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Abstract Background The American Heart Association (AHA) has recently introduced the concept of Cardiovascular-Kidney-Metabolic (CKM) syndrome, which is the result of an increasing emphasis on the interplay of metabolic, renal and cardiovascular diseases (CVD). Furthermore, there is substantial evidence of a correlation between the triglyceride glucose-body mass index (TyG-BMI ) and CVD as an assessment of insulin resistance (IR). However, it remains unknown whether this correlation exists in population with CKM syndrome. Methods All data for this study were obtained from the China Health and Retirement Longitudinal Study (CHARLS). The exposure was the participants’ TyG-BMI at baseline, which was calculated using a combination of triglycerides (TG), fasting blood glucose (FBG) and body mass index (BMI). The primary outcome was CVD, which were determined by the use of a standardised questionnaire during follow-up. To examine the relationship between TyG-BMI and CVD incidence in population with CKM syndrome, both Cox regression analyses and restricted cubic spline (RCS) regression analyses were performed. Results A total of 7376 participants were included in the final analysis. Of these, 1139, 1515, 1839, and 2883 were in CKM syndrome stages 0, 1, 2, and 3, respectively, at baseline. The gender distribution was 52.62% female, and the mean age was 59.17 ± 9.28 (years). The results of the fully adjusted COX regression analyses indicated that there was a 6.5% increase in the risk of developing CVD for each 10-unit increase in TyG-BMI,95% confidence interval (CI):1.041–1.090. The RCS regression analyses demonstrated a positive linear association between TyG-BMI and the incidence of CVD in the CKM syndrome population (P for overall

Abstract Uterine myomas are the most common pelvic tumors in women, which can lead to abnormal uterine bleeding, abdominal pain, pelvic compression symptoms, infertility, or adverse pregnancy. In this article, we provide a dataset named uterine myoma MRI dataset (UMD), which can be used for clinical research on uterine myoma imaging. The UMD is the largest publicly available uterine MRI dataset to date including 300 cases of uterine myoma T2-weighted imaging (T2WI) sagittal patient images and their corresponding annotation files. The UMD covers 9 types of uterine myomas classified by the International Federation of Obstetrics and Gynecology (FIGO), which were annotated and reviewed by 11 experienced doctors to ensure the authority of the annotated data. The UMD is helpful for uterine myomas classification and uterine 3D reconstruction tasks, which has important implications for clinical research on uterine myomas.

The proposed “Guanlan” ocean science satellite, led by China’s Laoshan Laboratory, includes an interferometric radar altimeter (IRA) as a key payload. As an integral part of its development, an airborne IRA experiment was conducted on 6 November 2021, with a flight path of approximately 90 km in the South China Sea. This study investigates the IRA’s ability to observe ocean sea surface height (SSH) across scales ranging from meters to mesoscale. The sea surface height anomaly (SSHA) of the IRA is aligned with the SSHA of the AVISO at scales greater than 30 km, but also demonstrates the ability to capture small-scale SSHA changes in two dimensions. We analyzed wavenumber spectra of SSHA obtained from the airborne IRA, ICESat-2, and SARAL/AltiKa satellite for this region. The results show a good agreement in power spectral density (PSD) levels between ICESat-2, SARAL/AltiKa and IRA at scales larger than 30 km. Within the submesoscale range of 1–10 km, the IRA SSHA spectrum exhibits a distinctly negative slope and the lowest energy level. The minimum PSD level of the IRA fell in the range of 10−4–10−3 m2/cycle/km, at scales around 1 km, which is more than an order of magnitude lower than that of ICESat-2, forming a spectral gap that is in agreement with the theoretical expectation. Furthermore, IRA-derived wave direction and significant wave height matched well with the MFWAM wave data. The results of this study underscore the considerable potential of airborne IRA in capturing SSHA across a range of scales, from oceanic waves to submesoscale.

Abstract Background The pathogenicity and virulence of the Omicron strain have weakened significantly pathogenesis of Omicron variants. Accumulating data indicated accessory proteins play crucial roles in host immune evasion and virus pathogenesis of SARS-CoV-2. Therefore, the impact of simultaneous deletion of accessory protein ORF7a, ORF7b and ORF8 on the clinical characteristics and specific immunity in Omicron breakthrough infected patients (BIPs) need to be verified. Methods Herein, plasma cytokines were identified using a commercial Multi-cytokine detection kit. Enzyme-linked immunosorbent assay and pseudovirus neutralization assays were utilized to determine the titers of SARS-CoV-2 specific binding antibodies and neutralizing antibodies, respectively. In addition, an enzyme-linked immunospot assay was used to quantify SARS-CoV-2 specific T cells and memory B cells. Results A local COVID-19 outbreak was caused by the Omicron BA.2 variant, which featured a deletion of 871 base pairs (∆871 BA.2), resulting in the removal of ORF7a, ORF7b, and ORF8. We found that hospitalized patients with ∆871 BA.2 had significantly shorter hospital stays than those with wild-type (WT) BA.2. Plasma cytokine levels in both ∆871 BA.2 and WT BA.2 patients were within the normal range of reference, and there was no notable difference in the titers of SARS-CoV-2 ancestor or Omicron-specific binding IgG antibodies, neutralizing antibody titers, effector T cells, and memory B cells frequencies between ∆871 BA.2 and WT BA.2 infected adult patients. However, antibody titers in ∆871 BA.2 infected adolescents were higher than in adults. Conclusions The simultaneous deletion of ORF7a, ORF7b, and ORF8 facilitates the rapid clearance of the BA.2 variant, without impacting cytokine levels or affecting SARS-CoV-2 specific humoral and cellular immunity in Omicron-infected individuals.

Abstract The immunogenicity of SARS-CoV-2 vaccines is poor in kidney transplant recipients (KTRs). The factors related to poor immunogenicity to vaccination in KTRs are not well defined. Here, observational study demonstrated no severe adverse effects were observed in KTRs and healthy participants (HPs) after first or second dose of SARS-CoV-2 inactivated vaccine. Different from HPs with excellent immunity against SARS-CoV-2, IgG antibodies against S1 subunit of spike protein, receptor-binding domain, and nucleocapsid protein were not effectively induced in a majority of KTRs after the second dose of inactivated vaccine. Specific T cell immunity response was detectable in 40% KTRs after the second dose of inactivated vaccine. KTRs who developed specific T cell immunity were more likely to be female, and have lower levels of total bilirubin, unconjugated bilirubin, and blood tacrolimus concentrations. Multivariate logistic regression analysis found that blood unconjugated bilirubin and tacrolimus concentration were significantly negatively associated with SARS-CoV-2 specific T cell immunity response in KTRs. Altogether, these data suggest compared to humoral immunity, SARS-CoV-2 specific T cell immunity response are more likely to be induced in KTRs after administration of inactivated vaccine. Reduction of unconjugated bilirubin and tacrolimus concentration might benefit specific cellular immunity response in KTRs following vaccination.

BackgroundThe application of artificial intelligence (AI) powered algorithm in clinical decision-making is globally popular among clinicians and medical scientists. In this research endeavor, we harnessed the capabilities of AI to enhance the precision of hysteroscopic myomectomy procedures.MethodsOur multidisciplinary team developed a comprehensive suite of algorithms, rooted in deep learning technology, addressing myomas segmentation tasks. We assembled a cohort comprising 56 patients diagnosed with submucosal myomas, each of whom underwent magnetic resonance imaging (MRI) examinations. Subsequently, half of the participants were randomly designated to undergo AI-augmented procedures. Our AI system exhibited remarkable proficiency in elucidating the precise spatial localization of submucosal myomas.ResultsThe results of our study showcased a statistically significant reduction in both operative duration (41.32 ± 17.83 minutes vs. 32.11 ± 11.86 minutes, p=0.03) and intraoperative blood loss (10.00 (6.25-15.00) ml vs. 10.00 (5.00-15.00) ml, p=0.04) in procedures assisted by AI.ConclusionThis work stands as a pioneering achievement, marking the inaugural deployment of an AI-powered diagnostic model in the domain of hysteroscopic surgery. Consequently, our findings substantiate the potential of AI-driven interventions within the field of gynecological surgery.

Background Patellofemoral pain (PFP) syndrome is a common knee joint functional disorder. Blood flow restriction (BFR) training has shown promise in improving PFP; however, the effectiveness of intermittent BFR (iBFR) training remains uncertain. This study aims to compare the rehabilitative effects of iBFR combined with low-load resistance training and high-load resistance training in PFP patients and to assess the effectiveness of iBFR combined with low-load resistance training for improving PFP.Methods and analysis This randomised, patient-assessor blinded, controlled trial will include 42 eligible PFP patients randomly allocated to an intervention group (iBFR combined with low-load resistance training) or a control group (high-load resistance training) in a 1:1 ratio. Participants will receive interventions three times per week for 8 weeks and will be followed up for 24 weeks. The primary outcome measure is pain, and the secondary outcomes include self-reported function, quality of life, muscle strength and muscle thickness. Assessments will be conducted at baseline, 8 weeks and 24 weeks during follow-up. Intention-to-treat analysis will be performed.Collectively, we expect that the findings of this randomised clinical trial will contribute to understanding the potential benefits of iBFR training and provide insightful guidance for developing more effective treatment strategies for patients with PFP.Ethics and dissemination This study was approved by the Sports Science Experiment Ethics Committee of Beijing Sport University (2022274H). Written informed consent will be obtained from all participants. Trial results will be disseminated through peer-reviewed publications.Trial registration number Chinese Clinical Trial Registry (ChiCTR2300068281).

BackgroundA third mRNA vaccine booster is recommended to improve immunity against SARS-CoV-2 in kidney transplant recipients (KTRs). However, the immunity against SARS-CoV-2 Ancestral strain and Delta and Omicron variants elicited by the third dose of inactivated booster vaccine in KTRs remains unknown.MethodsThe blood parameters related to blood cells count, hepatic function, kidney function, heart injury and immunity were explored clinically from laboratory examinations. SARS-CoV-2 specific antibody IgG titer was detected using an enzyme-linked immunosorbent assay. Cellular immunity was analyzed using interferon-γ enzyme-linked immunospot assay.ResultsThe results showed that there were no severe adverse effects and apparent changes of clinical laboratory biomarkers in KTRs and healthy volunteers (HVs) after homologous inactivated vaccine booster. A third dose of inactivated vaccine booster significantly increased anti-Ancestral-spike-trimer-IgG and anti-Ancestral-receptor binding domain (RBD)-IgG titers in KTRs and HVs compared with the second vaccination. However, the anti-Delta-RBD-IgG and anti-Omicron-RBD-IgG titers were significantly lower than anti-Ancestral-RBD-IgG titer in KTRs and HVs after the third dose. Notably, only 25.6% (10/39) and 10.3% (4/39) of KTRs had seropositivity for anti-Delta-RBD-IgG and anti-Omicron-RBD-IgG after booster, which were significantly lower than HVs (anti-Delta-RBD-IgG: 100%, anti-Omicron-RBD-IgG: 77.8%). Ancestral strain nucleocapsid protein and spike specific T cell frequency after booster was not significantly increased in KTRs compared with the second dose, significantly lower than that in HVs. Moreover, 33.3% (12/36), 14.3% (3/21) and 14.3% (3/21) of KTRs were positive for the Ancestral strain and Delta and Omicron spike-specific T cells, which were significantly lower than HVs (Ancestral: 80.8%, Delta: 53.8%, and Omicron: 57.7%).ConclusionsA third dose of inactivated booster vaccine may significantly increase humoral immunity against the Ancestral strain in KTRs, while humoral and cellular immunity against the Delta and Omicron variants were still poor in KTRs.

Medical image segmentation can effectively identify lesions in medicine, but some small and rare lesions cannot be well identified. Existing studies do not take into account the uncertainty of the occurrence of diseased tissue, and the problem of long-tailed distribution of medical data. Meanwhile, the grayscale image obtained from Magnetic Resonance Imaging (MRI) detection has problems, such as the features being difficult to extract and invalid features being difficult to distinguish. In order to solve these problems, we propose a new weighted attention ResUNet (WA-ResUNet) and a class weight formula based on the number of images contained in the class, which improves the performance of the model in the low-frequency class and the overall effect of the model by improving the degree of attention paid to the valid features and invalid ones and rebalancing the learning efficiency among the classes. We evaluated our method on an uterine MRI dataset and compared it with the ResUNet. WA-ResUNet increased Intersection over Union (IoU) in the low-frequency class (Nabothian cysts) by 21.87%, and the overall mIoU increased by more than 6.5%.

This study introduces an interferometric synthetic aperture radar (InSAR) altimeter for sea-level elevation measurement. To evaluate the system capability and demonstrate that the InSAR altimeter can meet the application requirements of sea-surface elevation measurement, the main factors affecting relative elevation accuracy are analyzed. The mathematical expressions for each elevation measurement parameter and sea-surface elevation are derived along with the error transfer coefficients between each elevation measurement parameter and relative sea-surface elevation accuracy. Using the single-control variable method, the sensitivity of each elevation measurement parameter to relative elevation accuracy is obtained. By introducing the parameter values into the derivation formula of theoretical analysis, theoretical results are obtained. The theoretical results are compared with the simulation results, which helps to verify the validity of the error analysis. Results reveal that the interference phase error is the main factor affecting the accuracy of relative ocean height measurements. This work could significantly guide the subsequent design of the InSAR altimeter system.

Due to land contamination and human activities, the sea surface height (SSH) data retrieved from altimeter coastal waveforms have poor precision and cannot provide effective information for various tasks. The along-track high-resolution characteristic of the new synthetic aperture radar (SAR) altimeter makes the retracking methods of traditional coastal waveforms difficult to apply. This study proposes a partial reconstruction method for SAR altimeter coastal waveforms. By making adaptive threshold judgments of model matching errors and repairing the contaminated waveforms based on the nearest linear prediction, the success rate of retracking and retrieval precision of SSH are significantly improved. The data from the coastal experimental areas of the Sentinel-3B satellite altimeter are processed. The results indicate that the mean proportion of waveform quality improvement brought by partial reconstruction is 80.30%, the mean retracking success rate of reconstructed waveforms is 85.60%, and the mean increasing percentage is 30.98%. The noise levels of SSH data retrieved by different methods are calculated to evaluate the processing precision. It is shown that the 20 Hz SSH precisions of the original and reconstructed coastal waveforms are 12.75 cm and 6.32 cm, respectively, and the corresponding 1 Hz SSH precisions are 2.85 cm and 1.41 cm, respectively. The results validate that the proposed partial reconstruction method has improved the SSH precision by a factor of two, and the comparison results with mean sea surface (MSS) model data further verify this conclusion.

Satellite radar altimeters are advanced remote sensing devices that play an important role in observing the global marine environment. Accurately estimating the noise level of altimeter in-orbit ranging data is crucial for evaluating the payload performance, analyzing sea conditions, and monitoring data quality. In this study, we propose an approach based on the differential processing of along-track odd–even data sequences for altimeter in-orbit range noise-level estimation. Using the long-term along-track data sequence can notably improve the issue in the existing method in that the noise level is underestimated owing to the utilization of a relatively short data segment. On the basis of an analysis of the influence of low-frequency components on noise-level estimation, the mathematical formulas of the above differential method were deduced, and the efficacy of the approach in assessing the noise level of altimeter in-orbit data was demonstrated by simulation experiments. This method was used to estimate the noise levels of the 20 Hz datasets of Jason-3 and Sentinel-6, and the idea of the time-domain difference was extended to the frequency domain. The statistical results showed that the 20 Hz noise levels at the significant wave height (SWH) = 2 m were 7.41 cm (Jason-3 low-resolution (LR) mode), 6.66 cm (Sentinel-6 LR mode), and 3.13 cm (Sentinel-6 high-resolution (HR) mode). The power spectrum density analysis further verified its accuracy. By reprocessing the 20 Hz data of Sentinel-6 into 10, 5, and 1 Hz, the effectiveness of the along-track odd–even differential method to directly evaluate the noise level of 1 Hz data was explored, and the impact of ocean signals such as swells on noise-level estimation in synthetic aperture mode was discussed.

Background. With wrist-worn wearables becoming increasingly available, it is important to understand their reliability and validity in different conditions. The primary objective of this study was to examine the reliability and validity of the Lexin Mio smart bracelet in measuring heart rate (HR) and energy expenditure (EE) in people with different physical activity levels exercising at different intensities. Methods. A total of 65 participants completed one maximal oxygen uptake test and two running exercise tests wearing the Mio smart bracelet, the Polar H10 HR band, and a gas-analysis system. Results. In terms of HR measurement reliability, the Mio smart bracelet showed good reliability in a left versus right test and good test–retest reliability (p > 0.05; mean absolute percentage error (MAPE) < 10%; intraclass correlation coefficient (ICC) > 0.4). For EE measurement, the Mio smart bracelet showed good reliability in a left versus right test, good test–retest reliability on the right (p > 0.05; MAPE > 10%; ICC > 0.4), and low test–retest reliability on the left (p > 0.05; MAPE > 10%; ICC < 0.4). Regarding validity, the Mio smart bracelet showed good validity for HR measurement (p > 0.05; MAPE < 10%; ICC > 0.4) and low validity for EE measurement (p < 0.05; MAPE > 10%; ICC < 0.4). Conclusion. The Lexin Mio smart bracelet showed good reliability and validity for HR measurement among people with different physical activity levels exercising at various exercise intensities in a laboratory setting. However, the smart bracelet showed good reliability and low validity for the estimation of EE.

Satellite radar altimeters have been successfully used for sea surface height (SSH) measurement for decades, gaining great insight in oceanography, meteorology, marine geology, etc. To further improve the observation precision and spatial resolution, radar altimeters have evolved from real aperture to synthetic aperture, from the Ku-band to Ka-band. Future synthetic aperture radar (SAR) altimeter of the Ka-band is expected to achieve better performance than its predecessors. To verify the SAR altimeter data processing method and explore the system advantage of the Ka-band, a Ku/Ka dual-band SAR altimeter airborne experiment was carried out over South China Sea on 6 November 2021. Through dedicated hardware design, this campaign has acquired the Ku and Ka dual-band echo data simultaneously. The airborne data are processed to estimate the SSH retrieval precision after a series of procedures (including height compensation, range migration correction, multi-look processing, waveform re-tracking). To accustom to the airborne experiment design, a SAR echo model that fully considers both the attitude variation of the aircraft and the elliptical footprint of radar beam is established. The retrieved SSH data are compared with the public SSH data along the flight path at the experiment day, showing good consistence for both bands. By calculating the theoretical precision of waveform re-tracking and re-processing the dual-band airborne data into different bandwidths, it is demonstrated that the Ku/Ka precision ratio is possible to achieve 1.4 within the 27 km offshore area, which indicates that Ka-band has better performance.

Imaging Radar Altimeter (IRA) is the current development tendency for ocean surface topography (OST) altimetry, which utilizes Synthetic Aperture Radar (SAR) and interferometry to improve the spatial resolution of OST to several kilometers or even better. Meanwhile, centimetric altimetry accuracy should be guaranteed for applications such as geostrophic currents or marine gravity anomaly inversion. However, the baseline length of IRA which determines the altimetric sensitivity is confined by the satellite platform, in consideration of baseline vibration and payload capability. Therefore, the baseline length from a single satellite can extend to only tens of meters, making it difficult to achieve centimetric accuracy. Referring to the successful experience from TerraSAR-X/TanDEM-X, satellite formation can easily extend the baseline length to hundreds or thousands of meters, depending on the helix orbit. Therefore, we propose the large baseline IRA (LB-IRA) from satellite formation for OST altimetry: the carrier frequency shift (CFS) is brought in to compensate for the severe baseline decorrelation, and the helix orbit is carefully selected to prevent severe time decorrelation from along-track baseline. The numerical results indicate that the LB-IRA, whose cross-track baseline ranges between 629~1000 m and along-tack baseline ranges between 0~40 m, can achieve ~1 cm relative accuracy at 1 km resolution.

The traditional altimetry satellite, which is based on pulse-limited radar altimeter, only measures ocean surface heights along tracks; hence, leads to poorer accuracy in the east component of the vertical deflections compared to the north component, which in turn limits the final accuracy of the marine gravity field inversion. Wide-swath altimetry using radar interferometry can measure ocean surface heights in two dimensions and, thus, can be used to compute vertical deflections in an arbitrary direction with the same accuracy. This paper aims to investigate the impact of Interferometric Radar Altimeter (InRA) errors on gravity field inversion. The error propagation between gravity anomalies and InRA measurements is analyzed, and formulas of their relationship are given. By giving a group of possible InRA parameters, numerical simulations are conducted to analyze the accuracy of gravity anomaly inversion. The results show that the accuracy of the gravity anomalies is mainly influenced by the phase errors of InRA; and the errors of gravity anomalies have a linear approximation relationship with the phase errors. The results also show that the east component of the vertical deflections has almost the same accuracy as the north component.

Interferometric imaging radar altimeter (InIRA) is the first spaceborne Ku-band interferometric synthetic aperture radar (InSAR) which is specially designed for ocean surface topography altimetry. It is on the Tiangong II space laboratory, which was launched on 15 September 2016. Different from any other spaceborne synthetic aperture radar (SAR), InIRA chooses a near-nadir incidence of 1°~8° in order to increase the altimetric precision and swath width. Limited by the size of the Tiangong II capsule, the baseline length of InIRA is only 2.3 m. However, benefitting from the low orbit, the signal-to-noise ratio of InIRA-acquired data is above 10 dB in most of the swath, which, to a certain extent, compensates for the short baseline deficiency. The altimetric precision is simulated based on the system parameters of InIRA. Results show that it is better than 7 cm on a 5-km grid and improves to 3 cm on a 10-km grid when the incidence is below 7.4°. The interferometric data of InIRA are processed to estimate the altimetric precision after a series of procedures (including image coregistration, flat-earth-phase removal, system parameters calibration and phase noise suppression). Results show that the estimated altimetric precision is close to but lower than the simulated precision among most of the swath. The intensity boundary phenomenon is first found between the near range and far range of the SAR images of InIRA. It can be explained by the modulation of ocean internal waves or oil slick, which smooths ocean surface roughness and causes the modulated area to appear either brighter or darker than its surroundings. This intensity boundary phenomenon indicates that the available swath of high altimetric precision will be narrower than expected.

The image intensities of low-backscattering areas in synthetic aperture radar (SAR) images are often seriously contaminated by the system noise floor and azimuthal ambiguity signal from adjacent high-backscattering areas. Hence, the image intensity of low-backscattering areas does not correctly reflect the backscattering intensity, which causes confusion in subsequent image processing or interpretation. In this paper, a method is proposed to estimate the normalized radar cross-section (NRCS) of low-backscattering area by utilizing the differences between noise, azimuthal ambiguity, and signal in the Doppler frequency domain of single-look SAR images; the aim is to eliminate the effect of system noise and azimuthal ambiguity. Analysis shows that, for a spaceborne SAR with a noise equivalent sigma zero (NESZ) of −25 dB and a single-look pixel of 8 m × 5 m, the NRCS-estimation precision of this method can reach −38 dB at a resolution of 96 m × 100 m. Three examples are given to validate the advantages of this method in estimating the low NRCS and the filtering of the azimuthal ambiguity.