Anaplasma bovis and Bartonella spp. in Libyan Jirds (Meriones libycus) from China.

ANAPLASMA BOVIS: (1), Bartonella krasnovii (3), and Bartonella sp. (17) were detected in 80 Libyan jirds (Meriones libycus) from China. These findings extend the known host and geographic ranges of these pathogens, with neither A. bovis nor B. krasnovii previously confirmed in Libyan jirds.

Detection of Sarcocystis albifronsi, Eimeria alpacae, and Cystoisospora felis in Eurasian lynx (Lynx lynx) in northwestern China.

Eurasian lynx (Lynx lynx) is widely distributed in various habitats in Asia and Europe, and it may harbor multiple pathogens. Currently, the information on protozoan infection in Eurasian lynx is scarce. In this study, we performed nested polymerase chain reaction (nPCR) analysis to detect intestinal protozoan infection in three dead Eurasian lynxes, in northwestern China. Three dead Eurasian lynxes, an adult female (#1), an adult male (#2), and a cub male (#3), were sampled in West Junggar Mountain, the northwestern region of Xinjiang Uyghur Autonomous Region. The intestine samples were analyzed using nPCR. We used primers targeting the cytochrome C oxidase subunit I gene (COI) for detection of Sarcocystis and Eimeria species and targeting the small subunit 18 S ribosomal RNA gene (18S rRNA) for detection of Cystoisospora species. The nPCR-positive products were sequenced, aligned, and phylogenetically analyzed. Three intestinal protozoa, Sarcocystis albifronsi, Eimeria alpacae, and Cystoisospora felis, were found in three Eurasian lynxes. The intestine sample of Eurasian lynx #2 was detected with S. albifronsi and E. alpacae. In addition, C. felis was only found in the intestine sample of Eurasian lynx #3. To the best of our knowledge, S. albifronsi and E. alpacae were detected in Eurasian lynx for the first time. In addition, C. felis was firstly found in Eurasian lynx in China. These findings extend our knowledge of the geographical distribution and host range of intestinal protozoa.

Novel trypanosomatid species detected in Mongolian pikas (Ochotona pallasi) and their fleas in northwestern China.

BACKGROUND: In the family Trypanosomatidae, the genus Trypanosoma contains protozoan parasites that infect a diverse range of hosts, including humans, domestic animals, and wildlife. Wild rodents, as natural reservoir hosts of various pathogens, play an important role in the evolution and emergence of Trypanosomatidae. To date, no reports are available on the trypanosomatid infection of pikas (Lagomorpha: Ochotonidae). METHODS: In this study, Mongolian pikas and their fleas were sampled at the China-Mongolia border, northwestern China. The samples were analyzed with polymerase chain reaction (PCR) and sequencing for the presence of Trypanosomatidae on the basis of both the 18S ribosomal RNA (18S rRNA) gene and the glyceraldehyde-3-phosphate dehydrogenase (gGAPDH) gene. The morphology of trypomastigotes was also observed in peripheral blood smears by microscopy. RESULTS: Molecular and phylogenetic analyses revealed a new genotype of the Trypanosoma lewisi clade that was found both in pika blood and flea samples. This genotype, which probably represents a new species, was provisionally designated as "Trypanosoma sp. pika". In addition, a novel genotype belonging to the genus Blechomonas of Trypanosomatidae was detected in fleas. On the basis of its molecular and phylogenetic properties, this genotype was named Blechomonas luni-like, because it was shown to be the closest related to B. luni compared with other flea-associated trypanosomatids. CONCLUSIONS: To the best of our knowledge, this is the first study to report any trypanosomatid species in Mongolian pikas and their fleas. Further studies are needed to investigate the epidemiology of these protozoan parasites, as well as to evaluate their pathogenicity for humans or domestic animals.

The great gerbil (Rhombomys opimus) as a host for tick species in Gurbantunggut Desert.

BACKGROUND: Rodents play an important role in the life cycle of ixodid and argasid ticks, particularly as hosts of larvae and nymphs. The great gerbil (Rhombomys opimus), the preferred prey item of several carnivores (e.g. the red fox and marbled polecat), is the dominant rodent species in the Gurbantunggut Desert in northwestern China. The aim of this study was to investigate tick species associated with different hosts in the habitat of great gerbils, including wildlife and livestock. METHODS: During 2018-2023, ticks were removed from 326 great gerbils, two red foxes (Vulpes vulpes), three marbled polecats (Vormela peregusna), 35 pastured sheep (Ovis aries), and one long-eared desert hedgehog (Hemiechinus auritus) in the Gurbantunggut Desert. Ticks were identified according to standard morphological keys. Then, they were further analyzed by molecular and phylogenic methods based on two mitochondrial markers, 16S rDNA and cytochrome c oxidase subunit I (COI) genes. RESULTS: A total of 889 ticks were collected, representing five species. These included Hyalomma asiaticum (n = 425: 24 larvae, 79 nymphs and 322 adults), Rhipicephalus turanicus (n = 153: 2 nymphs and 151 adults), Haemaphysalis erinacei (n = 298: 4 larvae, 7 nymphs and 287 adults), Ixodes acuminatus (n = 7: 4 nymphs and 3 adults) and Ornithodoros tartakovskyi (6 adults). Based on COI sequences, molecular and phylogenetic analyses showed that (i) I. acuminatus from great gerbils and marbled polecats clustered with I. acuminatus reported from Europe; (ii) O. tartakovskyi found in northwestern China belonged to an independent clade; (iii) Hy. asiaticum, R. turanicus and Ha. erinacei had 100% sequence identities to conspecific ticks sampled previously in China. CONCLUSIONS: The great gerbil is an important host for the developmental stages of I. acuminatus, O. tartakovskyi, Ha. erinacei, Hy. asiaticum and R. turanicus, thus supporting the life cycle of several tick species which, as adults, parasitize predators (red fox and marble polecat) as well as pastured sheep and hedgehogs in the Gurbantunggut Desert. Ixodes acuminatus and O. tartakovskyi were found for the first time on great gerbil and marbled polecat, respectively.

An image caption model based on attention mechanism and deep reinforcement learning.

Image caption technology aims to convert visual features of images, extracted by computers, into meaningful semantic information. Therefore, the computers can generate text descriptions that resemble human perception, enabling tasks such as image classification, retrieval, and analysis. In recent years, the performance of image caption has been significantly enhanced with the introduction of encoder-decoder architecture in machine translation and the utilization of deep neural networks. However, several challenges still persist in this domain. Therefore, this paper proposes a novel method to address the issue of visual information loss and non-dynamic adjustment of input images during decoding. We introduce a guided decoding network that establishes a connection between the encoding and decoding parts. Through this connection, encoding information can provide guidance to the decoding process, facilitating automatic adjustment of the decoding information. In addition, Dense Convolutional Network (DenseNet) and Multiple Instance Learning (MIL) are adopted in the image encoder, and Nested Long Short-Term Memory (NLSTM) is utilized as the decoder to enhance the extraction and parsing capability of image information during the encoding and decoding process. In order to further improve the performance of our image caption model, this study incorporates an attention mechanism to focus details and constructs a double-layer decoding structure, which facilitates the enhancement of the model in terms of providing more detailed descriptions and enriched semantic information. Furthermore, the Deep Reinforcement Learning (DRL) method is employed to train the model by directly optimizing the identical set of evaluation indexes, which solves the problem of inconsistent training and evaluation standards. Finally, the model is trained and tested on MS COCO and Flickr 30 k datasets, and the results show that the model has improved compared with commonly used models in the evaluation indicators such as BLEU, METEOR and CIDEr.

Endoscopic image classification algorithm based on Poolformer.

Image desmoking is a significant aspect of endoscopic image processing, effectively mitigating visual field obstructions without the need for additional surgical interventions. However, current smoke removal techniques tend to apply comprehensive video enhancement to all frames, encompassing both smoke-free and smoke-affected images, which not only escalates computational costs but also introduces potential noise during the enhancement of smoke-free images. In response to this challenge, this paper introduces an approach for classifying images that contain surgical smoke within endoscopic scenes. This classification method provides crucial target frame information for enhancing surgical smoke removal, improving the scientific robustness, and enhancing the real-time processing capabilities of image-based smoke removal method. The proposed endoscopic smoke image classification algorithm based on the improved Poolformer model, augments the model's capacity for endoscopic image feature extraction. This enhancement is achieved by transforming the Token Mixer within the encoder into a multi-branch structure akin to ConvNeXt, a pure convolutional neural network. Moreover, the conversion to a single-path topology during the prediction phase elevates processing speed. Experiments use the endoscopic dataset sourced from the Hamlyn Centre Laparoscopic/Endoscopic Video Dataset, augmented by Blender software rendering. The dataset comprises 3,800 training images and 1,200 test images, distributed in a 4:1 ratio of smoke-free to smoke-containing images. The outcomes affirm the superior performance of this paper's approach across multiple parameters. Comparative assessments against existing models, such as mobilenet_v3, efficientnet_b7, and ViT-B/16, substantiate that the proposed method excels in accuracy, sensitivity, and inference speed. Notably, when contrasted with the Poolformer_s12 network, the proposed method achieves a 2.3% enhancement in accuracy, an 8.2% boost in sensitivity, while incurring a mere 6.4 frames per second reduction in processing speed, maintaining 87 frames per second. The results authenticate the improved performance of the refined Poolformer model in endoscopic smoke image classification tasks. This advancement presents a lightweight yet effective solution for the automatic detection of smoke-containing images in endoscopy. This approach strikes a balance between the accuracy and real-time processing requirements of endoscopic image analysis, offering valuable insights for targeted desmoking process.

In vitro wheat protoplast cytotoxicity of polystyrene nanoplastics.

Nanoplastics are an emerging environmental pollutant, having a potential risk to the terrestrial ecosystem. In the natural environment, almost all the micro-or nano-plastics will be aged by many factors and their characterizations of the surface will be modified. However, the toxicity and mechanism of the modified polystyrene nanoparticles (PS-NPs) to plant cells are not clear. In the study, the amino- and carboxyl-modified PS-NPs with different sizes (20 and 200 nm) were selected as the typical representatives to investigate their effects on protoplast cell viability, reactive oxygen species (ROS) production in the cell and the leakage of cell-inclusion and apoptosis. The results indicated that the 20 nm amino-modified PS-NPs (PS-20A) could significantly damage the structure of the cell, especially the cell membrane, chloroplast and mitochondrion. After being modified by amino group, smaller size nanoplastics had the potential to cause more severe damage. In addition, compared with carboxyl-modified PS-NPs, the amino-modified PS-NPs induced more ROS production and caused higher membrane permeability/lactate dehydrogenase (LDH) leakage. Apoptosis assay indicated that the proportion of viable cells in the PS-20A treatment decreased significantly, and the proportion of necrotic cells increased by four times. This study provides new insights into the toxicity and damage mechanism of PS-NPs to terrestrial vascular plants at the cellular level, and guides people to pay attention to the quality and safety of agricultural products caused by nanoplastics.

Photoaging process and mechanism of four commonly commercial microplastics.

Microplastics (MPs) are the widespread emerging pollutants in the terrestrial systems, and photo-oxidation is an effective process for aging MPs on land. Here, four common commercial MPs were exposed to ultraviolet (UV) light to simulate the photo-aging of MPs on soil, and the changes in surface properties and eluates of photoaging MPs were studied. Results revealed that polyvinyl chloride (PVC) and polystyrene (PS) exhibited more pronounced physicochemical changes than polypropylene (PP) and polyethylene (PE) during photoaging on the simulated topsoil, due to the dechlorination of PVC and the debenzene ring of PS. Oxygenated groups accumulated in aged MPs were strongly correlated with dissolved organic matters (DOMs) leaching. Through analysis of the eluate, we found that photoaging altered the molecular weight and aromaticity of DOMs. PS-DOMs showed the greatest increase in humic-like substances after aging, whereas PVC-DOMs exhibited the highest amount of additive leaching. The chemical properties of additives explained their differences in photodegradation responses, which also accounted for the greater importance of chemical structure of MPs to their structural stability. These findings demonstrate that the extensive presence of cracks in aged MPs facilitates DOMs formation and the complexity of DOMs composition poses a potential threat to soil and groundwater safety.

Quantitative analysis of heart rate variability parameter and mental stress index.

Background: Cardiovascular disease not only occurs in the elderly but also tends to become a common social health problem. Considering the fast pace of modern life, quantified heart rate variability (HRV) indicators combined with the convenience of wearable devices are of great significance for intelligent telemedicine. To quantify the changes in human mental state, this article proposes an improved differential threshold algorithm for R-wave detection and recognition of electrocardiogram (ECG) signals. Methods: HRV is a specific quantitative indicator of autonomic nerve regulation of the heart. The recognition rate is increased by improving the starting position of R wave and the time-window function of the traditional differential threshold method. The experimental platform is a wearable sign monitoring system constructed based on body area networks (BAN) technology. Analytic hierarchy process (AHP) is used to construct the mental stress assessment model, the weight judgment matrix is constructed according to the influence degree of HRV analysis parameters on mental stress, and the consistency check is carried out to obtain the weight value of the corresponding HRV analysis parameters. Results: Experimental results show that the recognition rate of R wave of real-time 5 min ECG data collected by this algorithm is >99%. The comprehensive index of HRV based on weight matrix can greatly reduce the deviation caused by the measurement error of each parameter. Compared with traditional characteristic wave recognition algorithms, the proposed algorithm simplifies the process, has high real-time performance, and is suitable for wearable analysis devices with low-configuration requirements. Conclusion: Our algorithm can describe the mental stress of the body quantitatively and meet the requirements of application demonstration.

Design of hydrogel-based wearable EEG electrodes for medical applications.

The electroencephalogram (EEG) is considered to be a promising method for studying brain disorders. Because of its non-invasive nature, subjects take a lower risk compared to some other invasive methods, while the systems record the brain signal. With the technological advancement of neural and material engineering, we are in the process of achieving continuous monitoring of neural activity through wearable EEG. In this article, we first give a brief introduction to EEG bands, circuits, wired/wireless EEG systems, and analysis algorithms. Then, we review the most recent advances in the interfaces used for EEG recordings, focusing on hydrogel-based EEG electrodes. Specifically, the advances for important figures of merit for EEG electrodes are reviewed. Finally, we summarize the potential medical application of wearable EEG systems.

Microplastic particles alter wheat rhizosphere soil microbial community composition and function.

The wide existence of microplastics (MPs) in the terrestrial systems is proved by -many studies, and their presence could potentially change the soil chem-physical properties and processes. Various types of microplastics may have different behaviors, inducing distinct effects on the soil ecosystems. However, the knowledge of microplastic impacts on rhizosphere soil bacterial community structure is limited. In our study, three types of microplastics, i.e., polyethylene (PE), polyvinylchloride (PVC) and polystyrene (PS), with the same particle size (200 µm) and concentration (2%) were used to investigate their influences on the rhizosphere soil bacterial communities. Results revealed that the alpha diversities (richness, evenness and diversity) of microbiota in the rhizosphere soil were variously decreased by the microplastics, especially the PE MPs. The relative abundance of some various phyla and genera related to pollution degradation was miscellaneously increased, indicating that the MPs with different characterizations may have miscellaneous biodegradation pathways. Moreover, the PICRUSt2 analysis demonstrated that PS decreased most functional category levels and led to a decrease of bacterial genus number, however, PE and PVC improved metabolic pathways and xenobiotics biodegradation and metabolism. Our findings offer important knowledge of how the microplastics with different characterizations influence rhizosphere soil bacterial communities and their related function.

Multi-modal feature-fusion for CT metal artifact reduction using edge-enhanced generative adversarial networks.

Computed Tomography (CT) imaging is one of the most widely-used and cost-effective technology for organ screening and diseases diagnosis. Because of existence of metallic implants in some patients, the CT images acquired from these patients are often corrupted by undesirable metal artifacts, which causes severe problem of metal artifact. Although there have been proposed many methods to reduce metal artifact, reduction is still challenging and inadequate, and results are suffering from symptom variance, second artifact and poor subjective evaluation. To address these problems, we propose a novel metal artifact reduction method based on generative adversarial networks to simultaneously reduce metal artifacts and enhance texture structure of corrected CT images. Specifically, we firstly incorporate interactive information (text) and imaging CT (image) into a comprehensive feature to yield multi-modal feature-fusion representation, which overcomes the representative ability limitation of single-modal data. The incorporation of interaction information constrains the feature generation to ensure symptom consistency between corrected and target CT. Then, we design an edge-enhance sub-network to avoid second artifact and suppress noise. Besides, we invite three professional physicians to evaluate corrected CT image subjectively. In this paper, We achieved average increment of 11.3% PSNR and 12.1% SSIM on DeepLesion dataset. The subjective evaluations by physicians show that ours outperforms over 6.3%, 7.1%, 5.50% and 6.9% in term of sharpness, resolution, invariance and acceptability, respectively. Our proposed method can achieve high-quality metal artifact reduction results.

Microplastics lag the leaching of phenanthrene in soil and reduce its bioavailability to wheat.

Microplastics wildly occur in soil and they can become the carriers of persistent contaminants. However, the influence of microplastics on polycyclic aromatic hydrocarbons vertical translocation in the soil system after rainfall is limitedly understood. Here, experiments were conducted to study the influence of polyethylene (PE), polystyrene (PS) and polyvinyl chloride (PVC) microplastics on the leaching behavior and bioavailability of phenanthrene (Phe). The adsorption capacity of phenanthrene on the microplastics followed the order of PS > PE > PVC. The Phe concentrations in the top soil layer after 15 days of leaching with water were 30.25, 28.32 and 27.25 mg kg-1 for the treatments of Phe-PS, Phe-PE and Phe-PVC respectively, which is consistent with the adsorption capacities of microplastics. The concentrations of Phe were correlated with the microplastic adsorption capacities at soil depths of 5-45 cm. Under long-term leaching, Phe could reach the deeper soil layer. Phe concentrations significantly decreased in the leachate over time. Phe concentrations in wheat had a positive correlation with that in leachate/leached top soil layer. Our findings are beneficial to accurately evaluate the ecological risk of the combined contamination of PAHs and microplastics, and improve the understanding of the environmental behaviors of different microplastics.

The joint toxicity of polyethylene microplastic and phenanthrene to wheat seedlings.

Due to wide distribution, easy production, and difficult degradation, microplastic pollution has become a new environmental problem that has attracted worldwide attention. However, there is little information about the effects of microplastics in soil and their combined pollution with other organic pollutants on crop growth. In this study, we conducted soil culture experiments to evaluate the effects of polyethylene microplastics (PE-MPs) (0.5%, 1%, 2%, 5%, 8% w/w) individual and combined with phenanthrene (100 mg kg-1) on wheat growth for 15 days. Under PE-MPs alone and combined with phenanthrene exposure, dose-dependent toxicities in biomass, shoot height and root length were observed. Over 1% PE-MPs stimulate wheat root elongation. Compared with single phenanthrene treatment, the co-contamination of PE-MPs and phenanthrene reduces the accumulation of phenanthrene in wheat roots and leaves. In the range of 0-5%, the activity of wheat root antioxidant enzymes increases with increasing PE-MP concentration; but both phenanthrene and high concentrations (8%) of PE-MPs cause damage to the antioxidant system in wheat roots. In the presence or absence of phenanthrene, the photosynthetic pigment concentration of wheat leaves shows a dual concentration effect of low promotion and high inhibition under PE-MPs stress. The single pollution of PE-MPs destroys the photosynthetic system of wheat leaves, while the co-contamination of PE-MPs and phenanthrene exacerbates this destruction. Therefore, the co-contamination of PE-MPs and phenanthrene causes greater damage to wheat growth. Our findings can help to evaluate the individual and comprehensive toxicity of microplastics and polycyclic aromatic hydrocarbons to crops.

Role of miR164 in the growth of wheat new adventitious roots exposed to phenanthrene.

Polycyclic aromatic hydrocarbons (PAHs), ubiquitous organic pollutants in the environment, can accumulate in humans via the food chain and then harm human health. MiRNAs (microRNAs), a kind of non-coding small RNAs with a length of 18-30 nucleotides, regulate plant growth and development and respond to environmental stress. In this study, it is demonstrated that miR164 can regulate root growth and adventitious root generation of wheat under phenanthrene exposure by targeting NAC (NAM/ATAF/CUC) transcription factor. We observed that phenanthrene treatment accelerated the senescence and death of wheat roots, and stimulated the occurrence of new roots. However, it is difficult to compensate for the loss caused by old root senescence and death, due to the slower growth of new roots under phenanthrene exposure. Phenanthrene accumulation in wheat roots caused to generate a lot of reactive oxygen species, and enhanced lipoxygenase activity and malonaldehyde concentration, meaning that lipid peroxidation is the main reason for root damage. MiR164 was up-regulated by phenanthrene, enhancing the silence of NAC1, weakening the association with auxin signal, and inhibiting the occurrence of adventitious roots. Phenanthrene also affected the expression of CDK (the coding gene of cyclin-dependent kinase) and CDC2 (a gene regulating cell division cycle), the key genes in the cell cycle of pericycle cells, thereby affecting the occurrence and growth of lateral roots. In addition, NAM (a gene regulating no apical meristem) and NAC23 may also be related to the root growth and development in wheat exposed to phenanthrene. These results provide not only theoretical basis for understanding the molecular mechanism of crop response to PAHs accumulation, but also knowledge support for improving phytoremediation of soil or water contaminated by PAHs.

Proton-coupled cotransporter involves phenanthrene xylem loading in roots.

The uptake and translocation of polycyclic aromatic hydrocarbons (PAHs) by staple crops have gained much attention. However, the mechanism on phenanthrene xylem loading across plasma membrane is still unclear. In this study, we investigated the concentration dependence of phenanthrene xylem loading and the relationship between phenanthrene concentration and xylem sap pH. The impacts of metabolic inhibitor, temperature, and dissolved oxygen on phenanthrene concentration in xylem sap were observed as well. The Michaelis-Menten equation fits phenanthrene xylem loading across parenchyma cell membrane well and xylem sap pH decreases with the increase in treated phenanthrene concentration. Metabolic inhibitor, low temperature and low dissolved oxygen can suppress phenanthrene loading into xylem sap. The inhibitory rate of sodium vanadate on xylem sap phenanthrene is between 19.76% and 25.82%. Low temperature reduces phenanthrene concentration in xylem sap by 86.68%. Hypoxia (2 mg L-1) inhibits phenanthrene loading into xylem by 78.67%. Therefore, it is indicated that H+/phenanthrene cotransporter is implicated in phenanthrene loading into xylem. Our work offers a valuable model to understand the mechanism of PAH loading into xylem.

Diamond-Coated Plasma Probes for Hot and Hazardous Plasmas.

Plasma probes are simple and inexpensive diagnostic tools for fast measurements of relevant plasma parameters. While in earlier times being employed mainly in relatively cold laboratory plasmas, plasma probes are now routinely used even in toroidal magnetic fusion experiments, albeit only in the edge region, i.e., the so-called scrape-off layer (SOL), where temperature and density of the plasma are lower. To further avoid overheating and other damages, in medium-size tokamak (MST) probes are inserted only momentarily by probe manipulators, with usually no more than a 0.1 s per insertion during an average MST discharge of a few seconds. However, in such hot and high-density plasmas, their usage is limited due to the strong particle fluxes onto the probes and their casing which can damage the probes by sputtering and heating and by possible chemical reactions between plasma particles and the probe material. In an attempt to make probes more resilient against these detrimental effects, we tested two graphite probe heads (i.e., probe casings with probes inserted) coated with a layer of electrically isolating ultra-nano-crystalline diamond (UNCD) in the edge plasma region of the Experimental Advanced Superconducting Tokamak (EAST) in Hefei, People's Republic of China. The probe heads, equipped with various graphite probe pins, were inserted frequently even into the deep SOL up to a distance of 15 mm inside the last closed flux surface (LCFS) in low- and high-confinement regimes (L-mode and H-mode). Here, we concentrate on results most relevant for the ability to protect the graphite probe casings by UNCD against harmful effects from the plasma. We found that the UNCD coating also prevented almost completely the sputtering of graphite from the probe casings and thereby the subsequent risk of re-deposition on the boron nitride isolations between probe pins and probe casings by a layer of conductive graphite. After numerous insertions into the SOL, first signs of detachment of the UNCD layer were noticed.

An Algorithm Based on Text Position Correction and Encoder-Decoder Network for Text Recognition in the Scene Image of Visual Sensors.

Text recognition in natural scene images has always been a hot topic in the field of document-image related visual sensors. The previous literature mostly solved the problem of horizontal text recognition, but the text in the natural scene is usually inclined and irregular, and there are many unsolved problems. For this reason, we propose a scene text recognition algorithm based on a text position correction (TPC) module and an encoder-decoder network (EDN) module. Firstly, the slanted text is modified into horizontal text through the TPC module, and then the content of horizontal text is accurately identified through the EDN module. Experiments on the standard data set show that the algorithm can recognize many kinds of irregular text and get better results. Ablation studies show that the proposed two network modules can enhance the accuracy of irregular scene text recognition.

Establishment of patient-derived tumor spheroids for non-small cell lung cancer.

The prognosis of advanced non-small cell lung cancer (NSCLC) patients is poor. One of the reasons for this hampered progress has been a lack of in vitro models that would faithfully recapitulate the heterogeneity of tumors and response to treatment. In this study, surgically resected tumors were obtained from patients with stage I/II NSCLC during curative-intent surgery. Using a 3D patient-derived tumor spheroids culture system, our results demonstrate successful long-term expansion of primary NSCLC cells in vitro (> 120 days). Patient-derived tumor spheroid (PDS) cultures could be established with a success rate of 100% (3 out of 3 samples). Consistent with their growth in culture and their cancer type, many cells within the tumor spheroids were stained positive for Ki67 and thyroid transcription factor-1. The result of this study supports the establishment of an expandable 3D in vitro NSCLC model for drug screening, and enables the potential long term studies such as the establishment of drug resistant models.

Automatic anatomy recognition in whole-body PET/CT images.

PURPOSE: Whole-body positron emission tomography/computed tomography (PET/CT) has become a standard method of imaging patients with various disease conditions, especially cancer. Body-wide accurate quantification of disease burden in PET/CT images is important for characterizing lesions, staging disease, prognosticating patient outcome, planning treatment, and evaluating disease response to therapeutic interventions. However, body-wide anatomy recognition in PET/CT is a critical first step for accurately and automatically quantifying disease body-wide, body-region-wise, and organwise. This latter process, however, has remained a challenge due to the lower quality of the anatomic information portrayed in the CT component of this imaging modality and the paucity of anatomic details in the PET component. In this paper, the authors demonstrate the adaptation of a recently developed automatic anatomy recognition (AAR) methodology [Udupa et al., "Body-wide hierarchical fuzzy modeling, recognition, and delineation of anatomy in medical images," Med. Image Anal. 18, 752-771 (2014)] to PET/CT images. Their goal was to test what level of object localization accuracy can be achieved on PET/CT compared to that achieved on diagnostic CT images. METHODS: The authors advance the AAR approach in this work in three fronts: (i) from body-region-wise treatment in the work of Udupa et al. to whole body; (ii) from the use of image intensity in optimal object recognition in the work of Udupa et al. to intensity plus object-specific texture properties, and (iii) from the intramodality model-building-recognition strategy to the intermodality approach. The whole-body approach allows consideration of relationships among objects in different body regions, which was previously not possible. Consideration of object texture allows generalizing the previous optimal threshold-based fuzzy model recognition method from intensity images to any derived fuzzy membership image, and in the process, to bring performance to the level achieved on diagnostic CT and MR images in body-region-wise approaches. The intermodality approach fosters the use of already existing fuzzy models, previously created from diagnostic CT images, on PET/CT and other derived images, thus truly separating the modality-independent object assembly anatomy from modality-specific tissue property portrayal in the image. RESULTS: Key ways of combining the above three basic ideas lead them to 15 different strategies for recognizing objects in PET/CT images. Utilizing 50 diagnostic CT image data sets from the thoracic and abdominal body regions and 16 whole-body PET/CT image data sets, the authors compare the recognition performance among these 15 strategies on 18 objects from the thorax, abdomen, and pelvis in object localization error and size estimation error. Particularly on texture membership images, object localization is within three voxels on whole-body low-dose CT images and 2 voxels on body-region-wise low-dose images of known true locations. Surprisingly, even on direct body-region-wise PET images, localization error within 3 voxels seems possible. CONCLUSIONS: The previous body-region-wise approach can be extended to whole-body torso with similar object localization performance. Combined use of image texture and intensity property yields the best object localization accuracy. In both body-region-wise and whole-body approaches, recognition performance on low-dose CT images reaches levels previously achieved on diagnostic CT images. The best object recognition strategy varies among objects; the proposed framework however allows employing a strategy that is optimal for each object.