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Abstract Detection and anti‐detection with multispectral camouflage are of pivotal importance, while suffer from significant challenges due to the inherent contradiction between detection and anti‐detection and conflict microwave and infrared (IR) stealth mechanisms. Here, a strategy is proposed to asymmetrically control transmitted microwave wavefront under radar‐IR bi‐stealth scheme using composite metasurface. It is engineered composed of infrared stealth layer (IRSL), microwave absorbing layer (MAL), and asymmetric microwave transmissive structure (AMTS) with polarization conversion from top to bottom. Therein, IR emissivity, microwave reflectivity, and transmissivity are simultaneously modulated by elaborately designing the filling ratio of ITO square patches on IRSL, which ensures both efficient microwave transmission and IR camouflage. Furthermore, full‐polarized backward microwave stealth is achieved on MAL by transmitting and absorbing microwaves under x‐ and y‐ polarization, respectively, while forward wavefront is controlled by precise curvature phase compensation on AMTS according to ray‐tracing technology. For verification, a proof‐of‐concept metadevice is numerically and experimentally characterized. Both results coincide well, demonstrating spiral detective wavefront manipulation under y‐polarized forward wave excitation while effective reduction of radar cross section within 8–18 GHz and low IR emissivity (

Greedy search (GS) or exhaustive search plays a crucial role in decision trees and their various extensions. We introduce an alternative splitting method called smooth sigmoid surrogate (SSS) in which the indicator threshold function used in GS is approximated by a smooth sigmoid function. This approach allows for parametric smoothing or regularization of the erratic and discrete GS process, making it more effective in identifying the true cutoff point, particularly in the presence of weak signals, as well as less prone to the inherent end-cut preference problem. Additionally, SSS provides a convenient means of evaluating the best split by referencing a parametric nonlinear model. Moreover, in many variants of recursive partitioning, SSS can be reformulated as a one-dimensional smooth optimization problem, rendering it computationally more efficient than GS. Extensive simulation studies and real data examples are provided to evaluate and demonstrate its effectiveness.

Background: Clear cell renal cell carcinoma (ccRCC) comprises the majority, approximately 70–80%, of renal cancer cases and often remains asymptomatic until incidentally detected during unrelated abdominal imaging or at advanced stages. Currently, standardized screening tests for renal cancer are lacking, which presents challenges in disease management and improving patient outcomes. This study aimed to identify ccRCC-specific volatile organic compounds (VOCs) in the urine of ccRCC-positive patients and develop a urinary VOC-based diagnostic model. Methods: This study involved 233 pretreatment ccRCC patients and 43 healthy individuals. VOC analysis utilized stir-bar sorptive extraction coupled with thermal desorption gas chromatography/mass spectrometry (SBSE-TD-GC/MS). A ccRCC diagnostic model was established via logistic regression, trained on 163 ccRCC cases versus 31 controls, and validated with 70 ccRCC cases versus 12 controls, resulting in a ccRCC diagnostic model involving 24 VOC markers. Results: The findings demonstrated promising diagnostic efficacy, with an Area Under the Curve (AUC) of 0.94, 86% sensitivity, and 92% specificity. Conclusions: This study highlights the feasibility of using urine as a reliable biospecimen for identifying VOC biomarkers in ccRCC. While further validation in larger cohorts is necessary, this study’s capability to differentiate between ccRCC and control groups, despite sample size limitations, holds significant promise.

The lack of accuracy in the current prostate specific antigen (PSA) test for prostate cancer (PCa) screening causes around 60-75% of unnecessary prostate biopsies. Therefore, alternative diagnostic methods that have better accuracy and can prevent over-diagnosis of PCa are needed. Researchers have examined various potential biomarkers for PCa, and of those fatty acids (FAs) markers have received special attention due to their role in cancer metabolomics. It has been noted that PCa metabolism prefers FAs over glucose substrates for continued rapid proliferation. Hence, we proposed using a urinary FAs based model as a non-invasive alternative for PCa detection. Urine samples collected from 334 biopsy-designated PCa positive and 232 biopsy-designated PCa negative subjects were analyzed for FAs and lipid related compounds by stir bar sorptive extraction coupled with gas chromatography/mass spectrometry (SBSE-GC/MS). The dataset was split into the training (70%) and testing (30%) sets to develop and validate logit models and repeated for 100 runs of random data partitioning. Over the 100 runs, we confirmed the stability of the models and obtained optimal tuning parameters for developing the final FA based model. A PSA model using the values of the patients' PSA test results was constructed with the same cohort for the purpose of comparing the performances of the FA model against PSA test. The FA final model selected 20 FAs and rendered an AUC of 0.71 (95% CI = 0.67-0.75, sensitivity = 0.48, and specificity = 0.83). In comparison, the PSA model performed with an AUC of 0.51 (95% CI = 0.46-0.66, sensitivity = 0.44, and specificity = 0.71). The study supports the potential use of urinary FAs as a stable and non-invasive alternative test for PCa diagnosis.

Abstract Background Sub-therapeutic antibiotics are widely used as growth promoters in the poultry industry; however, the resulting antibiotic resistance threatens public health. A plant-derived growth promoter, Macleaya cordata extract (MCE), with effective ingredients of benzylisoquinoline alkaloids, is a potential alternative to antibiotic growth promoters. Altered intestinal microbiota play important roles in growth promotion, but the underlying mechanism remains unknown. Results We generated 1.64 terabases of metagenomic data from 495 chicken intestinal digesta samples and constructed a comprehensive chicken gut microbial gene catalog (9.04 million genes), which is also the first gene catalog of an animal’s gut microbiome that covers all intestinal compartments. Then, we identified the distinctive characteristics and temporal changes in the foregut and hindgut microbiota. Next, we assessed the impact of MCE on chickens and gut microbiota. Chickens fed with MCE had improved growth performance, and major microbial changes were confined to the foregut, with the predominant role of Lactobacillus being enhanced, and the amino acids, vitamins, and secondary bile acids biosynthesis pathways being upregulated, but lacked the accumulation of antibiotic-resistance genes. In comparison, treatment with chlortetracycline similarly enriched some biosynthesis pathways of nutrients in the foregut microbiota, but elicited an increase in antibiotic-producing bacteria and antibiotic-resistance genes. Conclusion The reference gene catalog of the chicken gut microbiome is an important supplement to animal gut metagenomes. Metagenomic analysis provides insights into the growth-promoting mechanism of MCE, and underscored the importance of utilizing safe and effective growth promoters.

Multivariate survival trees require few statistical assumptions, are easy to interpret, and provide meaningful diagnosis and prediction rules. Trees can handle a large number of predictors with mixed types and do not require predictor variable transformation or selection. These are useful features in many application fields and are often required in the current era of big data. The aim of this article is to introduce the R package MST. This package constructs multivariate survival trees using marginal model and frailty model based approaches. It allows the user to control and see how the trees are constructed. The package can also simulate high-dimensional, multivariate survival data from marginal and frailty models.

The purpose of this study was to determine whether maternal mental and physical health is associated with maternal testosterone and cortisol levels, parenting of very low birth weight infants, physical exercise, and White vs non-White race. A total of 40 mothers of very low birth weight infants were recruited from a neonatal intensive care unit at a University Hospital in the Southeast United States. Data were collected through a review of medical records, standardized questionnaires, and biochemical measurement. Maternal mental and physical health status using questionnaires as well as maternal testosterone and cortisol levels using an enzyme immunoassay were measured four times (birth, 40 weeks postmenstrual age [PMA], and 6 and 12 months [age of infant, corrected age]). General linear models showed that higher testosterone levels were associated with greater depressive symptoms, stress, and poorer physical health at 40 weeks PMA, and at 6 and 12 months. High cortisol levels were associated with greater anxiety at 40 weeks PMA; however, with better mental and physical health at 40 weeks PMA, and 6 and 12 months. Physical activity was associated with lower maternal perceived stress at 12 months. Maternal health did not differ by race, except anxiety, which was higher in White than non-White mothers after birth. As very low birth weight infants grew up, maternal physical health improved but mental health deteriorated. Testosterone and cortisol levels were found to be positively correlated in women but testosterone was more predictive of maternal mental and physical health than cortisol. Indeed testosterone consistently showed its associations with maternal health. Maternal stress might be improved through regular physical exercise.

A facile method for the preparation of microwave absorbers with low density, high microwave absorptivity, and broad band is of paramount importance to the progress in practical application. Herein, commonly-used metal organic frameworks (MOFs) prepared just by mechanical stirring in methanol at room temperature were chosen as sacrificial templates to synthesize porous carbon composites with tunable dielectric and magnetic properties. With the replacement of Co atoms on the surface of zeolitic imidazolate framework-67 (ZIF-67) by Zn atoms, a Co-doped porous carbon composite with a low-dielectric amorphous carbon/Zn shell was constructed after annealing, leading to excellent impedance matching condition. Consequently, the as-obtained composite (Co/C@C-800) shows marvelous microwave absorption properties with an absorption capacity of −43.97 dB and a corresponding effective absorption bandwidth of 4.1 GHz, far exceeding that of the traditional porous carbon and composites directly derived from ZIF-67. The results provide a convenient way to modify MOFs for enhanced microwave absorption materials from the synergy of dielectric and magnetic losses.

We proposed a statistical method to construct simultaneous confidence intervals on all linear combinations of means without assuming equal variance where the classical Scheffé's simultaneous confidence intervals no longer preserve the familywise error rate (FWER). The proposed method is useful when the number of comparisons on linear combinations of means is extremely large. The FWERs for proposed simultaneous confidence intervals under various configurations of mean variances are assessed through simulations and are found to preserve the predefined nominal level very well. An example of pairwise comparisons on heteroscedastic means is given to illustrate the proposed method.

Developing lightweight polymer-based composite materials with electromagnetic (EM) wave absorption and mechanical load-bearing properties is urgent for application in complex environments. Herein, lowcost two-dimensional graphite nanosheets (GNS) were utilized as the functional filler phase, and GNS/polyvinylidene fluoride (PVDF) composite foams were fabricated using the ice dissolution and normal pressure drying method. The foam exhibits a directionally aligned structure induced by the temperature field. Ice dissolution of strong polarity DMSO is achieved through solvent exchange between it and water. Furthermore, the EM wave absorption and compression properties can be adjusted by varying the ratio of GNS to PVDF. The maximum reflection loss reaches -57.68 dB at a frequency of 10.64 GHz and a thickness of 2.7 mm, with an impressive effective absorption bandwidth of 6.86 GHz, outperforming most reported absorptive materials. It demonstrates a maximum compression strength of 300.9 kPa at a deformation of 15%. Therefore, the foam not only has excellent EM wave absorption capabilities but also possesses strong compression load-bearing capacity, providing a new perspective for the design of structurally functionalized composite materials. [ABSTRACT FROM AUTHOR]

In randomized controlled trials, individual subjects experiencing recurrent events may display heterogeneous treatment effects. That is, certain subjects might experience beneficial effects, while others might observe negligible improvements or even encounter detrimental effects. To identify subgroups with heterogeneous treatment effects, an interaction survival tree approach is developed in this paper. The Classification and Regression Tree (CART) methodology (Breiman et al., 1984) is inherited to recursively partition the data into subsets that show the greatest interaction with the treatment. The heterogeneity of treatment effects is assessed through Cox's proportional hazards model, with a frailty term to account for the correlation among recurrent events on each subject. A simulation study is conducted for evaluating the performance of the proposed method. Additionally, the method is applied to identify subgroups from a randomized, double-blind, placebo-controlled study for chronic granulomatous disease. R implementation code is publicly available on GitHub at the following URL: https://github.com/xgsu/IT-Frailty. [ABSTRACT FROM AUTHOR]

This study focuses on the fabrication of SiCp/A356 aluminum matrix composites (AMCs) through stir casting and hot rolling, with the objective of investigating the effects of reduction on microstructural evolution and mechanical properties of SiCp/A356 AMCs. The composites were subjected to hot rolling at 500 °C for varying reduction levels of 30%, 50%, 70%, and 90%. As the reduction increased to 70%, the size of α-Al grains and SiC particle clusters increased. However, further reduction to 90% resulted in the flattening and elongation of α-Al grains, the dispersion of SiC particles into the grains, and a more uniform distribution of SiC particles. The relationship between reduction and SiC particle distribution was established. The ultimate tensile strength (UTS) and yield strength (YS) of SiCp/A356 AMCs showed a gradual increase with increasing reduction. The rolled composite with a 90% reduction exhibited the optimal combination of UTS, YS, and elongation (EL) values. Besides, the strengthening mechanisms were discussed and the dislocation strengthening has a significant contribution to the improvement of YS.

Abstract Development of large-scale alkaline seawater electrolysis requires robust and corrosion-resistant anodes. Here we propose engineering NiFe layered double hydroxide (LDH)-based anodes by incorporating a series of anions into the LDH interlayers. The most optimal NiFe LDH anode with intercalated phosphates demonstrates stable operation at a high current density of 1.0 A cm−2 for over 1000 hours in a 2 W-scale alkaline seawater electrolyzer (ASWE). Fundamental studies indicate that the basicity, indicated by pK a values, of the intercalated anions in NiFe LDH governs its oxygen evolution reaction activity and corrosion resistance. Highly basic anions (i.e., phosphates) securely anchor Fe sites and facilitate proton transfer to boost both durability and activity. Notably, we demonstrate the proof-of-concept for the NiFe anode in an industrial 1 kW-scale ASWE stack (1,081.2 cm2 anode area in total). This unit achieves a stable operating current density of 0.5 A cm−2 at about 2.0 V, twice that of the commercial alkaline pure water electrolyzer, contributing to an economically competitive hydrogen production cost of US$ 1.96 kgH2 −1.

Abstract This study aimed to preliminarily develop machine learning (ML) models capable of predicting the risk of device-associated infection and 30-day outcomes following invasive device procedures in intensive care unit (ICU) patients. The study utilized data from 8574 ICU patients who underwent invasive procedures, sourced from the Medical Information Mart for Intensive Care (MIMIC)-IV version 2.2 database. Patients were allocated into training and validation datasets in a 7:3 ratio. Seven ML models were employed for predicting device-associated infections, while five models were used for predicting 30-day survival outcomes. Model performance was primarily evaluated using the receiver operating characteristic (ROC) curve for infection prediction and the survival model’s concordance index (C-index). Top-performing models progressively reduced the number of variables based on their importance, thereby optimizing practical utility. The inclusion of all variables demonstrated that extreme gradient boosting (XGBoost) and extra survival trees (EST) models yielded superior discriminatory performance. Notably, when restricted to the top 10 variables, both models maintained performance levels comparable to when all variables were included. In the validation cohort, the XGBoost model, with the top 10 variables, achieved an area under the curve (AUC) of 0.810 (95% CI 0.808–0.812), an area under the precision-recall curve (AUPRC) of 0.226 (95% CI 0.222–0.230), and a Brier score (BS) of 0.053 (95% CI 0.053–0.054). The EST model, with the top 10 variables, reported a C-index of 0.756 (95% CI 0.754–0.757), a time-dependent AUC of 0.759 (95% CI 0.763–0.775), and an integrated Brier score (IBS) of 0.087 (95% CI 0.087–0.087). Both models are accessible via a web application. The internally evaluated XGBoost and EST models demonstrated exceptional predictive accuracy for device-associated infection risks and 30-day survival outcomes post-invasive procedures in ICU patients. Further validation is required to confirm the clinical utility of these two models in future studies.

Abstract Background For acute type A aortic dissection involving the aortic root with root diameter no more than 45 mm, there are various aortic root repair techniques. In this study, a novel surgical technique using a pericardial autograft for aortic root repair was introduced. We described its surgical steps in detail and compare its clinical outcomes with direct suture technique. Methods Between July 2017 and August 2022, 95 patients with acute type A aortic dissection who underwent aortic root repair were enrolled, including aortic root repair using pericardial autograft (group A, n = 49) or direct suture (group B, n = 46). The patient’s clinical data were retrospectively analyzed, and a 5-year follow-up was conducted. Results The 30-day mortality, re-exploration for bleeding, postoperative new-onset renal failure requiring continuous renal replacement therapy, stroke, and paraplegia occurred in 3%, 4%, 11%, 5%, and 2% of the overall patients, respectively. There was no significant difference in the 30-day mortality and complication rate between the two groups. The 30-day mortality and re-exploration for bleeding marked the primary endpoint events. Logistic regression analysis indicated that there was a significant correlation between the primary endpoint events and surgical technique (odds ratio, 0.002; 95% confidence interval, 0-0.159; P = 0.026). The aortic valve insufficiency of the two groups were significantly improved after operation (group A, P

The multispectral thermal imager is a cutting-edge tool for the real-time measurement of high-temperature and transient-temperature fields. It can achieve high-precision temperature distribution measurements in complex scenes by acquiring multi-spectral radiation information. However, the existing research mainly focuses on the temperature measurement function, and there is little exploration of its potential application. In this paper, the method of measuring the distance of a high-temperature target based on a multispectral thermal imager is proposed and verified for the first time, which solves the problem that the traditional ranging model cannot be accurately measured in high-temperature environments. By constructing the theoretical model of the multi-aperture optical splitting system, the internal relationship between temperature field pixel migration and target distance is analyzed, and the feasibility and applicability of the method is verified by experiments. The results show that the multispectral thermal imager can overcome the interference of high-temperature radiation to traditional ranging technology, realize high-precision temperature measurement, and obtain the target distance information simultaneously. The measurement error of 300 m is 12.09%, which can be applied to the real-time measurement of the flame temperature field.

Rolling bearings are essential transmission and support components in aircraft engines, playing a critical role in ensuring their safe and stable operation. Rolling bearing faults have a significant impact and should not be ignored. The effective diagnosis of bearing faults has always been a critical requirement for ensuring reliable operation. With the increasing demands of modern manufacturing to reduce costs and improve quality, the development of advanced bearing fault detection methods has become indispensable. This paper presents the brief review of recent trends in research on bearing failure modes, bearing fault detection and diagnosis methods, and development trends and prospects. This article provides a comprehensive review of the existing fault diagnosis methods for rolling bearings in four aspects: the integration of advanced sensor technology and advanced data processing technology, multimodal fusion, intelligent detection, and real-time monitoring. It discusses methods based on vibration analysis, acoustic methods, current-based methods, electromagnetic methods, infrared methods, radiographic methods, visual methods, and intelligent detection methods. This study reveals that the application of intelligent detection technology, multimodal fusion detection technology, and real-time online monitoring technology has achieved favorable results. In the future, bearing fault detection will develop in a more intelligent, integrated, and real-time direction.

The problem is that existing aircraft detection datasets rarely simultaneously consider the diversity of target features and the complexity of environmental factors, which has become an important factor restricting the effectiveness and reliability of aircraft detection algorithms. Although a large amount of research has been devoted to breaking through few-sample-driven aircraft detection technology, most algorithms still struggle to effectively solve the problems of missed target detection and false alarms caused by numerous environmental interferences in bird-eye optical remote sensing scenes. To further aircraft detection research, we have established a new dataset, Aircraft Detection in Complex Optical Scene (ADCOS), sourced from various platforms including Google Earth, Microsoft Map, Worldview-3, Pleiades, Ikonos, Orbview-3, and Jilin-1 satellites. It integrates 3903 meticulously chosen images of over 400 famous airports worldwide, containing 33,831 annotated instances employing the oriented bounding box (OBB) format. Notably, this dataset encompasses a wide range of various targets characteristics including multi-scale, multi-direction, multi-type, multi-state, and dense arrangement, along with complex relationships between targets and backgrounds like cluttered backgrounds, low contrast, shadows, and occlusion interference conditions. Furthermore, we evaluated nine representative detection algorithms on the ADCOS dataset, establishing a performance benchmark for subsequent algorithm optimization. The latest dataset will soon be available on the Github website.

A study proposes a data-driven tree method called 'treed variance' (TV) to model heteroscedasticity in linear regression. Results show that the proposed method provides not only a piecewise constant modeling of the error variance, but also facilitates a natural check of homoscedasticity.

Ship identification in optical remote sensing images is essential for a wide range of civil and military applications, including maritime rescue, port management, and sea area surveillance. However, current studies focus mainly on ship detection or coarse-grained ship size identification, rather than fine-grained type identification. Moreover, interference from clouds and port facilities as well as complex conditions such as occlusion and shadows increase the difficulty of ship type identification. To address these problems, we propose a novel ship identification method by employing adjacent-branched saliency filtering and prior representation-based classification strategies, which achieves high-precision type recognition performance for large and medium-sized ships under complex environmental interference conditions. In the candidate region extraction stage, a multiscale feature aggregation structure that utilizes feature map fusion in adjacent layers and receptive field mining within the same extraction branch is presented, providing fine representation of the location and edge characteristics of ship targets in complex scenes. In the classification stage, the low-rank term describing interclass differences and the graph-based regularization term describing intraclass differences are added to the representation model as prior constraints, which can correctly classify ships in the presence of complex environmental interference such as occlusion and shadow. Experimental results on two high-quality ship datasets indicate that the proposed method realizes state-of-the-art identification performance compared with benchmark methods.

The forest experience is good for people’s physical and mental health. However, few studies on the effects of pure forest based on the duration and way of experience on people’s physical and mental recovery. In this study, we took 180 first-year college students as research objects and conducted experiments in Pinus sylvestris and Betula platyphylla and the control group of grass plot. The changes of physiological and psychological indexes of the subjects were compared by two perception methods (onsite perception, video perception) and three perception duration (10 min, 20 min, 30 min). The results indicated that: (1) Differences between the two pure forests were mainly reflected in short-term recovery of diastolic blood pressure (DBP) and long-term recovery of total mood disorder (TMD). (2) Video perception was more conducive to short-term recovery of systolic blood pressure (SBP) and diastolic blood pressure (DBP). (3) Viewing the Pinus sylvestris for 20 min in different ways was the best way to relieve stress. It is suggested that, Pinus sylvestris can be used as the rehabilitation perception material, and reasonable path length or perception time can be selected for landscape construction in future. These results can provide scientific reference for landscape design based on forest health and environmental perception.

Abstract Background To introduce a new and simple classification and management of coronary artery involvement in aortic dissection and report results. Methods Coronary artery involvement was classified into two types according to the integrity of coronary intima: simple lesion (type S) and complex lesion (type C). Complex lesions were treated by CABG and simple lesions were treated by ostial repair or reimplantation. Data were collected and analyzed retrospectively. Results From January 2010 to December 2019, 267 consecutive patients were enrolled in the study, and among them complex lesions occurred in 27 patients (11.1%) and simple lesions was found in 240 patients(89.9%). Eleven untreated vessels with simple lesion were found to be involved again in the same operation and treated by CABG. The two type groups had comparable operative mortality (type S vs. type C, 9.6% vs. 18.5%, P = 0.28). 221 patients received follow-up with a median duration of 52 months. The overall survival rates at 1, 5, and 10 years postoperatively were 88.9%, 85.7%, and 79.8% in type S group and 79.2%, 79.2%, and 79.2% in type C group, respectively (P = 0.47). For the patients who received CABG and survived at discharge, radiographic follow-up with a median duration of 28 (IQR 7-55.5) months showed the freedom from occlusion of vein graft at 1, 5, and 10 years postoperatively were 87.5%, 70.0%, 28.0%. Conclusions According to the new classification, two types of lesions could be treated by corresponding methods with satisfactory early and long-term results. Unrepaired coronary artery was at a risk of re-involvement. Vein graft onto arteries without atherosclerosis still had a high occlusion rate.

Abstract Aims Our previous studies suggested that the complement system was critical in the prognosis of arrhythmogenic right ventricular cardiomyopathy (ARVC). The acylation‐stimulating protein (ASP), generated through the alternate complement pathway, was reported to regulate lipogenesis and triglyceride storage. This study aimed to investigate the role of ASP in predicting adverse cardiac events in an ARVC cohort. Methods and results We enrolled 111 ARVC patients and 106 healthy volunteers, and measured their plasma ASP levels using enzyme‐linked immunosorbent assays. Plasma ASP levels were significantly higher in the ARVC patients than in the healthy controls (2325.22 ± 20.08 vs. 2189.75 ± 15.55, P

This paper introduces an innovative differential sampling technique for calibrating AC waveforms, leveraging a commercially available 16-bit digital-to-analog converter (DAC) as the reference standard. The novelty of this approach lies in its enhanced stability over traditional direct sampling methods, especially as the frequency of the AC waveform increases. Notably, this technique provides a cost-effective sampler alternative to the differential sampling methods that rely on a programmable Josephson voltage standard (PJVS). A critical aspect of this methodology is the precise measurement of the DAC’s output voltage, for which a static measurement strategy is adopted to utilize the exceptional linearity and transfer accuracy of the Keysight 3458A (Santa Rosa, CA, USA) in its standard DCV mode. The differential sampling method has demonstrated good accuracy, achieving a near 1 µV/V agreement with a pulse-driven AC Josephson voltage standard (ACJVS) across a 40 Hz to 200 Hz frequency range. The method attained an expanded uncertainty (k = 2) of 1 part in 106 while measuring a 0.707107 VRMS sine wave at 50 Hz, showcasing its efficacy in precise AC waveform calibration.

Abstract Objective One-staged surgical treatment of aortic coarctation combined with cardiac anomalies is challenging. We aim to evaluate the feasibility of bilateral aortofemoral bypass technique in one-staged surgery treating coractation by comparing surgical outcomes with catheter intervention plus stent (hybrid). Methods Between January 2012 and December 2017, 50 patients underwent one-staged surgical procedures to treat coarctation and repair concomitant cardiac anomalies, like aortic root dilatation, cardiac valvular disease and so on. Among them, 30 patients underwent bilateral aortofemoral bypass and 20 patients underwent hybrid procedure to treat coarctation. We retrospectively analyzed the data of these patients and compared the early and late results. Results All the baseline clinical characteristics were comparable between groups except that the mean age of bypass group was 39.5 ± 14.0 years which was older than hybrid group (27.9 ± 8.5 years, P = 0.002). Technical success was achieved in all patients, with no hospital death or other severe complications. Immediately after surgery, in bypass and hybrid group, the mean upper-limb systolic blood pressure decreased from 159.4 to 119.7 mmHg and 148.4 to 111.6 mmHg, the median peak systolic gradient decreased from 68.0 to 10 mmHg and 46.5 to 10 mmHg respectively (P = 0.09). And the mean upper-lower limbs gradient decreased from 21.7 to 5.9 mmHg and 21.0 to 2.7 mmHg respectively (P = 0.104). The mean follow-up time was 76.92 ± 18.7 in bypass group and 85.4 ± 20.6 months in hybrid group. There were 4 late deaths in bypass group (one died of gastrointestinal bleeding, one died of pulmonary embolism and the other two died of heart failure caused by mechanical prosthetic valve dysfunction). The follow-up peak systolic gradient and other blood pressure parameters showed stable and no differences between two groups. Conclusions The bilateral aortofemoral bypass surgery is a safe and effective method which can be used in one-staged surgical strategy to treat coarctation complicated by cardiac anomalies and can be an alternative to the hybrid method.

Squamous cell carcinomas are an aggressive cancer type which can occur in multiple organ systems. Here, the authors analyse the proteome of SCC cancers from 17 organs and show commonly dysregulated proteins independent of location.

Abstract Cardiovascular diseases are the most common cause of death globally. Accurately modeling cardiac homeostasis, dysfunction, and drug response lies at the heart of cardiac research. Adult human primary cardiomyocytes (hPCMs) are a promising cellular model, but unstable isolation efficiency and quality, rapid cell death in culture, and unknown response to cryopreservation prevent them from becoming a reliable and flexible in vitro cardiac model. Combing the use of a reversible inhibitor of myosin II ATPase, (-)-blebbistatin (Bleb), and multiple optimization steps of the isolation procedure, we achieved a 2.74-fold increase in cell viability over traditional methods, accompanied by better cellular morphology, minimally perturbed gene expression, intact electrophysiology, and normal neurohormonal signaling. Further optimization of culture conditions established a method that was capable of maintaining optimal cell viability, morphology, and mitochondrial respiration for at least 7 days. Most importantly, we successfully cryopreserved hPCMs, which were structurally, molecularly, and functionally intact after undergoing the freeze-thaw cycle. hPCMs demonstrated greater sensitivity towards a set of cardiotoxic drugs, compared to human-induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs). Further dissection of cardiomyocyte drug response at both the population and single-cell transcriptomic level revealed that hPCM responses were more pronouncedly enriched in cardiac function, whereas hiPSC-CMs responses reflected cardiac development. Together, we established a full set of methodologies for the efficient isolation and prolonged maintenance of functional primary adult human cardiomyocytes in vitro, unlocking their potential as a cellular model for cardiovascular research, drug discovery, and safety pharmacology.

Experiences in natural environments can enhance human wellbeing and promote the recovery of physiological and psychological health. During the COVID-19 pandemic, university students' activity off-campus was limited, thus, the campus environment was particularly important for the recovery of students' physiological and psychological health. Although the benefits of sustained natural exposure are obvious for people's physiological and psychological health, the effects of brief exposure on physiological and psychological are unclear. In the present study, four types of campus environments, including square space, dense forest space, sparse forest space, and waterfront space, were selected to explore the transient recovery effects of different types of campus environments. Sixty university students were recruited, measuring their systolic blood pressure, diastolic blood pressure, and heart rate as physical parameters to assess stress recovery. Respondents also reported scores about their personal feelings in questionnaires to evaluate their psychological states. Both physiological and psychological indicators responded to the brief natural exposure (5 min), and physiological and psychological health was restored. However, only the recovery amounts of psychological indicators were significantly different in waterfront space, dense forest space, and sparse forest space. These results indicate that being compare with other spaces, the brief exposure in the waterfront space was the most beneficial to students' psychological health recovery. This recovery was attributed to the great role played by the sense of escape, but after the brief exposure, the attraction and compatibility of the environment would hinder the psychological health recovery. In conclusion, according to tests on both physiological and psychological aspects, the waterfront environment on campus is the best choice for students' transient health recovery.

BackgroundFrozen elephant trunk technique (FET) has been proven to provide an excellent landing zone for second-stage thoracoabdominal (TA) aortic repair. The aim of this study was to evaluate the impact of FET in TA aortic repair with normothermic iliac perfusion.MethodsFrom January 2008 to December 2019, 144 patients undergoing TA repair with normothermic iliac perfusion were enrolled in this study. Early and mid-term outcomes of patients with previous FET implantation (group A, n = 62) were compared with patients without previous FET implantation (group B, n = 82). The logistic regression analysis was performed to investigate the risk factors for adverse events, which were defined as early death, permanent stroke, permanent paraplegia, or permanent renal failure necessitating dialysis.ResultsThe proximal aortic clamp time and operating time was 14.26 ± 5.57 min and 357.40 ± 94.51 respectively in group A, which were both significantly shorter than that in group B (18.67 ± 5.24 min and 18.67 ± 5.24 min). The incidence of adverse event was significantly lower in group A than that in group B (9.7% vs. 25.6%, P = 0.027). There was no significant difference between two groups with regard to other complications or late outcomes. In addition, age >50 years, a Ccr

Summary: Mass spectrometry-based proteomic technology has greatly improved and has been widely applied in various biological science fields. However, proteome-wide accurate quantification of proteins in signaling pathways remains challenging. Here, we report a genome-wide amino acid coding-decoding quantitative proteomic (GwAAP) system to facilitate precise proteome quantification. For each protein, a unique code peptide was assigned and incorporated into the N-terminus of the targeted protein and used for identification and quantification. As a proof of principle, we systematically tagged 40 yeast proteins with codes and employed mass spectrometry to decode. We successfully recovered all 40 code peptides with a large and consistent quantitative dynamic range (CV slope 0.8). We further verified the alteration of the glucose and galactose metabolism pathways in yeast under different carbon source conditions. The GwAAP system could potentially provide a strategy to achieve absolute quantification of the entire yeast proteome without bias.

We propose a sparse estimation method, termed MIC (Minimum approximated Information Criterion), for generalized linear models (GLM) in fixed dimensions. What is essentially involved in MIC is the approximation of the ℓ0-norm by a continuous unit dent function. A reparameterization step is devised to enforce sparsity in parameter estimates while maintaining the smoothness of the objective function. MIC yields superior performance in sparse estimation by optimizing the approximated information criterion without reducing the search space and is computationally advantageous since no selection of tuning parameters is required. Moreover, the reparameterization tactic leads to valid significance testing results free of post-selection inference. We explore the asymptotic properties of MIC, and illustrate its usage with simulated experiments and empirical examples. [ABSTRACT FROM AUTHOR]

Abstract Background Total aortic arch replacement (TAR) with frozen elephant trunk (FET) requires hypothermic circulatory arrest (HCA) for 20 min, which increases the surgical risk. We invented an aortic balloon occlusion (ABO) technique that requires 5 min of HCA on average to perform TAR with FET and investigated the possible merit of this new method in this study. Methods This retrospective study included consecutive patients who underwent TAR and FET (consisting of 130 cases of ABO group and 230 cases of conventional group) in Fuwai Hospital between August 2017 and February 2019. In addition to the postoperative complications, the alterations of blood routine tests, alanine transaminase (ALT) and aspartate transaminase (AST) during in-hospital stay were also recorded. Results The 30-day mortality rates were similar between ABO group (4.6%) and conventional group (7.8%, P = 0.241). Multivariate analysis showed ABO reduced postoperative acute kidney injury (23.1% vs. 35.7%, P = 0.013) and hepatic injury (12.3% vs. 27.8%, P = 0.001), and maintained similar cost to patients (25.5 vs. 24.9 kUSD, P = 0.298). We also found that AST was high during intensive care unit (ICU) stay and recovered to normal before discharge, while ALT was not as high as AST in ICU but showed a rising tendency before discharge. The platelet count showed a rising tendency on postoperative day 3 and may exceed the preoperative value before discharge. Conclusions The ABO achieved the surgical goal of TAR with FET with an improved recovery process during the in-hospital stay.

Abstract Background Obesity is dramatically increasing worldwide, and more obese patients may develop aortic dissection and present for surgical repair. The study aims to analyse the impact of body mass index (BMI) on surgical outcomes in patients with acute Stanford type A aortic dissection (ATAAD). Methods From January 2017 to June 2019, the clinical data of 268 ATAAD patients in a single centre were retrospectively reviewed. They were divided into three groups based on the BMI: normal weight (BMI 18.5 to

ObjectiveTo develop and validate a nomogram model to predict postoperative 30-day mortality in acute type A aortic dissection patients receiving total aortic arch replacement with frozen elephant trunk technique.MethodClinical data on 1,156 consecutive acute type A aortic dissection patients who got total aortic arch replacement using the frozen elephant trunk technique was collected from January 2010 to December 2020. These patients were divided into training and testing cohorts at random with a ratio of 7:3. To predict postoperative 30-day mortality, a nomogram was established in the training set using the logistic regression model. The novel nomogram was then validated in the testing set. The nomogram's calibration and discrimination were evaluated. In addition, we created four machine learning prediction models in the training set. In terms of calibration and discrimination, the nomogram was compared to these machine learning models in testing set.ResultsLeft ventricular end-diastolic diameter 4 h were independent predictors of the 30-day mortality. The nomogram based on these 6 predictors manifested satisfying calibration and discrimination. In testing set, the nomogram outperformed the other 4 machine learning models.ConclusionThe novel nomogram is a simple and effective tool to predict 30-day mortality rate for acute type A aortic dissection patients undergoing total aortic arch replacement with frozen elephant trunk technique.

BackgroundThe hybrid arch repair (HAR) is an appealing surgical option in the management of aortic arch diseases. The aim is to evaluate the short and mid-term outcomes of type II HAR involving replacement of the ascending aorta, arch debranching, and zone 0 stent graft deployment in diverse arch pathologies.Methods200 patients with various diffuse aortic pathologies involving the arch were enrolled between 2016 and 2019. Complex arch diseases included acute type A dissection (n = 129, 64.5%), acute type B dissection (n = 16, 8.0%), aortic arch aneurysm (n = 42, 21.0%) and penetrating arch ulcer (n = 13, 6.5%). Mortality, morbidity, survival and re-intervention were analyzed.ResultsThe overall 30-day mortality rate was 8.0% (16/200). Stroke was present in 3.5% (7/200) of the general cohort and spinal cord injury was occurred in 3.0% (6/200). Multivariable logistic analysis showed that cardiac malperfusion and CPB time were the risk factors associated with 30-day mortality. The mean follow-up duration was 25.9 months (range 1–57.2 months), and the 3-year survival rate was 83.1%. On Cox regression analysis, age, diabetes, cardiac malperfusion and CPB time predicted short and mid-term overall mortality. A total of 3 patients required reintervention during the follow-up due to the thrombosis of epiaortic artificial vessels (n = 1), anastomotic leak at the site of the proximal ascending aorta (n = 1) and the type I endoleak (n = 1).ConclusionsType II HAR was performed with satisfactory early and mid-term outcomes in complex aortic arch pathologies.

In this paper, we describe an R package named coxphMIC, which implements the sparse estimation method for Cox proportional hazards models via approximated information criterion (Su et al., 2016). The developed methodology is named MIC which stands for "Minimizing approximated Information Criteria". A reparameterization step is introduced to enforce sparsity while at the same time keeping the objective function smooth. As a result, MIC is computationally fast with a superior performance in sparse estimation. Furthermore, the reparameterization tactic yields an additional advantage in terms of circumventing post-selection inference (Leeb and Pötscher, 2005). The MIC method and its R implementation are introduced and illustrated with the PBC data. [ABSTRACT FROM AUTHOR]