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Self-vibrating systems obtaining energy from their surroundings to sustain motion can offer great potential in micro-robots, biomedicine, radar systems, and amusement equipment owing to their adaptability, efficiency, and sustainability. However, there is a growing need for simpler, faster-responding, and easier-to-control systems. In the study, we theoretically present an advanced light-actuated liquid crystal elastomer (LCE) fiber–mass system which can initiate self-sliding motion along a rigid circular track under constant light exposure. Based on an LCE dynamic model and the theorem of angular momentum, the equations for dynamic control of the system are deduced to investigate the dynamic behavior of self-sliding. Numerical analyses show that the theoretical LCE fiber–mass system operates in two distinct states: a static state and a self-sliding state. The impact of various dimensionless variables on the self-sliding amplitude and frequency is further investigated, specifically considering variables like light intensity, initial tangential velocity, the angle of the non-illuminated zone, and the inherent properties of the LCE material. For every increment of π/180 in the amplitude, the elastic coefficient increases by 0.25% and the angle of the non-illuminated zone by 1.63%, while the light intensity contributes to a 20.88% increase. Our findings reveal that, under constant light exposure, the mass element exhibits a robust self-sliding response, indicating its potential for use in energy harvesting and other applications that require sustained periodic motion. Additionally, this system can be extended to other non-circular curved tracks, highlighting its adaptability and versatility. [ABSTRACT FROM AUTHOR]

Understanding, predicting and controlling the motion of the solid particles in the square cavity with obstacles are important. This work performs a lattice Boltzmann study on the motion of a neutrally buoyant circular particle in a lid-driven square cavity with a semicircular obstacle, where the effects of Reynolds numbers and initial positions of the circular particle on the motion of the circular particle are investigated. The motion of the circular particle is affected significantly by the semicircular obstacle, which is quite different from the case without obstacles. With the increase of the Reynolds number, the motion of the circular particle is divided into three stages. At low Reynolds numbers (5 0 0 ≤ Re ≤ 8 0 0), similar to the case without obstacles, no matter where the initial position of the circular particle is, the limit cycle of the circular particle is the same. Beyond a critical Reynolds number (between 800 and 900), the limit cycle of the circular particle is dependent on the initial position of the circular particle obviously, which is attributed to the opposing centrifugal and wall-repulsion forces. [ABSTRACT FROM AUTHOR]

Deep neural networks (DNNs) have emerged as a prominent model in medical image segmentation, achieving remarkable advancements in clinical practice. Despite the promising results reported in the literature, the effectiveness of DNNs necessitates substantial quantities of high-quality annotated training data. During experiments, we observe a significant decline in the performance of DNNs on the test set when there exists disruption in the labels of the training dataset, revealing inherent limitations in the robustness of DNNs. In this paper, we find that the neural memory ordinary differential equation (nmODE), a recently proposed model based on ordinary differential equations (ODEs), not only addresses the robustness limitation but also enhances performance when trained by the clean training dataset. However, it is acknowledged that the ODE-based model tends to be less computationally efficient compared to the conventional discrete models due to the multiple function evaluations required by the ODE solver. Recognizing the efficiency limitation of the ODE-based model, we propose a novel approach called the nmODE-based knowledge distillation (nmODE-KD). The proposed method aims to transfer knowledge from the continuous nmODE to a discrete layer, simultaneously enhancing the model's robustness and efficiency. The core concept of nmODE-KD revolves around enforcing the discrete layer to mimic the continuous nmODE by minimizing the KL divergence between them. Experimental results on 18 organs-at-risk segmentation tasks demonstrate that nmODE-KD exhibits improved robustness compared to ODE-based models while also mitigating the efficiency limitation. [ABSTRACT FROM AUTHOR]

The association between vascular calcification (VC) and kidney stone is still inconclusive. Therefore, we conducted a meta-analysis to estimate the risk of kidney stone disease in subjects with VC. To identify publications from related clinical studies, we performed a search on PubMed, Web of Science, Embase, and Cochrane Library databases from their inceptions until 1 September 2022. According to obvious heterogeneity, a random-effects model was used to calculate the odds ratios (ORs) and corresponding 95% confidence intervals (CIs). Subgroup analysis was conducted trying to dissect the effects of VC in different segments and population regions in predicting kidney stone risk. Seven articles were included with a total number of 69,135 patients, of which 10,052 have vascular calcifications and 4728 have kidney stones. There was a significantly higher risk of kidney stone disease in participants with VC versus control (OR = 1.54, 95% CI: 1.13–2.10). Sensitivity analysis confirmed the stability of the results. VC can be separated into abdominal, coronary, carotid, and splenic aortic calcification while pooled analysis of abdominal aorta calcification did not indicate a significant higher kidney stone risk. An obvious higher risk of kidney stone was observed in Asian VC patients (OR = 1.68, 95% CI: 1.07–2.61). Combined evidence of observational studies suggested patients with VC may be associated with an increased risk of kidney stone disease. Despite the predictive value was relatively low, it is still worth noting that patients with VC are under the threat of kidney stone disease. [ABSTRACT FROM AUTHOR]

With the large-scale grid integration of new energy sources, the power relationship between source and demand side is becoming more and more complex, the flexibility requirements of the distribution network are increasing, and new requirements for system safety and reliability are put forward, and it can't meet the peak regulating requirements of grid by relying solely on source side to cope with variable loads. In view of this, to make the grid operation flexibility improved by using an adjustable load capacity, the study first constructs a load classifying method on the foundation of fuzzy style K-plane clustering method to understand the interaction information of the load devices. Then the adjustable value of the load is analyzed from the demand response and standby perspectives, respectively, and an improved dynamic time-bending-based source-load similarity inscription method is proposed, which aims to unify the multiple load information obtained by clustering. The proposed clustering algorithm takes the highest value of 0.096 for the Davies-Bouldin index index, which is 0.012 and 0.014 higher than the K-plane clustering algorithm and the K-means algorithm, respectively. In addition, the load demand response regulation with the improved dynamic time bending method has a higher capacity for new energy consumption than the variance method, with a difference of 2.0 kW. This indicates that using load regulation to consume new energy to exploit the load curve will stimulate the active participation of customer-side load in maintaining power balance between the electricity consumption side and the demand side, and form an interest community between power supplying and demanding sides. [ABSTRACT FROM AUTHOR]

Triple-negative breast cancer (TNBC) accounts for 15–20% of all invasive breast cancer subtypes. Owing to its clinical characteristics, such as the lack of effective therapeutic targets, high invasiveness, and high recurrence rate, TNBC is difficult to treat and has a poor prognosis. Currently, with the accumulation of large amounts of medical data and the development of computing technology, artificial intelligence (AI), particularly machine learning, has been applied to various aspects of TNBC research, including early screening, diagnosis, identification of molecular subtypes, personalised treatment, and prediction of prognosis and treatment response. In this review, we discussed the general principles of artificial intelligence, summarised its main applications in the diagnosis and treatment of TNBC, and provided new ideas and theoretical basis for the clinical diagnosis and treatment of TNBC. [ABSTRACT FROM AUTHOR]

Object detection of overhead transmission lines is a solution for promoting inspection efficiency for power companies. However, aerial images contain many complex backgrounds and small objects, and traditional algorithms are incompetent in the identification of details of power transmission lines accurately. To address this problem, this paper develops an object detection method based on optimized You Only Look Once v5-small (YOLOv5s). This method is designed to be engineering-friendly, with the objective of maximal detection accuracy and computation simplicity. Firstly, to improve the detecting accuracy of small objects, a larger scale detection layer and jump connections are added to the network. Secondly, a self-attention mechanism is adopted to merge the feature relationships between spatial and channel dimensions, which could suppress the interference of complex backgrounds and boost the salience of objects. In addition, a small object enhanced Complete Intersection over Union (CIoU) is put forward as the loss function of the bounding box regression. This loss function could increase the derived loss for small objects automatically, thereby improving the detection of small objects. Furthermore, based on the scaling factors of batch-normalization layers, a pruning method is adopted to reduce the parameters and achieve a lightweight method. Finally, case studies are fulfilled by comparing the proposed method with classic YOLOv5s, which demonstrate that the detection accuracy is increased by 4%, the model size is reduced by 58%, and the detection speed is raised by 3.3%. [ABSTRACT FROM AUTHOR]

Background: Immunotherapy has revolutionized cancer treatment, but most patients are refractory to immunotherapy or acquire resistance, with the underlying mechanisms remaining to be explored. Methods: We characterized the transcriptomes of ~92,000 single cells from 3 pre-treatment and 12 post-treatment patients with non-small cell lung cancer (NSCLC) who received neoadjuvant PD-1 blockade combined with chemotherapy. The 12 post-treatment samples were categorized into two groups based on pathologic response: major pathologic response (MPR; n = 4) and non-MPR (NMPR; n = 8). Results: Distinct therapy-induced cancer cell transcriptomes were associated with clinical response. Cancer cells from MPR patients exhibited a signature of activated antigen presentation via major histocompatibility complex class II (MHC-II). Further, the transcriptional signatures of FCRL4+FCRL5+ memory B cells and CD16+CX3CR1+ monocytes were enriched in MPR patients and are predictors of immunotherapy response. Cancer cells from NMPR patients exhibited overexpression of estrogen metabolism enzymes and elevated serum estradiol. In all patients, therapy promoted expansion and activation of cytotoxic T cells and CD16+ NK cells, reduction of immunosuppressive Tregs, and activation of memory CD8+T cells into an effector phenotype. Tissue-resident macrophages were expanded after therapy, and tumor-associated macrophages (TAMs) were remodeled into a neutral instead of an anti-tumor phenotype. We revealed the heterogeneity of neutrophils during immunotherapy and identified an aged CCL3+ neutrophil subset was decreased in MPR patients. The aged CCL3+ neutrophils were predicted to interact with SPP1+ TAMs through a positive feedback loop to contribute to a poor therapy response. Conclusions: Neoadjuvant PD-1 blockade combined with chemotherapy led to distinct NSCLC tumor microenvironment transcriptomes that correlated with therapy response. Although limited by a small patient sample size subjected to combination therapy, this study provides novel biomarkers to predict therapy response and suggests potential strategies to overcome immunotherapy resistance. [ABSTRACT FROM AUTHOR]

Background: Limited data are currently available on protozoan parasites of the genus Sarcocystis that infect their avian hosts within the order Anseriformes (waterfowl). To date, no Sarcocystis species has been recorded in ducks in China. Methods: Leg muscles were sampled from 26 domestic ducks (Anas platyrhynchos) in China in 2021. Morphological characteristics of sarcocysts detected in the muscle tissue were described using light microscopy (LM) and transmission electron microscopy (TEM). Genomic DNA was extracted from single sarcocysts obtained from different ducks, and three genetic markers, 18S ribosomal DNA (18S rDNA), 28S ribosomal DNA (28S rDNA) and mitochondrial (mt) cytochrome oxidase subunit 1 (cox1), were amplified and cloned for sequence analyses. Results: Sarcocysts were observed by LM in only three of the 28 samples (10.7%). These sarcocysts had a thick cyst wall with numerous brush-like villar protrusions (vps) of 3.8–4.3 μm in length (n = 30) on the cyst surface. TEM observation showed that the sarcocysts had lanceolated vps. Each vps narrowed in the stalk and contained a bundle of microtubules that extended into the ground substance. Comparisons of the new sequences with those deposited in GenBank showed that the most similar sequences were those of Sarcocystishalieti in the great cormorant Phalacrocorax carbo and European starling Sturnus vulgaris, and Sarcocystis calchasi in the domestic pigeon (Columba livia) at the 18S rDNA (99.1% identity); Sarcocystiswenzeli from the domestic chicken Gallus gallus at the 28S rDNA (95.9–96.0% identity); and Sarcocystis speeri from the opossum at the mtcox1 (98.2% identity). The new 18S rDNA, 28S rDNA and mitochondrial cox1 sequences shared up to 99.0%, 95.6% and 97.7% identity, respectively, with those of Sarcocystis spp. obtained from Anseriformes avian hosts. Phylogenetic analysis inferred from the sequences of the three genetic markers placed the organism within a group of Sarcocystis spp. obtained from avian or carnivorous intermediate hosts and avian, marsupial or carnivorous definitive hosts. Based on the morphological observation and molecular analyses, the organism found in the Chinese domestic ducks was regarded as a new species and named Sarcocystis platyrhynchosi n. sp. Conclusions: Based on morphology and sequence analyses, the microcysts diagnosed in the domestic ducks examined in this study were named as a new species. This is the first record of Sarcocystis spp. from waterfowl in China. Sarcocysts of similar morphology occur frequently in different Anseriformes birds, and the relationships among these species need to be further clarified in future studies using more molecular markers. [ABSTRACT FROM AUTHOR]

When various urban functions are integrated into one location, they form a mixture of functions. The emerging big data promote an alternative way to identify mixed functions. However, current methods are largely unable to extract deep features in these data, resulting in low accuracy. In this study, we focused on recognizing mixed urban functions from the perspective of human activities, which are essential indicators of functional areas in a city. We proposed a framework to comprehensively extract deep features of human activities in big data, including activity dynamics, mobility interactions, and activity semantics, through representation learning methods. Then, integrating these features, we employed fuzzy clustering to identify the mixture of urban functions. We conducted a case study using taxi flow and social media data in Beijing, China, in which five urban functions and their correlations with land use were recognized. The mixture degree of urban functions in each location was revealed, which had a negative correlation with taxi trip distance. The results confirmed the advantages of our method in understanding mixed urban functions by employing various representation learning methods to comprehensively depict human activities. This study has important implications for urban planners in understanding urban systems and developing better strategies. [ABSTRACT FROM AUTHOR]

Exposure to fine particulate matter (PM2.5) was associated with an increased incidence of liver metabolic disease. Melatonin has been shown to prevent liver glucolipid metabolism disorders. However, whether melatonin could rescue PM2.5‐induced liver metabolic abnormalities remains uncertain. This study was to evaluate the mitigating effect of melatonin on PM2.5‐accelerated hepatic glucose metabolism imbalance in vivo and in vitro. Schiff periodic acid shiff staining and other results showed that PM2.5 led to a decrease in hepatic glycogen reserve and an increase in glucose content, which was effectively alleviated by melatonin. Targeted lipidomics is used to identify lipid biomarkers associated with this process, including glycerolipids, glycerophospholipids, and sphingolipids. In addition, gene microarray and quantitative polymerase chain reaction analysis of ApoE−/− mice liver suggested that PM2.5 activated the miR‐200a‐3p and inhibited DNAJB9, and the targeting relationship was verified by luciferase reports for the first time. Further investigation demonstrated that DNAJB9 might motivate endoplasmic reticulum (ER) stress by regulating Ca2+ homeostasis, thus altering the protein expression of GSK3B, FOXO1, and PCK2. Meanwhile, melatonin effectively inhibited miR‐200a‐3p and glucose metabolism disorder. Knockout of miR‐200a‐3p in L02 cells revealed that miR‐200a‐3p is indispensable in the damage of PM2.5 and the therapeutic effect of melatonin. In summary, melatonin alleviated PM2.5‐induced liver metabolic dysregulation by regulating ER stress via miR‐200a‐3p/DNAJB9 signaling pathway. Our data provide a prospective targeted therapy for air pollution‐related liver metabolism disorders. [ABSTRACT FROM AUTHOR]

Background. Hypoxia is one of the driving forces of cancer progression, recurrence, and metastasis. However, the association between the tumor hypoxic tumor microenvironment and the tumor mutation burden (TMB) is poorly understood in gastrointestinal cancer. Methods. Approximately 2,000 samples from colorectal cancer (CRC) and stomach adenocarcinoma (STAD) patients were obtained from the gene expression omnibus database and the cancer genome Atlas databases and were clustered and subtyped by nonnegative matrix factorization. Significant differentially expressed genes that were possibly related to survival differences between the hypoxic and normoxic groups were subjected to multivariate Cox regression. Results. Gastrointestinal cancer patients with CRC and STAD were further divided into two subgroups, namely, the hypoxia group and the normoxia group, and hypoxia was correlated with unfavorable outcomes. Notably, hypoxic tumors had lower TMB but significantly higher levels of immune and stromal infiltration. A signature of HEYL and NRP1 selected by LASSO classified gastrointestinal cancer patients into either a low or high-risk group, allowing for the combination of TMB status with markers of hypoxia in future clinical applications. Conclusions. Hypoxia is an independent prognostic factor and a strong immune infiltration indicator in gastrointestinal tumors of different organs, especially for cancers with low TMB. [ABSTRACT FROM AUTHOR]

Background: So called cell-free fetal DNA (cffDNA) in the maternal plasma, which is derived from placenta, is widely used to screen fetal aneuploidies, including trisomy 21, 18, 13 and sex chromosomes. Here we reported a case of trisomy 8 mosaicism (T8M), which was initially identified via cffDNA screening in noninvasive prenatal testing (NIPT). Methods: A 35-year-old woman received cffDNA screening at 17th week of gestation. Amniocentesis was performed subsequently, and karyotyping, single-nucleotide polymorphism array (SNP-array) and BACs-on-Beads™ (BoBs™) were used to determine fetal chromosome content. Interphase fluorescence in situ hybridization (FISH) was applied to determine the copy number of chromosome 8. Results: An enhanced risk for fetal trisomy 8 was identified by cffDNA screening in the studied pregnant woman. After amniocentesis trisomy 8 was found in 1 of 73 metaphases. SNP-array on DNA derived from cultured amniocytes and neonatal cord blood cells suggested the presence of T8M. Interphase FISH on native neonatal cord blood cells confirmed T8M with a percentage of 10%. The Bobs™ fluorescence data also suggested that 8q23-8q24 was amplified. Conclusions: The current study shows that NIPT is suited to provide hints on rare autosomal trisomies, which have to be further validated and confirmed by other approaches. [ABSTRACT FROM AUTHOR]

Hemostasis of deep irregular wounds is a severe problem in clinical practice. The development of rapid-acting hemostatic agents for deep and irregular wound is urgently needed. Here, sodium alginate/carboxycellulose/polydopamine (SA/CNF/PDA) microspheres was prepared by reverse emulsification and crosslinking with Ca2+, and SA/CNF/PDA composite hemostatic microspheres with porous structure were obtained by freeze-drying. SA/CNF/PDA composite hemostatic microspheres exhibited excellent porosity and water absorption which could rapidly absorb blood on the wound surface. Moreover, SA/CNF/PDA composite microspheres demonstrated remarkable hemostatic capabilities both in vitro and in vivo. It exhibited strong hemostatic performance in models of mouse tail-break and liver damage. Especially in liver injury model, it was completely hemostatic in 95 s, and blood loss (19.3 mg). The hemostatic efficacy of the SA/CNF/PDA composite microspheres was amplified through the stimulation of both exogenous and endogenous coagulation pathways. Therefore, SA/CNF/PDA composite hemostatic microspheres are suitable for rapid hemostasis of deep irregular wounds which are potential rapid hemostatic material for surgical application. • SA/CNF/PDA hemostatic microsphere was obtained by reverse emulsification and freeze-drying. • SA/CNF/PDA microsphere stopped bleeding within 95 s in liver injury model. • The activation of exogenous and endogenous coagulation pathways were activated. [ABSTRACT FROM AUTHOR]

CO 2 -active enhances the performance of municipal solid waste incineration fly ash as a supplementary cementitious material, increasing its utilization in cementitious systems. CFC3, a low-carbon cementitious material, effectively utilizes CO 2 -active incineration fly ash (CIFA). To minimize cement usage, the component effects on hydration need to be studied. In this study, hydration, mechanical and environmental properties of CFC3 were evaluated based on cement dosage and calcined clay/CIFA values. The maximum compressive strength of the samples reached 18.0 MPa at 3d and 47.6 MPa at 56d. The introduction of CIFA delayed the reactions of C 3 S and aluminates. Calcined clay contributes to improved gel polymerization, optimizes the Si/Al CASH ratio, and refines pore structure. A decrease in cement content increased in the aluminate phases, making monocarbonate the primary hydration product. The results of leaching tests indicated that Cd and Pb in R2C50 were transformed into non-leachable, inactive substances. Demonstrating the environmental friendliness of CFC3. • CFC3 is a low-carbon material can effectively utilize incineration fly ash. • The use of incineration fly ash causes extra ettringite and Friedel's salt. • Higher calcined clay usage resulted in two distinct aluminate reaction periods. • CFC3 can reduce the cement content to 35%. [ABSTRACT FROM AUTHOR]

Understanding, predicting and controlling the motion of the solid particles in a confined cavity is significant. The motion of a neutrally buoyant circular particle in a lid-driven square cavity is studied with the lattice Boltzmann method, where the effects of the initial position, particle size and Reynolds number are investigated. The obvious characteristic of the motion of the circular particle is the existence of the limit cycle, which is the competitive result of the inertia, wall-repulsion force and vortex behavior. The limit cycle is insensitive to the initial position of the circular particle, namely, no matter where the circular particle is placed initially, the limit cycle is the same. With the increase of the particle size, the wall-repulsion force becomes stronger, which is dominant over the centrifugal force, and the limit cycle shrinks toward the center of the square cavity. With the increase of the Reynolds number, a new secondary vortex develops at the top left corner of the square cavity, and the limit cycle is pushed toward the bottom right corner of the square cavity. [ABSTRACT FROM AUTHOR]

The prediction of dose distribution in volumetric modulated arc therapy (VMAT) plays a curial role in radiotherapy. Accurate VMAT dose prediction for prostate cancer is always a great challenge because of the complexity of the VMAT dose distributions and the low contrast of the organs and tissues in the male pelvic CT images. In this paper, a novel progressive refinement UNet (PRUNet) with rank loss is proposed to address the aforementioned problem. On the one hand, the proposed PRUNet extends the traditional UNet with a novel progressive refinement module to generate more realistic dose distributions. The progressive refinement module generates multiple dose predictions with different resolutions in one forward pass and refines the dose prediction with predicted details at finer levels from lower resolution to higher resolution. On the other hand, it turns out that the dosimetric metrics are sensitive to the order relation among the dose values in dose distributions. A new rank loss function is proposed to optimize the similarity between the order relations among the dose values in dose predictions and that in real dose distributions. The proposed PRUNet is trained in a multi-task framework to jointly learn the dose distribution and the order relation among dose values. To evaluate the performance of the proposed PRUNet, the VMAT dose distributions and anatomical information of 64 prostate cancer patients are collected. The proposed model generates more accurate dose distributions with better quantitative dosimetric metrics than the state of the art UNet models do. [ABSTRACT FROM AUTHOR]

Miniaturized microscopes with large field-of-view (FOV) have wide applications in biomedical imaging and automated machine vision. Conventional microscopes with a single objective lens have tradeoffs among FOV, resolution and device thickness. Thanks to the high compactness and design flexibility, metalens has a great potential for building the next generation compact imagers. However, there have been various challenges and performance tradeoffs in the design, fabrication and implementation of metalens that could support a large FOV. Here, we present a metalens array based miniaturized microscope that provides extremely high compactness and large FOV. Each metalens unit can image the object tile immediately below it. By tiling such metalens units, we can scale up the FOV while keeping the same device thickness and imaging quality as the microscope with a single metalens unit. Our metalens array enables a compact microscope that can perform large FOV imaging through arbitrary polarized light. We experimentally demonstrated the miniaturized metalens array microscope in 1310 nm wavelength, which has an FOV of 3 × 4 mm2 and can resolve 6.9 μm lines, with 4 mm distance between the sample surface to the camera sensor. Although this is a proof-of-concept demonstration, our metalens array microscope provides a promising solution for portable and implantable camera for large-FOV high-resolution imaging. • The metalens array based miniaturized microscope can perform large field-of-view imaging through arbitrary polarized light. • The metalens array microscope is compact with a very small device thickness. • The field of view of the metalens array microscope can be scaled up while the device thickness remains unchanged. • Metalens array microscope can be used as a portable and implantable camera for large-field-of-view, high-resolution imaging. [ABSTRACT FROM AUTHOR]

—With the development of energy storage technology and sharing economy, the shared energy storage in integrated energy system provides potential benefit to reduce system operation costs and carbon emissions. This paper presents a bi-level carbon-oriented planning method of shared energy storage station for multiple integrated energy systems. Firstly, the energy-carbon relationship of the multiple integrated energy systems is established, and the node carbon intensity models of power grid, integrated energy system and shared energy storage station are established. Secondly, a bi-level planning model of shared energy storage station is developed. The upper layer model solves the optimal capacity planning problem of shared energy storage station to minimize average emission reduction cost in a long time scale. The lower layer model solves the optimal operation problem of multiple integrated energy systems with the goal of minimizing the operation cost in a short time scale. Furthermore, considering the uncertainty of wind and photovoltaic power in integrated energy system, the conditional value at risk method is adopted as the risk measurement index in the lower layer operation cost. Finally, the case study verifies the advantages of the proposed method in economy and environmental friendliness through the comparative analysis of three different energy storage planning cases. Simulation results show that, compared with the energy storage planned separately for each integrated energy system, it is more environmental friendly and economical to provide energy storage services for each integrated energy system through shared energy storage station, the carbon emission reduction rate has increased by 166.53 %, and the system operation cost decreases by 33.48 %. • Node carbon intensity model is established for integrated energy system. • Carbon emission reduction model of integrated energy system is developed. • Carbon-oriented planning model of shared energy storage is established. [ABSTRACT FROM AUTHOR]

Background: Data on the genus Sarcocystis in insectivores are limited. The Asian gray shrew Crocidura attenuata is one of the most common species of the insectivore family Soricidae in South Asia and Southeast Asia. To our knowledge, species of Sarcocystis have never been recorded previously in this host. Methods: Tissues were obtained from 42 Asian gray shrews caught in 2017 and 2018 in China. Sarcocysts were observed using light microscopy (LM) and transmission electron microscopy (TEM). To describe the parasite life cycle, muscle tissues of the host infected with sarcocysts were force-fed to two beauty rat snakes Elaphe taeniura. Individual sarcocysts from different Asian gray shrews, and oocysts/sporocysts isolated from the small intestines and feces of the experimental snakes, were selected for DNA extraction, and seven genetic markers, namely, two nuclear loci [18S ribosomal DNA (18S rDNA) and internal transcribed spacer region 1 (ITS1)], three mitochondrial genes [cytochrome oxidase subunit 1 (cox1), cox3 and cytochrome b], and two apicoplast genes (RNA polymerase beta subunit and caseinolytic protease C), were amplified, sequenced and analyzed. Results: Sarcocysts were found in 17 of the 42 (40.5%) Asian gray shrews. Under LM, the microscopic sarcocysts showed saw- or tooth-like protrusions measuring 3.3–4.5 μm. Ultrastructurally, the sarcocyst wall contained numerous lancet- or leaf-like villous protrusions, similar to those described for type 9h of the common cyst wall classification. The experimental beauty rat snakes shed oocysts/sporocysts measuring 11.9–16.7 × 9.2–10.6 μm with a prepatent period of 10–11 days. Comparison of the newly obtained sequences with those previously deposited in GenBank revealed that those of 18S rDNA and cox1 were most similar to those of Sarcocystis scandentiborneensis recorded in the tree shrews Tupaia minor and Tupaiatana (i.e., 97.6–98.3% and 100% identity, respectively). Phylogenetic analysis based on 18S rDNA or ITS1 sequences placed this parasite close to Sarcocystis spp. that utilize small animals as intermediate hosts and snakes as the known or presumed definitive host. On the basis of morphological and molecular characteristics and host specificity, the parasite was proposed as a new species, named Sarcocystis attenuati. Conclusions: Sarcocysts were recorded in Asian gray shrews, to our knowledge for the first time. Based on morphological and molecular characterization, a new species of parasite is proposed: Sarcocystisattenuati. According to the LM and TEM results, S. attenuati sarcocysts are distinct from those of Sarcocystis spp. in other insectivores and those of S. scandentiborneensis in tree shrews. The 18S rDNA or cox1 sequences of Sarcocystis attenuati shared high similarity with those of Sarcocystisscandentiborneensis, Sarcocystis zuoi, Sarcocystis cf. zuoi in the Malayan field rat, and Sarcocystis sp. in the greater white-toothed shrew. Therefore, we suggest that more research on the relationships of these closely related taxa should be undertaken in the future. [ABSTRACT FROM AUTHOR]

The solid particles with different sizes exist widely, like cell separation, food processing, water treatment, thus, investigating the motion of the solid particles with different sizes is important. This study investigates the motion of a pair of neutrally buoyant circular particles with different sizes in a lid-driven square cavity using the lattice Boltzmann method. The motion of the circular particles with different sizes and that of the circular particles with identical sizes are quite different. The steady trajectories of the circular particles with identical sizes are identical, which is not affected by the Reynolds number. Differently, the circular particles with different sizes orbit along different steady trajectories, namely, the steady trajectory of the small particle is closer to the walls of the square cavity, while that of the large particle shrinks toward the center of the square cavity, which may provide us a possible method to separate them. However, it is not always effective, if the Reynolds number is low, the velocity difference between the circular particles with different sizes is small, which may fail to separate them completely. [ABSTRACT FROM AUTHOR]

Despite dramatic responses to immune checkpoint inhibitors (ICIs) in patients with colon cancer (CC) harboring deficient mismatch repair (dMMR), more than half of these patients ultimately progress and experience primary or secondary drug resistance. There is no useful biomarker that is currently validated to accurately predict this resistance or stratify patients who may benefit from ICI-based immunotherapy. As hypoxic and acidic tumor microenvironment would greatly impair tumor-suppressing functions of tumor-infiltrating lymphocytes (TILs), we sought to explore distinct immunological phenotypes by analysis of the intratumoral hypoxia state using a well-established gene signature. Based on the Gene Expression Omnibus (GEO) (n = 88) and The Cancer Genome Atlas (TCGA) (n = 49) databases of patients with CC, we found that dMMR CC patients could be separated into normoxia subgroup (NS) and hypoxia subgroup (HS) with different levels of expression of hypoxia-related genes (lower in NS group and higher in HS group) using NMF package. Tumoral parenchyma in the HS group had a relatively lower level of immune cell infiltration, particularly CD8+ T cells and M1 macrophages than the NS group, and coincided with higher expression of immune checkpoint molecules and C-X-C motif chemokines, which might be associated with ICI resistance and prognosis. Furthermore, three genes, namely, MT1E, MT2A, and MAFF, were identified to be differentially expressed between NS and HS groups in both GEO and TCGA cohorts. Based on these genes, a prognostic model with stable and valuable predicting ability has been built for clinical application. In conclusion, the varying tumor-immune microenvironment (TIME) classified by hypoxia-related genes might be closely associated with different therapeutic responses of ICIs and prognosis of dMMR CC patients. [ABSTRACT FROM AUTHOR]

Particulate flows with thermal convection exist widely, and the lattice Boltzmann method is proved to be an accurate and efficient solver. Two issues are crucial, namely, the treatment of the velocity and temperature boundaries at the particle surface and the initialization of the fresh fluid nodes due to the movement of the particle. However, these two issues are treated separately, and the inconsistency decreases the numerical accuracy and stability. Thus, a consistent treatment of these two issues is presented, which includes the prediction and correction steps, and it is validated by four numerical experiments. The present method is of the second-order accuracy, and it provides a consistent treatment for particulate flows with thermal convection. [ABSTRACT FROM AUTHOR]

Imaging systems with miniaturized device footprint, real‐time processing speed, and high‐resolution 3D visualization are critical to broad biomedical applications such as endoscopy. Most of existing imaging systems rely on bulky lenses and mechanically refocusing to perform 3D imaging. Here, GEOMScope, a lensless single‐shot 3D microscope that forms image through a single layer of thin microlens array and reconstructs objects through an innovative algorithm combining geometrical‐optics‐based pixel back projection and background suppressions, is demonstrated. The effectiveness of GEOMScope is verified on resolution target, fluorescent particles, and volumetric objects. Comparing to other widefield lensless imaging devices, the required computational resource is significantly reduced, and the reconstruction speed is increased by orders of magnitude. This enables to image and recover large volume 3D object in high resolution with near real‐time processing speed. Such a low computational complexity is attributed to the joint design of imaging optics and reconstruction algorithms, and a joint application of geometrical optics and machine learning in the 3D reconstruction. More broadly, the excellent performance of GEOMScope in imaging resolution, volume, and reconstruction speed implicates that geometrical optics can greatly benefit and play an important role in computational imaging. [ABSTRACT FROM AUTHOR]

The motion of a neutrally buoyant circular particle in a parallel double-lid-driven square cavity is studied with the lattice Boltzmann method. To understand, predict and control the motion of the circular particle, the effects of the initial position and particle size are studied. If the circular particle is placed at the centerline of the square cavity, at the steady state, it is confined at the bottom left corner, otherwise, the circular particle is stabilized at the 8-like trajectory, which is created by both the inertia of the circular particle and the confinement of the boundaries of the square cavity. The effect of the particle size on the motion of the circular particle is obvious, with the increase of the particle size, the confinement of the boundaries of the square cavity becomes stronger, and the 8-like trajectory shrinks toward the center. Furthermore, if the particle size is large enough, the centrifugal motion of the circular particle becomes weaker, and the circular particle cannot cross the centerline of the square cavity. [ABSTRACT FROM AUTHOR]

Purpose: Precise segmentation of clinical target volume (CTV) is the key to stomach cancer radiotherapy. We proposed a novel stochastic width‐deep neural network (SW‐DNN) for better automatically contouring stomach CTV. Methods: Stochastic width‐deep neural network was an end‐to‐end approach, of which the core component was a novel SW mechanism that employed shortcut connections between the encoder and decoder in a random manner, and thus the width of the SW‐DNN was stochastically adjustable to obtain improved segmentation results. In total, 150 stomach cancer patient computed tomography (CT) cases with the corresponding CTV labels were collected and used to train and evaluate the SW‐DNN. Three common quantitative measures: true positive volume fraction (TPVF), positive predictive value (PPV), and Dice similarity coefficient (DSC) were used to evaluate the segmentation accuracy. Results: Clinical target volumes calculated by SW‐DNN had significant quantitative advantages over three state‐of‐the‐art methods. The average DSC value of SW‐DNN was 2.1%, 2.8%, and 3.6% higher than that of three state‐of‐the‐art methods. The average DSC, TPVF, and PPV values of SW‐DNN were 2.1%, 4.0%, and 0.3% higher than that of the corresponding constant width DNN. Conclusions: Stochastic width‐deep neural network provided better performance for contouring stomach cancer CTV accurately and efficiently. It is a promising solution in clinical radiotherapy planning for stomach cancer. [ABSTRACT FROM AUTHOR]

In recent years, as an effective method to mine information from the complex network, community discovery has been widely used in social network, financial risk control and other fields. However, the existing community discovery algorithms are not effective in dealing with complex network which always contains fuzzy community structure. With the help of graph convolution, the proposed algorithm defines the connectivity between any nodes in a network and constructs the symmetric doubly stochastic matrix. Then, the algorithm enhances the network by the nonlinear transformation of the eigenvalues of the symmetric doubly stochastic matrix and makes the original fuzzy community structure become clear. Experimental results show that this method can effectively sharpen the community structure of a network and improve the effect of community partitioning. [ABSTRACT FROM AUTHOR]

Graves' ophthalmopathy (GO) is an autoimmune inflammatory disorder associated with thyroid disease, and radiotherapy is an effective treatment that causes few side effects among patients in the moderate-to-severe stage. The clinical target volume (CTV) refers to tissues with potential tumor spread or subclinical diseases, where accurate segmentation of these tissues is required for the successful radiotherapy. Traditional segmentation methods for the CTV are based on low-level hand-crafted features that require significant domain knowledge and sensitive to the variations. To overcome these shortcomings, a novel neural network architecture called multi-scale attention U-Net (MAU-Net) is proposed to automatically segment the CTV by computed tomography for GO disease. Abstract features ranging from low- to high-levels are extracted by a deep residual network, then processed by a multi-scale module composed of multiple convolutional operations to accommodate various scales of the CTV. A novel attention module is proposed and applied following the multi-scale module, which uses signals from high-level features to selectively highlight the low-features. A total of 178 CT cases are used to train and evaluate the proposed MAU-Net. The experimental results show that MAU-Net achieves higher segmentation accuracy than the state-of-the-art methods. The MAU-Net converges more quickly in the training phase, and achieves lower error on the validation dataset than the vanilla U-Net. [ABSTRACT FROM AUTHOR]

We study data-free knowledge distillation (KD) for monocular depth estimation (MDE), which learns a lightweight model for real-world depth perception tasks by compressing it from a trained teacher model while lacking training data in the target domain. Owing to the essential difference between image classification and dense regression, previous methods of data-free KD are not applicable to MDE. To strengthen its applicability in real-world tasks, in this paper, we propose to apply KD with out-of-distribution simulated images. The major challenges to be resolved are (i) lacking prior information about scene configurations of real-world training data and (ii) domain shift between simulated and real-world images. To cope with these difficulties, we propose a tailored framework for depth distillation. The framework generates new training samples for embracing a multitude of possible object arrangements in the target domain and utilizes a transformation network to efficiently adapt them to the feature statistics preserved in the teacher model. Through extensive experiments on various depth estimation models and two different datasets, we show that our method outperforms the baseline KD by a good margin and even achieves slightly better performance with as few as 1 / 6 of training images, demonstrating a clear superiority. • Novel data-free distillation for depth estimation using OOD simulated images. • Analysis of scene similarity, dataset size, and domain gap for accurate distillation. • Specialized framework addressing challenges in data-free depth distillation. • Superior performance with different depth estimation models and benchmark datasets. [ABSTRACT FROM AUTHOR]

[Display omitted] • An electrochemical sensor was used for monitoring of H 2 O 2 released from cancer cells. • Cu-TCPP has better supporting and electrocatalytic activity than Co-TCPP or Zn-TCPP. • AuPt/Cu-TCPP displays the best electrocatalytic activity towards H 2 O 2 reduction. • The sensor exhibits a low detection limit of 3.1 nM and a wide linear range. Two-dimensional (2D) metal–organic frameworks (MOFs) as supporting nanomaterials to encapsulate or load metal nanoparticles have been widely applied in electrochemical sensing. Therefore, the influences of tetrakis(4-carboxyphenyl) porphyrin-based MOFs (M-TCPP (M = Co, Cu, Zn)) as supporting materials on the electrocatalytic activity were studied. A surfactant-assisted method was employed to facilely synthesize three types of 2D M-TCPP nanosheet MOFs. Polyvinylpyrrolidone was selected as a surfactant for preparing M-TCPP and played a key role in the controlled anisotropic growth of MOF crystals, resulting in the formation of 2D MOF nanosheets. Then, one-step electrodeposition of gold-platinum nanoparticles (AuPt NPs) on the M-TCPP-modified glassy carbon electrode (AuPt/M-TCPP/GCE) was explored for reducing hydrogen peroxide (H 2 O 2). Cyclic voltammetry was applied to investigate the electrocatalytic performance of AuPt/M-TCPP/GCE, and AuPt/Cu-TCPP/GCE exhibited better electrocatalytic characteristics than AuPt/Co-TCPP/GCE and AuPt/Zn-TCPP/GCE. The electrochemical H 2 O 2 sensor displayed a low detection limit of 3.1 nM in the wide concentration range of 0.01 μM to 80 mM. In addition, the proposed sensor showed high stability, good reproducibility, and selectivity. Moreover, HepG2 human liver cancer cells were selected for real-time detection of H 2 O 2 to verify the feasibility of this technology for the evaluation of anticancer drugs. The results showed that Cu-TCPP can be used as an efficient supporting material for enhancing the detection property of electrochemical sensors. [ABSTRACT FROM AUTHOR]

The motion of the solid particles in the enclosed cavity is important, to investigate the interaction between the motion of the solid particles and the fluid flow, the motion of a neutrally buoyant elliptical particle in a lid-driven square cavity is studied with the lattice Boltzmann method. To understand, predict and control the motion of the elliptical particle, the effects of the aspect ratio, initial orientation, initial position, particle size and Reynolds number are studied. The obvious characteristic of the motion of the elliptical particle in the square cavity is the existence of the limit cycle, which is created by the inertia of the elliptical particle, confinement of the boundaries of the square cavity and vortex behavior. Compared with the circular particle, with the increase of the aspect ratio, the roundness of the limit cycle decreases, namely, the limit cycle becomes flatter. Especially, the limit cycle is insensitive to the initial orientation and position, namely, the limit cycle is the same no matter where the elliptical particle is placed initially. With the increase of the particle size, the confinement of the boundaries becomes stronger, and the limit cycle is squeezed toward the center of the square cavity. Finally, with the increase of the Reynolds number, the vortex at the top left corner develops, and the limit cycle is pushed toward the bottom right corner of the square cavity. • A global limit cycle for the motion of the elliptic particle is observed. • The limit cycle is insensitive to the initial position of the elliptic particle. • The limit cycle shrinks toward the center of the square cavity with the increase of the particle size. • The limit cycle migrates toward the bottom right corner of the square cavity with the increase of Re. [ABSTRACT FROM AUTHOR]

Mitochondria are highly dynamic organelles that constantly undergo fission and fusion. Disruption of mitochondrial dynamics undermines their function and causes several human diseases. The fusion of the outer (OMM) and inner mitochondrial membranes (IMM) is mediated by two classes of dynamin-like protein (DLP): mitofusin (MFN)/fuzzy onions 1 (Fzo1) and optic atrophy 1/mitochondria genome maintenance 1 (OPA1/Mgm1). Given the lack of structural information on these fusogens, the molecular mechanisms underlying mitochondrial fusion remain unclear, even after 20 years. Here, we review recent advances in structural studies of the mitochondrial fusion machinery, discuss their implication for DLPs, and summarize the pathogenic mechanisms of disease-causing mutations in mitochondrial fusion DLPs. Crystal structures of truncated mitofusin (MFN)1 and MFN2, the dynamin-like fusogens of the outer mitochondrial membrane, reveal their structural kinship to bacterial dynamin-like protein (BDLP). Human MFN1 and MFN2 bear subtle differences that govern the distinct biochemical properties. GTP-dependent dimerization and conformational changes are key features of MFNs in driving outer membrane fusion. Short optic atrophy 1/short mitochondria genome maintenance 1 (s-OPA1/s-Mgm1) resembles fission dynamins in 3D architecture, highlighting a mechanism of inner mitochondrial membrane (IMM) merging distinct from that of other known types of homotypic fusion. OPA1/Mgm1 uses multiple intermolecular assemblies to achieve either IMM fusion or cristae shaping. Structures of the mitochondrial fusion machinery provide important rules for comparing fusion DLPs with fission DLPs. [ABSTRACT FROM AUTHOR]

A novel silicon-containing phthalonitrile monomer named bis(4-(4′-(4′-phenoxy)phenyl)phenyl)dimethylsilane phthalonitrile (SiBPPN) was successfully designed and synthesized. The chemical structure was characterized by proton nuclear magnetic resonance and Fourier transform infrared (FTIR) analyses, and its molecular weight was determined by mass spectrometry. Its melting point is lower than that of 4,4′-bis(3,4-dicyanophenoxy)biphenyl (BPPN), which has no silicon atom, and its solubility is also much better than that of BPPN. The curing behavior of SiBPPN was studied by differential scanning calorimetry and FTIR analyses in detail. The thermal and thermomechanical properties of the polymer and laminate were studied by thermogravimetric analysis and dynamic mechanical analysis. The results show that the cured SiBPPN (c-SiBPPN) possesses excellent thermal and mechanical properties. Under nitrogen atmosphere, its residual weight ratio at 800°C is 81.5% and the 5% thermal degradation temperature is 546°C. In addition, quartz-fiber (QF)-reinforced c-SiBPPN composites exhibit mechanical properties superior to those of QF-reinforced cured BPPN composites. The interlaminar shear strength and bending strength of the composite are 30.44 and 389 MPa at room temperature, and the interlaminar shear strength and bending strength of the composite are 22.25 and 339 MPa at 300°C. [ABSTRACT FROM AUTHOR]

In the present study, we prepared cinnamaldehyde (CA) conjugated chitosan-stabilized emulsions (CSCAEs), and the influence of pH on their properties and lipolysis behavior was investigated. Compared to the emulsions stabilized by chitosan itself (CSEs), CSCAEs had better stability against pH during storage. As pH increased from 2.5 to 6.25, the viscosity and modulus of CSCAEs increased. However, when pH shifted from 6.25 to 6.5, emulsion showed lower viscosity and modulus. Confocal laser scanning microscopy results demonstrated that oil droplets still kept intact and individually distributed, and chitosan homogenously covered on the oil droplets at low pH conditions (pH 2.5, 4.0). At higher pH conditions (pH 5.0, 5.5), a few chitosan aggregates on the oil droplets were observed. At pH 6.0 and 6.25, the compact gel network structure was formed. At pH 6.5, some void was found among the chitosan gel network. In vitro simulated digestion experiments presented that pH had no significant effect on the lipolysis process of emulsions. When the oil content varied from 10% to 50%, emulsions still kept good stability against pHs, but the lipolysis extent after digestion decreased. This knowledge provides a strategy for improving stability of chitosan-stabilized emulsion against harsh pH conditions. • Cinnamaldehyde conjugated chitosan emulsions had good stability against pH. • The absorption and desorption of chitosan could be controlled by pH. • Rheological properties of emulsions were modulated by pH. • Lipolysis behavior of emulsions depended on the pH condition and oil content. [ABSTRACT FROM AUTHOR]

Transcatheter mitral valve replacement is increasingly being used as a treatment for high-risk patients who have native mitral valve disease; however, no comprehensive studies on its effectiveness have been reported. We therefore searched the literature for reports on patients with native mitral valve disease who underwent transcatheter access treatment. We found 40 reports, published from September 2013 through April 2017, that described the cases of 66 patients (mean age, 71 ± 12 yr; 30 women; 30 patients with mitral stenosis, 34 with mitral regurgitation, and 2 mixed) who underwent transcatheter mitral valve replacement. We documented their baseline clinical characteristics, comorbidities, diagnostic imaging results, procedural details, and postprocedural results. Access was transapical in 41 patients and transseptal in 25. The 30-day survival rate was 82.5%. The technical success rate (83.3% overall) was slightly but not significantly better in patients who had mitral regurgitation than in those who had mitral stenosis. Transapical access procedures resulted in fewer valve-in-valve implantations than did transseptal access procedures (P=0.026). These current results indicate that transcatheter mitral valve replacement is feasible in treating native mitral disease. The slightly higher technical success rate in patients who had mitral regurgitation suggests that a valve with a specific anchoring system is needed when treating mitral stenosis. Our findings indicate that transapical access is more reliable than transseptal access and that securely anchoring the valve is still challenging in transseptal access. [ABSTRACT FROM AUTHOR]

• The applied deep neural network DeepLabv3+ performed clinical acceptable dose distribution for rectal cancer radiotherapy with mean square error of 0.001 and mean normalized dose difference of 0.40% taking the clinically approved dose as the baseline. • The proposed prior dose information-aided planning scheme significantly reduced the manual volumetric modulated arc therapy optimization time from 28.76 min to 13.00 min (1-year experienced group), and 25.49 min to 11.83 min (6-year experienced group), respectively, with superior replans of lower maximum dose, higher minimum dose and lower homogeneity index for planning target volumes. • Dose prediction systems based on deep neural networks can be promising tools for clinical accelerated radiotherapy planning. To apply a deep neural network to predict dose distributions of rectal cancer patients for accelerated volume modulated arc technique (VMAT) planning. Computed tomography scans and approved VMAT plans together with Dose approved of 187 patients treated from February 2018 to April 2019 were randomly selected for this retrospective study. The deep neural network DeepLabv3+ was applied for dose distribution prediction. A prior dose information-aided planning scheme was introduced. Prediction precision was evaluated by mean square error (MSE), normalized dose difference (δD), and dose–volume histogram (DVH) indices using a paired t test. Information-aided and experienced replanning were performed by 1-year and 6-year experienced dosimetrists, respectively. Replanning time and DVH indices were evaluated by two-way variance analysis. The DeepLabv3+ prediction results (Dose DeepLabv3+) were all clinically acceptable. Taking Dose approved as the baseline, the MSE was 0.001 and mean δD was 0.40% with an inter-quartile range of 0.079%–0.30% for Dose DeepLabv3+. No significant differences were found for the planning target volume quantitative parameters between Dose approved and Dose DeepLabv3+ , except for the conformality index. For the two-way variance analysis, a significantly different replanning time was found between the information-aided and experienced replanning with maximum time-saving of 15.76 min. Information-aided replans had the advantage of lower maximum dose, higher minimum dose, and lower homogeneity index, and the disadvantage of lower conformality index and higher machine unites with significant differences. DeepLabv3+ successfully predicted rectal cancer dose distribution, and the predicted prior information helped save planning times for multi-level experienced dosimetrists. [ABSTRACT FROM AUTHOR]

Background: A number of studies have reported hyperprogressive disease (HPD) in non-small cell lung cancer (NSCLC) after treatment with immune checkpoint inhibitor (ICI). This study aimed to summarize the incidence and survival outcome of HPD in NSCLC and identify the clinicopathological features associated with HPD based on available eligible studies.Methods: Four databases (Medline/PubMed, Embase, Web of Science, and Cochrane Library) were searched for eligible studies on HPD published before January 23, 2020, to evaluate the incidence, outcome, and clinical features of HPD. Statistical analyses were performed using STATA 15.0. All meta-analyses were performed based on the random-effects model.Results: This study included 6 studies involving 1389 patients. The incidence of HPD ranged from 8.02 to 30.43%. Compared with patients with non-HPD, those with HPD were associated with worse overall survival. We identified that Eastern Cooperative Oncology Group > 1, Royal Marsden Hospital score ≥ 2, serum lactate dehydrogenase > upper limit of normal, the number of metastasis sites > 2, and liver metastasis were associated with the risk of HPD.Conclusions: This study summarized the clinical features of HPD in NSCLC patients. The meta-analysis showed that five pre-treatment clinicopathological features might be associated with HPD, which may help in selecting patients for ICIs. [ABSTRACT FROM AUTHOR]

In this paper, we propose a new interpretation of the information maximization method (InfoMax) from a perspective of the rate distortion theory. We show that under specific conditions, InfoMax is equivalent to the minimization of a compression rate under the constraint of zero distortion. Zero distortion, or equivalently, zero reconstruction error between the input and its reconstruction, does not provide meaningful solutions in many cases. Based on the new interpretation, we extend InfoMax to be able to deal with non-zero distortion and also to learn under/over-complete representations. Experimental results on synthetic as well as real data show the effectiveness of our method. [ABSTRACT FROM AUTHOR]

• Automatic contouring quality can be quantitatively improved by convolutional neural networks at different feature resolution levels according to the contouring targets with different textures and volume characteristics. • Our proposed convolutional neural networks had better contouring results with 1.1–13.4% higher volumetric Dice similarity coefficient and 1.2–10.0% higher surface Dice coefficient, and reduced the manual correction time to 7.29 min for rectal cancer CTV and 4 min for each OAR. • Our proposed algorithms may be possible aided tools for clinical rectal cancer contouring practice. Manual delineation of clinical target volumes (CTVs) and organs at risk (OARs) is time-consuming, and automatic contouring tools lack clinical validation. We aimed to construct and validate the use of convolutional neural networks (CNNs) to set better contouring standards for rectal cancer radiotherapy. We retrospectively collected and evaluated computed tomography (CT) scans of 199 rectal cancer patients treated at our hospital from February 2018 to April 2019. Two CNNs—DeepLabv3+ for extracting high-level semantic information and ResUNet for extracting low-level visual features—were used for the CTV and small intestine contouring, and bladder and femoral head contouring, respectively. Contouring quality was compared using the paired t test. Five-point objective grading was performed independently by two experienced radiation oncologists and verified by a third. The CNN manual correction time was recorded. CTVs calculated using DeepLabv3+ (CTV DeepLabv3+) had significant quantitative parameter advantages over CTV ResUNet (volumetric Dice coefficient, 0.88 vs 0.87, P = 0.0005; surface Dice coefficient, 0.79 vs 0.78, P = 0.008). Among 315 graded cases, DeepLabv3+ obtained the highest scores with 284 cases, consistent with the objective criteria, whereas CTV ResUNet had the minimum mean manual correction time (7.29 min). DeepLabv3+ performed better than ResUNet for small intestine contouring and ResUNet performed better for bladder and femoral head contouring. The manual correction time for OARs was <4 min for both models. CNNs at various feature resolution levels well delineate rectal cancer CTVs and OARs, displaying high quality and requiring shorter computation and manual correction time. [ABSTRACT FROM AUTHOR]

The Jurassic sequence in the northern Qaidam Basin can be represented by the lower coal‐bearing swamp‐lacustrine sediments unit and the upper reddish clastic deposits suite, which recorded dramatic transition of deposit environment changes. Whole‐rock geochemical data of this succession in Dameigou profile were used to reconstruct the provenance and chemical weathering history. Based on the major element discrimination diagrams, trace element ratios and chondritenormalized REE patterns, most sediments were derived from a similar source area with felsic‐intermediate rocks as dominant contributors. Multiple geochemical parameters and index displayed good correlation, via vertical variations sequence, Jurassic chemical weathering history of northern Qaidam Basin was established, and four stages were recognized from the profile. Phases I and III experienced intense chemical weathering, while Phases II and IV are characterized by mild to moderate chemical weathering. Based on this, long‐term Jurassic climatic evolution of the Qaidam Basin was reconstructed. Early‐middle period of Early Jurassic and middle period of Middle Jurassic developed warm and humid climate. On the contrary, late Early Jurassic‐early Middle Jurassic and late Middle Jurassic‐Late Jurassic was deposited under relatively semiarid to arid climatic conditions. [ABSTRACT FROM AUTHOR]

The future renewable-based power system will have an increased need for balancing power. Prosumers, having both generation and consumption capabilities, are expected to provide balancing power to the grid, if their flexibility can be appropriately managed. Meanwhile, undesirable line congestions and voltage violations may arise in the distribution network, when flexible resources respond to external control or price signals on a large scale. Hence, the development of an effective framework to coordinate flexibility at the distribution system level is of utmost importance. Such a framework should allow for an optimal provision of prosumer balancing power services within the boundaries of local network security constraints. In this study, a balancing market participation framework is proposed, adopting the concept of network-constrained transactive energy, to facilitate the interactions between the transmission system operator and aggregators who manage prosumer energy profiles. This framework retains user privacy and complies with the current market setup, where flexible energy is traded on the spot and balancing markets; however, it is ensured that the resulting energy profiles do not cause problems in the distribution network. [ABSTRACT FROM AUTHOR]

• Equilibrium position of the non-isothermal particle deviates from the centerline of the channel. • Dependence of the equilibrium position of the particle on Gr is not monotonic. • Equilibrium position of the particle is closer to the centerline of the channel with Re increasing. The migration of a neutrally buoyant particle in a shear flow with thermal convection is studied with the lattice Boltzmann method. Due to the effect of thermal convection, the equilibrium position of the particle is different qualitatively from the isothermal case. The dependence of the equilibrium position of the particle on the Grashof number is not monotonic, and four driving forces, which affect the migration of the particle, are investigated. Since the migration of the particle is affected by both forced convection and thermal convection, with the Reynolds number increasing, forced convection becomes stronger, which weakens the effect of thermal convection, as a result, the equilibrium position of the particle is closer to the isothermal case. [ABSTRACT FROM AUTHOR]

The unraveling of enzymatic reactions, especially identification of enzymatic substrates or products, is important to elucidate biological processes. Here a selenium-isotopic signature for mass spectrometric identification of enzymatic-related species is demonstrated by using selenium-containing peptides (SePeps) as substrates. Thus a strategy is proposed for rapid and precise assay of multiple enzyme activity. These SePeps can be synthesized by introduction of one selenomethionine residue in the sequence and simply identified in the full-scan mode with the feature of distinctive selenium-isotopic distribution without MS/MS verifications, which proposes a novel solution to the specific identification of enzyme-related species, allows to exclude the interferences of species with tiny mass differences in bio-samples, and meanwhile can offer a judgement on data accuracy for the analysis of enzyme activities. As a proof-of-concept, a method for multiple analysis of two representative enzymes in MCF-7 cell lysate has been developed with the isotopic peak areas of either SePep substrates or enzymatic products with the top intensities. These results could be the foundation to extend the method for more complicated enzyme systems. The selenium-isotopic signature provides a powerful protocol for high-throughput assays of peptide-metabolizing enzymes with enhanced confidence and can be extended to screen enzymatic reaction-related substrates. A selenium-isotopic signature is demonstrated for rapid mass spectrometric identification of enzyme-related species and assays of enzyme activity with enhanced confidence. Image 1 • The selenomethionine is introduced to peptide as a selenium-isotopic signature. • The peptides provide unique isotope patterns that are verified by HRMS. • The identifications of substrates and products can be performed by tracing the Se isotope in the full-scan MS mode. • This strategy provides a powerful protocol for high-throughput assays of enzymes with enhanced confidence. [ABSTRACT FROM AUTHOR]

To improve the accuracy and efficiency of fish behavior assessment, this paper focuses on quantitatively exploring the variations and relationships between different monitoring dimensions. A systematic comparison was conducted between 3D and 2D behavioral factors using an infrared tracing system, during both day and night. Significant differences in swimming distance were observed among the different monitoring methods, as determined by two‐way ANOVA and Tukey's test. A correction was applied to account for the disparities observed in 2D swimming distance, ensuring accurate measurements. These findings present a cost‐effective and efficient approach for obtaining precise 3D distance data. Additionally, a kinematic factor called the "number of U‐turns" was proposed to provide a more intuitive characterization of directional changes in fish swimming. Significant differences were observed between 2D and 3D data, with higher percentages of false U‐turn counts and missing U‐turn counts compared to correct counts in the 2D view. These findings suggest that reducing the monitoring dimension may impact the accurate estimation of swimming motion, potentially resulting in inaccurate outcomes. Finally, the statistical analyses of the non‐linear properties of fractal dimension revealed significant differences among the various monitoring methods. This conclusion has practical implications for biologists and physicists, enabling them to improve the accuracy of behavioral phenotyping for organisms exhibiting 3D motion. [ABSTRACT FROM AUTHOR]

Background: Small round cell tumor (SRCT) is a group of malignancy with similar optical microscopic morphology. Despite its low incidence, SRCT has a high malignant degree and poor prognosis. Besides, atypical clinical symptoms make it difficult in preoperative diagnosis. Case report: A 67-year-old man was presented to the outpatient service with dysuria and weak urine stream lasting for 3 months. After oral treatment with tamsulosin and finasteride for 2 months, the symptoms worsen. Transurethral prostate holmium laser enucleation was operated and postoperative pathology result revealed small blue round cell malignant tumor. Further immunohistochemistry and fluorescence in situ hybridization examination indicated Ewing-like SRCT. So a Da Vinci Robotic prostatectomy was performed further and whole-genome sequencing was conducted. Several gene mutations including RAF1, ARID1A, SMARCA4, and BCL2L11 were found but no FDA-approved drug could treat specifically. Then the patient received Ewing-type therapeutic regimens treatment and has been followed up to date (over 24 months). Conclusion: Because of its non-elevated serum PSA level, prostate SRCT is often ignored as a possibility of malignant tumor and regarded as benign prostatic hyperplasia (BPH). The possibility of prostate SRCT need to be considered if dysuria symptoms could not alleviate significantly after a period of oral treatment. [ABSTRACT FROM AUTHOR]

Particulate matter (PM) air pollution is closely related to lower respiratory infections (LRIs). However, the global LRI burden attributable to PM remains unclear. Here, we provide a comprehensive assessment of the PM 2.5 -attributable LRI burden using data from the Global Burden and Disease Study (GBD) 2019. We found that PM 2.5 air pollution contributed to approximately 0.7 million deaths and 37.6 million disability-adjusted life years (DALYs) of LRIs in 2019. The LRI burden attributable to PM 2.5 has decreased from 1990 to 2019, with a more pronounced decrease in household PM 2.5 than in ambient PM 2.5. Unlike the decreasing trend in LRI burden due to household PM 2.5 worldwide, nearly one fifth of countries experienced an increase of LRI burden due to ambient PM 2.5. The burden was unevenly distributed to less developed countries, mainly in Sub-Saharan Africa. All age groups experienced a decrease in the PM 2.5 -attributable burden, with the most significant decrease in children younger than 10 years. Notably, individuals aged 20–84 years experienced an increase in the LRI burden attributable to ambient PM 2.5. Males had higher burden than females in the elder age and higher SDI regions. This study provided an evidence-based guidance for the prevention of LRIs and control of PM 2.5 air pollution. [Display omitted] • The LRI burden attributable to PM 2.5 has decreased from 1990 to 2019. • The LRI burden attributable to PM 2.5 was higher in less developed regions. • All age groups witnessed a decrease in the LRI burden attributable to PM 2.5. • The LRI burden attributable to ambient PM 2.5 increased in adults aged 20–84 years. • Males had a higher burden than females in the elder age and higher SDI regions. [ABSTRACT FROM AUTHOR]

Programmed death ligand 1 (PD-L1) exosomes are important biomarkers of immune activation in the initial stages of treatment and can predict clinical responses to PD-1 blockade in various cancer patients. However, traditional PD-L1 exosome bioassays face challenges such as high interface fouling in complex detection environments, limited detection specificity, and poor clinical serum applicability. Inspired by the multi-branched structure of trees, a biomimetic tree-like multifunctional antifouling peptide (TMAP)-assisted electrochemical sensor was developed for high-sensitivity exosomes detection. Multivalent interaction of TMAP significantly enhances the binding affinity of PD-L1 exosomes, thanks to the designed branch antifouling sequence, TMAPs antifouling performance is further improved. The addition of Zr4+ forms coordination bonds with the exosome's lipid bilayer phosphate groups to achieve highly selective and stable binding without interference from protein activity. The specific coordination between AgNCs and Zr4+ contributes to a dramatic change in the electrochemical signals, and lowing detection limit. The designed electrochemical sensor exhibited excellent selectivity and a wide dynamic response within the PD-L1 exosome concentration range from 78 to 7.8 × 107 particles/mL. Overall, the multivalent binding ability of TMAP and the signal amplification characteristics of AgNCs have a certain driving role in achieving clinical detection of exosomes. [ABSTRACT FROM AUTHOR]

The epigenome may be an important interface between exposure to environmental contaminants and adverse outcome on human health. Many environmental pollutants deregulate gene expression and promote diseases by modulating the epigenome. Adverse epigenetic responses have been widely used for risk assessment of chemical substances. Various pollutants, including trace elements and persistent organic pollutants, have been detected frequently in the environment. Epigenetic toxicity of environmental matrices including water, air, soil, and food cannot be ignored. This review provides a comprehensive overview of epigenetic effects of pollutants and environmental matrices. We start with an overview of the mechanisms of epigenetic regulation and the effects of several types of environmental pollutants (trace elements, persistent organic pollutants, endocrine disrupting chemicals, and volatile organic pollutants) on epigenetic modulation. We then discuss the epigenetic responses to environmental water, air, and soil based on in vivo and in vitro assays. Finally, we discuss recommendations to promote the incorporation of epigenotoxicity into contamination screening and health risk assessment. Image 1097 • Integrate review of epigenetic profiles of environmental exposure. • Epigenetic markers as linkage between pollutants exposure and adverse outcomes. • Progress of epigenetic modulations as risk assessment indicators on various matrices. • Epigenetic responses incorporated into epigenotoxicant screening and risk assessment. [ABSTRACT FROM AUTHOR]

• We propose to use deep neural networks (DNNs) together with atrous spatial pyramid pooling (ASPP) to automatically segment the macular edema related lesions. • A module called stochastic ASPP (sASPP) is proposed to combat the co-adaptation of multiple atrous convolutions. • The stochastic operation in sASPP can significantly alleviate the overfitting problem. • A total of 10880 OCT slices are used to train and evaluate the proposed method. • Experimental results demonstrate that the DNNs together with ASPP outperforms the state-of-the-art method. Macular edema is an eye disease that can affect visual acuity. Typical disease symptoms include subretinal fluid (SRF) and pigment epithelium detachment (PED). Optical coherence tomography (OCT) has been widely used for diagnosing macular edema because of its non-invasive and high resolution properties. Segmentation for macular edema lesions from OCT images plays an important role in clinical diagnosis. Many computer-aided systems have been proposed for the segmentation. Most traditional segmentation methods used in these systems are based on low-level hand-crafted features, which require significant domain knowledge and are sensitive to the variations of lesions. To overcome these shortcomings, this paper proposes to use deep neural networks (DNNs) together with atrous spatial pyramid pooling (ASPP) to automatically segment the SRF and PED lesions. Lesions-related features are first extracted by DNNs, then processed by ASPP which is composed of multiple atrous convolutions with different fields of view to accommodate the various scales of the lesions. Based on ASPP, a novel module called stochastic ASPP (sASPP) is proposed to combat the co-adaptation of multiple atrous convolutions. A large OCT dataset provided by a competition platform called "AI Challenger" are used to train and evaluate the proposed model. Experimental results demonstrate that the DNNs together with ASPP achieve higher segmentation accuracy compared with the state-of-the-art method. The stochastic operation added in sASPP is empirically verified as an effective regularization method that can alleviate the overfitting problem and significantly reduce the validation error. [ABSTRACT FROM AUTHOR]