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Abstract Background Accurately redirecting reconstructed Positron emission tomography (PET) images into short-axis (SA) images shows great significance for subsequent clinical diagnosis. We developed a system for automatic redirection and quantitative analysis of myocardial PET images. Methods A total of 128 patients were enrolled for 18 F-FDG PET/CT myocardial metabolic images (MMIs), including 3 image classifications: without defects, with defects, and excess uptake. The automatic reorientation system includes five modules: regional division, myocardial segmentation, ellipsoid fitting, image rotation and quantitative analysis. First, the left ventricular geometry-based canny edge detection (LVG-CED) was developed and compared with the other 5 common region segmentation algorithms, the optimized partitioning was determined based on partition success rate. Then, 9 myocardial segmentation methods and 4 ellipsoid fitting methods were combined to derive 36 cross combinations for diagnostic performance in terms of Pearson correlation coefficient (PCC), Kendall correlation coefficient (KCC), Spearman correlation coefficient (SCC), and determination coefficient. Finally, the deflection angles were computed by ellipsoid fitting and the SA images were derived by affine transformation. Furthermore, the polar maps were used for quantitative analysis of SA images, and the redirection effects of 3 different image classifications were analyzed using correlation coefficients. Results On the dataset, LVG-CED outperformed other methods in the regional division module with a 100% success rate. In 36 cross combinations, PSO-FCM and LLS-SVD performed the best in terms of correlation coefficient. The linear results indicate that our algorithm (LVG-CED, PSO-FCM, and LLS-SVD) has good consistency with the reference manual method. In quantitative analysis, the similarities between our method and the reference manual method were higher than 96% at 17 segments. Moreover, our method demonstrated excellent performance in all 3 image classifications. Conclusion Our algorithm system could realize accurate automatic reorientation and quantitative analysis of PET MMIs, which is also effective for images suffering from interference.

Abstract Background Low-dose ungated CT is commonly used for total-body PET attenuation and scatter correction (ASC). However, CT-based ASC (CT-ASC) is limited by radiation dose risks of CT examinations, propagation of CT-based artifacts and potential mismatches between PET and CT. We demonstrate the feasibility of direct ASC for multi-tracer total-body PET in the image domain. Methods Clinical uEXPLORER total-body PET/CT datasets of [18F]FDG (N = 52), [18F]FAPI (N = 46) and [68Ga]FAPI (N = 60) were retrospectively enrolled in this study. We developed an improved 3D conditional generative adversarial network (cGAN) to directly estimate attenuation and scatter-corrected PET images from non-attenuation and scatter-corrected (NASC) PET images. The feasibility of the proposed 3D cGAN-based ASC was validated using four training strategies: (1) Paired 3D NASC and CT-ASC PET images from three tracers were pooled into one centralized server (CZ-ASC). (2) Paired 3D NASC and CT-ASC PET images from each tracer were individually used (DL-ASC). (3) Paired NASC and CT-ASC PET images from one tracer ([18F]FDG) were used to train the networks, while the other two tracers were used for testing without fine-tuning (NFT-ASC). (4) The pre-trained networks of (3) were fine-tuned with two other tracers individually (FT-ASC). We trained all networks in fivefold cross-validation. The performance of all ASC methods was evaluated by qualitative and quantitative metrics using CT-ASC as the reference. Results CZ-ASC, DL-ASC and FT-ASC showed comparable visual quality with CT-ASC for all tracers. CZ-ASC and DL-ASC resulted in a normalized mean absolute error (NMAE) of 8.51 ± 7.32% versus 7.36 ± 6.77% (p

Abstract Background Gastropods of the genus Biomphalaria (Family Planorbidae) are exploited as vectors by Schistosoma mansoni, the most common causative agent of human intestinal schistosomiasis. Using improved genomic resources, overviews of how Biomphalaria responds to S. mansoni and other metazoan parasites can provide unique insights into the reproductive, immune, and other systems of invertebrate hosts, and their responses to parasite challenges. Results Using Illumina-based RNA-Seq, we compared the responses of iM line B. glabrata at 2, 8, and 40 days post-infection (dpi) to single infections with S. mansoni, Echinostoma paraensei (both digenetic trematodes) or Daubaylia potomaca (a nematode parasite of planorbid snails). Responses were compared to unexposed time-matched control snails. We observed: (1) each parasite provoked a distinctive response with a predominance of down-regulated snail genes at all time points following exposure to either trematode, and of up-regulated genes at 8 and especially 40dpi following nematode exposure; (2) At 2 and 8dpi with either trematode, several snail genes associated with gametogenesis (particularly spermatogenesis) were down-regulated. Regarding the phenomenon of trematode-mediated parasitic castration in molluscs, we define for the first time a complement of host genes that are targeted, as early as 2dpi when trematode larvae are still small; (3) Differential gene expression of snails with trematode infection at 40dpi, when snails were shedding cercariae, was unexpectedly modest and revealed down-regulation of genes involved in the production of egg mass proteins and peptide processing; and (4) surprisingly, D. potomaca provoked up-regulation at 40dpi of many of the reproduction-related snail genes noted to be down-regulated at 2 and 8dpi following trematode infection. Happening at a time when B. glabrata began to succumb to D. potomaca, we hypothesize this response represents an unexpected form of fecundity compensation. We also document expression patterns for other Biomphalaria gene families, including fibrinogen domain-containing proteins (FReDs), C-type lectins, G-protein coupled receptors, biomphalysins, and protease and protease inhibitors. Conclusions Our study is relevant in identifying several genes involved in reproduction that are targeted by parasites in the vector snail B. glabrata and that might be amenable to manipulation to minimize their ability to serve as vectors of schistosomes.

Background: A high body mass index (BMI) increases the risk of hypertension. However, little is known about the dose-dependent association between BMI and hypertension. Therefore, this study investigated the prevalence of hypertension in 7568 subjects from the Jiangsu Province, Eastern China, and analyzed the dose–response relationship between BMI and hypertension risk. Methods: The eligible subjects completed a structured questionnaire and clinical biochemical indicators were measured according to standardized protocols. Multivariate logistic regression models were used to evaluate the association between BMI and hypertension. Restricted cubic spline (RCS) analysis was used to analyze the dose–response relationship between BMI and hypertension risk. Moreover, sensitivity analysis was performed to verify the robustness of our findings. Results: The prevalence of hypertension was 35.3 % in the total population. BMI was significantly associated with systolic and diastolic blood pressure. The fully-adjusted odds ratio (OR) with 95 % confidence interval (CI) for hypertension was 1.17 (1.15, 1.19) for every 1 kg/m2 increase in BMI. Furthermore, the OR (95 % CI) for hypertension in the highest BMI group (Obesity) was 4.14 (3.45, 4.96) after adjusting for covariates compared with the normal group. Multivariable adjusted RCS analysis showed a positive and linear dose–response relationship between BMI and hypertension risk both in male and female populations (all P for non-linearity > 0.05). Conclusion: Our study demonstrated a positive and linear dose–response relationship between BMI and the risk of hypertension. The results of this study provide evidence for BMI-related clinical interventions to reduce the risk of hypertension.

Abstract Background Control and elimination of schistosomiasis is an arduous task, with current strategies proving inadequate to break transmission. Exploration of genetic approaches to interrupt Schistosoma mansoni transmission, the causative agent for human intestinal schistosomiasis in sub-Saharan Africa and South America, has led to genomic research of the snail vector hosts of the genus Biomphalaria. Few complete genomic resources exist, with African Biomphalaria species being particularly underrepresented despite this being where the majority of S. mansoni infections occur. Here we generate and annotate the first genome assembly of Biomphalaria sudanica sensu lato, a species responsible for S. mansoni transmission in lake and marsh habitats of the African Rift Valley. Supported by whole-genome diversity data among five inbred lines, we describe orthologs of immune-relevant gene regions in the South American vector B. glabrata and present a bioinformatic pipeline to identify candidate novel pathogen recognition receptors (PRRs). Results De novo genome and transcriptome assembly of inbred B. sudanica originating from the shoreline of Lake Victoria (Kisumu, Kenya) resulted in a haploid genome size of ~ 944.2 Mb (6,728 fragments, N50 = 1.067 Mb), comprising 23,598 genes (BUSCO = 93.6% complete). The B. sudanica genome contains orthologues to all described immune genes/regions tied to protection against S. mansoni in B. glabrata, including the polymorphic transmembrane clusters (PTC1 and PTC2), RADres, and other loci. The B. sudanica PTC2 candidate immune genomic region contained many PRR-like genes across a much wider genomic region than has been shown in B. glabrata, as well as a large inversion between species. High levels of intra-species nucleotide diversity were seen in PTC2, as well as in regions linked to PTC1 and RADres orthologues. Immune related and putative PRR gene families were significantly over-represented in the sub-set of B. sudanica genes determined as hyperdiverse, including high extracellular diversity in transmembrane genes, which could be under pathogen-mediated balancing selection. However, no overall expansion in immunity related genes was seen in African compared to South American lineages. Conclusions The B. sudanica genome and analyses presented here will facilitate future research in vector immune defense mechanisms against pathogens. This genomic/transcriptomic resource provides necessary data for the future development of molecular snail vector control/surveillance tools, facilitating schistosome transmission interruption mechanisms in Africa.

Abstract Objective This study aims to evaluate the efficacy and safety of adjunctive hyperbaric oxygen therapy (HBOT) in acute ischaemic stroke (AIS) based on existing evidence. Methods We conducted a comprehensive search through April 15, 2023, of seven major databases for randomized controlled trials (RCTs) comparing adjunctive hyperbaric HBOT with non-HBOT (no HBOT or sham HBOT) treatments for AIS. Data extraction and assessment were independently performed by two researchers. The quality of included studies was evaluated using the tool provided by the Cochrane Collaboration. Meta-analysis was conducted using Rev Man 5.3. Results A total of 8 studies involving 493 patients were included. The meta-analysis showed no statistically significant differences between HBOT and the control group in terms of NIHSS score (MD = -1.41, 95%CI = -7.41 to 4.58), Barthel index (MD = 8.85, 95%CI = -5.84 to 23.54), TNF-α (MD = -5.78, 95%CI = -19.93 to 8.36), sICAM (MD = -308.47, 95%CI = -844.13 to 13227.19), sVCAM (MD = -122.84, 95%CI = -728.26 to 482.58), sE-selectin (MD = 0.11, 95%CI = -21.86 to 22.08), CRP (MD = -5.76, 95%CI = -15.02 to 3.51), adverse event incidence within ≤ 6 months of follow-up (OR = 0.98, 95%CI = 0.25 to 3.79). However, HBOT showed significant improvement in modified Rankin score (MD = 0.10, 95%CI = 0.03 to 0.17), and adverse event incidence at the end of treatment (OR = 0.42, 95%CI = 0.19 to 0.94) compared to the control group. Conclusion While our findings do not support the routine use of HBOT for improving clinical outcomes in AIS, further research is needed to explore its potential efficacy within specific therapeutic windows and for different cerebral occlusion scenarios. Therefore, the possibility of HBOT offering clinical benefits for AIS cannot be entirely ruled out.

To ensure the safe operation and dispatching control of a low-voltage distributed photovoltaic (PV) power distribution network (PDN), the load forecasting problem of the PDN is studied in this study. Based on deep learning technology, this paper proposes a robot-assisted load forecasting method for low-voltage distributed photovoltaic power distribution networks using enhanced long short-term memory (LSTM). This method employs the frequency domain decomposition (FDD) to obtain boundary points and incorporates a dense layer following the LSTM layer to better extract data features. The LSTM is used to predict low-frequency and high-frequency components separately, enabling the model to precisely capture the voltage variation patterns across different frequency components, thereby achieving high-precision voltage prediction. By verifying the historical operation data set of a low-voltage distributed PV-PDN in Guangdong Province, experimental results demonstrate that the proposed “FDD+LSTM” model outperforms both recurrent neural network and support vector machine models in terms of prediction accuracy on both time scales of 1 h and 4 h. Precisely forecast the voltage in different seasons and time scales, which has a certain value in promoting the development of the PDN and related technology industry chain.

ObjectivesThe aims of this study were to explore the incidence characteristics and trend prediction of lymphoma from 2005 to 2035, and to provide data basis for the prevention and control of lymphoma in China.MethodThe data on lymphoma incidence in China from 2005 to 2017 were obtained from the Chinese Cancer Registry Annual Report. The Joinpoint regression model was used to calculate annual percentage change (APC) and average annual percentage change (AAPC) to reflect time trends. Age–period–cohort models were conducted to estimate age, period, and cohort effects on the lymphoma incidence. A Bayesian age–period–cohort model was used to predict lymphoma incidence trends from 2018 to 2035.ResultsFrom 2005 to 2017, the incidence of lymphoma was 6.26/100,000, and the age-standardized incidence rate (ASIR) was 4.11/100,000, with an AAPC of 1.4% [95% confidence interval (CI): 0.3%, 2.5%]. The ASIR was higher in men and urban areas than in women and rural areas, respectively. The age effect showed that the incidence risk of lymphoma increased with age. In the period effect, the incidence risk of lymphoma in rural areas decreased first and then increased with 2010 as the cutoff point. The overall risk of lymphoma incidence was higher in the cohort before the 1970–1974 birth cohort than in the cohort after. From 2018 to 2035, the lymphoma incidence in men, women, and urban areas will show an upward trend.ConclusionFrom 2005 to 2017, the incidence of lymphoma showed an increasing trend, and was different in regions, genders, and age groups in China. It will show an upward trend from 2018 to 2035. These results are helpful for the formulation and adjustment of lymphoma prevention, control, and management strategies, and have important reference significance for the treatment of lymphoma in China.

Abstract Real‐time telemedicine detection can solve the problem of the shortage of public medical resources caused by the coming aging society. However, the development of such an integrated monitoring system is hampered by the need for high‐performance sensors and the strict‐requirement of long‐distance signal transmission and reproduction. Here, a bionic crack‐spring fiber sensor (CSFS) inspired by spider leg and cirrus whiskers for stretchable and weavable electronics is reported. Trans‐scale conductive percolation networks of multilayer graphene around the surface of outer spring‐like Polyethylene terephthalate (PET) fibers and printing Ag enable a high sensitivity of 28475.6 and broad sensing range over 250%. The electromechanical changes in different stretching stages are simulated by Comsol to explain the response mechanism. The CSFS is incorporated into the fabric and realized the human‐machine interactions (HMIs) for robot control. Furthermore, the 5G Narrowband Internet of Things (NB‐IoT) system is developed for human healthcare data collection, transmission, and reproduction together with the integration of the CSFS, illustrating the huge potential of the approach in human–machine communication interfaces and intelligent telemedicine rehabilitation and diagnosis monitoring.

Recently developed sixth-order wave aberration expressions of soft X-rays and a vacuum ultraviolet optical system are first extended to plane-symmetric refractive optical systems, and then, applying the transformation relations between plane-symmetric and paraxial refractive optical system, the sixth-order intrinsic and extrinsic wave aberration coefficient expressions of a paraxial refractive optical system are derived. In addition, the corresponding fifth-order aberration expressions are also obtained. Finally, the resultant aberration expressions are applied to calculate the aberration on the image plane of one design example of a paraxial refractive optical system with a large aperture, and these calculation results are compared with ones obtained by ray-tracing software Zemax to prove that they have satisfactory calculation accuracy.

In recent years, the interest in medical monitoring for human health has been rapidly increasing due to widespread concern. Hydrogels are widely used in medical monitoring and other fields due to their excellent mechanical properties, electrical conductivity and adhesion. However, some of the non-degradable materials in hydrogels may cause some environmental damage and resource waste. Therefore, organic renewable natural polymers with excellent properties of biocompatibility, biodegradability, low cost and non-toxicity are expected to serve as an alternative to those non-degradable materials, and also provide a broad application prospect for the development of natural-polymer-based hydrogels as flexible electronic devices. This paper reviews the progress of research on many different types of natural-polymer-based hydrogels such as proteins and polysaccharides. The applications of natural-polymer-based hydrogels in body movement detection and biomedical monitoring are then discussed. Finally, the present challenges and future prospects of natural polymer-based hydrogels are summarized.

Amyotrophic lateral sclerosis (ALS) is a debilitating motor neurological disorder for which there is still no cure. The disease seriously jeopardizes the health and lifespan of adult populations. The authors extensively retrieved the current literature about clinical and experimental ALS treatments. Based on them, this review primarily focused on summarizing the current potential clinical usage and trialing therapeutics of ALS. Currently, the clinical ALS treatments have focused primarily on relieving symptoms to improve the quality of life yet. There are a number of therapeutic approaches such as medicine, gene therapy, neuron protectants, combination therapy and stem cells. Among them, Stem cells including embryonic stem cells, mesenchymal stem cells, neural stem cells, and many other types of stem cells have been used in ALS treatment, and although the short-term efficacy is good, it is worth exploring whether this improved efficacy leads to prolonged patient survival. In addition, the supportive treatments also exert an important effect on improving the quality of life and prolong the survival of ALS patients in absence of effectively care for stopping or reversing the progression of ALS.

With the fast development of large-scale Photovoltaic (PV) plants, the automatic PV fault identification and positioning have become an important task for the PV intelligent systems, aiming to guarantee the safety, reliability, and productivity of large-scale PV plants. In this paper, we propose a residual learning-based robotic (UAV) image analysis model for low-voltage distributed PV fault identification and positioning. In our target scenario, the unmanned aerial vehicles (UAVs) are deployed to acquire moving images of low-voltage distributed PV power plants. To get desired robustness and accuracy of PV image detection, we integrate residual learning with attention mechanism into the UAV image analysis model based on you only look once v4 (YOLOv4) network. Then, we design the sophisticated multi-scale spatial pyramid fusion and use it to optimize the YOLOv4 network for the nuanced task of fault localization within PV arrays, where the Complete-IOU loss is incorporated in the predictive modeling phase, significantly enhancing the accuracy and efficiency of fault detection. A series of experimental comparisons in terms of the accuracy of fault positioning are conducted, and the experimental results verify the feasibility and effectiveness of the proposed model in dealing with the safety and reliability maintenance of low-voltage distributed PV systems.

Schistosomiasis is one of the world's most devastating parasitic diseases, afflicting 251 million people globally. The Neotropical snail Biomphalaria glabrata is an important intermediate host of the human blood fluke Schistosoma mansoni and a predominant model for schistosomiasis research. To fully exploit this model snail for biomedical research, here we report a haplotype-like, chromosome-level assembled and annotated genome of the homozygous iM line of B. glabrata that we developed at the University of New Mexico. Using multiple sequencing platforms, including Illumina, PacBio, and Omni-C sequencing, 18 sequence contact matrices representing 18 haploid chromosomes (2n = 36) were generated (337x genome coverage), and 96.5% of the scaffold sequences were anchored to the 18 chromosomes. Protein-coding genes (n = 34,559), non-coding RNAs (n = 2,406), and repetitive elements (42.52% of the genome) were predicted for the whole genome, and detailed annotations for individual chromosomes were also provided. Using this genomic resource, we have investigated the genomic structure and organization of the Toll-like receptor (TLR) and fibrinogen-domain containing protein (FReD) genes, the two important immune-related gene families. Notably, TLR-like genes are scattered on 13 chromosomes. In contrast, almost all (39 of 40) fibrinogen-related genes (FREPs) (immunoglobulin superfamily (IgSF) + fibrinogen (FBG)) are clustered within a 5-million nucleotide region on chromosome 13, yielding insight into mechanisms involved in the diversification of FREPs. This is the first genome of schistosomiasis vector snails that has been assembled at the chromosome level, annotated, and analyzed. It serves as a valuable resource for a deeper understanding of the biology of vector snails, especially Biomphalaria snails.

IntroductionOptimal treatment strategies for post-stroke dysphagia (PSD) remain to be explored. Electroacupuncture (EA) has attracted widespread attention due to its simplicity, cheapness, and safety. However, the efficacy of EA in the treatment of PSD lacks high-level evidence-based medical support. This study aimed to systematically evaluate the clinical value of EA in the treatment of PSD.MethodsA total of seven databases were searched for relevant literature. All randomized controlled trials (RCTs) on EA alone or EA combined with other interventions for the treatment of PSD were assessed using the modified Jadad scale. The studies with a score of ≥4 were included. The quality of the included studies was then assessed using the Cochrane Collaboration’s tool. The meta-analysis was performed using Rev. Man 5.3 software.ResultsTwelve studies involving 1,358 patients were included in the meta-analysis. Meta-analysis results showed that the EA group was superior to the control group in terms of clinical response rate (OR = 2.63, 95% CI = 1.97 to 3.53) and videofluoroscopic swallowing study (VFSS) score (MD = 0.73, 95% CI = 0.29 to 1.16). There was no significant difference between the two groups in the standardized swallowing assessment (SSA) score (MD = -3.11, 95% CI = -6.45 to 0.23), Rosenbek penetration-aspiration scale (PAS) score (MD = -0.68, 95% CI = -2.78 to 1.41), Swallowing Quality of Life (SWAL-QOL) score (MD = 13.24, 95% CI = -7.74 to 34.21), or incidence of adverse events (OR = 1.58, 95% CI = 0.73 to 3.38).ConclusionThis study shows that EA combined with conventional treatment or other interventions can significantly improve the clinical response rate and VFSS score in patients with PSD without increasing adverse reactions.Systematic review registration: https://www.crd.york.ac.uk/PROSPERO/display_record.php?RecordID=396840.

Introduction: This study aimed to investigate the effects of electroacupuncture on cortical activation and swallowing muscle groups. The study examined brain activation in healthy subjects performing swallowing tasks during electroacupuncture. Additionally, the study analyzed electromyographic signals of swallowing muscle groups after electroacupuncture. Methods: Twenty-seven healthy subjects were randomly separated into three groups. They underwent electroacupuncture at HT5 acupoint (HT5 group), or GB20 acupoint (GB20 group), or HT5 + GB20 acupoint (HT5 + GB20 group) for 30 min of intervention. Subjects performed a swallowing task while receiving electroacupuncture. Functional near-infrared spectroscopy (fNIRS) was used to detect cortical activation and functional connectivity (FC). The mean amplitude values of the swallowing muscle groups after electroacupuncture were also measured. Statistical analysis was used to investigate the differences between the three groups. The protocol was registered with the China Clinical Trials Registry with the registration number ChiCTR2300067457. Results: Compared with the HT5 group, the HT5 + GB20 group showed higher cortical activation in the LM1 (t = 2.842, P

BackgroundThis study compared the differences in the degree of brain activation, and swallowing function scales in patients with post-stroke dysphagia after treatment. We explored the mechanism of cortical remodeling and the improvement effect of electroacupuncture on swallowing function in patients and provided a theoretical basis for the clinical application of electroacupuncture.MethodsFifty patients with post-stroke dysphagia were randomized to the control or electroacupuncture group. The control group underwent conventional swallowing rehabilitation for 30 min each time for 12 sessions. In the electroacupuncture group, electroacupuncture was performed based on conventional swallowing rehabilitation for 30 min each time for 12 sessions. Cortical activation tests and swallowing function assessments were performed before and after treatment. Statistical analyses were used to investigate the differences within and between the two groups to explore the treatment effects.ResultsThere were no statistical differences in clinical characteristics and baseline data between the two groups before treatment. Cortical activation and swallowing function were improved to different degrees in both groups after treatment compared with before treatment. After treatment, the electroacupuncture group showed higher LPM (t = 4.0780, p

Piezoelectric materials play an increasingly important role in energy harvesters, sensors, and actuators. Flexible and thin piezoelectric films have been demonstrated to provide advanced functionalities and improved performances. However, the research on flexible inorganic piezoelectric thin films has rarely been systematically summarized. Here, we summarize the recent advances in the flexible inorganic piezoelectric thin films, focusing on their structural designs, fabrication techniques, and applications in various practical scenarios. Specifically, different fabrication techniques suitable for diverse inorganic piezoelectric nanostructures are reviewed, including sol–gel, hydrothermal, electrospinning, and other techniques, and the integration process with flexible substrates is further discussed. Biomedical and industrial applications of the flexible piezoelectric thin films are emphasized. Finally, some existing challenges and future perspectives are discussed.

Abstract Objectives By comparing the prognostic performance of 18F-FDG PET/CT-based radiomics combining dose features [Includes Dosiomics feature and the dose volume histogram (DVH) features] with that of conventional radiomics in head and neck cancer (HNC), multidimensional prognostic models were constructed to investigate the overall survival (OS) in HNC. Materials and methods A total of 220 cases from four centres based on the Cancer Imaging Archive public dataset were used in this study, 2260 radiomics features and 1116 dosiomics features and 8 DVH features were extracted for each case, and classified into seven different models of PET, CT, Dose, PET+CT, PET+Dose, CT+Dose and PET+CT+Dose. Features were selected by univariate Cox and Spearman correlation coefficients, and the selected features were brought into the least absolute shrinkage and selection operator (LASSO)-Cox model. A nomogram was constructed to visually analyse the prognostic impact of the incorporated dose features. C-index and Kaplan–Meier curves (log-rank analysis) were used to evaluate and compare these models. Results The cases from the four centres were divided into three different training and validation sets according to the hospitals. The PET+CT+Dose model had C-indexes of 0.873 (95% CI 0.812–0.934), 0.759 (95% CI 0.663–0.855) and 0.835 (95% CI 0.745–0.925) in the validation set respectively, outperforming the rest models overall. The PET+CT+Dose model did well in classifying patients into high- and low-risk groups under all three different sets of experiments (p

A plane-symmetric optical system with a two-dimensional field light source, such as a soft X-ray and vacuum ultraviolet optical system, is widely used for synchrotron radiation source devices, microscopes and so on. Therefore, this paper studied third-order intrinsic aberration modification with second-order accuracy transfer of pupil coordinates and extrinsic aberration of these kinds of optical systems. First, we discuss the extrinsic aberration calculation method and derive the corresponding aberration expressions; in addition, we apply optical geometric relations and the polynomial fitting method to obtain a second-order accuracy transfer relationship expression of the pupil coordinates between adjacent optical surfaces and derived the modification calculation expressions of the intrinsic aberration caused by the above factor. Finally, the third-order intrinsic aberration modification with second-order accuracy transfer of pupil coordinates and extrinsic aberration expressions derived in this paper are applied to calculate ray spot diagrams of two soft X-ray and vacuum ultraviolet optical systems with meridional and sagittal field angle light sources, and these results are compared with those obtained from the ray-tracing software Shadow; this showed that the calculation accuracy of the aberration expressions is sufficient.

Objective: To comprehensively capture intra-tumor heterogeneity in head and neck cancer (HNC) and maximize the use of valid information collected in the clinical field, we propose a novel multi-modal image–text fusion strategy aimed at improving prognosis. Method: We have developed a tailored diagnostic algorithm for HNC, leveraging a deep learning-based model that integrates both image and clinical text information. For the image fusion part, we used the cross-attention mechanism to fuse the image information between PET and CT, and for the fusion of text and image, we used the Q-former architecture to fuse the text and image information. We also improved the traditional prognostic model by introducing time as a variable in the construction of the model, and finally obtained the corresponding prognostic results. Result: We assessed the efficacy of our methodology through the compilation of a multicenter dataset, achieving commendable outcomes in multicenter validations. Notably, our results for metastasis-free survival (MFS), recurrence-free survival (RFS), overall survival (OS), and progression-free survival (PFS) were as follows: 0.796, 0.626, 0.641, and 0.691. Our results demonstrate a notable superiority over the utilization of CT and PET independently, and exceed the result derived without the clinical textual information. Conclusions: Our model not only validates the effectiveness of multi-modal fusion in aiding diagnosis, but also provides insights for optimizing survival analysis. The study underscores the potential of our approach in enhancing prognosis and contributing to the advancement of personalized medicine in HNC.

ObjectiveIn the last three decades, there has been a surge in research on cancer organoids using 3D culture technologies, which has resulted in the development of physiological human cancer models. This study aims to provide an overview of the global trends and frontiers in research on cancer organoids.MethodsA total of 3189 publications on organoids in cancer research from 1991 to 2021 were collected from the Science Citation Index-Expanded (SCIE) of Web of Science (WoS). Bibliometric methods such as the R package “Bibliometrix,” Citespace, and VOS viewer software were employed to investigate and visualize bibliographic coupling, co-citation, co-authorship, and co-occurrence trends, as well as publication trends in the field of organoids in cancer research.ResultsFrom 1991 to 2021, there has been a significant increase in publications on cancer organoids, with most articles being from North America, Eastern Asia, and Western Europe. The USA had the highest number of publications, citations, prolific authors, and research funding globally. Cancers was the journal with the most publications, while Nature had the best total link strength. Harvard University were the most contributive institutions. The global research in this field could be classified into five clusters: chemotherapy study, organoids for drug screening, different models, molecular mechanism study, and organoid construction. These areas are expected to remain hotspots for future research.ConclusionsThe number of publications on organoids in cancer research is expected to increase based on current global trends.

The [Fe, Al]-FER zeolites, which are prepared from the interzeolite conversion method (from MWW to FER topology) with high Al and Fe content (Si/Al of 8–18 and Si/Fe of 11–13), exhibit excellent catalytic performances and hydrothermal tolerance for NH3-SCR reaction. The interzeolite conversion process can be tuned by optimizing the zeolite synthesis conditions such as synthesis gel composition, crystallization time, crystallization temperature, and adding MWW seeds. The work can provide a new strategy to synthesize high Al and Fe content zeolite with high hydrothermal stability for NOx removal.

Using newly developed genetic resources, comparative genomics, and genetic mapping, this study provides novel insights into schistosome resistance in the snail Biomphalaria glabrata, an important intermediate host of Schistosoma mansoni, a causative agent of human schistosomiasis.

In the past 35 years, the natural coastline along Jiaozhou Bay has undergone extensive changes under the influence of human activities, and the coastal wetland area has been drastically reduced. Therefore, it is of great importance to study the spatio-temporal changes of the Jiaozhou Bay coastline, and their trends and causes, for sustainable economic development and the rational utilization of coastal resources. This paper constructed a comprehensive method for extracting the coastline information and change analysis based on long time series remote sensing data. Based on multi-spectral optical data and dual-polarization SAR data, the Normalized Difference Water Index (NDWI) and the Sentinel-1 Dual-polarized Water body Index (SDWI) combined with the Otsu threshold segmentation method were used to automatically extract the spatial distribution of coastline. The U-Net semantic segmentation model was used to classify the land cover types in the land direction of the coastline to count the coastline types. The End Point Rate (EPR) and Linear Regression Rate (LRR) were used to analyze the coastline changes, and the land reclamation was calculated according to the changing trends. The Pearson coefficient was used to study the reasons for the coastline changes. With an average time interval of 5 years, eight coastlines of Jiaozhou Bay in different years were extracted, and the coastline types were obtained. Then, the changes of the coastlines in Jiaozhou Bay from 1987 to 2022 were analyzed. The results show that: 1) Coastline type information provides important information for analyzing the coastline changes in long time series, and coastline information can be effectively extracted using multi-spectral optical data and dual-polarization SAR data. When the resolution of remote sensing data is 30m, the average error of the two types of data is better than one pixel, and the error between the data is about 1-2 pixels. 2) Based on the U-Net model, the overall accuracy of coastline classification using multi-spectral optical data and dual-polarization SAR data is 94.49% and 94.88%, respectively, with kappa coefficients of 0.9143 and 0.8949. 3) In the past 35 years, Jiaozhou Bay area has shown an obvious trend towards the ocean, with an average annual expansion of 16.723m. 4) The coastline of the Jiaozhou Bay area is dynamic. Due to the frequent human activities, the coastline has been reconstructed on a large scale, and the length of artificial coastline has increased significantly. The proportion of artificial coastline length has increased from 33.72% in 1987 to 59.33% in 2022. 5) In the past 35 years, the land reclamation area has reached 41.45km2, of which Shibei District, Licang District, and Huangdao District are the three most frequent areas, with an area of 34.62 km2.

The aspheric surface is a commonly used method to improve the imaging quality of the fisheye lens, but it is difficult to determine the position and initial value. Based on the wave aberration theory of the plane-symmetric optical system, a method of using an aspheric surface to design a fisheye lens is proposed, which can quickly determine the appropriate aspheric surface to improve the imaging performance. First, the wave aberration of each optical surface of the fisheye lens is calculated and its aberration characteristics are analyzed. Then, a numerical evaluation function is reported based on the aberration distribution of the fisheye lens on the image plane. According to the functional relationship between the evaluation function and the aspheric coefficient, the position of the aspheric surface and the initial value of the aspheric coefficient can be calculated. Finally, the adaptive and normalized real-coded genetic algorithm is used as the evaluation function to optimize the fisheye lens using an aspheric surface. The proposed method can provide an effective solution for designing a fisheye lens using an aspheric surface.

New composite hydrogels (CH) based on bacterial cellulose (BC) and poly-1-vinyl-1,2,4-triazole (PVT) doped with orthophosphoric acid (oPA), presenting interpenetrating polymeric networks (IPN), have been synthesized. The mesoscopic study of the supramolecular structure (SMS) of both native cellulose, produced by the strain Komagataeibacter rhaeticus, and the CH based on BC and containing PVT/oPA complex were carried out in a wide range of momentum transfer using ultra- and classical small-angle neutron scattering techniques. The two SMS hierarchical levels were revealed from 1.6 nm to 2.5 μm for the objects under investigation. In addition, it was shown that the native BC had a correlation peak on the small-angle scattering curves at 0.00124 Å−1, with the correlation length ξ being equal to ca. 510 nm. This motive was also retained in the IPN. The data obtained allowed the estimation of the fractal dimensions and ranges of self-similarity and gave new information about the BC mesostructure and its CH. Furthermore, we revealed them to be in coincidence with Brown’s BC model, which was earlier supported by Fink’s results.

BackgroundBiomphalaria pfeifferi is the world's most widely distributed and commonly implicated vector snail species for the causative agent of human intestinal schistosomiasis, Schistosoma mansoni. In efforts to control S. mansoni transmission, chemotherapy alone has proven insufficient. New approaches to snail control offer a way forward, and possible genetic manipulations of snail vectors will require new tools. Towards this end, we here offer a diverse set of genomic resources for the important African schistosome vector, B. pfeifferi.Methodology/principal findingsBased largely on PacBio High-Fidelity long reads, we report a genome assembly size of 772 Mb for B. pfeifferi (Kenya), smaller in size than known genomes of other planorbid schistosome vectors. In a total of 505 scaffolds (N50 = 3.2Mb), 430 were assigned to 18 large linkage groups inferred to represent the 18 known chromosomes, based on whole genome comparisons with Biomphalaria glabrata. The annotated B. pfeifferi genome reveals a divergence time of 3.01 million years with B. glabrata, a South American species believed to be similar to the progenitors of B. pfeifferi which undertook a trans-Atlantic colonization < five million years ago.Conclusions/significanceThe genome for this preferentially self-crossing species is less heterozygous than related species known to be preferential out-crossers; its smaller genome relative to congeners may similarly reflect its preference for selfing. Expansions of gene families with immune relevance are noted, including the FReD gene family which is far more similar in its composition to B. glabrata than to Bulinus truncatus, a vector for Schistosoma haematobium. Provision of this annotated genome will help better understand the dependencies of trematodes on snails, enable broader comparative insights regarding factors contributing to susceptibility/ resistance of snails to schistosome infections, and provide an invaluable resource with respect to identifying and manipulating snail genes as potential targets for more specific snail control programs.

BackgroundUpper limb intelligence robots are widely used to improve the upper limb function of patients with stroke, but the treatment mechanism is still not clear. In this study, functional near-infrared spectroscopy (fNIRS) was used to evaluate the concentration changes of oxygenated hemoglobin (oxy-Hb) and deoxyhemoglobin (deoxy-Hb) in different brain regions and functional connectivity (FC) of the cerebral cortex in patients with stroke.MethodTwenty post-stroke patients with upper limb dysfunction were included in the study. They all received three different types of shoulder joint training, namely, active intelligent feedback robot training (ACT), upper limb suspension training (SUS), and passive intelligent feedback robot training (PAS). During the training, activation of the cerebral cortex was detected by fNIRS to obtain the concentration changes of hemoglobin and FC of the cerebral cortex. The fNIRS signals were recorded over eight ROIs: bilateral prefrontal cortices (PFC), bilateral primary motor cortices (M1), bilateral primary somatosensory cortices (S1), and bilateral premotor and supplementary motor cortices (PM). For easy comparison, we defined the right hemisphere as the ipsilesional hemisphere and flipped the lesional right hemisphere in the Nirspark.ResultCompared with the other two groups, stronger cerebral cortex activation was observed during ACT. One-way repeated measures ANOVA revealed significant differences in mean oxy-Hb changes among conditions in the four ROIs: contralesional PFC [F(2, 48) = 6,798, p < 0.01], ipsilesional M1 [F(2, 48) = 6.733, p < 0.01], ipsilesional S1 [F(2, 48) = 4,392, p < 0.05], and ipsilesional PM [F(2, 48) = 3.658, p < 0.05]. Oxy-Hb responses in the contralesional PFC region were stronger during ACT than during SUS (p < 0.01) and PAS (p < 0.05). Cortical activation in the ipsilesional M1 was significantly greater during ACT than during SUS (p < 0.01) and PAS (p < 0.05). Oxy-Hb responses in the ipsilesional S1 (p < 0.05) and ipsilesional PM (p < 0.05) were significantly higher during ACT than during PAS, and there is no significant difference in mean deoxy-Hb changes among conditions. Compared with SUS, the FC increased during ACT, which was characterized by the enhanced function of the ipsilesional cortex (p < 0.05), and there was no significant difference in FC between the ACT and PAS.ConclusionThe study found that cortical activation during ACT was higher in the contralesional PFC, and ipsilesional M1 than during SUS, and showed tighter cortical FC between the cortices. The activation of the cerebral cortex of ACT was significantly higher than that of PAS, but there was no significant difference in FC. Our research helps to understand the difference in cerebral cortex activation between upper limb intelligent feedback robot rehabilitation and other rehabilitation training and provides an objective basis for the further application of upper limb intelligent feedback robots in the field of stroke rehabilitation.

Abstract Among the snail genera most responsible for vectoring human-infecting schistosomes, Bulinus, Biomphalaria, and Oncomelania, the former is in many respects the most important. Bulinid snails host the most common human blood fluke, Schistosoma haematobium, responsible for approximately two-thirds of the estimated 237 million cases of schistosomiasis. They also support transmission of schistosomes to millions of domestic and wild animals. Nonetheless, our basic knowledge of the 37 Bulinus species remains incomplete, especially with respect to genome information, even including mitogenome sequences. We determined complete mitogenome sequences for Bulinus truncatus, B. nasutus, and B. ugandae, and three representatives of B. globosus from eastern, central, and western Kenya. A difference of the location of tRNA-Asp was found between mitogenomes from the three species of the Bulinus africanus group and B. truncatus. Phylogenetic analysis using partial cox1 sequences suggests that B. globosus is a complex comprised of multiple species. We also highlight the status of B. ugandae as a distinct species with unusual interactions with the S. haematobium group parasites deserving of additional investigation. We provide sequence data for potential development of genetic markers for specific or intraspecific Bulinus studies, help elucidate the relationships among Bulinus species, and suggest ways in which mitogenomes may help understand the complex interactions between Schistosoma and Bulinus snails and their relatives.

The main core of InSAR (interferometric synthetic aperture radar) data processing is phase unwrapping, and the output has a direct impact on the quality of the data processing products. Noise introduced from the SAR system and interferometric processing is unavoidable, causing local phase inaccuracy and limiting the unwrapping results of traditional unwrapping methods. With the successful implementation of deep learning in a variety of industries in recent years, new concepts for phase unwrapping have emerged. This research offers a one-step InSAR phase unwrapping method based on an improved pix2pix network model. We achieved our aim by upgrading the pix2pix network generator model and introducing the concept of quality map guidance. Experiments on InSAR phase unwrapping utilizing simulated and real data with different noise intensities were carried out to compare the method with other unwrapping methods. The experimental results demonstrated that the proposed method is superior to other unwrapping methods and has a good robustness to noise.

Based on the cognitive-behavioral model of pathological internet use, this study explored the relationship between zhongyong thinking (doctrine of the mean) and internet addiction, and examined the mediation of maladaptive cognition and the moderation of subject. Convenience sampling was used to select 1,518 college students for the questionnaire. The participants were 15–26 years old (M = 19.77; SD = 1.45), including 776 male and 742 female students. The results showed that zhongyong thinking was significantly negatively correlated with maladaptive cognition (r = −0.19, p < 0.001) and internet addiction (r = −0.14, p < 0.001). Maladaptive cognition was significantly positively correlated with internet addiction (r = 0.46, p < 0.001). After controlling for age, gender, zhongyong thinking negatively predicted internet addiction (B = −0.06, p < 0.05), maladaptive cognition positively predicted Internet addiction (B = 0.45, p < 0.001). Zhongyong thinking negatively predicted maladaptive cognition (B = −0.19, p < 0.001). Moreover, the bias-corrected bootstrapping mediation test indicated that the process by which zhongyong thinking predicted Internet addiction through maladaptive cognition was significant, indirect effect = −0.08, SE = 0.01, 95% CI = [−0.11, −0.06]. Subject has no moderating effect on the relationship between zhongyong thinking and maladaptive cognition. The interaction between zhongyong thinking and subject was not a significant predictor of maladaptive cognition (B = 0.05, p > 0. 05). The present results suggest that zhongyong thinking as a traditional Chinese wisdom can still play an important role in regulating young people's behavior in the digital age.

Cyberbullying has become a worldwide phenomenon. Although the topic has drawn decent academic attention and many studies have been conducted on Chinese samples, variable interests in these studies have not captured the thinking and behavioral characteristics of Chinese people. Based on the dual filial piety model and self-determination theory, this study examined the effect of filial piety belief on cyberbullying perpetration and tested the mediation of relatedness need satisfaction. A total of 856 university students completed the questionnaires, including dual filial piety scale, relatedness need satisfaction scale and cyberbullying perpetration scale. The regression results found that reciprocal filial piety negatively predicted and authoritarian filial piety positively predicted cyberbullying perpetration. The SEM results showed that reciprocal filial piety and authoritarian filial piety impacted cyberbullying perpetration through the mediating effect of relatedness need satisfaction. Reciprocal filial piety was positively while authoritarian filial piety negatively correlated with relatedness need satisfaction and relatedness need satisfaction was negatively correlated with cyberbullying perpetration. The results provide a new position to understand the effect of family factors on cyberbullying perpetration by placing the topic within traditional Chinese family value.

BackgroundExtant research has indicated that parenting practice, such as harsh parenting, rejection, and neglect increases the risk of mobile phone addiction. However, no research to date has examined the association between parenting by lying about money and adolescent mobile phone addiction.ObjectiveThe current study used a survey to test whether parenting by lying about money may be associated with adolescent mobile phone addiction. The mediation of anxiety and moderation of socioeconomic status were also examined.Materials and methodsWe recruited 971 adolescents from five secondary schools in a city in central China. Of the participants, 448 (46.14%) were boys and 523 (53.86%) were girls (Mage = 13.63, SDage = 1.01).ResultsThe results of mediation analysis indicated that parenting by lying about money positively predicted mobile phone addiction (B = 0.144, p < 0.01); parenting by lying about money positively predicted anxiety (B = 0.126, p < 0.01) and mobile phone addiction (B = 0.107, p < 0.01). Anxiety positively predicted mobile phone addiction (B = 0.293, p < 0.01). Moreover, the bias-corrected bootstrapping mediation test indicated that the process by which parenting by lying about money predicted mobile phone addiction through anxiety was significant (indirect effect = 0.037, SE = 0.011, 95% CI = [0.017, 0.059]).ConclusionThe current study suggests that parenting by lying about money may lead to mobile phone addiction through the mediation of anxiety. However, the effect was stronger for adolescents with higher level of socioeconomic status than their counterparts.

DNA‐damaging agents, such as doxorubicin (Adriamycin), are widely used for the treatment of small cell lung cancer (SCLC). However, drug resistance is one of the major challenges for treatment of SCLC. Herein, we investigated the mechanisms underlying drug resistance in SCLC cells and the effects of resveratrol (Res) on drug resistance. We report that Adriamycin treatment of H69AR (multidrug resistance phenotype) cells resulted in a lower rate of growth inhibition, up‐regulation of MRP1 and P‐glycoprotein (P‐gp), and higher P‐gp activity as compared with susceptible H69 cells treated with Adriamycin. Moreover, the signal transducer and activator of transcription 3/vascular endothelial growth factor (STAT3/VEGF) pathway was overactivated in H69AR cells, especially after interleukin‐23 treatment. The inflammatory microenvironment promoted the drug resistance of H69AR cells by activating the STAT3/VEGF pathway. The addition of Res suppressed the expression levels of inflammatory mediators, inhibited the STAT3/VEGF pathway, impeded P‐gp activity, and decreased the drug resistance of H69AR cells. H69AR cells exhibited Adriamycin resistance through activation of the STAT3/VEGF pathway, and Res ameliorated the inflammatory microenvironment to suppress the STAT3/VEGF pathway to reduce drug resistance. Our results suggest that Res may have therapeutic potential for SCLC treatment.

Artificial skin, also known as bioinspired electronic skin (e-skin), refers to intelligent wearable electronics that imitate the tactile sensory function of human skin and identify the detected changes in external information through different electrical signals. Flexible e-skin can achieve a wide range of functions such as accurate detection and identification of pressure, strain, and temperature, which has greatly extended their application potential in the field of healthcare monitoring and human-machine interaction (HMI). During recent years, the exploration and development of the design, construction, and performance of artificial skin has received extensive attention from researchers. With the advantages of high permeability, great ratio surface of area, and easy functional modification, electrospun nanofibers are suitable for the construction of electronic skin and further demonstrate broad application prospects in the fields of medical monitoring and HMI. Therefore, the critical review is provided to comprehensively summarize the recent advances in substrate materials, optimized fabrication techniques, response mechanisms, and related applications of the flexible electrospun nanofiber-based bio-inspired artificial skin. Finally, some current challenges and future prospects are outlined and discussed, and we hope that this review will help researchers to better understand the whole field and take it to the next level.

The concept of value co-creation brings about changes in tourists’ roles from value receivers to producers. Most existing studies take value co-creation behavior as a single dimension, ignoring the role switching of tourists. Starting from the precise constitution of value co-creation behavior, this paper, utilizing the method of structural equation modeling (SEM), discusses the mechanism of the effects of tourist participation behavior and citizenship behavior on destination loyalty through each sub-dimension of perceived value. The results showed the following: (1) The participation behavior (in-role) and citizenship behavior (extra-role) of tourists affect different value dimensions. (2) The value co-created by tourists presents a hierarchical state from the primary to the higher level. Among the types of value, novelty and social value belong to the primary level while quality, economic, knowledge, and emotional value belong to the higher level. (3) Destination loyalty is driven not only by tourist behavior (in-role) but also by citizenship behavior (extra-role). Based on the perspective of role switching, this paper establishes the theoretical framework of role switching in the era of value co-creation and proposes some strategic suggestions for marketing transformation.

Drosophila m6A writer complex regulates alternative splicing of the Sex-lethal gene. Here the authors show that a potential E3 ligase Hakai interacts with the fly m6A writer complex and that m6A level is reduced in Hakai mutant flies.

Polarimetric calibration is indispensable to quantitatively apply and analyze the polarimetric synthetic aperture radar (PolSAR) image. At present, the polarimetric calibration methods relying on the assumption of reflection symmetry have been widely used, which need to extract the reference targets that meet the assumptions before calibration and then calculate the cross-pol channel imbalance and crosstalk errors. However, the distortion in the uncalibrated image will affect the calculation of polarization features, resulting in inaccurate target extraction results. Consequently, we proposed a reflection symmetric target extraction method that combines with spatial statistics information. The method first takes the initial extraction result based on the polarization power total Span and introduces the hypothesis testing to judge the homogeneous samples. Finally, we automatically calculate the threshold by the Otsu algorithm to achieve high-precision extraction of the reflection symmetric targets. Meanwhile, we carried out the polarimetric calibration experiments based on real C- and X-band airborne PolSAR data and conducted qualitative and quantitative evaluation and analysis of the experimental results. The studies demonstrated that, compared with classical approaches, the proposed approach further improved the accuracy of polarimetric calibration by extracting more accurate reference samples.

Purpose: This study aims to investigate the impact of aggregation methods used for the generation of texture features on their robustness of nasopharyngeal carcinoma (NPC) based on 18F-FDG PET/CT images. Methods: 128 NPC patients were enrolled and 95 texture features were extracted for each patient including six feature families under different aggregation methods. For GLCM and GLRLM features, six aggregation methods were considered. For GLSZM, GLDZM, NGTDM and NGLDM features, three aggregation methods were considered. The robustness of the features affected by aggregation methods was assessed by the pair-wise intra-class correlation coefficient (ICC). Furthermore, the effects of discretization and partial volume correction (PVC) on the percent of ICC categories of all texture features were evaluated by overall ICC instead of the pair-wise ICC. Results: There were 12 features with excellent pair-wise ICCs varying aggregation methods, namely joint average, sum average, autocorrelation, long run emphasis, high grey level run emphasis, short run high grey level emphasis, long run high grey level emphasis, run length variance, SZM high grey level emphasis, DZM high grey level emphasis, high grey level count emphasis and dependence count percentage. For GLCM and GLRLM features, 19/25 and 14/16 features showed excellent pair-wise ICCs varying aggregation methods (averaged and merged) on the same dimensional features (2D, 2.5D or 3D). Different discretization levels and partial volume corrections lead to consistent robustness of textural features affected by aggregation methods. Conclusion: Different dimensional features with the same aggregation methods showed worse robustness compared with the same dimensional features with different aggregation methods. Different discretization levels and PVC algorithms had a negligible effect on the percent of ICC categories of all texture features.

Dynamic positron emission tomography (PET) imaging usually suffers from high statistical noise due to low counts of the short frames. This study aims to improve the image quality of the short frames by utilizing information from other modality. We develop a deep learning-based joint filtering framework for simultaneously incorporating information from longer acquisition PET frames and high-resolution magnetic resonance (MR) images into the short frames. The network inputs are noisy PET images and corresponding MR images while the outputs are linear coefficients of spatially variant linear representation model. The composite of all dynamic frames is used as training label in each sample, and it is down-sampled to 1/10th of counts as the training input. L1-norm combined with two gradient-based regularizations constitute the loss function during training. Ten realistic dynamic PET/MR phantoms based on BrainWeb are used for pre-training and eleven clinical subjects from Alzheimer’s Disease Neuroimaging Initiative further for fine-tuning. Simulation results show that the proposed method can reduce the statistical noise while preserving image details and achieve quantitative enhancements compared with Gaussian, guided filter, and convolutional neural network trained with the mean squared error. The clinical results perform better than others in terms of the mean activity and standard deviation. All of the results indicate that the proposed deep learning-based joint filtering framework is of great potential for dynamic PET image denoising.

Dynamic positron emission tomography (PET) image reconstruction is challenging due to the low-count statistics of individual frames. This study proposes a novel reconstruction framework aiming to enhance the quantitative accuracy of individual dynamic frames via the introduction of priors based on multiscale superpixel clusters. The clusters are derived from pre-reconstruction composite images using superpixel clustering followed by fuzzy c-means (FCM) clustering. A multiscale aggregation is exploited during the superpixel clustering to generate multiscale superpixel clusters. Then, maximum a posteriori (MAP) PET reconstruction with different-scale clusters is separately applied to individual frame and fused to generate the final result. Using realistic simulated dynamic brain PET data, the quantitative performance of the proposed method is investigated and compared with the maximum-likelihood expectation-maximization (MLEM), Bowsher method, and kernelized expectation-maximization (the kernel method). The proposed method achieves substantial improvements in both visual and quantitative accuracy (in terms of the signal-to-noise ratio and contrast versus noise performances). The method is also tested with a 60 min 18F-FDG rat study performed with an Inveon small animal PET scanner. The proposed method is shown to outperform the other methods via improvements in visual and quantitative accuracy (in terms of noise versus the mean intensity of the region of interest).

The quantitative accuracy of positron emission tomography (PET) is affected by several factors, including the intrinsic resolution of the imaging system and inherently noisy data, which result in a low signal-to-noise ratio (SNR) of PET image. To address this problem, in this paper, we proposed a novel deep learning denoising framework aiming to enhance the quantitative accuracy of dynamic PET images via introduction of deep image prior (DIP) combined with Regularization by Denoising (RED), as such the method is labeled as DeepRED denoising. The network structure is based on encoder-decoder architecture and uses skip connections to combine hierarchical features to generate the estimated image. The network input can be random noise or other prior images (such as the patient’s own static PET image), avoiding the need of high quality noiseless images, which is limited in PET clinical practice due to high radiation dose. Based on simulated data and real patient data, the quantitative performance of the proposed method was compared with conventional Gaussian filtering (GF), non-local mean (NLM), block-matching and 3D filtering (BM3D), DIP and stochastic gradient Langevin dynamics (SGLD) method. Overall, the proposed method can outperform other conventional methods in substantial visual as well as quantitative accuracy improvements (in terms of noise versus bias performance) with and without prior images.

To investigate the prognostic value of peri-tumoral radiomics features of pre-treatment PET/CT images in patients with head and neck cancer. 166 patients from 4 centers (111 for training and 55 for external independent testing) were retrospectively analyzed. 11 regions were used for feature extraction, (1) Intra-tumoral region (Intra) was first dilated radially along the edge by 3, 6, 9, 12 and 15 mm to obtain (2) 5 solid combined regions (noted as Comb_3, 6, 9, 12, and 15, respectively), and (3) 5 hollow annular regions with equal ring width of 3 mm were then generated as peri-tumoral regions (noted as Peri_3, 6, 9, 12 and 15, respectively). 92 individual/integrated models were constructed by using features from Clinical alone, CT or PET alone, Clinical+PET, Clinical+CT, PET+CT, Clinical+PET+CT, Intra+Peri, Clinical+Intra+Peri and Clinical+PET+CT (Intra+Peri). In individual models, only 4 models showed p

Abstract Background Convolutional neural networks (CNNs) have been extensively applied to two-dimensional (2D) medical image segmentation, yielding excellent performance. However, their application to three-dimensional (3D) nodule segmentation remains a challenge. Methods In this study, we propose a multi-view secondary input residual (MV-SIR) convolutional neural network model for 3D lung nodule segmentation using the Lung Image Database Consortium and Image Database Resource Initiative (LIDC-IDRI) dataset of chest computed tomography (CT) images. Lung nodule cubes are prepared from the sample CT images. Further, from the axial, coronal, and sagittal perspectives, multi-view patches are generated with randomly selected voxels in the lung nodule cubes as centers. Our model consists of six submodels, which enable learning of 3D lung nodules sliced into three views of features; each submodel extracts voxel heterogeneity and shape heterogeneity features. We convert the segmentation of 3D lung nodules into voxel classification by inputting the multi-view patches into the model and determine whether the voxel points belong to the nodule. The structure of the secondary input residual submodel comprises a residual block followed by a secondary input module. We integrate the six submodels to classify whether voxel points belong to nodules, and then reconstruct the segmentation image. Results The results of tests conducted using our model and comparison with other existing CNN models indicate that the MV-SIR model achieves excellent results in the 3D segmentation of pulmonary nodules, with a Dice coefficient of 0.926 and an average surface distance of 0.072. Conclusion our MV-SIR model can accurately perform 3D segmentation of lung nodules with the same segmentation accuracy as the U-net model.

Abstract Background The AIG (avrRpt2-induced gene) family of GTPases, characterized by the presence of a distinctive AIG1 domain, is mysterious in having a peculiar phylogenetic distribution, a predilection for undergoing expansion and loss, and an uncertain functional role, especially in invertebrates. AIGs are frequently represented as GIMAPs (GTPase of the immunity associated protein family), characterized by presence of the AIG1 domain along with coiled-coil domains. Here we provide an overview of the remarkably expanded AIG repertoire of the freshwater gastropod Biomphalaria glabrata, compare it with AIGs in other organisms, and detail patterns of expression in B. glabrata susceptible or resistant to infection with Schistosoma mansoni, responsible for the neglected tropical disease of intestinal schistosomiasis. Results We define the 7 conserved motifs that comprise the AIG1 domain in B. glabrata and detail its association with at least 7 other domains, indicative of functional versatility of B. glabrata AIGs. AIG genes were usually found in tandem arrays in the B. glabrata genome, suggestive of an origin by segmental gene duplication. We found 91 genes with complete AIG1 domains, including 64 GIMAPs and 27 AIG genes without coiled-coils, more than known for any other organism except Danio (with > 100). We defined expression patterns of AIG genes in 12 different B. glabrata organs and characterized whole-body AIG responses to microbial PAMPs, and of schistosome-resistant or -susceptible strains of B. glabrata to S. mansoni exposure. Biomphalaria glabrata AIG genes clustered with expansions of AIG genes from other heterobranch gastropods yet showed unique lineage-specific subclusters. Other gastropods and bivalves had separate but also diverse expansions of AIG genes, whereas cephalopods seem to lack AIG genes. Conclusions The AIG genes of B. glabrata exhibit expansion in both numbers and potential functions, differ markedly in expression between strains varying in susceptibility to schistosomes, and are responsive to immune challenge. These features provide strong impetus to further explore the functional role of AIG genes in the defense responses of B. glabrata, including to suppress or support the development of medically relevant S. mansoni parasites.

BackgroundWe seek to provide a comprehensive overview of transcriptomics responses of immune-related features of the gastropod Biomphalaria glabrata (Bg) following exposure to Schistosoma mansoni (Sm), a trematode causing human schistosomiasis. Responses of schistosome-susceptible (M line, or SUS) and -resistant (BS-90, or RES) Bg strains were characterized following exposure to Sm for 0.5, 2, 8 or 40 days post-exposure (dpe).MethodsRNA-Seq and differential expression analysis were undertaken on 56 snails from 14 groups. We considered 7 response categories: 1) constitutive resistance factors; 2) constitutive susceptibility factors; 3) generalized stress responses; 4) induced resistance factors; 5) resistance factors suppressed in SUS snails; 6) suppressed/manipulated factors in SUS snails; and 7) tolerance responses in SUS snails. We also undertook a gene co-expression network analysis. Results from prior studies identifying schistosome resistance/susceptibility factors were examined relative to our findings.ResultsA total of 792 million paired-end reads representing 91.2% of the estimated 31,985 genes in the Bg genome were detected and results for the 7 categories compiled and highlighted. For both RES and SUS snails, a single most supported network of genes with highly correlated expression was found.Conclusions1) Several constitutive differences in gene expression between SUS and RES snails were noted, the majority over-represented in RES; 2) There was little indication of a generalized stress response shared by SUS and RES snails at 0.5 or 2 dpe; 3) RES snails mounted a strong, multi-faceted response by 0.5 dpe that carried over to 2 dpe; 4) The most notable SUS responses were at 40 dpe, in snails shedding cercariae, when numerous features were either strongly down-regulated indicative of physiological distress or parasite manipulation, or up-regulated, suggestive of tolerance or survival-promoting effects; 5) Of 55 genes previously identified in genome wide mapping studies, 29 (52.7%) were responsive to Sm, as were many familiar resistance-associated genes (41.0%) identified by other means; 6) Both network analysis and remarkably specific patterns of expression of lectins and G protein-coupled receptors in categories 4, 6 and 7 were indicative of orchestrated responses of different suites of genes in SUS or RES snails following exposure to Sm.