[Analysis of clinical effect of arthroscopic release at different time in treating knee adhesion after arthroscopic surgery]

Objective: To explore the efficacy of arthroscopic release in treating postoperative knee adhesion and investigate the influence of release timing on the treatment outcomes. Methods: A total of 50 patients who accepted arthroscopic release in Peking University Third Hospital from February 2017 to December 2021 were included in the retrospective cohort. The study cohort comprised 28 men and 22 women, with a mean age of (30.8±11.9) years. All the primary surgeries were manipulated under arthroscopes. A comparison was made between pre-and postoperative range of motion (ROM), visual analog scale (VAS), International Knee Documentation Committee (IKDC) scores, and Tegner activity scale scores for the patients. According to the interval between the appearance of adhesion and arthroscopic release, the patients were divided into four groups:<3 months group (n=12), 3-6 months group (n=16),>6-12 months group (n=14), and>12 months group (n=8). Inter-group comparisons on postoperative ROM, IKDC scores, and Tegner activity scale scores and improvement values of each outcome were conducted. Results: All the patients were followed up for (36.4±19.7) months. Patients gained significant improvement in flexion, extension, IKDC scores, and Tegner scores (125.0°±20.0° vs 75.7°±27.5°, 2.3°±4.8° vs 7.4°±7.3°, 69.8±17.7 vs 51.4±12.8, 4.1±2.1 vs 2.2±1.1) (all P<0.05), while the VAS scores did not show significant improvement. There were no significant differences among different groups in postoperative extension, IKDC scores or Tegner scores, nor in their improvements. However, patients in the ≤6 months group could gain better postoperative flexion and improvement in flexion than those in the >6 months group (129.9°±20.0° vs 118.8°±17.4°, 58.6°±32.8° vs 37.3°±23.1°) (P<0.05). Conclusions: Arthroscopic release presents a great effect in treating knee adhesion after arthroscopic operation. Once the symptoms of adhesion appear and physical rehabilitation fails to improve the ROM, one should accept early surgical intervention (less than 6 months) for a better outcome.

Short-term anaerobic treatment maintained the quality of Actinidia arguta by activating the antioxidant defense system

BACKGROUND

This study aimed to investigate the effect of 6, 12, and 24 h short-term anaerobic treatment on kiwiberry quality and antioxidant properties at 5 °C.

RESULTS

Short-term anaerobic treatment was found to delay ripening and softening in kiwiberries, evident from changes in ethylene release, total soluble solids, starch, protopectin, and fruit texture. The 24 h treatment group exhibited the lowest decay rate of 12% on day 49, a 38% reduction compared with the control group. Anaerobic treatment reduced flesh translucency and decay in the fruit. The 12 h and 24 h treatments enhanced the activities of superoxide dismutase, peroxidase, catalase, and ascorbate peroxidase, and increased the level of total phenolics, flavonoids, anthocyanins, and ascorbic acid. Moreover, it lowered oxidative damage in cell membranes, evidenced by reduced malondialdehyde content and relative conductivity.

CONCLUSION

These results indicate that anaerobic treatment maintains the fruit quality by stimulating its antioxidant defense system. Therefore, short-term anaerobic treatment emerges as a promising method for kiwiberry storage. © 2024 Society of Chemical Industry.

A Deep Learning Model for Predicting Molecular Subtype of Breast Cancer by Fusing Multiple Sequences of DCE-MRI From Two Institutes

RATIONALE AND OBJECTIVES

To evaluate the performance of deep learning (DL) in predicting different breast cancer molecular subtypes using DCE-MRI from two institutes.

MATERIALS AND METHODS

This retrospective study included 366 breast cancer patients from two institutes, divided into training (n = 292), validation (n = 49) and testing (n = 25) sets. We first transformed the public DCE-MRI appearance to ours to alleviate small-data-size and class-imbalance issues. Second, we developed a multi-branch convolutional-neural-network (MBCNN) to perform molecular subtype prediction. Third, we assessed the MBCNN with different regions of interest (ROIs) and fusion strategies, and compared it to previous DL models. Area under the curve (AUC) and accuracy (ACC) were used to assess different models. Delong-test was used for the comparison of different groups.

RESULTS

MBCNN achieved the optimal performance under intermediate fusion and ROI size of 80 pixels with appearance transformation. It outperformed CNN and convolutional long-short-term-memory (CLSTM) in predicting luminal B, HER2-enriched and TN subtypes, but without demonstrating statistical significance except against CNN in TN subtypes, with testing AUCs of 0.8182 vs. [0.7208, 0.7922] (p=0.44, 0.80), 0.8500 vs. [0.7300, 0.8200] (p=0.36, 0.70) and 0.8900 vs. [0.7600, 0.8300] (p=0.03, 0.63), respectively. When predicting luminal A, MBCNN outperformed CNN with AUCs of 0.8571 vs. 0.7619 (p=0.08) without achieving statistical significance, and is comparable to CLSTM. For four-subtype prediction, MBCNN achieved an ACC of 0.64, better than CNN and CLSTM models with ACCs of 0.48 and 0.52, respectively.

CONCLUSION

Developed DL model with the feature extraction and fusion of DCE-MRI from two institutes enabled preoperative prediction of breast cancer molecular subtypes with high diagnostic performance.

Curcumin alleviates myocardial inflammation, apoptosis, and oxidative stress induced by acute pulmonary embolism by regulating microRNA-145-5P/insulin receptor substrate 1 axis

The treatment of patients with acute pulmonary embolism (APE) is extremely challenging due to the complex clinical presentation and prognosis of APE related to the patient's hemodynamic status and insufficient arterial blood flow and right ventricular overload. Protective efficacy against cardiovascular diseases of curcumin, a common natural polyphenolic compound, which has antithrombotic properties and reduces platelet accumulation in the circulation by inhibiting thromboxane synthesis has been demonstrated. However, the direct effect of curcumin on APE has rarely been studied. Therefore, the present study aimed to investigate the therapeutic potential of curcumin in APE and associated myocardial injury to provide new insights into curcumin as a promising competitive new target for the treatment of APE. A suspension of 12 mg/kg microspheres was injected intravenously into rats. An APE rat model was built. Before modeling, intragastric 100 mg/kg curcumin was given, and/or lentiviral plasmid vector targeting microRNA-145-5p or insulin receptor substrate 1 (IRS1) was injected. Pulmonary artery pressure was measured to assess right ventricular systolic pressure (RVSP). Hematoxylin and eosin (H&E) staining was performed on liver tissues and myocardial tissues of APE rats. TUNEL (terminal deoxynucleotidyl transferase biotin-dUTP nick end labeling) staining and immunohistochemical (IHC) staining were conducted to measure apoptosis and CyPA-CD147 expression in the myocardium, respectively. Inflammatory indices interleukin-1beta (IL-1β), interleukin-6 (IL-6) and tumor necrosis factor alpha (TNF-α) were measured by ELISA in cardiac tissues. RT-qPCR and Western blot were performed to determine the expression levels of related genes. In addition, by dual luciferase reporter assay and RIP assay, the relationship between microRNA-145-5p and insulin receptor substrate 1 (IRS1) was confirmed. In results: curcumin improved APE-induced myocardial injury, reduced myocardial tissue edema, and thrombus volume. It attenuated APE-induced myocardial inflammation and apoptosis, as well as reduced lung injury and pulmonary artery pressure. Curcumin promoted microRNA-145-5p expression in APE rat myocardium. MicroRNA-145-5p overexpression protected against APE-induced myocardial injury, and microRNA-145-5p silencing abolished the beneficial effects of curcumin in APE-induced myocardial injury. IRS1 was targeted by microRNA-145-5p. IRS1 silencing attenuated APE-induced myocardial injury, and enhanced therapeutic effect of curcumin on myocardial injury in APE rats. In conclusion, curcumin alleviates myocardial inflammation, apoptosis, and oxidative stress induced by APE by regulating microRNA-145-5p/IRS1 axis.

Inside to outside puncture following endoscopic localization-A novel technique to insert ports and create retromuscular space in eTEP for ventral hernias

PURPOSE

Enhanced-view totally extraperitoneal plasty (eTEP) has been used worldwide to repair ventral hernias. This study aimed to describe a novel technique to insert ports and create retromuscular space in more detail.

METHODS

From 2020 to 2022, 23 consecutive ventral hernia repairs were performed using the eTEP technique. In all cases, inside-to-outside puncture following endoscopic localization was utilized to insert ports and create retromuscular space.

RESULTS

All cases were completed with the eTEP technique, and no cases with conversion to open repair or IPOM technique. There were no epigastric vessel injuries and posterior sheath tears due to puncture. In addition, no postoperative hematoma cases were reported.

CONCLUSION

Inside-to-outside puncture following endoscopic localization to insert ports and create retromuscular space is a safe, feasible, reproducible technique in eTEP for ventral hernia repair.

CORONet: A Cross-Sequence Joint Representation and Hypergraph Convolutional Network for Classifying Molecular Subtypes of Breast Cancer Using Incomplete DCE-MRI

Breast cancer, the predominant malignancy among women, is characterized by significant heterogeneity, leading to the emergence of distinct molecular subtypes. Accurate differentiation of these molecular subtypes holds paramount clinical significance, owing to substantial variations in prognosis, therapeutic strategies, and survival outcomes. In this study, we propose a cross-sequence joint representation and hypergraph convolution network (CORONet) for classifying molecular subtypes of breast cancer using incomplete DCE-MRI. Specifically, we first build a cross-sequence joint representation (COR) module to integrate image imputation and feature representation into a unified framework, encouraging effective feature extraction for subsequent classification. Then, we fuse multiple COR features and applied feature selection to reduce the redundant information between sequences. Finally, we deploy hypergraph structures to model high-order correlation among different subjects and extracted high-level semantic features by hypergraph convolutions for molecular subtyping. Extensive experiments on incomplete DCE-MRIs of 395 patients from the TCIA repository showed a significant improvement of our CORONet over state of the arts, with the area under the curve (AUC) of 0.891 and 0.903 for luminal and triple-negative (TN) subtype prediction, respectively. Similar advantages of CORONet were also confirmed in partial complete DCE-MRIs of 144 patients, achieving an AUC of 0.858 and 0.832 for predicting luminal and TN subtypes of breast cancer, respectively. Nevertheless, both of these values were lower compared to the scenario where DCE-MRIs from all 395 patients were utilized. Our study contributes to the precise molecular subtyping using incomplete multi-sequence DCE-MRI, thereby offering promising prospects for future risk stratification of breast cancer patients.

Logarithmic total variation regularization via preconditioned conjugate gradient method for sparse reconstruction of bioluminescence tomography

BACKGROUND AND OBJECTIVE

Bioluminescence Tomography (BLT) is a powerful optical molecular imaging technique that enables the noninvasive investigation of dynamic biological phenomena. It aims to reconstruct the three-dimensional spatial distribution of bioluminescent sources from optical measurements collected on the surface of the imaged object. However, BLT reconstruction is a challenging ill-posed problem due to the scattering effect of light and the limitations in detecting surface photons, which makes it difficult for existing methods to achieve satisfactory reconstruction results. In this study, we propose a novel method for sparse reconstruction of BLT based on a preconditioned conjugate gradient with logarithmic total variation regularization (PCG-logTV).

METHOD

This PCG-logTV method incorporates the sparsity of overlapping groups and enhances the sparse structure of these groups using logarithmic functions, which can preserve edge features and achieve more stable reconstruction results in BLT. To accelerate the convergence of the algorithm solution, we use the preconditioned conjugate gradient iteration method on the objective function and obtain the reconstruction results. We demonstrate the performance of our proposed method through numerical simulations and in vivo experiment.

RESULTS AND CONCLUSIONS

The results show that the PCG-logTV method obtains the most accurate reconstruction results, and the minimum position error (LE) is 0.254mm, which is 26%, 31% and 34% of the FISTA (0.961), IVTCG (0.81) and L1-TV (0.739) methods, and the root mean square error (RMSE) and relative intensity error (RIE) are the smallest, indicating that it is closest to the real light source. In addition, compared with the other three methods, the PCG-logTV method also has the highest DICE similarity coefficient, which is 0.928, which means that this method can effectively reconstruct the three-dimensional spatial distribution of bioluminescent light sources, has higher resolution and robustness, and is beneficial to the preclinical and clinical studies of BLT.

Epidemiology of human papillomavirus on condyloma acuminatum in Shandong Province，China

Condyloma acuminatum (CA) is a sexually transmitted disease (STD) caused by human papillomavirus (HPV) infection. It is important to study the prevalence and distribution of HPV genotypes before implementing the HPV vaccination program. Therefore, the aim of this study was to evaluate the epidemiological characteristics of CA cases and the distribution of HPV genotypes in Shandong Province, China. One-to-one questionnaire surveys were conducted on all patients diagnosed with CA in sentinel hospitals from Shandong Province, China. HPV genotypes were determined using the polymerase chain reaction (PCR)-reverse dot blot hybridization method. The study enrolled 1185 patients (870 males and 315 females) and found that CA patients are mainly males and sexually active people between the ages of 20 and 40. Recurrence occurred in 34.7% patients. Among the 880 CA patients who underwent HPV typing, the HPV test positivity rate was 91.4%. In these cases, low-risk (LR) HPV infection was predominant, with an infection rate of 91.3%, while high-risk (HR) HPV genotypes were found in 53.5% patients. The most frequent HPV genotypes encountered were HPV6 (57.8%), HPV11 (37.2%), HPV16 (13.7%), and HPV42 (10.3%). HPV6 and/or HPV11 are the main infections in all patients, and more than half of the patients are coinfected with HR-HPV. However, unlike other regions, HPV42 has a higher prevalence rate among CA patients in Shandong Province and is a nonvaccine HPV genotype. Therefore, regular HPV typing helps to understand the characteristics of specific genotypes and the choice of the best type for vaccine coverage.

Self-Supervised Triplet Contrastive Learning for Classifying Endometrial Histopathological Images

Early identification of endometrial cancer or precancerous lesions from histopathological images is crucial for precise endometrial medical care, which however is increasing hampered by the relative scarcity of pathologists. Computer-aided diagnosis (CAD) provides an automated alternative for confirming endometrial diseases with either feature-engineered machine learning or end-to-end deep learning (DL). In particular, advanced self-supervised learning alleviates the dependence of supervised learning on large-scale human-annotated data and can be used to pre-train DL models for specific classification tasks. Thereby, we develop a novel self-supervised triplet contrastive learning (SSTCL) model for classifying endometrial histopathological images. Specifically, this model consists of one online branch and two target branches. The second target branch includes a simple yet powerful augmentation module named random mosaic masking (RMM), which functions as an effective regularization by mapping the features of masked images close to those of intact ones. Moreover, we add a bottleneck Transformer (BoT) model into each branch as a self-attention module to learn the global information by considering both content information and relative distances between features at different locations. On public endometrial dataset, our model achieved four-class classification accuracies of 77.31 ± 0.84, 80.87 ± 0.48 and 83.22 ± 0.87% using 20, 50 and 100% labeled images, respectively. When transferred to the in-house dataset, our model obtained a three-class diagnostic accuracy of 96.81% with 95% confidence interval of 95.61-98.02%. On both datasets, our model outperformed state-of-the-art supervised and self-supervised methods. Our model may help pathologists to automatically diagnose endometrial diseases with high accuracy and efficiency using limited human-annotated histopathological images.

Hyperon Polarization along the Beam Direction Relative to the Second and Third Harmonic Event Planes in Isobar Collisions at sqrt[s_{NN}]=200 GeV

The polarization of Λ and Λ[over ¯] hyperons along the beam direction has been measured relative to the second and third harmonic event planes in isobar Ru+Ru and Zr+Zr collisions at sqrt[s_{NN}]=200  GeV. This is the first experimental evidence of the hyperon polarization by the triangular flow originating from the initial density fluctuations. The amplitudes of the sine modulation for the second and third harmonic results are comparable in magnitude, increase from central to peripheral collisions, and show a mild p_{T} dependence. The azimuthal angle dependence of the polarization follows the vorticity pattern expected due to elliptic and triangular anisotropic flow, and qualitatively disagrees with most hydrodynamic model calculations based on thermal vorticity and shear induced contributions. The model results based on one of existing implementations of the shear contribution lead to a correct azimuthal angle dependence, but predict centrality and p_{T} dependence that still disagree with experimental measurements. Thus, our results provide stringent constraints on the thermal vorticity and shear-induced contributions to hyperon polarization. Comparison to previous measurements at RHIC and the LHC for the second-order harmonic results shows little dependence on the collision system size and collision energy.

[Study on formulation and revision of standard limits for inhalable particulate matter (PM10) and fine particulate matter (PM2.5) in "Standards for indoor air quality（GB/T 18883-2022）" in China]

The pollution and health effects of indoor inhalable particulate matter (PM10) and fine particulate matter (PM2.5) are increasingly receiving public attention. The"Standards for indoor air quality (GB/T 18883-2022)"has revised the standard limit for PM10 and added the standard limit for PM2.5. This study analyzed and interpreted the relevant technical contents of the revision of the standard limits for two indicators, including the exposure status, health effects, and the basis for the determination of the limit value. It also proposed prospects for the future development and revision of standard limits for indoor particulate matters.

Temporal Structures in Positron Spectra and Charge-Sign Effects in Galactic Cosmic Rays

We present the precision measurements of 11 years of daily cosmic positron fluxes in the rigidity range from 1.00 to 41.9 GV based on 3.4×10^{6} positrons collected with the Alpha Magnetic Spectrometer (AMS) aboard the International Space Station. The positron fluxes show distinctly different time variations from the electron fluxes at short and long timescales. A hysteresis between the electron fluxes and the positron fluxes is observed with a significance greater than 5σ at rigidities below 8.5 GV. On the contrary, the positron fluxes and the proton fluxes show similar time variation. Remarkably, we found that positron fluxes are modulated more than proton fluxes with a significance greater than 5σ for rigidities below 7 GV. These continuous daily positron fluxes, together with AMS daily electron, proton, and helium fluxes over an 11-year solar cycle, provide unique input to the understanding of both the charge-sign and mass dependencies of cosmic rays in the heliosphere.

Radiation Induced Lung Injury in Rats after Pre-Oxygenation Radiotherapy

PURPOSE/OBJECTIVE(S)

Deep inspiratory breath holding (DIBH) has been widely used during the radiotherapy of thoracic tumors. The main disadvantage of voluntary DIBH is the short duration of each breath hold. The hypocapnia induced by hyperoxia (oxygen concentration > 50%) pre-oxygenation (PreO2) combined with mechanical hyperventilation has been reported to prolong the duration of single breath hold, but its safety remains controversial, especially the sensitivity of lung tissue to radiation damage under hyperoxia exposure has not been elucidated. In this study, we aim to investigate the changes of radiation induced lung injury in rats after PreO2 radiation.

MATERIALS/METHODS

We evaluated the lung tissue of rats at different time points (48h, 2w, 4w, 8w, 12w) after thoracic radiation (15Gy single fraction to the right lung), and sequenced the transcriptome of lung tissue at 48 hours after irradiation. Rat cohorts (n = 7/group): 1. Control (Con); 2. Radiation group (RT); 3. Pre-oxygenation (oxygen concentration > 90%) for 8 hours before thoracic radiation (PreO2).

RESULTS

The inflammatory exudation emerged in the pulmonary interstitium at 48 hours, and reached the most serious alveolitis after four weeks of irradiation (the comparison of alveolitis scores in RT4w vs Con4w and PreO2(4w) vs Con4w, P<0.001) on hematoxylin-eosin staining. While the alveolitis scores in RT group and PreO2 group were not statistically different at each time point. Masson staining showed that the pulmonary fibrosis in the RT group and the PreO2 group reached an obvious pathological change at 12 weeks after irradiation, but the difference between the two groups was not significant. Transcriptome sequencing showed that the number of differential genes in PreO2 vs Con was 559 (302 up-regulated genes and 257 down-regulated genes). The GO enrichment analysis indicated that chromosome segregation was the most significant functional item with P value in the comparative analysis, and the KEGG enrichment analysis suggested that cell division was the most significant enrichment pathway of these differential genes. While there was a small quantity of differential genes in PreO2 vs RT group (3 up-regulated genes and 12 down-regulated genes). Pentose and glucuronate conversions were the most significant enrichment pathway of these differential genes.

CONCLUSION

This study demonstrated that PreO2 radiotherapy did not increase the severity of radiation induced lung injury in rats compared to conventional radiotherapy. Further study should be conducted to confirm these results and to investigate the regulatory mechanism of pneumonia caused by PreO2 radiotherapy.

Regularized reconstruction based on joint smoothly clipped absolute deviation regularization and graph manifold learning for fluorescence molecular tomography

Objective.Fluorescence molecular tomography (FMT) is an optical imaging modality that provides high sensitivity and low cost, which can offer the three-dimensional distribution of biomarkers by detecting the fluorescently labeled probe noninvasively. In the field of preclinical cancer diagnosis and treatment, FMT has gained significant traction. Nonetheless, the current FMT reconstruction results suffer from unsatisfactory morphology and location accuracy of the fluorescence distribution, primarily due to the light scattering effect and the ill-posed nature of the inverse problem.Approach.To address these challenges, a regularized reconstruction method based on joint smoothly clipped absolute deviation regularization and graph manifold learning (SCAD-GML) for FMT is presented in this paper. The SCAD-GML approach combines the sparsity of the fluorescent sources with the latent manifold structure of fluorescent source distribution to achieve more accurate and sparse reconstruction results. To obtain the reconstruction results efficiently, the non-convex gradient descent iterative method is employed to solve the established objective function. To assess the performance of the proposed SCAD-GML method, a comprehensive evaluation is conducted through numerical simulation experiments as well asin vivoexperiments.Main results.The results demonstrate that the SCAD-GML method outperforms other methods in terms of both location and shape recovery of fluorescence biomarkers distribution.Siginificance.These findings indicate that the SCAD-GML method has the potential to advance the application of FMT inin vivobiological research.

Osteogenesis and osteoclastogenesis on a chip: Engineering a self-assembling 3D coculture

Healthy bone is maintained by the process of bone remodeling. An unbalance in this process can lead to pathologies such as osteoporosis which are often studied with animal models. However, data from animals have limited power in predicting the results that will be obtained in human clinical trials. In search for alternatives to animal models, human in vitro models are emerging as they address the principle of reduction, refinement, and replacement of animal experiments (3Rs). At the moment, no complete in vitro model for bone-remodeling exists. Microfluidic chips offer great possibilities, particularly because of the dynamic culture options, which are crucial for in vitro bone formation. In this study, a scaffold free, fully human, 3D microfluidic coculture model of bone remodeling is presented. A bone-on-a-chip coculture system was developed in which human mesenchymal stromal cells differentiated into the osteoblastic lineage and self-assembled into scaffold free bone-like tissues with the shape and dimensions of human trabeculae. Human monocytes were able to attach to these tissues and to fuse into multinucleated osteoclast-like cells, establishing the coculture. Computational modeling was used to determine the fluid flow induced shear stress and strain in the formed tissue. Furthermore, a set-up was developed allowing for long-term (35 days) on-chip cell culture with benefits including continuous fluid-flow, low bubble formation risk, easy culture medium exchange inside the incubator and live cell imaging options. This on-chip coculture is a crucial advance towards developing in vitro bone remodeling models to facilitate drug testing.

Sparse reconstruction based on dictionary learning and group structure strategy for cone-beam X-ray luminescence computed tomography

As a dual-modal imaging technology that has emerged in recent years, cone-beam X-ray luminescence computed tomography (CB-XLCT) has exhibited promise as a tool for the early three-dimensional detection of tumors in small animals. However, due to the challenges imposed by the low absorption and high scattering of light in tissues, the CB-XLCT reconstruction problem is a severely ill-conditioned inverse problem, rendering it difficult to obtain satisfactory reconstruction results. In this study, a strategy that utilizes dictionary learning and group structure (DLGS) is proposed to achieve satisfactory CB-XLCT reconstruction performance. The group structure is employed to account for the clustering of nanophosphors in specific regions within the organism, which can enhance the interrelation of elements in the same group. Furthermore, the dictionary learning strategy is implemented to effectively capture sparse features. The performance of the proposed method was evaluated through numerical simulations and in vivo experiments. The experimental results demonstrate that the proposed method achieves superior reconstruction performance in terms of location accuracy, target shape, robustness, dual-source resolution, and in vivo practicability.

FISTA-NET: Deep Algorithm Unrolling for Cerenkov luminescence tomography

Cerenkov luminescence tomography (CLT) is a highly sensitive and promising imaging technique that can be used to reconstruct the three-dimensional distribution of radioactive probes in living animals. However, the accuracy of CLT reconstruction is limited by the simplified radiative transfer equation and ill-conditioned inverse problem. To address this issue, we propose a model-based deep learning network that combines the neural network with a model-based approach to enhance the performance of CLT reconstruction. The Fast Iterative Shrinkage Thresholding Algorithm (FISTA), a traditional model-based approach, is expanded into a deep network (known as FISTA-NET). Each layer in the network represents an iteration of the algorithm steps, and connecting these layers can form a deep neural network. In addition, different from the traditional FISTA, the key parameters in FISTA, such as gradient step size and threshold value, can be learned through training data without manual production. To evaluate the performance of FISTA-NET, numerical simulation experiments were conducted, which demonstrate its excellent positioning and shape recovery abilities.Clinical Relevance-This indicates that FISTA-NET strategy can significantly improve the quality of CLT reconstruction, which is further beneficial to the assessment of disease activity and treatment effect based on CLT.

Consistent Learning-Based Breast Tumor Segmentation and Its Application in Sentinel Lymph Node Metastasis Prediction

Accurate staging of lymph nodes provides crucial diagnostic information for breast cancer patients, where segmentation is of great importance by localizing and visualizing the breast tumor of interest. Nevertheless, current segmentation methods perform average when facing large span of tumor sizes, degraded image quality, blurred tumor boundaries, and resulting noise during manual annotation. Therefore, we develop a Multi-scale RepVGG-based Segmentation Network (MPSegNet) to segment breast tumor from MR images. In particular, we construct a consistent learning framework for the MPSegNet to alleviate the impact of noisy labels upon segmentation results. The rationale is that different views covering the same breast tumors are supposed to generate identical segmentation predictions. Then, we predict SLN metastasis given segmented breast tumors, where we evaluate the relationships between the predictive performance and tumor segmentations under different consistencies. The results show the superiority of our method over other state-of-the-art methods. A high consistency among multiple views can boost the segmentation performance during consistent learning. However, the optimal segmentation does not produce the best SLN metastatic prediction results, implying that the dependence of classification upon segmentation needs to be elaborately investigated further.Clinical Relevance- This study facilitates more accurate segmentation of breast tumors with consistent learning, and provides an initial analysis between tumor segmentation and subsequent prediction of SLN metastasis, which has potential significance for the precise medical care of breast cancer patients.

Regularization parameter based on incomplete variables for X-ray luminescence computed tomography

X-ray luminescence computed tomography (XLCT) is an emerging molecular imaging technique for biological application. However, it is still a challenge to get a stable and accurate solution of the reconstruction of XLCT. This paper presents a regularization parameter selection strategy based on incomplete variables frame for XLCT. A residual information, which is derived from Karush-Kuhn-Tucker (KKT) equivalent condition, is employed to determine the regularization parameter. This residual contains the relevant information about the solution norm and gradient norm, which improved the recovered results. Simulation and phantom experiments are designed to test the performance of the algorithm.Clinical Relevance- The results have not yet been used in clinical relevance currently, we believed that this strategy will facilitate the development of the preclinical applications in FMT.

Assessing the Role of Different Heterogeneous Regions in DCE-MRI for Predicting Molecular Subtypes of Breast Cancer based on Network Architecture Search and Vision Transformer

Breast cancer, the most common female malignancy, is highly heterogeneous, manifesting as different molecular subtypes. It is clinically important to distinguish between these molecular subtypes due to marked differences in prognosis, treatment and survival outcomes. In this study, we first performed convex analysis of mixtures (CAM) analysis on both intratumoral and peritumoral regions in DCE-MRI to generate multiple heterogeneous regions. Then, we developed a vision transformer (ViT)-based DL model and performed network architecture search (NAS) to evaluate all the combination of different heterogeneous regions for predicting molecular subtypes of breast cancer. Experimental results showed that the input plasma from both peritumoral and intratumoral regions, and the fast-flow kinetics from intratumoral regions were critical for predicting different molecular subtypes, achieving an area under receiver operating characteristic curve (AUROC) value of 0.66-0.68.Clinical Relevance- This study reduces the redundancy in multiple heterogeneous subregions and supports the precise prediction of molecular subtypes, which is of potential importance for the medicine care and treatment planning of patients with breast cancer.

Measurements of the Elliptic and Triangular Azimuthal Anisotropies in Central ^{3}He+Au, d+Au and p+Au Collisions at sqrt[s_{NN}]=200 GeV

The elliptic (v_{2}) and triangular (v_{3}) azimuthal anisotropy coefficients in central ^{3}He+Au, d+Au, and p+Au collisions at sqrt[s_{NN}]=200  GeV are measured as a function of transverse momentum (p_{T}) at midrapidity (|η|<0.9), via the azimuthal angular correlation between two particles both at |η|<0.9. While the v_{2}(p_{T}) values depend on the colliding systems, the v_{3}(p_{T}) values are system independent within the uncertainties, suggesting an influence on eccentricity from subnucleonic fluctuations in these small-sized systems. These results also provide stringent constraints for the hydrodynamic modeling of these systems.

Frequency importance analysis for chemical exchange saturation transfer magnetic resonance imaging using permuted random forest

Chemical exchange saturation transfer magnetic resonance imaging (CEST MRI) is a promising molecular imaging tool that allows sensitive detection of endogenous metabolic changes. However, because the CEST spectrum does not display a clear peak like MR spectroscopy, its signal interpretation is challenging, especially under 3-T field strength or with a large saturation B₁ . Herein, as an alternative to conventional Z-spectral fitting approaches, a permuted random forest (PRF) method is developed to determine featured saturation frequencies for lesion identification, so-called CEST frequency importance analysis. Briefly, voxels in the CEST dataset were labeled as lesion and control according to multicontrast MR images. Then, by considering each voxel's saturation signal series as a sample, a permutation importance algorithm was employed to rank the contribution of saturation frequency offsets in the differentiation of lesion and normal tissue. Simulations demonstrated that PRF could correctly determine the frequency offsets (3.5 or -3.5 ppm) for classifying two groups of Z-spectra, under a range of B₀ , B₁ conditions and sample sizes. For ischemic rat brains, PRF only displayed high feature importance around amide frequency at 2 h postischemia, reflecting that the pH changes occurred at an early stage. By contrast, the data acquired at 24 h postischemia exhibited high feature importance at multiple frequencies (amide, water, and lipids), which suggested the complex tissue changes that occur during the later stages. Finally, PRF was assessed using 3-T CEST data from four brain tumor patients. By defining the tumor region on amide proton transfer-weighted images, PRF analysis identified different CEST frequency importance for two types of tumors (glioblastoma and metastatic tumor) (p < 0.05, with each image slice as a subject). In conclusion, the PRF method was able to rank and interpret the contribution of all acquired saturation offsets to lesion identification; this may facilitate CEST analysis in clinical applications, and open up new doors for comprehensive CEST analysis tools other than model-based approaches.

Observation of Directed Flow of Hypernuclei _{Λ}^{3}H and _{Λ}^{4}H in sqrt[s_{NN}]=3 GeV Au+Au Collisions at RHIC

We report here the first observation of directed flow (v_{1}) of the hypernuclei _{Λ}^{3}H and _{Λ}^{4}H in mid-central Au+Au collisions at sqrt[s_{NN}]=3  GeV at RHIC. These data are taken as part of the beam energy scan program carried out by the STAR experiment. From 165×10^{6} events in 5%-40% centrality, about 8400 _{Λ}^{3}H and 5200 _{Λ}^{4}H candidates are reconstructed through two- and three-body decay channels. We observe that these hypernuclei exhibit significant directed flow. Comparing to that of light nuclei, it is found that the midrapidity v_{1} slopes of _{Λ}^{3}H and _{Λ}^{4}H follow baryon number scaling, implying that the coalescence is the dominant mechanism for these hypernuclei production in the 3 GeV Au+Au collisions.

Properties of Cosmic-Ray Sulfur and Determination of the Composition of Primary Cosmic-Ray Carbon, Neon, Magnesium, and Sulfur: Ten-Year Results from the Alpha Magnetic Spectrometer

We report the properties of primary cosmic-ray sulfur (S) in the rigidity range 2.15 GV to 3.0 TV based on 0.38×10^{6} sulfur nuclei collected by the Alpha Magnetic Spectrometer experiment (AMS). We observed that above 90 GV the rigidity dependence of the S flux is identical to the rigidity dependence of Ne-Mg-Si fluxes, which is different from the rigidity dependence of the He-C-O-Fe fluxes. We found that, similar to N, Na, and Al cosmic rays, over the entire rigidity range, the traditional primary cosmic rays S, Ne, Mg, and C all have sizeable secondary components, and the S, Ne, and Mg fluxes are well described by the weighted sum of the primary silicon flux and the secondary fluorine flux, and the C flux is well described by the weighted sum of the primary oxygen flux and the secondary boron flux. The primary and secondary contributions of the traditional primary cosmic-ray fluxes of C, Ne, Mg, and S (even Z elements) are distinctly different from the primary and secondary contributions of the N, Na, and Al (odd Z elements) fluxes. The abundance ratio at the source for S/Si is 0.167±0.006, for Ne/Si is 0.833±0.025, for Mg/Si is 0.994±0.029, and for C/O is 0.836±0.025. These values are determined independent of cosmic-ray propagation.

Generalized conditional gradient method with adaptive regularization parameters for fluorescence molecular tomography

Fluorescence molecular tomography (FMT) is an optical imaging technology with the ability of visualizing the three-dimensional distribution of fluorescently labelled probes in vivo. However, due to the light scattering effect and ill-posed inverse problems, obtaining satisfactory FMT reconstruction is still a challenging problem. In this work, to improve the performance of FMT reconstruction, we proposed a generalized conditional gradient method with adaptive regularization parameters (GCGM-ARP). In order to make a tradeoff between the sparsity and shape preservation of the reconstruction source, and to maintain its robustness, elastic-net (EN) regularization is introduced. EN regularization combines the advantages of L₁-norm and L₂-norm, and overcomes the shortcomings of traditional L_p-norm regularization, such as over-sparsity, over-smoothness, and non-robustness. Thus, the equivalent optimization formulation of the original problem can be obtained. To further improve the performance of the reconstruction, the L-curve is adopted to adaptively adjust the regularization parameters. Then, the generalized conditional gradient method (GCGM) is used to split the minimization problem based on EN regularization into two simpler sub-problems, which are determining the direction of the gradient and the step size. These sub-problems are addressed efficiently to obtain more sparse solutions. To assess the performance of our proposed method, a series of numerical simulation experiments and in vivo experiments were implemented. The experimental results show that, compared with other mathematical reconstruction methods, GCGM-ARP method has the minimum location error (LE) and relative intensity error (RIE), and the maximum dice coefficient (Dice) in the case of different sources number or shape, or Gaussian noise of 5%-25%. This indicates that GCGM-ARP has superior reconstruction performance in source localization, dual-source resolution, morphology recovery, and robustness. In conclusion, the proposed GCGM-ARP is an effective and robust strategy for FMT reconstruction in biomedical application.

Beam Energy Dependence of Triton Production and Yield Ratio (N_{t}×N_{p}/N_{d}^{2}) in Au+Au Collisions at RHIC

We report the triton (t) production in midrapidity (|y|<0.5) Au+Au collisions at sqrt[s_{NN}]=7.7-200  GeV measured by the STAR experiment from the first phase of the beam energy scan at the Relativistic Heavy Ion Collider. The nuclear compound yield ratio (N_{t}×N_{p}/N_{d}^{2}), which is predicted to be sensitive to the fluctuation of local neutron density, is observed to decrease monotonically with increasing charged-particle multiplicity (dN_{ch}/dη) and follows a scaling behavior. The dN_{ch}/dη dependence of the yield ratio is compared to calculations from coalescence and thermal models. Enhancements in the yield ratios relative to the coalescence baseline are observed in the 0%-10% most central collisions at 19.6 and 27 GeV, with a significance of 2.3σ and 3.4σ, respectively, giving a combined significance of 4.1σ. The enhancements are not observed in peripheral collisions or model calculations without critical fluctuation, and decreases with a smaller p_{T} acceptance. The physics implications of these results on the QCD phase structure and the production mechanism of light nuclei in heavy-ion collisions are discussed.

[Association of hs-CRP with frailty and its components among the elderly over 65 years old in 9 longevity areas of China]

Objective: To investigate the association of the levels of high sensitivity C-reactive protein (hs-CRP) with frailty and its components among the elderly over 65 years old in 9 longevity areas of China. Methods: Cross-sectional data from the Health Ageing and Biomarkers Cohort Study (HABCS, 2017-2018) were used and the elderly over 65 years old were included in this study. Through questionnaire interview and physical examination, the information including demographic characteristics, behavior, diet, daily activity, cognitive function, and health status was collected. The association between hs-CRP and frailty and its components in the participants was analyzed by multivariate logistic regression model and restrictive cubic spline. Results: A total of 2 453 participants were finally included, the age was (84.8±19.8) years old. The median hs-CRP level was 1.13 mg/L and the prevalence of frailty was 24.4%. Compared with the low-level group (hs-CRP<1.0 mg/L), the OR (95%CI) value of the high-level group (hs-CRP>3.0 mg/L) was 1.79 (1.35-2.36) mg/L. As for the components, the hs-CRP level was also positively associated with ADL disability, IADL disability, functional limitation and multimorbidity. After adjusting for confounding factors, compared with the low-level group, the OR (95%CI) values of the high-level group for the four components were 1.68 (1.25-2.27), 1.88 (1.42-2.50), 1.68 (1.31-2.14) and 1.39 (1.12-1.72), respectively. Conclusion: There is a positive association between the levels of hs-CRP and the risk of frailty among the elderly over 65 years old in 9 longevity areas of China. The higher hs-CRP level may increase the risk of frailty by elevating the risk of four physical functional disabilities, namely ADL disability, IADL disability, functional limitation and multimorbidity.

Temporal Structures in Electron Spectra and Charge Sign Effects in Galactic Cosmic Rays

We present the precision measurements of 11 years of daily cosmic electron fluxes in the rigidity interval from 1.00 to 41.9 GV based on 2.0×10^{8} electrons collected with the Alpha Magnetic Spectrometer (AMS) aboard the International Space Station. The electron fluxes exhibit variations on multiple timescales. Recurrent electron flux variations with periods of 27 days, 13.5 days, and 9 days are observed. We find that the electron fluxes show distinctly different time variations from the proton fluxes. Remarkably, a hysteresis between the electron flux and the proton flux is observed with a significance of greater than 6σ at rigidities below 8.5 GV. Furthermore, significant structures in the electron-proton hysteresis are observed corresponding to sharp structures in both fluxes. This continuous daily electron data provide unique input to the understanding of the charge sign dependence of cosmic rays over an 11-year solar cycle.

[A case of malignant peritoneal mesothelioma]

Malignant mesothelioma is a highly malignant disease that most often occurs in the pleural cavity, followed by the peritoneum and pericardium. Malignant peritoneal mesothelioma (MPM) accounts for 10%-15% of all mesothelioma. The most important risk factor for MPM is exposure to asbestos. MPM has no specific clinical symptoms, imaging and histopathology are critical for the diagnosis. There are currently no generally accepted guidelines for curative treatment of MPM. The patient mainly presented with abdominal pain, abdominal distension and discomfort. Due to extensive omentum metastasis, no further surgical treatment was performed. Pemetrexed combined with cisplatin chemotherapy was given for 2 cycles, and the patient is still alive.

Seasonal differences in the spatial patterns of wildfire drivers and susceptibility in the southwest mountains of China

Wildfires directly affect global ecosystem stability and severely threaten human life. The mountainous areas of Southwest China experience frequent wildfires. Mapping the susceptibility patterns and analyzing the drivers of wildfires are crucial for effective wildfire management, especially considering that the inclusion of seasonal dimensions will produce more dynamic results. Using Yunnan Province of China as a case study area, a method was attempted to distinguish dependable wildfires by season, while possible wildfire drivers were obtained and refined within seasons. The patterns of wildfire susceptibility in different seasons were modeled based on the Maxent and random forest models. Then, the spatial relationships between wildfire and potential drivers were analyzed integrating with GeoDetector to evaluate the variable importance of drivers and the marginal effect of drivers. The results showed that the two models effectively depicted each season's wildfire susceptibility. The susceptible wildfire areas in spring and winter are located throughout Yunnan Province, with anthropogenic factors being the most significant drivers. During the summer and autumn, wildfire risk areas are relatively concentrated, showing a trend of dominant drought-driven and humid conditions. The differences in wildfire drivers across seasons reflect the lagged effect of climate factors on wildfires, leading to significant discrepancies in the marginal effects of how seasonal drivers affect wildfires. The findings improve our understanding of the effects of the interseasonal variability of environmental variables on wildfires and promote the development of specific seasonal wildfire management strategies.

A 2-Stage Root Analog Implant with Compact Structure, Uniform Roughness, and High Accuracy

Immediate implant placement has the advantages of shortening the operation time, reducing the treatment cycle and cost. At present, this technology has been used widely, but the indications of immediate implantation are still limited. Here, a novel type of root analog implant (RAI) was manufactured by selective laser melting technology to address the limitation. Under optimized condition, RAIs were printed with the internal density of 99.73% and the uniform surface roughness of 11 μm (Sa). Besides, the deviation between RAI specimen and design models is controlled within 0.15 mm after optimizing scanning parameters. The substrate printed could promote human bone marrow stromal cell proliferation, spreading, and osteogenic differentiation. The bone-implant contact (BIC, 75% ± 7%) and bone volume/total volume (BV/TV, 74% ± 7%) of RAIs were significantly higher than that of conventional implants (BIC, 66% ± 5%; BV/TV, 62% ± 5%) in in vivo experiments. Further, customized abutments were designed for the RAIs, improving the masticatory ability of the beagle dogs after crown restoration. This study aims to design a personalized 2-stage RAI with compact structure and uniform roughness, in order to achieve better fracture resistance, initial osseointegration efficiency, and dispersed stress in immediate implantation. It provides a certain guiding value for standardizing the manufacture and clinical application of RAI in immediate implantation.

First-in-human, phase I study of AK109, an anti-VEGFR2 antibody in patients with advanced or metastatic solid tumors

BACKGROUND

Vascular endothelial growth factor receptor 2 (VEGFR2) plays a key role in antiangiogenesis which has been an essential strategy for cancer treatment. We report the first-in-human study of AK109, a novel anti-VEGFR2 monoclonal antibody, to characterize the safety profile and pharmacokinetics/pharmacodynamics (PK/PD) properties, and explore the preliminary antitumor efficacy in patients with solid tumors.

PATIENTS AND METHODS

This was a multicenter, open-label, phase I study, including dose escalation and dose expansion (NCT04547205). Patients with advanced cancers were treated 2 and 3 weekly with escalating doses of AK109. A 3 + 3 design was used to determine the maximum tolerated dose. Blood was sampled for PK/PD analysis. The primary endpoint was safety and recommended phase II dose (RP2D).

RESULTS

A total of 40 patients were enrolled. No dose-limiting toxicity was observed. However, 38 patients reported treatment-related adverse events (TRAEs); grade ≥3 TRAEs occurred in 10 patients. The most common TRAEs were proteinuria (n = 24, 60%), hypertension (n = 13, 32.5%), increased aspartate transaminase (n = 11, 27.5%), thrombopenia (n = 10, 25%), and anemia (n = 10, 25%). A total of 28 patients (70%) reported adverse events of special interest (AESIs). The most common AESIs were proteinuria (60%), hypertension (32.5%), and hemorrhage (32.5%), mainly including gum bleeding and urethrorrhagia. AK109 exhibited an approximately linear PK exposure with dose escalation at 2-12 mg/kg. PD analyses showed rapid target engagement. Among the 40 patients, 4 achieved partial response and 21 achieved stable disease with an objective response rate of 10% and a disease control rate of 62.5%. Based on the safety profile, the PK/PD profile, and preliminary antitumor activities, 12 mg/kg Q2W and 15 mg/kg Q3W were selected as RP2D.

CONCLUSIONS

AK109 showed manageable safety profile and promising antitumor activity, supporting further clinical development in a large population.

Automatic deep learning method for detection and classification of breast lesions in dynamic contrast-enhanced magnetic resonance imaging

Background

The purpose of this study was to develop a deep learning-based system with a cascade feature pyramid network for the detection and classification of breast lesions in dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI).

Methods

This retrospective study enrolled 191 consecutive patients with pathological confirmed breast lesions who underwent preoperative magnetic resonance imaging (MRI) at the Second Affiliated Hospital of Xi'an Jiaotong University. Patients were randomly divided into a training set comprising 153 patients with 126 malignant and 27 benign lesions and a validation set containing 38 patients with 31 malignant and 7 benign lesions under 5-fold cross-validation. Two radiologists annotated the location and classification of all lesions. After augmentation with pseudo-color image fusion, MRI images were fed into the developed cascade feature pyramid network system, feature pyramid network, and faster region-based convolutional neural network (CNN) for breast lesion detection and classification, respectively. The performance on large (>2 cm) and small (≤2 cm) breast lesions was further evaluated. Average precision (AP), mean AP, F1-score, sensitivity, and false positives were used to evaluate different systems. Cohen's kappa scores were calculated to assess agreement between different systems, and Student's t-test and the Holm-Bonferroni method were used to compare multiple groups.

Results

The cascade feature pyramid network system outperformed the other systems with a mean AP and highest sensitivity of 0.826±0.051 and 0.970±0.014 (at 0.375 false positives), respectively. The F1-score of the cascade feature pyramid network in real detection was also superior to that of the other systems at both the slice and patient levels. The mean AP values of the cascade feature pyramid network reached 0.779±0.152 and 0.790±0.080 in detecting large and small lesions, respectively. Especially for small lesions, the cascade feature pyramid network achieved the best performance in detecting benign and malignant breast lesions at both the slice and patient levels.

Conclusions

The deep learning-based system with the developed cascade feature pyramid network has the potential to detect and classify breast lesions on DCE-MRI, especially small lesions.

[Association between urinary arsenic level and serum testosterone in Chinese men aged 18 to 79 years]

Objective: To investigate the association between the urinary arsenic level and serum total testosterone in Chinese men aged 18 to 79 years. Methods: A total of 5 048 male participants aged 18 to 79 years were recruited from the China National Human Biomonitoring (CNHBM) from 2017 to 2018. Questionnaires and physical examinations were used to collect information on demographic characteristics, lifestyle, food intake frequency and health status. Venous blood and urine samples were collected to detect the level of serum total testosterone, urine arsenic and urine creatinine. Participants were divided into three groups (low, middle, and high) based on the tertiles of creatinine-adjusted urine arsenic concentration. Weighted multiple linear regression was fitted to analyze the association of urinary arsenic with serum total testosterone. Results: The weighted average age of 5 048 Chinese men was (46.72±0.40) years. Geometric mean concentration (95%CI) of urinary arsenic, creatinine-adjusted urine arsenic and serum testosterone was 22.46 (20.08, 25.12) μg/L, 19.36 (16.92, 22.15) μg/L and 18.13 (17.42, 18.85) nmol/L, respectively. After controlling for covariates, compared with the low-level urinary arsenic group, the testosterone level of the participants in the middle-level group and the high-level group decreased gradually. The percentile ratio (95%CI) was -5.17% (-13.14%, 3.54%) and -10.33% (-15.68%, -4.63). The subgroup analysis showed that the association between the urinary arsenic level and testosterone level was more obvious in the group with BMI<24 kg/m² group (P_interaction<0.05). Conclusion: There is a negative association between the urinary arsenic level and serum total testosterone in Chinese men aged 18-79 years.

[Anti-inflammatory mechanism of Balanophora involucrata: a network pharmacology and molecular docking-based analysis and verification in lipopolysaccharide-induced RAW264.7 cells]

OBJECTIVE

To investigate the main chemical constituents of Balanophora involucrata and the mechanism of its antiinflammatory effect based on network pharmacology and molecular docking technology.

METHODS

Literature reports, Materia Medica, GeneCards and other databases were searched for anti-inflammatory compounds and their targets. String database and Cytoscape 3.7.2 software were used to obtain the protein-protein interaction (PPI) network and the drug-active ingredienttargets network and for GO and KEGG enrichment analyses. Molecular docking was performed using Auto Dock Tools 1.5.6. In an inflammatory RAW264.7 cell model induced by lipopolysaccharide (LPS), the effect of 25, 50, 100, 200 μg/mL Balanophora involucrata extract was tested on the production of inflammatory cytokines and phosphorylation level of PI3K and Akt using ELISA and Western blotting.

RESULTS

A total of 318 common targets of drugs and diseases were identified, and the core targets were Src, HSP90AA1 and PIK3CA, involving cancer, PI3K/Akt, MAPK and other signaling pathways as shown by KEGG analysis. Molecular docking showed that both the main active constituents of Balanophora involucrata could spontaneously bind to the core targets. In the inflammatory cell model, treatment with Balanophora involucrata extract significantly inhibited the production of IL-1β at the concentrations of 100 and 200 μg/mL, reduced IL-6 and TNF-α expressions at the concentrations of 50, 100, and 200 μg/mL, and lowered phosphorylation levels of PI3K and Akt proteins at the concentrations of 25, 50, 100, and 200 μg/mL (all P < 0.05).

CONCLUSIONS

The anti-inflammatory mechanism of Balanophora involucrata involves multiple targets and multiple pathways, and its effect is mediated possibly by reducing IL-1β, IL-6 and TNF-α production and inhibiting phosphorylation levels of PI3K and Akt proteins to suppress the activation of the PI3K/Akt signaling pathway.

Measurement of Sequential ϒ Suppression in Au+Au Collisions at sqrt[s_{NN}]=200 GeV with the STAR Experiment

We report on measurements of sequential ϒ suppression in Au+Au collisions at sqrt[s_{NN}]=200  GeV with the STAR detector at the Relativistic Heavy Ion Collider (RHIC) through both the dielectron and dimuon decay channels. In the 0%-60% centrality class, the nuclear modification factors (R_{AA}), which quantify the level of yield suppression in heavy-ion collisions compared to p+p collisions, for ϒ(1S) and ϒ(2S) are 0.40±0.03(stat)±0.03(sys)±0.09(norm) and 0.26±0.08(stat)±0.02(sys)±0.06(norm), respectively, while the upper limit of the ϒ(3S) R_{AA} is 0.17 at a 95% confidence level. This provides experimental evidence that the ϒ(3S) is significantly more suppressed than the ϒ(1S) at RHIC. The level of suppression for ϒ(1S) is comparable to that observed at the much higher collision energy at the Large Hadron Collider. These results point to the creation of a medium at RHIC whose temperature is sufficiently high to strongly suppress excited ϒ states.

Beam Energy Dependence of Fifth- and Sixth-Order Net-Proton Number Fluctuations in Au+Au Collisions at RHIC

We report the beam energy and collision centrality dependence of fifth and sixth order cumulants (C_{5}, C_{6}) and factorial cumulants (κ_{5}, κ_{6}) of net-proton and proton number distributions, from center-of-mass energy (sqrt[s_{NN}]) 3 GeV to 200 GeV Au+Au collisions at RHIC. Cumulant ratios of net-proton (taken as proxy for net-baryon) distributions generally follow the hierarchy expected from QCD thermodynamics, except for the case of collisions at 3 GeV. The measured values of C_{6}/C_{2} for 0%-40% centrality collisions show progressively negative trend with decreasing energy, while it is positive for the lowest energy studied. These observed negative signs are consistent with QCD calculations (for baryon chemical potential, μ_{B}≤110  MeV) which contains the crossover transition range. In addition, for energies above 7.7 GeV, the measured proton κ_{n}, within uncertainties, does not support the two-component (Poisson+binomial) shape of proton number distributions that would be expected from a first-order phase transition. Taken in combination, the hyperorder proton number fluctuations suggest that the structure of QCD matter at high baryon density, μ_{B}∼750  MeV at sqrt[s_{NN}]=3  GeV is starkly different from those at vanishing μ_{B}∼24  MeV at sqrt[s_{NN}]=200  GeV and higher collision energies.

[Observational study on peripapillary hyper-reflective ovoid mass-like structures in children and adolescents with myopia]

Objective: To investigate the correlation of peripapillary hyper-reflective ovoid mass-like structures (PHOMS) in children and adolescents with myopia and its correlation factors. Methods: It was a cross-sectional study. From September 2021 to January 2022, myopic children and adolescents aged 6-16 years treated in Wuhan Central Hospital and Renmin Hospital of Wuhan University with a myopic spherical equivalent (SE) ≥0.5 D were consecutively included. All patients underwent best corrected visual acuity, refraction, intraocular pressure, slit lamp microscope, axial length, fundus photography and enhanced depth imaging optical coherence tomography (EDI-OCT) examination. EDI-OCT optic disc parameter measurements included diameter, degree of tilt and shift and PHOMS height. The patients were divided into PHOMS group and non-PHOMS group according to the presence or absence of PHOMS. According to the height of PHOMS, the patients were further divided into 3 subgroups: large (>400 μm), medium (200-400 μm) and small (<200 μm). The optic disc characteristics of the PHOMS group and the non-PHOMS group and each subgroup were observed, and the correlation factors of PHOMS were analyzed. Mann-Whitney U test, Kruskal-Wallis test, chi-square test, Logistic regression analysis and Kendall's tau-b correlation coefficient were used. Results: A total of 108 patients (108 eyes) were included, including 46 males (46 eyes) and 62 females (62 eyes). There were 70 eyes (64.8%) in the PHOMS group and 38 eyes (35.2%) in the non-PHOMS group. Small PHOMS can only be detected by EDI-OCT, while medium to large PHOMS showed blurred optic disc boundaries on fundoscopy images. Univariate Logistic regression analysis showed that PHOMS was associated with age (OR=1.36, 95%CI: 1.13-1.65, P=0.001) and myopic SE (OR=4.57, 95%CI: 2.51-8.32, P<0.001), axial length (OR=2.28, 95%CI: 1.37-3.82, P=0.002), optic disc tilt (OR=3.44, 95%CI: 2.09-5.66, P<0.001), optic disc shift (OR=0.95, 95%CI: 0.93-0.98, P<0.001) and optic disc diameter (OR=0.75, 95%CI: 0.58-0.95, P=0.019). Multivariate Logistic regression analysis showed that the higher the myopic SE (OR=3.01, 95%CI: 1.27-7.17, P=0.013) and the greater the tilt of the optic disc (OR=4.06,95%CI:1.99-8.29,P<0.001), the higher the risk of PHOMS. Kendall's tau-b correlation coefficient analysis showed that the height of PHOMS was negatively correlated with optic disc shift (r=-0.31, P<0.001). Conclusions: PHOMS can be found in a subset of myopic children. The fundus manifestations of PHOMS of different heights are slightly different. The large myopic SE and great optic disc tilt are risk factors of PHOMS, and their magnitudes correlate with the border tissue angle.

[Association of lead exposure with stunting and underweight among children aged 3-5 years in China]

Objective: To evaluate the association of lead exposure with stunting and underweight among children aged 3-5 years in China. Methods: Data was collected from China National Human Biomonitoring (CNHBM) between January 2017 and December 2018. A total of 3 554 children aged 3-5 years were included. Demographic characteristic, lifestyle and nutritional status were collected through questionnaires. Height and weight were measured by standardized method. Stunting and underweight status were determined by calculating height for age Z-score and weight for age Z-score. Blood and urine samples were collected to detect the concentrations of blood lead, urinary lead and urinary creatinine. Children were stratified into 4 groups (Q₁ to Q₄) by quartiles of blood lead level and corrected urinary lead level, respectively. Complex sampling logistic regression models were applied to evaluate the association of the blood lead level, urinary lead level with stunting and underweight. Results: Among 3 554 children, the age was (4.09±1.06) years, of which 1 779 (80.64%) were female and 1 948 (55.84%) were urban residents. The prevalence of stunting and wasting was 7.34% and 2.96%, respectively. The M (Q₁, Q₃) for blood lead levels and urinary lead levels in children was 17.49 (12.80, 24.71) μg/L, 1.20 (0.61, 2.14) μg/g Cr, respectively. After adjusting for confounding factors, compared with the lowest blood lead concentration group Q₁, the risk of stunting gradually increased in the Q₃ and Q₄ group (P_trend=0.010), with OR (95%CI) values of 1.40 (0.80-2.46) and 1.80 (1.07-3.04), respectively. Compared with the lowest urinary lead concentration group Q₁, the risk of stunting still increased in the Q₃ and Q₄ group (P_trend=0.012), with OR (95%CI) values of 1.69 (1.01-2.84) and 1.79 (1.05-3.06), respectively. The correlation between the lead exposure and underweight was not statistically significant (P>0.05). Conclusion: Lead exposure is positively associated with the risk of stunting among children aged 3-5 years in China.

[Mediation effect of inflammatory biomarkers on the association between blood lead levels and blood pressure changes in Chinese adults]

Objective: To investigate the role of inflammatory biomarkers in the relationship between blood lead levels and blood pressure changes. Methods: A total of 9 910 people aged 18-79 years who participated in the China National Human Biomonitoring in 2017-2018 were included in this study. A self-made questionnaire was used to collect demographic characteristics, lifestyle and other information, and the data including height, weight and blood pressure were determined through physical examination. Blood and urinary samples were collected for the detection of blood lead and cadmium levels, urinary arsenic levels, white blood cells, neutrophils, lymphocytes, and hypersensitive C-reactive protein (hs-CRP). Weighted linear regression models were used to evaluate the associations between blood lead, inflammatory biomarkers and blood pressure. Mediation analysis was performed to investigate the role of inflammation in the relationship between blood lead levels and blood pressure changes. Results: The median (Q₁, Q₃) age of all participants was 45.4 (33.8, 58.4)years, including 4 984 males accounting for 50.3%. Multivariate logistic regression model analysis showed that after adjusting for age, gender, residence area, BMI, education level, smoking and drinking status, family history of hypertension, consumption frequency of rice, vegetables, and red meat, fasting blood glucose, total cholesterol, triglycerides, blood cadmium and urinary arsenic levels, there was a positive association between blood lead levels, inflammatory biomarkers and blood pressure (P<0.05). Each 2.71 μg/L (log-transformed) increase of the lead was associated with a 2.05 (95%CI: 0.58, 3.53) mmHg elevation in systolic blood pressure (SBP), 2.24 (95%CI: 1.34, 3.14) mmHg elevation in diastolic blood pressure (DBP), 0.25 (95%CI: 0.05, 0.46) mg/L elevation in hs-CRP, 0.16 (95%CI: 0.03, 0.29)×10⁹/L elevation in white blood cells, and 0.11 (95%CI: 0.02, 0.21)×10⁹/L elevation in lymphocytes, respectively. Mediation analysis showed that the levels of hs-CRP significantly mediated the association of blood lead with SBP, with a proportion about 3.88% (95%CI: 0.45%, 7.32%). The analysis also found that the levels of hs-CRP and neutrophils significantly mediated the association of blood lead with SBP, with a proportion about 4.10% (95%CI: 1.11%, 7.10%) and 2.42% (95%CI: 0.07%, 4.76%), respectively. Conclusion: This study suggests that inflammatory biomarkers could significantly mediate the association of blood lead levels and blood pressure changes.

[Association of body mass index and waist circumference with frailty among people aged 80 years and older in Chinese]

Objective: To examine the association of body mass index (BMI) and waist circumference (WC) with frailty among oldest-old adults in China. Methods: A total of 7 987 people aged 80 years and older (oldest-old) who participated in the Chinese Longitudinal Healthy Longevity Survey (CLHLS) in 2017-2018 were included. Information on demographic characteristics, behavior pattern, diet, activities of daily living, cognitive function, health status, disease condition were collected by questionnaire and physical examination. Generalized linear mixed model and restricted cubic splines (RCS) were used to analyze the association of BMI and WC with frailty. Results: The mean age of all participants was 91.7 years, and their mean BMI and WC were (21.3±3.5) kg/m² and (82.9±10.5) cm, respectively. The proportion of male was 42.3% (3 377/7 987), and the proportion of people with frailty was 33.7% (2 664/7 987). After controlling confounding factors, compared with T₂ (19.1-22.1 kg/m²) of BMI, the OR (95%CI) of the female T₁ (<19.1 kg/m²) and T₃ (≥22.2 kg/m²) group was 1.39 (1.17-1.65) and 1.27 (1.07-1.52), respectively. Compared with T₂ (77-85 cm) of WC, the OR (95%CI) of female T₁ (<77 cm) and T₃ (≥86 cm) group was 1.20 (1.01-1.42) and 1.10 (0.93-1.31), respectively. The results of multiple linear regression model with restrictive cubic spline showed that there was a non-linear association of BMI and WC with frailty in female. Conclusion: There is a U-shaped association of BMI and WC with frailty in female participants.

ABPO-TVSCAD: alternating Bregman proximity operators approach based on TVSCAD regularization for bioluminescence tomography

Objective.Bioluminescence tomography (BLT) is a promising non-invasive optical medical imaging technique, which can visualize and quantitatively analyze the distribution of tumor cells in living tissues. However, due to the influence of photon scattering effect and ill-conditioned inverse problem, the reconstruction result is unsatisfactory. The purpose of this study is to improve the reconstruction performance of BLT.Approach.An alternating Bregman proximity operators (ABPO) method based on TVSCAD regularization is proposed for BLT reconstruction. TVSCAD combines the anisotropic total variation (TV) regularization constraints and the non-convex smoothly clipped absolute deviation (SCAD) penalty constraints, to make a trade-off between the sparsity and edge preservation of the source. ABPO approach is used to solve the TVSCAD model (ABPO-TVSCAD for short). In addition, to accelerate the convergence speed of the ABPO, we adapt the strategy of shrinking the permission source region, which further improves the performance of ABPO-TVSCAD.Main results.The results of numerical simulations andin vivoxenograft mouse experiment show that our proposed method achieved superior accuracy in spatial localization and morphological reconstruction of bioluminescent source.Significance.ABPO-TVSCAD is an effective and robust reconstruction method for BLT, and we hope that this method can promote the development of optical molecular tomography.

Capacity-enhanced and kinetic-expedited zinc-ion storage ability in a Zn3V3O8/VO2 cathode enabled by heterostructural design

Heterostructured double-phase composites are promising electrode candidates for high-performance secondary metal batteries due to their superior capacity and ion transfer kinetics compared with the pristine phase. Herein, a Zn₃V₃O₈/VO₂ (ZVO/VO) heterostructure with abundant phase boundaries was designed as the cathode for aqueous zinc-ion batteries (ZIBs). The preparation method is based on a solid pre-intercalation approach, and the Zn content in the ZVO/VO heterostructure can be precisely controlled. The electrochemical performance of ZVO/VO containing different amounts of Zn, pristine ZVO, and VO phases was compared. ZVO/VO showed superior capacity and cycling stability compared to pristine ZVO and VO. The ZVO/VO heterostructure showed a capacity of 328.4 mA h g^-1 at 0.3 A g^-1 after 200 cycles. The long-term cycling performance of ZVO/VO was evaluated at 3 A g^-1, and it delivered a capacity retention of 90.5% after 1000 cycles. The ion storage mechanism of the ZVO/VO electrode was analyzed by ex situ X-ray diffraction (XRD), X-ray photoelectron spectroscopy (XPS) and scanning electron microscopy (SEM). This work provides a simple strategy for designing vanadium-based heterostructure composites as advanced cathodes for ZIBs.

Elastic net-based non-negative iterative three-operator splitting strategy for Cerenkov luminescence tomography

Cerenkov luminescence tomography (CLT) provides a powerful optical molecular imaging technique for non-invasive detection and visualization of radiopharmaceuticals in living objects. However, the severe photon scattering effect causes ill-posedness of the inverse problem, and the location accuracy and shape recovery of CLT reconstruction results are unsatisfactory for clinical application. Here, to improve the reconstruction spatial location accuracy and shape recovery ability, a non-negative iterative three operator splitting (NNITOS) strategy based on elastic net (EN) regularization was proposed. NNITOS formalizes the CLT reconstruction as a non-convex optimization problem and splits it into three operators, the least square, L_1/2-norm regularization, and adaptive grouping manifold learning, then iteratively solved them. After stepwise iterations, the result of NNITOS converged progressively. Meanwhile, to speed up the convergence and ensure the sparsity of the solution, shrinking the region of interest was utilized in this strategy. To verify the effectiveness of the method, numerical simulations and in vivo experiments were performed. The result of these experiments demonstrated that, compared to several methods, NNITOS can achieve superior performance in terms of location accuracy, shape recovery capability, and robustness. We hope this work can accelerate the clinical application of CLT in the future.

[Improvement effect of Lycium barbarum polysaccharide on the intestinal flora of pregnant rats and their offspring under chronic stress]

Objective: To understand the improvement effect of Lycium barbarum polysaccharide (LBP) on the intestinal flora of mother mice during pregnancy and their offspring who experienced chronic stress, and provide new ideas for improving the effect of stress on the intestinal tract. Methods: From July to October 2019, 24 SPF-grade female SD rats were selected and divided into control group, stress group, and stress+LBP group, with 8 rats in each group. A chronic unpredictable mild stimulation model during pregnancy was established (21 days) , and 40 mg/kg LBP solution was administered by gavage on the 8th day of stress. Venous blood from the medial canthus of the female mice was collected on the 1st day before stress and on the 1st, 7th, 14th and 21st days, respectively. Cortisol was measured and corticosterone concentration was calculated. The fresh feces of famale mice after stress and 20-day postnatal offspring mice were collected, and Illumina Miseq sequencing technology, alpha diversity and community composition were used to analyze the diversity and structure of intestinal flora. Results: On the 7th and 14th days of stress, the plasma corticosterone concentration of female mice in the stress group and stress+LBP group was higher than that in the control group (P<0.05) . In the Alpha diversity of female mice, the Ace index of the stress group was lower than that of the control group (P<0.05) . The analysis of intestinal flora structure showed that at the species level, the proportions of Lachnospiraceae and Lactobacillus in the stress+LBP group were higher than those in the stress group and control group. At the order level, the proportion of Clostridiales in the stress+LBP group was higher than that in the stress group and lower than that in the control group, while the proportion of Lactobacillales was higher than that in the stress group and control group. In the Alpha diversity of the offspring group, the Shannon index, Ace index and Chao index of the stress+LBP offspring group were higher than those of the stress offspring group (P<0.05) . The proportion of Lactobacillus in the stress+LBP offspring group was higher than that in the control offspring group and stress offspring group, and the proportions of Lachnospiraceae and Ruminococcaceae in the stress+LBP offspring group were higher than those in the stress offspring group, the proportion of Bacteroidales in the stress+LBP offspring group was lower than that in the stress offspring group, and the proportion of Clostridiales in the stress+LBP offspring group was higher than that in the stress and control offspring groups. Conclusion: The intervention of LBP may improve the changes in the intestinal flora diversity, abundance and flora structure of mother mice and offspring caused by pregnancy stress, thereby maintaining the balance of intestinal flora.

Comparison of amino acid digestibility and its additivity determined with slaughter or cecectomy method for yellow-feather chicken

The objective of this experiment was to compare the slaughter and cecectomy methods to determine amino acid (AA) digestibility of corn and soybean meal and their additivity in a corn-soybean meal diet. A completely randomized design was adopted to determine endogenous AA losses (EAAL) and AA digestibility in each of corn, soybean meal, and a corn-soybean meal diet using either slaughter or cecectomy methods. Each treatment contained 6 replicates with 3 chickens per replicate. The endogenous loss (EL) of histidine and glycine was lower and the EL of methionine and phenylalanine was greater when determined by slaughter vs. cecectomy (P < 0.05). The EL of arginine, isoleucine, leucine, lysine, methionine, phenylalanine, valine, alanine, aspartic acid, glutamic acid, and serine determined by slaughter were 1.2 to 3.2 times of those from cecectomy. The standard error (SE) of EL of 14 AA (excluding histidine and glycine) obtained by slaughter method was 2.1 to 9.6 times of those by cecectomy method. The apparent and standardized digestibility was not affected by methods for most AA except apparent digestibility of methionine, phenylalanine and glycine, and standardized digestibility of glycine in corn. The apparent and standardized digestibility of most AA except apparent digestibility of glycine and standardized digestibility of lysine, cysteine and glycine were less for slaughter versus cecectomy methods in soybean meal (P < 0.05). Using slaughter method resulted in reduced apparent digestibility of 15 AA (except glycine) and reduced standardized digestibility of 7 AA (arginine, isoleucine, leucine, valine, aspartic acid, glutamic acid, and proline) relative to cecectomy method (P < 0.05), but the standardized digestibility of glycine was greater when determined by slaughter vs. cecectomy methods in corn-soybean meal diet (P < 0.05). The mean value of SE of 16 AA digestibility in slaughter method was 2.9 times of that by cecectomy method. The apparent digestibility of 2 and 9 of 16 AA and the standardized digestibility of 15 and 7 of 16 AA were additive when using slaughter and cecectomy determinations, respectively. In conclusion, compared to the slaughter method, cecectomy method had less SE and EAAL but greater apparent digestibility of methionine and phenylalanine in corn, and the apparent digestibility of 15 AA (except glycine) in soybean meal and corn-soybean meal diet. Additivity in apparent and standardized AA digestibility was more inconsistent when determined with slaughter vs. cecectomy methods. These findings suggest that the cecectomy method is more suitable than the slaughter method to determine the digestibility of AA.