primarily due to large excitonic binding energies and strong light‐matter interaction. Based on first‐principles calculations, it is demonstrated that the phonon polaritons formed by two infrared‐active phonon modes in monolayer MoSi2N4 and WSi2N4 possess ultra‐high confinement factors of around ≈105 and 103, surpassing those of conventional polaritonic thin‐film materials by two orders of magnitude. It is observed that the first bright exciton possesses a substantial binding energies of 750 and 740 meV in these two monolayers, with the radiative recombination lifetimes as long as 25 and 188 ns, and the Rabi splitting of the formed cavity‐exciton polaritons reaching 373 and 321 meV, respectively. The effective masses of the cavity exciton polaritons are approximately 10−5me, providing the potential for high‐temperature quantum condensation. The ultra‐confined and ultra‐low‐loss phonon polaritons, as well as strongly‐coupled cavity exciton polaritons with ultra‐small polaritonic effective masses in these two monolayers, offering the flexible control of light at the nanoscale, probably leading to practical applications in nanophotonics, meta‐optics, and quantum materials.

Background Lower extremity endovascular revascularization for peripheral artery disease carries nonnegligible perioperative risks; however, outcome prediction tools remain limited. Using machine learning, we developed automated algorithms that predict 30‐day outcomes following lower extremity endovascular revascularization. Methods and Results The National Surgical Quality Improvement Program targeted vascular database was used to identify patients who underwent lower extremity endovascular revascularization (angioplasty, stent, or atherectomy) for peripheral artery disease between 2011 and 2021. Input features included 38 preoperative demographic/clinical variables. The primary outcome was 30‐day postprocedural major adverse limb event (composite of major reintervention, untreated loss of patency, or major amputation) or death. Data were split into training (70%) and test (30%) sets. Using 10‐fold cross‐validation, 6 machine learning models were trained using preoperative features. The primary model evaluation metric was area under the receiver operating characteristic curve. Overall, 21 886 patients were included, and 30‐day major adverse limb event/death occurred in 1964 (9.0%) individuals. The best performing model for predicting 30‐day major adverse limb event/death was extreme gradient boosting, achieving an area under the receiver operating characteristic curve of 0.93 (95% CI, 0.92–0.94). In comparison, logistic regression had an area under the receiver operating characteristic curve of 0.72 (95% CI, 0.70–0.74). The calibration plot showed good agreement between predicted and observed event probabilities with a Brier score of 0.09. The top 3 predictive features in our algorithm were (1) chronic limb‐threatening ischemia, (2) tibial intervention, and (3) congestive heart failure. Conclusions Our machine learning models accurately predict 30‐day outcomes following lower extremity endovascular revascularization using preoperative data with good discrimination and calibration. Prospective validation is warranted to assess for generalizability and external validity.

Summary: Peripheral artery disease (PAD) biomarkers have been studied in isolation; however, an algorithm that considers a protein panel to inform PAD prognosis may improve predictive accuracy. Biomarker-based prediction models were developed and evaluated using a model development (n = 270) and prospective validation cohort (n = 277). Plasma concentrations of 37 proteins were measured at baseline and the patients were followed for 2 years. The primary outcome was 2-year major adverse limb event (MALE; composite of vascular intervention or major amputation). Of the 37 proteins tested, 6 were differentially expressed in patients with vs. without PAD (ADAMTS13, ICAM-1, ANGPTL3, Alpha 1-microglobulin, GDF15, and endostatin). Using 10-fold cross-validation, we developed a random forest machine learning model that accurately predicts 2-year MALE in a prospective validation cohort of PAD patients using a 6-protein panel (AUROC 0.84). This algorithm can support PAD risk stratification, informing clinical decisions on further vascular evaluation and management.

Abstract Image stitching is a fundamental pillar of computer vision, and its effectiveness hinges significantly on the quality of the feature descriptors. However, the existing feature descriptors face several challenges, including inadequate robustness to noise or rotational transformations and limited adaptability during hardware deployment. To address these limitations, this paper proposes a set of feature descriptors for image stitching named Lightweight Multi-Feature Descriptors (LMFD). Based on the extensive extraction of gradients, means, and global information surrounding the feature points, feature descriptors are generated through various combinations to enhance the image stitching process. This endows the algorithm with formidable rotational invariance and noise resistance, thereby improving its accuracy and reliability. Furthermore, the feature descriptors take the form of binary matrices consisting of 0s and 1s, not only facilitating more efficient hardware deployment but also enhancing computational efficiency. The utilization of binary matrices significantly reduces the computational complexity of the algorithm while preserving its efficacy. To validate the effectiveness of LMFD, rigorous experimentation was conducted on the Hpatches and 2D-HeLa datasets. The results demonstrate that LMFD outperforms state-of-the-art image matching algorithms in terms of accuracy. This empirical evidence solidifies the superiority of LMFD and substantiates its potential for practical applications in various domains.

This paper delves into the modification mechanism and deterioration mechanism of basalt fiber (BF) on the sulfate resistance of graphite tailings (GT) cement-based materials. Initially, the comprehensive properties of basalt fiber modified graphite tailings cement mortar (BFM-GTCM) under different sulfate cycles, such as apparent morphology, water absorption and mechanical characteristics were investigated. Subsequently, the relationship between the evolution of microstructure, interface stability, pore structure, chemical composition and functional groups of BFM-GTCM and its resistance to sulfate erosion under different cycles was revealed by various microscopic characterization and analysis methods (SEM/XRD/MIP/FTIR/DSI). Simultaneously, a corrosion coefficient-pore structure relationship model was also put forth based on multivariate regression theory, and the mechanism enhancing BFM-GTCM resistance to sulfate attack was investigated. The results demonstrated that a suitable blend of BF and GT can prevent sulfate ion penetration, significantly slow down the generation of corrosion products (AFt and gypsum) in cement mortar during sulfate attack, postpone the occurrence of new cracks and the growth of existing ones, improve pore structure, and significantly lessen the degree of durability degradation of BF-GTCM. Among them, 0.3% BF addition and 20% GT replacement was the ideal ratio.

Hybrid electric vehicle (HEV) is one of the ideal transportation tools to face the challenge of ‘Carbon peak carbon neutralization’. The high complexity of the latest HEVs result to the difficulties in vehicle fault diagnostics, which is considered to be the main factors of vehicle durability. In this study, a multi-fault mode detection method of a P2 diesel HEV was investigated by using support vector machine(SVM). The HEV physical model was built and validated by using the experimental data under China typical urban driving cycle (CTUDC). The SVM algorithm was coded in Matlab/Simulink environment. The training data vectors for normal mode and fault mode were acquired from the HEV model. Through the analysis of failure mode, the OVO-SVM method was proved as the best accuracy, the success rate of diagnosis reaches 98%. Case studies of single fault mode and multi-fault mode fault detection were conducted. Offline and online level test were performed to show the effectiveness of the detection algorithm. The study may support the development of intelligent diagnostic methods for the different types of HEVs.

Soluble interleukin 1 receptor-like 1 (ST2) is a circulating protein demonstrated to be associated with cardiovascular diseases; however, it has not been studied as a biomarker for peripheral artery disease (PAD). Using a prospectively recruited cohort of 476 patients (312 with PAD and 164 without PAD), we conducted a prognostic study of PAD using clinical/biomarker data. Plasma concentrations of three circulating proteins [ST2, cytokine-responsive gene-2 (CRG-2), vascular endothelial growth factor (VEGF)] were measured at baseline and the cohort was followed for 2 years. The outcome of interest was a 2-year major adverse limb event (MALE; composite of major amputation, vascular intervention, or acute limb ischemia). Using 10-fold cross-validation, a random forest model was trained using clinical characteristics and plasma ST2 levels. The primary model evaluation metric was the F1 score. Out of the three circulating proteins analyzed, ST2 was the only one that was statistically significantly higher in individuals with PAD compared to patients without PAD (mean concentration in plasma of 9.57 [SD 5.86] vs. 11.39 [SD 6.43] pg/mL, p < 0.001). Over a 2-year period, 28 (9%) patients with PAD experienced MALE. Our predictive model, incorporating clinical features and plasma ST2 levels, achieved an F1 score of 0.713 for forecasting 2-year MALE outcomes. Patients identified as high-risk by this model showed a significantly increased likelihood of developing MALE (HR 1.06, 95% CI 1.02–1.13, p = 0.003). By combining clinical characteristics and plasma ST2 levels, our proposed predictive model offers accurate risk assessment for 2-year MALE in PAD patients. This algorithm supports risk stratification in PAD, guiding clinical decisions regarding further vascular evaluation, specialist referrals, and appropriate medical or surgical interventions, thereby potentially enhancing patient outcomes.

Cytokine-induced neutrophil chemoattractant 1 (CINC-1), a cluster of differentiation 95 (CD95), fractalkine, and T-cell immunoglobulin and mucin domain 1 (TIM-1) are circulating proteins known to be involved in inflammation. While their roles have been studied in neurological conditions and cardiovascular diseases, their potential as peripheral artery disease (PAD) biomarkers remain unexplored. We conducted a cross-sectional diagnostic study using data from 476 recruited patients (164 without PAD and 312 with PAD). Plasma levels of CINC-1, CD95, fractalkine, and TIM-1 were measured at baseline. A PAD diagnosis was established at recruitment based on clinical exams and investigations, defined as an ankle-brachial index < 0.9 or toe-brachial index < 0.67 with absent/diminished pedal pulses. Using 10-fold cross-validation, we trained a random forest algorithm, incorporating clinical characteristics and biomarkers that showed differential expression in PAD versus non-PAD patients to predict a PAD diagnosis. Among the proteins tested, CINC-1, CD95, and fractalkine were elevated in PAD vs. non-PAD patients, forming a 3-biomarker panel. Our predictive model achieved an AUROC of 0.85 for a PAD diagnosis using clinical features and this 3-biomarker panel. By combining the clinical characteristics with these biomarkers, we developed an accurate predictive model for a PAD diagnosis. This algorithm can assist in PAD screening, risk stratification, and guiding clinical decisions regarding further vascular assessment, referrals, and medical/surgical management to potentially improve patient outcomes.

Background and Objectives: Inflammatory proteins and their prognostic value in patients with carotid artery stenosis (CAS) have not been adequately studied. Herein, we identified CAS-specific biomarkers from a large pool of inflammatory proteins and assessed the ability of these biomarkers to predict adverse events in individuals with CAS. Materials and Methods: Samples of blood were prospectively obtained from 336 individuals (290 with CAS and 46 without CAS). Plasma concentrations of 29 inflammatory proteins were determined at recruitment, and the patients were followed for 24 months. The outcome of interest was a major adverse cardiovascular event (MACE; composite of stroke, myocardial infarction, or death). The differences in plasma protein concentrations between patients with vs. without a 2-year MACE were determined using the independent t-test or Mann–Whitney U test to identify CAS-specific prognostic biomarkers. Kaplan–Meier and Cox proportional hazards analyses with adjustment for baseline demographic and clinical characteristics were performed to assess the prognostic value of differentially expressed inflammatory proteins in predicting a 2-year MACE in patients with CAS. Results: The mean age of the cohort was 68.8 (SD 10.2) years and 39% were female. The plasma concentrations of two inflammatory proteins were significantly higher in individuals with a 2-year MACE relative to those without a 2-year MACE: IL-6 (5.07 (SD 4.66) vs. 3.36 (SD 4.04) pg/mL, p = 0.03) and CD163 (233.825 (SD 230.306) vs. 159.673 (SD 175.669) pg/mL, p = 0.033). Over a follow-up period of 2 years, individuals with elevated levels of IL-6 were more likely to develop MACE (HR 1.269 (95% CI 1.122–1.639), p = 0.042). Similarly, over a 2-year period, patients with high levels of CD163 were more likely to develop MACE (HR 1.413 (95% CI 1.022–1.954), p = 0.036). Conclusions: The plasma levels of inflammatory proteins IL-6 and CD163 are independently associated with adverse outcomes in individuals with CAS. These CAS-specific prognostic biomarkers may assist in the risk stratification of patients at an elevated risk of a MACE and subsequently guide further vascular evaluation, specialist referrals, and aggressive medical/surgical management, thereby improving outcomes for patients with CAS.

Abstract Background Surgery is a common treatment strategy for patients with neurofibromatosis type 1 (NF1)-related plexiform neurofibroma (PN) and has limited efficacy. FCN-159 is a novel anti-tumorigenic drug via selective inhibition of MEK1/2. This study assesses the safety and efficacy of FCN-159 in patients with NF1-related PN. Methods This is a multicenter, open-label, single-arm, phase I dose-escalation study. Patients with NF1-related PN that was non-resectable or unsuitable for surgery were enrolled; they received FCN-159 monotherapy daily in 28-day cycles. Results Nineteen adults were enrolled in the study, 3 in 4 mg, 4 in 6 mg, 8 in 8 mg, and 4 in 12 mg. Among patients included in dose-limiting toxicity (DLT) analysis, DLTs (grade 3 folliculitis) were reported in 1 of 8 patients (16.7%) receiving 8 mg and 3 of 3 (100%) patients receiving 12 mg. The maximum tolerated dose was determined to be 8 mg. FCN-159-related treatment-emergent adverse events (TEAEs) were observed in 19 patients (100%); most of which were grade 1 or 2. Nine (47.4%) patients reported grade 3 study-drug–related TEAEs across all dose levels, including four experiencing paronychia and five experiencing folliculitis. Of the 16 patients analyzed, all (100%) had reduced tumor size and six (37.5%) achieved partial responses; the largest reduction in tumor size was 84.2%. The pharmacokinetic profile was approximately linear between 4 and 12 mg, and the half-life supported once daily dosing. Conclusions FCN-159 was well tolerated up to 8 mg daily with manageable adverse events and showed promising anti-tumorigenic activity in patients with NF1-related PN, warranting further investigation in this indication. Trial registration ClinicalTrials.gov, NCT04954001. Registered 08 July 2021.

Trematodes of the genus Ogmocotyle are intestinal flukes that can infect a variety of definitive hosts, resulting in significant economic losses worldwide. However, there are few studies on molecular data of these trematodes. In this study, the mitochondrial (mt) genome of Ogmocotyle ailuri isolated from red panda (Ailurus fulgens) was determined and compared with those from Pronocephalata to investigate the mt genome content, genetic distance, gene rearrangements and phylogeny. The complete mt genome of O. ailuri is a typical closed circular molecule of 14 642 base pairs, comprising 12 protein-coding genes (PCGs), 22 transfer RNA genes, 2 ribosomal RNA genes and 2 non-coding regions. All genes are transcribed in the same direction. In addition, 23 intergenic spacers and 2 locations with gene overlaps were determined. Sequence identities and sliding window analysis indicated that cox1 is the most conserved gene among 12 PCGs in O. ailuri mt genome. The sequenced mt genomes of the 48 Plagiorchiida trematodes showed 5 types of gene arrangement based on all mt genome genes, with the gene arrangement of O. ailuri being type I. Phylogenetic analysis using concatenated amino acid sequences of 12 PCGs revealed that O. ailuri was closer to Ogmocotyle sikae than to Notocotylus intestinalis. These data enhance the Ogmocotyle mt genome database and provide molecular resources for further studies of Pronocephalata taxonomy, population genetics and systematics.

Abstract Insufficient immune cell infiltration into the tumor microenvironment (TME) greatly compromises the clinical application of immune‐checkpoint inhibitors (ICIs)‐based immunotherapy. Recent findings have shown that activation of the cyclic GMP‐AMP synthase‐stimulator of interferon genes (cGAS‐STING) pathway can enhance natural immunity and increase lymphocyte infiltration into the TME, which presents a promising strategy for cancer immunotherapy. In this study, we constructed hydroxyapatite nanoparticles co‐loaded with curcumin and L‐oxaliplatin (Cur/L‐OHP@HAP NPs). We analyzed the particle‐size distribution, zeta potential, spectral characteristics (Fourier‐transform infrared spectroscopy, X‐ray photoelectron spectroscopy, ultraviolet–visible spectroscopy), and drug‐release properties of the Cur/L‐OHP@HAP NPs. The cellular uptake of the Cur/L‐OHP@HAP NPs detected by flow cytometry and confocal laser‐scanning microscopy. We comprehensively evaluated the anti‐tumor properties and immune‐activating effects of the NPs, both in vitro and in vivo. Physicochemical characterizations demonstrated that the Cur/L‐OHP@HAP NPs were successfully synthesized and were capable of pH‐dependent drug release. Notably, the Cur/L‐OHP@HAP NPs efficiently entered cancer cells, after which the released L‐OHP induced nuclear DNA (nDNA) damage to some extent. HAP promoted the release of intracellular Ca2+ stores in cancer cells, and curcumin inhibited Ca2+ efflux, resulting in intracellular Ca2+ overload and the release of mitochondrial DNA (mtDNA). Damage to both nDNA and mtDNA greatly stimulated the cGAS‐STING pathway, thereby activating natural immunity, accompanied by immune cell recruitment to the TME. In summary, the Cur/L‐OHP@HAP NPs show good prospects for improving cancer immunotherapy.

The effect of interface dislocation networks on the mechanical properties of new Ni–based single crystal alloys containing Rhenium (Re) is very large. Because the interface dislocations are microscopic in the nano–scale range, this has not been investigated, and it is very difficult to prepare new Ni–based single crystal alloys containing Re. Therefore, six kinds of new Ni–based single crystal alloys containing Re were prepared, and the hardness tests and nonlinear ultrasonic lamb wave tests were performed on the samples. It was found that the density of interface dislocation networks increases with the increase in the content of Re, which improves the blocking ability of matrix phase dislocation cutting into precipitated phase and enhances the inhibition of dislocation movement. The nonlinear ultrasonic lamb wave tests showed that the materials exhibit better mechanical properties when the density of the interface dislocation networks increases. Meanwhile, a new molecular dynamics model which is closer to the real state of an Ni–based single crystal alloy was constructed to reveal the evolution mechanism of interface dislocation networks. The results showed that the potential energy of Re atoms at the interface is the lowest, which affects the reduction of the potential energy of other atoms at the interface, and thus the stability of the model is improved. In addition, according to the change in the total length of dislocation loops in the model system, with the increase in the content of Re atoms, the inhibition of dislocation movement by dislocation networks at the interface is strengthened.

After more than five decades, Moore’s Law for transistors is approaching the end of the international technology roadmap of semiconductors (ITRS). The fate of complementary metal oxide semiconductor (CMOS) architecture has become increasingly unknown. In this era, 3D transistors in the form of gate-all-around (GAA) transistors are being considered as an excellent solution to scaling down beyond the 5 nm technology node, which solves the difficulties of carrier transport in the channel region which are mainly rooted in short channel effects (SCEs). In parallel to Moore, during the last two decades, transistors with a fully depleted SOI (FDSOI) design have also been processed for low-power electronics. Among all the possible designs, there are also tunneling field-effect transistors (TFETs), which offer very low power consumption and decent electrical characteristics. This review article presents new transistor designs, along with the integration of electronics and photonics, simulation methods, and continuation of CMOS process technology to the 5 nm technology node and beyond. The content highlights the innovative methods, challenges, and difficulties in device processing and design, as well as how to apply suitable metrology techniques as a tool to find out the imperfections and lattice distortions, strain status, and composition in the device structures.

In recent years, the deformation detection technology for underground tunnels has played a crucial role in coal mine safety management. Currently, traditional methods such as the cross method and those employing the roof abscission layer monitoring instrument are primarily used for tunnel deformation detection in coal mines. With the advancement of photogrammetric methods, three-dimensional laser scanners have gradually become the primary method for deformation detection of coal mine tunnels. However, due to the high-risk confined spaces and distant distribution of coal mine tunnels, stationary three-dimensional laser scanning technology requires a significant amount of labor and time, posing certain operational risks. Currently, mobile laser scanning has become a popular method for coal mine tunnel deformation detection. This paper proposes a method for detecting point cloud deformation of underground coal mine tunnels based on a handheld three-dimensional laser scanner. This method utilizes SLAM laser radar to obtain complete point cloud information of the entire tunnel, while projecting the three-dimensional point cloud onto different planes to obtain the coordinates of the tunnel centerline. By using the calculated tunnel centerline, the three-dimensional point cloud data collected at different times are matched to the same coordinate system, and then the tunnel deformation parameters are analyzed separately from the global and cross-sectional perspectives. Through on-site collection of tunnel data, this paper verifies the feasibility of the algorithm and compares it with other centerline fitting and point cloud registration algorithms, demonstrating higher accuracy and meeting practical needs.

Image stitching is an important method for digital image processing, which is often prone to the problem of the irregularity of stitched images after stitching. And the traditional image cropping or complementation methods usually lead to a large number of information loss. Therefore, this paper proposes an image rectification method based on deformable mesh and residual network. The method aims to minimize the information loss at the edges of the spliced image and the information loss inside the image. Specifically, the method can select the most suitable mesh shape for residual network regression according to different images. Its loss function includes global loss and local loss, aiming to minimize the loss of image information within the grid and global target. The method in this paper not only greatly reduces the information loss caused by irregular shapes after image stitching, but also adapts to different images with various rigid structures. Meanwhile, its validation on the DIR-D dataset shows that the method outperforms the state-of-the-art methods in image rectification.

Coastlines with extensive estuaries and broad tidal flats are acutely vulnerable to coastal development. The tidal wetlands of the Yellow Sea are globally important for waterbirds, yet river mouths have disproportionately been developed as industrial ports, fishing ports, or have become abandoned fishing ports, with the type of management strategies depending on biophysical attributes and regional economic drivers. However, river mouths also support extensive upper tidal flat ecosystems, in contrast to many open coastal regions of the Yellow Sea, where reclamation has excised many of the upper tidal flats and dramatically reduced the time that tidal flats are available for foraging and roosting waterbirds each day. However, the extent to which waterbirds disproportionately occurs in river mouths compared to the open coast in the region remains unclear. We used a paired survey design to quantify the waterbird communities and habitat attributes (i.e., areas of upper tidal flats, Spartina alterniflora, and human activity) of 15 river mouths and 15 otherwise similar adjacent open coasts areas along the Yellow Sea coast. Waterbird species richness and abundance were higher in river mouths than open coasts. Among river mouths, the most species rich waterbird communities occurred in fishing ports and the most species poor in industrial ports. Notably, upper tidal flats were absent in many of the open coast regions, which had been subject to reclamation. Our results suggest that river mouths, especially those river mouths currently used as fishing ports, are probably of crucial importance for waterbird conservation on the Jiangsu coast due to their larger areas of upper tidal flats. Our work highlights the need to ensure that the tidal flats in river mouth systems are effectively protected to promote the completion of the annual cycle of migratory waterbirds.

Background Carotid endarterectomy (CEA) is a major vascular operation for stroke prevention that carries significant perioperative risks; however, outcome prediction tools remain limited. The authors developed machine learning algorithms to predict outcomes following CEA. Methods and Results The National Surgical Quality Improvement Program targeted vascular database was used to identify patients who underwent CEA between 2011 and 2021. Input features included 36 preoperative demographic/clinical variables. The primary outcome was 30‐day major adverse cardiovascular events (composite of stroke, myocardial infarction, or death). The data were split into training (70%) and test (30%) sets. Using 10‐fold cross‐validation, 6 machine learning models were trained using preoperative features. The primary metric for evaluating model performance was area under the receiver operating characteristic curve. Model robustness was evaluated with calibration plot and Brier score. Overall, 38 853 patients underwent CEA during the study period. Thirty‐day major adverse cardiovascular events occurred in 1683 (4.3%) patients. The best performing prediction model was XGBoost, achieving an area under the receiver operating characteristic curve of 0.91 (95% CI, 0.90–0.92). In comparison, logistic regression had an area under the receiver operating characteristic curve of 0.62 (95% CI, 0.60–0.64), and existing tools in the literature demonstrate area under the receiver operating characteristic curve values ranging from 0.58 to 0.74. The calibration plot showed good agreement between predicted and observed event probabilities with a Brier score of 0.02. The strongest predictive feature in our algorithm was carotid symptom status. Conclusions The machine learning models accurately predicted 30‐day outcomes following CEA using preoperative data and performed better than existing tools. They have potential for important utility in guiding risk‐mitigation strategies to improve outcomes for patients being considered for CEA.

Background: Angiogenesis plays an important role in peripheral artery disease (PAD) and angiogenesis-related proteins may act as prognostic biomarkers. This study assesses the potential for angiogenesis-related proteins to predict adverse events associated with PAD. Methods: This was a case-control study. Patients with PAD (n = 250) and without PAD (n = 125) provided blood samples and were followed prospectively for three years. Concentrations of 17 angiogenesis-related proteins were measured in plasma. The incidence of major adverse limb event (MALE), defined as a composite of major amputation or vascular intervention, was the primary outcome. Worsening PAD status, defined as a drop in ankle brachial index ≥ 0.15, was the secondary outcome. Multivariable regression adjusted for baseline characteristics was conducted to determine the prognostication value of angiogenesis-related proteins in predicting MALE. Findings: Relative to patients without PAD, 8 proteins related to angiogenesis were expressed differentially in PAD patients. Worsening PAD status and MALE were observed in 52 (14%) and 83 (22%) patients, respectively. Hepatocyte growth factor (HGF) was the most reliable predictor of MALE (adjusted HR 0.79, 95% CI 0.15–0.86). Compared to individuals with high HGF, patients with low HGF had a decreased three-year freedom from MALE [66% vs 88%, p = 0.001], major amputation [93% vs 98%, p = 0.023], vascular intervention [68% vs 88%, p = 0.001], and worsening PAD status [81% vs 91%, p = 0.006]. Interpretation: Measuring plasma levels of HGF in individuals with PAD can assist in identifying patients at elevated risk of adverse events related to PAD who may benefit from additional evaluation or treatment.

With the advantages of flexible parking locations and convenient cycling, Dockless Bicycle-sharing (DBS) has become increasingly popular worldwide. However, with the massive increase of DBSs and electric fences, DBS systems face several challenges: (1) the hardness of identifying the DBS tidal zones; (2) the difficulty of accurately evaluating and identifying overload fences; (3) the issues of rebalancing DBS in time. To deal with these challenges, we propose a Dockless Bicycle-sharing Dynamic Rebalance (DBSDR) system to dynamically provide the optimal bicycle guidance for the DBS network. The DBSDR system contains three modules: DBS tidal zone identification, evaluation framework of overload fences, and DBS dynamic guidance. For DBS tidal zone identification, tidal zone identification and location from each fence with bicycle flows are provided with the HDBSCAN clustering method. The evaluation framework, covering DBS flows and the parking demand density, is proposed to assess the characteristics of overload fences. Finally, a DBS dynamic guidance method is provided to balance DBS for the tidal phenomenon with guiding users to the optimal target fence. Extensive experiments conducted on real-world DBS datasets show the effectiveness and accuracy of rebalancing the tidal phenomenon in the DBS system.

Diplodiscus japonicus and Diplodiscus mehari (Trematoda: Diplodiscidae) are two important parasites in wood frogs, which have large infection rates and essential importance of ecology, economy and society. In this study, the complete mitochondrial (mt) genomes of D. japonicus and D. mehari were sequenced, then compared with other related trematodes in the superfamily Paramphistomoidea. The complete circular mt sequence of D. japonicus and D. mehari were 14,210 bp and 14,179 bp in length, respectively. Both mt genomes comprised 36 functional subunits, consisting of 12 protein-coding genes (PCGs), two ribosomal RNA (rRNA) genes, 22 transfer RNA (tRNA) genes, and one non-coding region. The mt genes of D. japonicus and D. mehari were transcribed in the same direction, and the gene arrangements were identical to those of Paramphistomoidea trematodes. In the 12 PCGs, GTG was the most common initiation codon, whereas TAG was the most common termination codon. All tRNAs had a typical cloverleaf structure except tRNA Ser1. A comparison with related Paramphistomoidea trematode mt genomes suggested that the cox1 gene of D. mehari was the longest in these trematodes. Phylogenetic analyses revealed that Paramphistomoidea trematodes formed a monophyletic branch, Paramphistomidae and Gastrothylacidae were more closely related than Diplodiscidae. And the further analysis with Pronocephalata branch found that the flukes parasitic in amphibians (frogs) formed one group, and the flukes from ruminants (cattle, sheep, ect) formed another group. Our study demonstrated the importance of sequencing mt genomes of D. japonicus and D. mehari, which will provide significant molecular resources for further studies of Paramphistomoidea taxonomy, population genetics and systematics.

This study aimed to explore the anti-tumor effect of icaritin loading poly (lactic-co-glycolic acid) nanoparticles (refer to PLGA@Icaritin NPs) on gastric cancer (GC) cells. Transmission Electron Microscope (TEM), size distribution, zeta potential, drug-loading capability, and other physicochemical characteristics of PLGA@Icaritin NPs were carried out. Furthermore, flow cytometry, confocal laser scanning microscope (CLSM), Cell Counting Kit-8 (CCK-8), Transwell, Elisa assay and Balb/c mice were applied to explore the cellular uptake, anti-proliferation, anti-metastasis, immune response activation effects, and related anti-tumor mechanism of PLGA@Icaritin NPs in vitro and in vivo. PLGA@Icaritin NPs showed spherical shape, with appropriate particle sizes and well drug loading and releasing capacities. Flow cytometry and CLSM results indicated that PLGA@Icaritin could efficiently enter into GC cells. CCK-8 proved that PLGA@Icaritin NPs dramatically suppressed cell growth, induced Lactic dehydrogenase (LDH) leakage, arrested more GC cells at G2 phase, and inhibited the invasion and metastasis of GC cells, compared to free icaritin. In addition, PLGA@Icaritin could help generate dozens of reactive oxygen species (ROS) within GC cells, following by significant mitochondrial membrane potentials (MMPs) loss and excessive production of oxidative-mitochondrial DNA (Ox-mitoDNA). Since that, Ox-mitoDNA further activated the releasing of damage associated molecular pattern molecules (DAMPs), and finally led to immunogenic cell death (ICD). Our in vivo data also elaborated that PLGA@Icaritin exerted a powerful inhibitory effect (∼80%), compared to free icaritin (∼60%). Most importantly, our results demonstrated that PLGA@Icaritin could activate the anti-tumor immunity via recruitment of infiltrating CD4+ cells, CD8+ T cells and increased secretion of cytokine immune factors, including interferon-γ (IFN-γ) tumor necrosis factor-α (TNF-α) and interleukin-1 (IL-1).++ Our findings validate that the successful design of PLGA@Icaritin, which can effectively active ICD and facilitate tumor recruitment in GC through inducing mitoDNA oxidative damage.

The application of variable buoyancy systems (VBS) in autonomous underwater vehicles (AUVs) have greatly improved their maneuverability, endurance, adaptability to environmental change and ability to accomplish a variety of tasks. As there are various types of AUVs, the types of VBS are also different. Thus, it is necessary to further research AUV VBS and control technology. First, the principles and characteristics of different types of AUV VBS are explained in detail, and their applicable scenarios summarized. Typical applications of VBS in AUV maneuvering control are then introduced, including balancing, hovering, landing and bottoming. Next, the existing buoyancy adjustment technology, buoyancy observation technology and cooperative maneuvering control technology of AUV VBS are reviewed and evaluated. Finally, the development prospects of AUV VBS are evaluated.

While water splitting electrolysis offers an appealing means to produce H2 fuel, catalysts show sluggish reaction rate in neutral media. Here, authors utilize hydrogen spillover from oxygen-deficient tungsten oxides to Ru nanoparticles to boost the neutral-pH H2 evolution performances.

Background: Artificial intelligence (AI) and machine learning (ML) are rapidly advancing fields with increasing utility in health care. We conducted a survey to determine the perceptions of Canadian vascular surgeons toward AI/ML. Methods: An online questionnaire was distributed to 162 members of the Canadian Society for Vascular Surgery. Self-reported knowledge, attitudes, and perceptions with respect to potential applications, limitations, and facilitators of AI/ML were assessed. Results: Overall, 50 of the 162 Canadian vascular surgeons (31%) responded to the survey. Most respondents were aged 30 to 59 years (72%), male (80%), and White (67%) and practiced in academic settings (72%). One half of the participants reported that their knowledge of AI/ML was poor or very poor. Most were excited or very excited about AI/ML (66%) and were interested or very interested in learning more about the field (83.7%). The respondents believed that AI/ML would be useful or very useful for diagnosis (62%), prognosis (72%), patient selection (56%), image analysis (64%), intraoperative guidance (52%), research (88%), and education (80%). The limitations that the participants were most concerned about were errors leading to patient harm (42%), bias based on patient demographics (42%), and lack of clinician knowledge and skills in AI/ML (40%). Most were not concerned or were mildly concerned about job replacement (86%). The factors that were most important to encouraging clinicians to use AI/ML models were improvements in efficiency (88%), accurate predictions (84%), and ease of use (84%). The comments from respondents focused on the pressing need for the implementation of AI/ML in vascular surgery owing to the potential to improve care delivery. Conclusions: Canadian vascular surgeons have positive views on AI/ML and believe this technology can be applied to multiple aspects of the specialty to improve patient care, research, and education. Current self-reported knowledge is poor, although interest was expressed in learning more about the field. The facilitators and barriers to the effective use of AI/ML identified in the present study can guide future development of these tools in vascular surgery.

Subsidence prediction is essential for preventing and controlling geohazards in coal mining areas. However, the Interferometric Synthetic Aperture Radar (InSAR) technique is limited in deriving the goaf displacements with a large gradient and fast deformation rates, hindering its application for potential risk evaluation over the mining areas. In this study, we proposed a three-dimensional and full parameter inversion (TDFPI) model to derive the large-gradient subsidence and then investigate its application for building damage assessment over coal mining areas. By taking the Guotun coal mine as the case study, the TDFPI model was demonstrated to have effectively predicted the large-gradient deformation of the mining areas and successfully evaluated the house damage in Chelou village, which agrees well with our field investigations. Specifically, the predicted subsidence results were validated with high fitting accuracy against field measurements, with RMSE of 0.083 m and 0.102 m, respectively, on observation line A and line F. In addition, the classified damage levels are highly consistent with in situ field surveys for the house cracks in Chelou village, presenting its practicality and effectiveness for building damage evaluation, and thus can provide a useful tool for potential risk assessment and prevention over the mining areas.

Sulfur hexafluoride (SF6) gas is extensively utilized as an insulating and arc-quenching medium in the circuit breakers and isolating switches of electrical equipment. It effectively isolates the circuits from the atmosphere and promptly extinguishes arcs. Therefore, the issue of SF6 gas leakage poses a significant threat to the related application fields, and the detection of SF6 gas leakage becomes extremely important. Infrared imaging detection offers advantages including non-contact, high precision, and visualization. However, most existing infrared detection systems are equipped with only one filter to detect SF6 gas. The images captured contain background noise and system noise, making these systems vulnerable to interference from such noises. To address these issues, we propose a method for monitoring SF6 gas leakage based on a customized binocular imaging (CBI) system. The CBI system has two filters, greatly reducing the interference of system noise and background noise. The first filter features the absorption resonant peak of SF6 gas. The second filter is used to record background noise and system noise. One aspect to note is that, in order to avoid the interference of other gases, the central wavelength of this second filter should keep away from the absorption resonant peaks of those gases. Accordingly, the central wavelengths of our customized filters were determined as 10,630 nm and 8370 nm, respectively. Then, two cameras of the same type were separately assembled with a customized filter, and the CBI prototype was accomplished. Finally, we utilized the difference method using two infrared images captured by the CBI system, to monitor the SF6 gas leakage. The results demonstrate that our developed system achieves a high accuracy of over 99.8% in detecting SF6 gas. Furthermore, the CBI system supports a plug-and-play customization to detect various gases for different scenarios.

The particles in high-temperature and high-speed airflow in the battlefield environment will form sliding friction and wear on the aeroengine turbine blades, thus reducing the service performance of the blades. However, few studies has been reported on the tribological properties of Ni-based single crystal alloy. Accordingly, the tribological properties of Ni-based single crystal alloys with different contents of Re (0 wt%, 1.5 wt%, 2.5 wt%, 3.5 wt%, 4.5 wt% and 5.5 wt%) are investigated by tribological experiments and molecular dynamics simulations in this paper. The results of tribological experiments show that Ni-based single crystal alloy without Re exhibits the characteristics of abrasive wear and adhesive wear, while the wear state is significantly improved after adding Re element. In particular, the worn surface of Ni-based single crystal alloy containing 5.5% Re (NSCA5) is the smoothest and only a few minor defects are observed. In addition, the micro-tribological characteristics of Ni-based single crystal alloy are analyzed by molecular dynamics simulations, the results show that Re atoms can inhibit the dislocation movement and reduce the system potential energy, which enhance the stability and hardness of Ni-based single crystal alloy, thereby the wear resistance of the material are improved.

Co-contamination of arsenic and fluoride is widely distributed in groundwater. However, little is known about the interactively influence of arsenic and fluoride, especially the combined mechanism in cardiotoxicity. Cellular and animal models exposure to arsenic and fluoride were established to assess the oxidative stress and autophagy mechanism of cardiotoxic damage using the factorial design, a widely used statistical method for assessing two factor interventions. In vivo, combined exposure to high arsenic (50 mg/L) and high fluoride (100 mg/L) induced myocardial injury. The damage is accompanied by accumulation of myocardial enzyme, mitochondrial disorder, and excessive oxidative stress. Further experiment identified that arsenic and fluoride induced the accumulation of autophagosome and increased expression level of autophagy related genes during the cardiotoxicity process. These findings were further demonstrated through the in vitro model of arsenic and fluoride-treated the H9c2 cells. Additionally, combined of arsenic-fluoride exposure possesses the interactively influence on oxidative stress and autophagy, contributing to the myocardial cell toxicity. In conclusion, our data suggest that oxidative stress and autophagy are involved in the process of cardiotoxic injury, and that these indicators showed interaction effect in response to the combined exposure of arsenic and fluoride.

Background: Peripheral artery disease (PAD) involves atherosclerosis of the lower extremity arteries and is a major contributor to limb loss and death worldwide. Several studies have demonstrated that interleukins (ILs) play an important role in the development and progression of PAD; however, a comprehensive literature review has not been performed. Methods: A systematic review was conducted and reported according to PRISMA guidelines. MEDLINE was searched from inception to 5 December 2022, and all studies assessing the association between ILs and PAD were included. Results: We included 17 studies from a pool of 771 unique articles. Five pro-inflammatory ILs (IL-1β, IL-2, IL-5, IL-6, and IL-8) and one pro-atherogenic IL (IL-12) were positively correlated with PAD diagnosis and progression. In contrast, two anti-inflammatory ILs (IL-4 and IL-10) were protective against PAD diagnosis and adverse limb events. Specifically, IL-6 and IL-8 were the most strongly associated with PAD and can act as potential disease biomarkers to support the identification and treatment of PAD. Conclusions: Ongoing work to identify and validate diagnostic/prognostic inflammatory biomarkers for PAD has the potential to assist clinicians in identifying high-risk patients for further evaluation and management which could reduce the risk of adverse cardiovascular and limb events.

Background: Sarcopenia, the age-related loss of skeletal muscle mass/function, has been identified as a marker of frailty. We examined the association between sarcopenia and adverse events following transcatheter aortic valve implantation (TAVI). Methods: A retrospective cohort study was conducted at Toronto General Hospital. All patients who underwent TAVI in the time period 2007-2017 with preoperative computed tomography were included. Skeletal muscle index (SMI) was calculated radiographically using psoas muscle area at the L3 vertebral level, divided by height. Various measures of sarcopenia, including mean SMI, SMI below the sex-specific median, and SMI in the lowest sex-specific quartile were calculated. The primary outcome was postoperative adverse events, defined as a composite of in-hospital mortality and morbidity including cardiovascular, pulmonary, neurologic, access-related, and gastrointestinal complications. Univariate and multivariate logistic regression were performed to determine the association between sarcopenia and adverse events. Results: A total of 468 patients (mean age: 80.7 years) were included. Baseline comorbidity burden was high, particularly congestive heart failure (93.4%). Postoperative adverse events occurred in 62 patients (13.2%). Univariate logistic regression demonstrated that postoperative adverse events were correlated with mean SMI (odds ratio [OR] 0.81, 95% confidence interal [CI] 0.66-0.97), events were less than the SMI (OR 2.16, 95% CI 1.24-3.84), and SMI in the sex-specific lowest quartile (OR 2.34, 95% CI 1.33-4.07). On multivariate analysis, SMI in the sex-specific lowest quartile was an independent predictor of adverse events (OR 2.53, 95% CI 1.41-4.50). Conclusions: Sarcopenia defined by radiologic psoas muscle measurements was independently associated with in-hospital mortality and morbidity following TAVI. Résumé: Contexte: La sarcopénie, soit la perte de masse et de fonction des muscles squelettiques liée à l’âge, a été identifiée comme un marqueur de fragilité. Nous avons examiné l’association entre la sarcopénie et les événements indésirables suivant l’implantation valvulaire aortique par cathéter (IVAC). Méthodologie: Une étude de cohorte rétrospective a été menée au Toronto General Hospital. Tous les patients ayant subi une IVAC avec tomodensitométrie préopératoire au cours de la période 2007-2017 ont été inclus. L’indice de masse musculaire squelettique (IMMS) a été calculé par radiographie en utilisant la surface du psoas au niveau de la vertèbre L3, divisée par la taille. Diverses mesures de la sarcopénie, y compris l’IMMS moyen, l’IMMS sous la médiane selon le sexe et l’IMMS dans le quartile inférieur selon le sexe, ont été calculées. Le critère d’évaluation principal était les événements indésirables postopératoires, définis comme un critère composite comprenant la mortalité et la morbidité à l’hôpital, notamment les complications cardiovasculaires, pulmonaires, neurologiques, gastro-intestinales et liées à l’accès vasculaire. Des régressions logistiques univariée et multivariée ont été effectuées pour déterminer l’association entre la sarcopénie et les événements indésirables. Résultats: Un total de 468 patients (âge moyen : 80,7 ans) ont été inclus. Le fardeau de comorbidité au départ était élevé, en particulier pour ce qui est de l’insuffisance cardiaque congestive (93,4 %). Des événements indésirables postopératoires sont survenus chez 62 patients (13,2 %). La régression logistique univariée a montré que les événements indésirables postopératoires étaient en corrélation avec un IMMS moyen (rapport des cotes [RC] : 0,81, intervalle de confiance [IC] à 95 % : 0,66 à 0,97), un IMMS sous la médiane selon le sexe (RC : 2,16; IC à 95 % : 1,24 à 3,84) et un IMMS dans le quartile inférieur selon le sexe (RC : 2,34; IC à 95 % : 1,33 à 4,07). Lors de l’analyse multivariée, un IMMS situé dans le quartile inférieur selon le sexe était un prédicteur indépendant d’événements indésirables (RC : 2,53; IC à 95 % : 1,41 à 4,50). Conclusions: La sarcopénie définie par les mesures radiologiques du psoas était indépendamment associée à la mortalité et à la morbidité à l’hôpital à la suite d’une IVAC.

BackgroundAtmospheric fine particulate matter (PM2.5) can induce abnormal early embryo development, resulting in adverse pregnancy outcomes such as embryo damage and spontaneous abortion. The vascular remodeling of maternal-fetal interface regulated by hypoxia inducible factor-1α (HIF-1α)/vascular endothelial growth factor (VEGF) axis is a key link in early embryo development.ObjectiveTo investigate the effects of pre-pregnancy PM2.5 exposure on the uterine state of mice before conception and the vascular remodeling of maternal-fetal interface after conception, and to further explore the regulatory role of the HIF-1α/VEGF axis.MethodsForty eight-week-old C57BL/6J sexually mature female mice and several males (for mating, without any treatment) were adaptive fed for 1 week. The female mice were divided into a PM2.5 exposure group and a control group, 20 mice per group. The PM2.5 exposure group was given 3 mg·kg−1 PM2.5 suspension by nasal instillation, once every other day for four weeks; the control group were treated with the same dose of blank sampling membrane suspension. Body weight of the mice was recorded every week during the experimental period. At the end of the exposure, six mice from each group were sacrificed. Then the uterus was weighted and its organ coefficients were calculated, a histopathological morphology evaluation was conducted by HE staining, and the mRNA expressions of HIF-1α, VEGF and its receptors Flt-1 and Flk-1 in the uterus samples were further examined. The remaining 14 female mice in each group were caged with male mice overnight with a sex ratio of 2:1, then we calculated the pregnancy rate. On gestation day 10 (GD10), the female mice were decapitated and the uterus was dissected, the histopathological morphology of embryo and placenta were observed by HE staining, and the mRNA expressions of HIF-1α, VEGF and its receptors Flt-1 and Flk-1 were detected as well in the uterus samples.ResultsCompared with the control group, the pre-pregnancy PM2.5 exposure had no significant effect on body weight gain of the female mice, but decreased uterine organ coefficient, accompanied by pathological damage such as endometrium thinning as well as decreased mRNA expressions of HIF-1α, VEGF and its receptors Flt-1 and Flk-1 (all Ps

Abstract Although wind power is a promising source of renewable energy, previous studies have focused on uncovering species and abundance decreases caused by wind farms. However, very few studies focus on collision risk of onshore wind farms in relation to birds’ movements which are the important indicators for balancing wind energy development and biodiversity conservation. Here, birds’ movement were recorded by combining 15 ducks’ satellite tracking and six field surveys to assess collision risks in Yangtze River Mouth, the wintering site for migratory waterbirds along the East Asian–Australasian Flyway. It is found that distances between ducks’ locations and nearest wind turbines in middle and later wintering periods were significantly higher than during early period. Besides, ducks inside wind farm tended to fly outside turbine rotor height range (45–135 m: between lowest and highest points the rotor tips) within 300 m from the dyke where the turbines were located, thus decreasing their collision risk. Ducks also tended to fly below the minimum rotor tip height (

Abstract Machine learning (ML) is a rapidly advancing field with increasing utility in health care. We conducted a systematic review and critical appraisal of ML applications in vascular surgery. MEDLINE, Embase, and Cochrane CENTRAL were searched from inception to March 1, 2021. Study screening, data extraction, and quality assessment were performed by two independent reviewers, with a third author resolving discrepancies. All original studies reporting ML applications in vascular surgery were included. Publication trends, disease conditions, methodologies, and outcomes were summarized. Critical appraisal was conducted using the PROBAST risk-of-bias and TRIPOD reporting adherence tools. We included 212 studies from a pool of 2235 unique articles. ML techniques were used for diagnosis, prognosis, and image segmentation in carotid stenosis, aortic aneurysm/dissection, peripheral artery disease, diabetic foot ulcer, venous disease, and renal artery stenosis. The number of publications on ML in vascular surgery increased from 1 (1991–1996) to 118 (2016–2021). Most studies were retrospective and single center, with no randomized controlled trials. The median area under the receiver operating characteristic curve (AUROC) was 0.88 (range 0.61–1.00), with 79.5% [62/78] studies reporting AUROC ≥ 0.80. Out of 22 studies comparing ML techniques to existing prediction tools, clinicians, or traditional regression models, 20 performed better and 2 performed similarly. Overall, 94.8% (201/212) studies had high risk-of-bias and adherence to reporting standards was poor with a rate of 41.4%. Despite improvements over time, study quality and reporting remain inadequate. Future studies should consider standardized tools such as PROBAST and TRIPOD to improve study quality and clinical applicability.

ObjectiveAiming at solving the roll problem of the new X-rudder autonomous underwater vehicle (XAUV) during field tests, a series of anti-roll fixed depth and heading control experiments and maneuverability tests are carried out. MethodFirst, the XAUV's system structure and function are introduced, and its mathematical model is established. Second, based on the previous field test results, the roll problem of the XAUV in surface navigation is analyzed. A roll control experiment with an open-loop differential rudder angle is then carried out, and an anti-roll tracking controller is designed on the basis of feedback linearized PD control of yaw and roll, incremental feedback control of depth and constrained nonlinear programming. Finally, a series of maneuverability tests is carried out in a maneuvering basin to verify the effectiveness and functionality of the proposed method, and the maneuverability of the XAUV. ResultsThe test results show that under the same hull, the rotation diameter of the cruciform rudder is 1.2 times that of the X-rudder. Moreover, with the proposed control method, the roll angle of the XAUV can be effectively reduced to 2° when the propeller speed is 1 680 r/min, and the depth and heading control of the XAUV can be ensured at the same time. ConclusionThe X-rudder can improve the maneuverability of AUVs with its unique roll control ability. The anti-roll fixed depth and heading control strategy proposed in this paper can make full use of the maneuverability advantages of the XAUV, and realize effective roll angle control simultaneously with depth and heading control.

BackgroundLevels of inflammatory proteins and their prognostic potential have been inadequately studied in patients with peripheral artery disease (PAD). In this study, we quantified and assessed the ability of inflammatory proteins in predicting PAD-related adverse events.MethodsIn this prospective case-control study, blood samples were collected from patients without PAD (n = 202) and patients with PAD (n = 275). The PAD cohort was stratified by disease severity based on ankle brachial index (ABI): mild (n = 49), moderate (n = 164), and severe (n = 62). Patients were followed for 2 years. Plasma concentrations of 5 inflammatory proteins were measured: Alpha-2-Macroglobulin (A2M), Fetuin A, Alpha-1-Acid Glycoprotein (AGP), Serum Amyloid P component (SAP), and Adipsin. The primary outcome of our study was major adverse limb event (MALE), defined as the need for vascular intervention (open or endovascular revascularization) or major amputation. The secondary outcome was worsening PAD status, defined as a drop in ABI greater than or equal to 0.15 over the study period. Multivariable logistic regression was performed to assess the prognostic value of inflammatory proteins in predicting MALE, adjusting for confounding variables.ResultsCompared to patients without PAD, three inflammatory proteins were differentially expressed in patients with PAD (AGP, Fetuin A, and SAP). The primary outcome (MALE) and secondary outcome (worsening PAD) status were noted in 69 (25%) and 60 (22%) patients, respectively. PAD-related adverse events occurred more frequently in severe PAD patients. Based on our data, the inflammatory protein AGP was the most reliable predictor of primary and secondary outcomes. On multivariable analysis, there was a significant association between AGP and MALE in all PAD disease states [mild: adjusted HR 1.13 (95% CI 1.05–1.47), moderate: adjusted HR 1.23 (95% CI 1.16–1.73), severe: adjusted HR 1.37 (95% CI 1.25–1.85)]. High levels of AGP were associated with lower 2-year MALE-free survival in all PAD disease states [mild (64% vs. 100%, p = 0.02), moderate (64% vs. 85%, p = 0.02), severe (55% vs. 88%, p = 0.02), all PAD (62% vs. 88%, p = 0.01)].ConclusionLevels of inflammatory protein AGP may help in risk stratifying PAD patients at high risk of MALE and worsening PAD status and subsequently facilitate further vascular evaluation and initiation of aggressive medical/surgical management.

ObjectiveThe aim of this study was to test the hypothesis whether serum level of calpains could become a meaningful biomarker for diagnosis of acute lung injury (ALI) in clinical after cardiac surgery using cardiopulmonary bypass (CPB) technology.Methods and resultsSeventy consecutive adults underwent cardiac surgery with CPB were included in this prospective study. Based on the American-European Consensus Criteria (AECC), these patients were divided into ALI (n = 20, 28.57%) and non-ALI (n = 50, 71.43%) groups. Serum level of calpains in terms of calpains’ activity which was expressed as relative fluorescence unit (RFU) per microliter and measured at beginning of CPB (baseline), 1 h during CPB, end of CPB as well as 1, 12, and 24 h after CPB. Difference of serum level of calpains between two groups first appeared at the end of CPB and remained different at subsequent test points. Univariate and multivariate logistic regression analysis indicated that serum level of calpains 1 h after CPB was an independent predictor for postoperative ALI (OR 1.011, 95% CI 1.001, 1.021, p = 0.033) and correlated with a lower PaO2/FiO2 ratio in the first 2 days (The first day: r = -0.389, p < 0.001 and the second day: r = -0.320, p = 0.007) as well as longer mechanical ventilation time (r = 0.440, p < 0.001), intensive care unit (ICU) length of stay (LOS) (r = 0.419, p < 0.001) and hospital LOS (r = 0.297, p = 0.013).ConclusionElevated serum level of calpains correlate with impaired lung function and poor clinical outcomes, indicating serum level of calpains could act as a potential biomarker for postoperative ALI following CPB in adults.Clinical trial registration[https://clinicaltrials.gov/show/NCT05610475], identifier [NCT05610475].

Peripheral artery disease (PAD) is a chronic atherosclerotic disorder that involves the lower extremity arteries, manifesting in claudication, rest pain, and tissue loss [...]

This research investigates the effects of iron tailings content on the mechanical properties and durability of concrete under dry–wet cycling and negative temperature conditions (−10 °C), where iron tailings replace river sand at rates of 0%, 10%, 20%, and 30%. A variety of tests were conducted on the iron tailings concrete, including compressive strength, flexural strength, splitting tensile strength, mass loss, and relative dynamic modulus, and its pore characteristics were analyzed using low-field nuclear magnetic resonance (NMR) experiments. The results reveal that when 20% of the river sand was replaced with iron tailings, the concrete achieved optimal splitting strength, compressive strength, and flexural strength at 28 days, improving by 0.46 MPa, 3.14 MPa, and 0.41 MPa, respectively, compared to conventional concrete. Furthermore, the concrete containing this proportion of iron tailings demonstrated superior mechanical properties and durability in both negative temperature conditions and dry–wet cycling experiments. Due to the excellent physical and chemical properties of iron tailings, they enhance the performance of concrete when incorporated in appropriate quantities. The fine granularity of iron tailings helps to compensate for the granularity defects in concrete aggregates by filling internal voids, optimizing the pore structure, and improving the concrete’s density and integrity. This enhances the concrete’s mechanical properties and its resistance to external solutions and harmful ion penetration. Additionally, the active substances in iron tailings promote the hydration reaction of cement, leading to the formation of an increased amount of C-S-H gel and other hydration products in the cement system.

Environmental sanitation of maternal contact during pregnancy is extremely important for the development of different fetal tissues and organs. In particular, during early pregnancy, any adverse exposure may cause abnormal fetal growth or inhibit the development of embryogenic organs. The potential risks of phthalate exposure, which affects the development of humans and animals, are becoming a serious concern worldwide. However, the specific molecular mechanism of di-(2-ethylhexyl) phthalate (DEHP)-induced cardiotoxicity in fetal mice remains unclear. In this study, animal models of DEHP gavage at concentrations of 250, 500, and 1000 mg/kg/day within 8.5–18.5 days of pregnancy were established. The cell proliferation, survival, and apoptosis rates were evaluated using CCK8, EdU, TUNEL and flow cytometry. The molecular mechanism was assessed via transcriptome sequencing, immunohistochemistry, immunofluorescence, reverse transcription-quantitative polymerase chain reaction, and Western blot analysis. In vivo, DEHP increased apoptosis, decreased Ki67 and CD31 expression, reduced heart weight and area, slowed down myocardial sarcomere development, and caused cardiac septal defect in fetal mice heart. Transcriptome sequencing showed that DEHP decreased NRG1 expression and downregulated the ErbB2/ErbB4-PI3K/AKT signaling pathway-related target genes. In vitro, primary cardiomyocytes were cultured with DEHP at a concentration of 150 μg/mL combined with ErbB inhibitor (AG1478, 10 μmol/L) and/or NRG1 protein (100 ng/mL) for 72 h. After DEHP intervention, the expression of NRG1 and the phosphorylation level of ErbB2, ErbB4, PI3K, and AKT decreased, and the apoptosis-related protein levels increased. Moreover, the apoptosis rate increased. After adding exogenous NRG1, the phosphorylation level of the NRG1/ERbB2/ERbB4-PI3K/AKT pathway increased, and the apoptosis-related protein levels decreased. Further, the apoptosis rate reduced. Interestingly, after exposure to DEHP and AG1478 + NRG1, the anti-apoptotic effect of NRG1 and cardiomyocyte proliferation decreased by inhibiting the NRG1/ERbB2/ERbB4-PI3K/AKT pathway. Hence, the NRG1-dependent regulation of the ERbB2/ERbB4-PI3K/AKT signaling pathway may be a key mechanism of DEHP-induced myocardial cytotoxicity.