Learned Tensor Neural Network Texture Prior for Photon-Counting CT Reconstruction.

Photon-counting computed tomography (PCCT) reconstructs multiple energy-channel images to describe the same object, where there exists a strong correlation among different channel images. In addition, reconstruction of each channel image suffers photon count starving problem. To make full use of the correlation among different channel images to suppress the data noise and enhance the texture details in reconstructing each channel image, this paper proposes a tensor neural network (TNN) architecture to learn a multi-channel texture prior for PCCT reconstruction. Specifically, we first learn a spatial texture prior in each individual channel image by modeling the relationship between the center pixels and its corresponding neighbor pixels using a neural network. Then, we merge the single channel spatial texture prior into multi-channel neural network to learn the spectral local correlation information among different channel images. Since our proposed TNN is trained on a series of unpaired small spatial-spectral cubes which are extracted from one single reference multi-channel image, the local correlation in the spatial-spectral cubes is considered by TNN. To boost the TNN performance, a low-rank representation is also employed to consider the global correlation among different channel images. Finally, we integrate the learned TNN and the low-rank representation as priors into Bayesian reconstruction framework. To evaluate the performance of the proposed method, four references are considered. One is simulated images from ultra-high-resolution CT. One is spectral images from dual-energy CT. The other two are animal tissue and preclinical mouse images from a custom-made PCCT systems. Our TNN prior Bayesian reconstruction demonstrated better performance than other state-of-the-art competing algorithms, in terms of not only preserving texture feature but also suppressing image noise in each channel image.

Phosphodiesterase 8 (PDE8): Distribution and Cellular Expression and Association with Alzheimer's Disease.

Phosphodiesterase 8 (PDE8), as a member of PDE superfamily, specifically promotes the hydrolysis and degradation of intracellular cyclic adenosine monophosphate (cAMP), which may be associated with pathogenesis of Alzheimer's disease (AD). However, little is currently known about potential role in the central nervous system (CNS). Here we investigated the distribution and expression of PDE8 in brain of mouse, which we believe can provide evidence for studying the role of PDE8 in CNS and the relationship between PDE8 and AD. Here, C57BL/6J mice were used to observe the distribution patterns of two subtypes of PDE8, PDE8A and PDE8B, in different sexes in vivo by western blot (WB). Meanwhile, C57BL/6J mice were also used to demonstrate the distribution pattern of PDE8 in selected brain regions and localization in neural cells by WB and multiplex immunofluorescence staining. Furthermore, the triple transgenic (3×Tg-AD) mice and wild type (WT) mice of different ages were used to investigate the changes of PDE8 expression in the hippocampus and cerebral cortex during the progression of AD. PDE8 was found to be widely expressed in multiple tissues and organs including heart, kidney, stomach, brain, and liver, spleen, intestines, and uterus, with differences in expression levels between the two subtypes of PDE8A and PDE8B, as well as two sexes. Meanwhile, PDE8 was widely distributed in the brain, especially in areas closely related to cognitive function such as cerebellum, striatum, amygdala, cerebral cortex, and hippocampus, without differences between sexes. Furthermore, PDE8A was found to be expressed in neuronal cells, microglia and astrocytes, while PDE8B is only expressed in neuronal cells and microglia. PDE8A expression in the hippocampus of both female and male 3×Tg-AD mice was gradually increased with ages and PDE8B expression was upregulated only in cerebral cortex of female 3×Tg-AD mice with ages. However, the expression of PDE8A and PDE8B was apparently increased in both cerebral cortex and hippocampus in both female and male 10-month-old 3×Tg-AD mice compared WT mice. These results suggest that PDE8 may be associated with the progression of AD and is a potential target for its prevention and treatment in the future.

Contribution of platelets to disruption of the blood-brain barrier during arterial baroreflex dysfunction.

BACKGROUND: Arterial baroreflex dysfunction, like many other central nervous system disorders, involves disruption of the blood-brain barrier, but what causes such disruption in ABR dysfunction is unclear. Here we explored the potential role of platelets in this disruption. METHODS: ABR dysfunction was induced in rats using sinoaortic denervation, and the effects on integrity of the blood-brain barrier were explored based on leakage of Evans blue or FITC-dextran, while the effects on expression of CD40L in platelets and of key proteins in microvascular endothelial cells were explored using immunohistochemistry, western blotting and enzyme-linked immunosorbent assay. Similar experiments were carried out in rat brain microvascular endothelial cell line, which we exposed to platelets taken from rats with ABR dysfunction. RESULTS: Sinoaortic denervation permeabilized the blood-brain barrier and downregulated zonula occludens-1 and occludin in rat brain, while upregulating expression of CD40L on the surface of platelets and stimulating platelet aggregation. Similar effects of permeabilization and downregulation were observed in healthy rats that received platelets from animals with ABR dysfunction, and in rat brain microvascular endothelial cells, but only in the presence of lipopolysaccharide. These effects were associated with activation of NF-κB signaling and upregulation of matrix metalloprotease-9. These effects of platelets from animals with ABR dysfunction were partially blocked by neutralizing antibody against CD40L or the platelet inhibitor clopidogrel. CONCLUSION: During ABR dysfunction, platelets may disrupt the blood-brain barrier when CD40L on their surface activates NF-kB signaling within cerebral microvascular endothelial cells, leading to upregulation of matrix metalloprotease-9. Our findings imply that targeting CD40L may be effective against cerebral diseases involving ABR dysfunction.

Proceedings of the 17th International Meeting on Fully 3D Image Reconstruction in Radiology and Nuclear Medicine.

Contained within this volume are the scholarly contributions presented in both oral and poster formats at Fully3D 2023: The 17th International Meeting on Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine. This conference convened from July 16-21, 2023, at Stony Brook University in New York. For ease of reference, all papers are organized alphabetically according to the last names of the primary authors. Our heartfelt appreciation goes out to all participants who took the time to submit, present, and revise their work for inclusion in these proceedings. Collectively, we would also like to express our profound gratitude to our generous sponsors, detailed in subsequent pages, who have played an instrumental role in offering awards and facilitating the various conference activities. Additionally, our thanks extend to the diligent reporter who collated invaluable feedback from attendees, which can be found in the pages that follow. September 7, 2023 Fully3D 2023 Co-Chairs: Jerome Liang, Paul Vaska, and Chuan Huang.

Ralstonia solanacearum differentially modulates soil physicochemical properties and rhizospheric bacteriome of resistant and susceptible tobacco cultivars.

Ralstonia solanacearum is a devastating soilborne pathogen which poses significant yield and economic losses to tobacco production globally. The impact of R. solanacearum on rhizosphere bacteriome and soil physicochemical characteristics in resistant and susceptible tobacco cultivars is poorly understood. This study aims to determine the effect of R. solanacearum on soil physicochemical parameters and rhizosphere bacteriome of resistant (K326) and susceptible (Hongda) tobacco cultivars at various growth stages. Results demonstrated that the contents of available potassium and phosphorus, as well as soil pH were significantly increased in K326 soils (CK and T2) compared with Hongda (T1) after 21, 42, and 63 days post-inoculation (dpi) of R. solanacearum except for available nitrogen which showed an opposite trend. The qPCR results showed a significant decrease in R. solanacearum population in rhizosphere of K326 (T2) compared to the Hongda (T1) at 21 and 63 dpi than that after 42 dpi. The rhizosphere bacteriome analysis through 16S rRNA amplicon sequencing revealed that rhizosphere bacterial community composition was significantly different between two tobacco cultivars (Hongda and K326) and this effect was more prominent after 63 dpi (93 days after post-transplantation), suggesting that each cultivar recruits a unique set of bacterial communities. There was no obvious difference observed in the rhizosphere bacteriome of CK (K326) and T2 (K326), which might be attributed to the same genetic makeup and inherent resistance of K326 to bacterial wilt infection. Analysis of co-occurrence networks revealed that the microbial network in T1 (Hongda) was more complex than those in T2 (K326) and CK (K326), while the networks in CK and T2 were almost identical. The present research highlights the time-course relationship between environmental factors and rhizosphere bacteriome of tobacco cultivars showing different levels of resistance against R. solanacearum. Conclusively, studying the plant-soil-microbe interaction system in susceptible and resistant tobacco cultivars may enable us to develop effective integrated disease control plans for the healthy production of tobacco crops.

ELONGATED HYPOCOTYL 5a modulates FLOWERING LOCUS T2 and gibberellin levels to control dormancy and bud break in poplar.

Photoperiod is a crucial environmental cue for phenological responses, including growth cessation and winter dormancy in perennial woody plants. Two regulatory modules within the photoperiod pathway explain bud dormancy induction in poplar (Populus spp.): the circadian oscillator LATE ELONGATED HYPOCOTYL 2 (LHY2) and GIGANTEA-like genes (GIs) both regulate the key target for winter dormancy induction FLOWERING LOCUS T2 (FT2). However, modification of LHY2 and GIs cannot completely prevent growth cessation and bud set under short-day (SD) conditions, indicating that additional regulatory modules are likely involved. We identified PtoHY5a, an orthologs of the photomorphogenesis regulatory factor ELONGATED HYPOCOTYL 5 (HY5) in poplar (Populus tomentosa), that directly activates PtoFT2 expression and represses the circadian oscillation of LHY2, indirectly activating PtoFT2 expression. Thus, PtoHY5a suppresses SD-induced growth cessation and bud set. Accordingly, PtoHY5a knockout facilitates dormancy induction. PtoHY5a also inhibits bud-break in poplar by controlling gibberellic acid (GA) levels in apical buds. Additionally, PtoHY5a regulates the photoperiodic control of seasonal growth downstream of phytochrome PHYB2. Thus, PtoHY5a modulates seasonal growth in poplar by regulating the PtoPHYB2-PtoHY5a-PtoFT2 module to determine the onset of winter dormancy, and by fine-tuning GA levels to control bud-break.

Overexpression of PtoMYB99 diminishes poplar tolerance to osmotic stress by suppressing ABA and JA biosynthesis.

Drought poses a serious challenge to sustained plant growth and crop yields in the context of global climate change. Drought tolerance in poplars and their underlying mechanisms still remain largely unknown. In this article, we investigated the overexpression of PtoMYB99 - both a drought and abscisic acid (ABA) induced gene constraining drought tolerance in poplars (as compared with wild type poplars). First, we found that PtoMYB99-OE lines exhibited increased stomatal opening and conductance, higher transpiration and photosynthetic rates, as well as reduced levels of ABA and jasmonic acid (JA). Second, PtoMYB99-OE lines accumulated more reactive oxygen species (ROS), including H2O2 and O2-, as well as malonaldehyde (MDA), proline, and soluble sugar under osmotic stress; conversely, the activity of antioxidant enzymes (SOD, POD, and CAT), was weakened in the PtoMYB99-OE lines. Third, the expression of ABA biosynthetic genes, PtoNCED3.1 and PtoNCED3.2, as well as JA biosynthetic genes, PtoOPR3.1 and PtoOPR3.2, was significantly reduced in the PtoMYB99-OE lines under both normal conditions and osmotic stress. Based on our results, we conclude that the overexpression of PtoMYB99 compromises tolerance to osmotic stress in poplar. These findings contribute to the understanding of the role of the MYB genes in drought stress and the biosynthesis of ABA and JA.

The heat response regulators HSFA1s promote Arabidopsis thermomorphogenesis via stabilizing PIF4 during the day.

During summer, plants often experience increased light inputs and high temperatures, two major environmental factors with contrasting effects on thermomorphological traits. The integration of light and temperature signaling to control thermomorphogenesis in plants is critical for their acclimation in such conditions, but the underlying mechanisms remain largely unclear. We found that heat shock transcription factor 1d (HSFA1d) and its homologs are necessary for plant thermomorphogenesis during the day. In response to warm daytime temperature, HSFA1s markedly accumulate and move into the nucleus where they interact with phytochrome-interacting factor 4 (PIF4) and stabilize PIF4 by interfering with phytochrome B-PIF4 interaction. Moreover, we found that the HSFA1d nuclear localization under warm daytime temperature is mediated by constitutive photomorphogenic 1-repressed GSK3-like kinase BIN2. These results support a regulatory mechanism for thermomorphogenesis in the daytime mediated by the HSFA1s-PIF4 module and uncover HSFA1s as critical regulators integrating light and temperature signaling for a better acclimation of plants to the summer high temperature.

Polymeric Materials for Rare Earth Elements Recovery.

Rare earth elements (REEs) play indispensable roles in various advanced technologies, from electronics to renewable energy. However, the heavy global REEs supply and the environmental impact of traditional mining practices have spurred the search for sustainable REEs recovery methods. Polymeric materials have emerged as promising candidates due to their selective adsorption capabilities, versatility, scalability, and regenerability. This paper provides an extensive overview of polymeric materials for REEs recovery, including polymeric resins, polymer membranes, cross-linked polymer networks, and nanocomposite polymers. Each category is examined for its advantages, challenges, and notable developments. Furthermore, we highlight the potential of polymeric materials to contribute to eco-friendly and efficient REEs recovery, while acknowledging the need to address challenges such as selectivity, stability, and scalability. The research in this field actively seeks innovative solutions to reduce reliance on hazardous chemicals and minimize waste generation. As the demand for REEs continues to rise, the development of sustainable REEs recovery technologies remains a critical area of investigation, with the collaboration between researchers and industry experts driving progress in this evolving field.

MM-GLCM-CNN: A multi-scale and multi-level based GLCM-CNN for polyp classification.

Distinguishing malignant from benign lesions has significant clinical impacts on both early detection and optimal management of those early detections. Convolutional neural network (CNN) has shown great potential in medical imaging applications due to its powerful feature learning capability. However, it is very challenging to obtain pathological ground truth, addition to collected in vivo medical images, to construct objective training labels for feature learning, leading to the difficulty of performing lesion diagnosis. This is contrary to the requirement that CNN algorithms need a large number of datasets for the training. To explore the ability to learn features from small pathologically-proven datasets for differentiation of malignant from benign polyps, we propose a Multi-scale and Multi-level based Gray-level Co-occurrence Matrix CNN (MM-GLCM-CNN). Specifically, instead of inputting the lesions' medical images, the GLCM, which characterizes the lesion heterogeneity in terms of image texture characteristics, is fed into the MM-GLCN-CNN model for the training. This aims to improve feature extraction by introducing multi-scale and multi-level analysis into the construction of lesion texture characteristic descriptors (LTCDs). To learn and fuse multiple sets of LTCDs from small datasets for lesion diagnosis, we further propose an adaptive multi-input CNN learning framework. Furthermore, an Adaptive Weight Network is used to highlight important information and suppress redundant information after the fusion of the LTCDs. We evaluated the performance of MM-GLCM-CNN by the area under the receiver operating characteristic curve (AUC) merit on small private lesion datasets of colon polyps. The AUC score reaches 93.99% with a gain of 1.49% over current state-of-the-art lesion classification methods on the same dataset. This gain indicates the importance of incorporating lesion characteristic heterogeneity for the prediction of lesion malignancy using small pathologically-proven datasets.

Imbalance of multiple neurotransmitter pathways leading to depression-like behavior and cognitive dysfunction in the triple transgenic mouse model of Alzheimer disease.

Depression is among the most frequent psychiatric comorbid conditions in Alzheimer disease (AD). However, pharmacotherapy for depressive disorders in AD is still a big challenge, and the data on the efffcacy of current antidepressants used clinically for depressive symptoms in patients with AD remain inconclusive. Here we investigated the mechanism of the interactions between depression and AD, which we believe would aid in the development of pharmacological therapeutics for the comorbidity of depression and AD. Female APP/PS1/Tau triple transgenic (3×Tg-AD) mice at 24 months of age and age- and sex-matched wild-type (WT) mice were used. The shuttle-box passive avoidance test (PAT) were implemented to assess the abilities of learning and memory, and the open field test (OFT) and the tail suspension test (TST) were used to assess depression-like behavior. High-performance liquid chromatography coupled to tandem mass spectrometry (HPLC-MS/MS) was used to detect the level of neurotransmitters related to depression in the hippocampus of mice. The data was identified by orthogonal projections to latent structures discriminant analysis (OPLS-DA). Most neurotransmitters exert their effects by binding to the corresponding receptor, so the expression of relative receptors in the hippocampus of mice was detected using Western blot. Compared to WT mice, 3×Tg-AD mice displayed significant cognitive impairment in the PAT and depression-like behavior in the OFT and TST. They also showed significant decreases in the levels of L-tyrosine, norepinephrine, vanillylmandelic acid, 5-hydroxytryptamine, and acetylcholine, in contrast to significant increases in 5-hydroxyindoleacetic acid, L-histidine, L-glutamine, and L-arginine in the hippocampus. Moreover, the expression of the alpha 1a adrenergic receptor (ADRA1A), serotonin 1 A receptor (5HT1A), and γ-aminobutyric acid A receptor subunit alpha-2 (GABRA2) was significantly downregulated in the hippocampus of 3×Tg-AD mice, while histamine H3 receptor (H3R) expression was significantly upregulated. In addition, the ratio of phosphorylated cAMP-response element-binding protein (pCREB) and CREB was significantly decreased in the hippocampus of 3×Tg-AD mice than WT mice. We demonstrated in the present study that aged female 3×Tg-AD mice showed depression-like behavior accompanied with cognitive dysfunction. The complex and diverse mechanism appears not only relevant to the imbalance of multiple neurotransmitter pathways, including the transmitters and receptors of the monoaminergic, GABAergic, histaminergic, and cholinergic systems, but also related to the changes in L-arginine and CREB signaling molecules.

Optimization, and biological evaluation of 3-O-ß-chacotriosyl betulinic acid amide derivatives as novel small-molecule Omicron.

SARS-CoV-2 Omicron viruses possess a high antigenic shift, and the approved anti-SARS-CoV-2 drugs are extremely limited, which makes the development of new antiviral drugs for the clinical treatment and prevention of SARS-CoV-2 outbreaks imperative. We have previously discovered a new series of markedly potent small-molecule inhibitors of SARS-CoV-2 virus entry, exampled by the hit compound 2. Here, we report a further study of bioisosteric replacement of the eater linker at the C-17 position of 2 with a variety of aromatic amine moieties, followed by a focused structure-activity relationship study, leading to the discovery of a series of novel 3-O-ß-chacotriosyl BA amide derivatives as small-molecule Omicron fusion inhibitors with improved potency and selectivity index. Particularly, our medicinal chemistry efforts have resulted in a potent, and efficacious lead compound S-10 with appreciable pharmacokinetic properties, which exhibited broad-spectrum potency against Omicron and other variants with EC50 values ranging from 0.82 to 5.45 µM. Mutagenesis studies confirmed that inhibition of Omicron viral entry was mediated by the direct interaction with S in the prefusion state. These results reveal that S-10 is suitable for further optimization as Omicron fusion inhibitors, with the potential to be developed as therapeutic agents for the treatment and control of SARS-CoV-2 ant its variants infections.

A pH and Temperature Dual-Responsive Microgel-Embedded, Adhesive, and Tough Hydrogel for Drug Delivery and Wound Healing.

Stimuli-responsive hydrogels have attracted much attention over the past decade for potential bioengineering applications such as wound dressing and drug delivery. In this work, a pH and temperature dual-responsive microgel-embedded hydrogel has been fabricated by incorporating poly(N-isopropylacrylamide-co-acrylic acid) (PNIPAAm-co-AAc) based microgel particles into polyacrylamide (PAAm)/chitosan (CS) semi-interpenetrating polymer network (semi-IPN), denoted as microgel@PAM/CS. The resultant hydrogel possesses excellent mechanical properties including stretchability, compressibility, and elasticity. In addition, the microgel@PAM/CS hydrogels can tightly adhere to the surfaces of a variety of tissues such as porcine skin, kidney, intestine, liver, and heart. Moreover, it shows controlled dual-drug release profile of both bovine serum albumin (BSA) (as a model protein) and sulfamethoxazole (SMZ), an antibiotic. Excellent antimicrobial properties are obtained for SMZ-loaded microgel@PAM/CS hydrogels. Compared with traditional drug administration methods such as by mouth, injection, and inhalation, the microgel@PAM/CS hydrogels possess advantages such as higher drug loading efficiency (by more than 80%) and controllable and sustained (over 48 h) release. The microgel@PAM/CS hydrogels can significantly enhance the wound healing process. This work provides a facile approach for the fabrication of multifunctional stimuli-responsive microparticle-embedded hydrogels with semi-IPN structures, and the as-prepared microgel@PAM/CS hydrogels have great potential for applications as smart wound dressing materials in biomedical engineering.

Exploring Dual-Energy CT Spectral Information for Machine Learning-Driven Lesion Diagnosis in Pre-Log Domain.

In this study, we proposed a computer-aided diagnosis (CADx) framework under dual-energy spectral CT (DECT), which operates directly on the transmission data in the pre-log domain, called CADxDE, to explore the spectral information for lesion diagnosis. The CADxDE includes material identification and machine learning (ML) based CADx. Benefits from DECT's capability of performing virtual monoenergetic imaging with the identified materials, the responses of different tissue types (e.g., muscle, water, and fat) in lesions at each energy can be explored by ML for CADx. Without losing essential factors in the DECT scan, a pre-log domain model-based iterative reconstruction is adopted to obtain decomposed material images, which are then used to generate the virtual monoenergetic images (VMIs) at selected n energies. While these VMIs have the same anatomy, their contrast distribution patterns contain rich information along with the n energies for tissue characterization. Thus, a corresponding ML-based CADx is developed to exploit the energy-enhanced tissue features for differentiating malignant from benign lesions. Specifically, an original image-driven multi-channel three-dimensional convolutional neural network (CNN) and extracted lesion feature-based ML CADx methods are developed to show the feasibility of CADxDE. Results from three pathologically proven clinical datasets showed 4.01% to 14.25% higher AUC (area under the receiver operating characteristic curve) scores than the scores of both the conventional DECT data (high and low energy spectrum separately) and the conventional CT data. The mean gain >9.13% in AUC scores indicated that the energy spectral-enhanced tissue features from CADxDE have great potential to improve lesion diagnosis performance.

Transcriptome and Low-Affinity Sodium Transport Analysis Reveals Salt Tolerance Variations between Two Poplar Trees.

Salinity stress severely hampers plant growth and productivity. How to improve plants' salt tolerance is an urgent issue. However, the molecular basis of plant resistance to salinity still remains unclear. In this study, we used two poplar species with different salt sensitivities to conduct RNA-sequencing and physiological and pharmacological analyses; the aim is to study the transcriptional profiles and ionic transport characteristics in the roots of the two Populus subjected to salt stress under hydroponic culture conditions. Our results show that numerous genes related to energy metabolism were highly expressed in Populus alba relative to Populus russkii, which activates vigorous metabolic processes and energy reserves for initiating a set of defense responses when suffering from salinity stress. Moreover, we found the capacity of Na+ transportation by the P. alba high-affinity K+ transporter1;2 (HKT1;2) was superior to that of P. russkii under salt stress, which enables P. alba to efficiently recycle xylem-loaded Na+ and to maintain shoot K+/Na+ homeostasis. Furthermore, the genes involved in the synthesis of ethylene and abscisic acid were up-regulated in P. alba but downregulated in P. russkii under salt stress. In P. alba, the gibberellin inactivation and auxin signaling genes with steady high transcriptions, several antioxidant enzymes activities (such as peroxidase [POD], ascorbate peroxidase [APX], and glutathione reductase [GR]), and glycine-betaine content were significantly increased under salt stress. These factors altogether confer P. alba a higher resistance to salinity, achieving a more efficient coordination between growth modulation and defense response. Our research provides significant evidence to improve the salt tolerance of crops or woody plants.

A Joint-Parameter Estimation and Bayesian Reconstruction Approach to Low-Dose CT.

Most penalized maximum likelihood methods for tomographic image reconstruction based on Bayes' law include a freely adjustable hyperparameter to balance the data fidelity term and the prior/penalty term for a specific noise-resolution tradeoff. The hyperparameter is determined empirically via a trial-and-error fashion in many applications, which then selects the optimal result from multiple iterative reconstructions. These penalized methods are not only time-consuming by their iterative nature, but also require manual adjustment. This study aims to investigate a theory-based strategy for Bayesian image reconstruction without a freely adjustable hyperparameter, to substantially save time and computational resources. The Bayesian image reconstruction problem is formulated by two probability density functions (PDFs), one for the data fidelity term and the other for the prior term. When formulating these PDFs, we introduce two parameters. While these two parameters ensure the PDFs completely describe the data and prior terms, they cannot be determined by the acquired data; thus, they are called complete but unobservable parameters. Estimating these two parameters becomes possible under the conditional expectation and maximization for the image reconstruction, given the acquired data and the PDFs. This leads to an iterative algorithm, which jointly estimates the two parameters and computes the to-be reconstructed image by maximizing a posteriori probability, denoted as joint-parameter-Bayes. In addition to the theoretical formulation, comprehensive simulation experiments are performed to analyze the stopping criterion of the iterative joint-parameter-Bayes method. Finally, given the data, an optimal reconstruction is obtained without any freely adjustable hyperparameter by satisfying the PDF condition for both the data likelihood and the prior probability, and by satisfying the stopping criterion. Moreover, the stability of joint-parameter-Bayes is investigated through factors such as initialization, the PDF specification, and renormalization in an iterative manner. Both phantom simulation and clinical patient data results show that joint-parameter-Bayes can provide comparable reconstructed image quality compared to the conventional methods, but with much less reconstruction time. To see the response of the algorithm to different types of noise, three common noise models are introduced to the simulation data, including white Gaussian noise to post-log sinogram data, Poisson-like signal-dependent noise to post-log sinogram data and Poisson noise to the pre-log transmission data. The experimental outcomes of the white Gaussian noise reveal that the two parameters estimated by the joint-parameter-Bayes method agree well with simulations. It is observed that the parameter introduced to satisfy the prior's PDF is more sensitive to stopping the iteration process for all three noise models. A stability investigation showed that the initial image by filtered back projection is very robust. Clinical patient data demonstrated the effectiveness of the proposed joint-parameter-Bayes and stopping criterion.

Arterial Baroreflex Dysfunction Promotes Neuroinflammation by Activating the Platelet CD40L/Nuclear Factor Kappa B Signaling Pathway in Microglia and Astrocytes.

Arterial baroreflex (ABR) dysfunction has previously been associated with neuroinflammation, the most common pathological feature of neurological disorders. However, the mechanisms mediating ABR dysfunction-induced neuroinflammation are not fully understood. In the present study, we investigated the role of platelet CD40 ligand (CD40L) in neuroinflammation in an in vivo model of ABR dysfunction, and microglia and astrocyte activation in vitro. ABR dysfunction was induced in Sprague‒Dawley rats by sinoaortic denervation (SAD). We used ELSA and immunofluorescence to assess the effect of platelet CD40L on glial cell polarization and the secretion of inflammatory factors. By flow cytometry, we found that rats subjected to SAD showed a high level of platelet microaggregation and upregulation of CD40L on the platelet surface. The promotion of platelet invasion and accumulation was also observed in the brain tissues of rats subjected to SAD. In the animal model and cultured N9 microglia/C6 astrocytoma cells, platelet CD40L overexpression promoted neuroinflammation and activated M1 microglia, A1 astrocytes, and the nuclear factor kappa B (NFκB) signaling pathway. These effects were partially blocked by inhibiting platelet activity with clopidogrel or inhibiting CD40L-mediated signaling. Our results suggest that during ABR dysfunction, CD40L signaling in platelets converts microglia to the M1 phenotype and astrocytes to the A1 phenotype, activating NFκB and resulting in neuroinflammation. Thus, our study provides a novel understanding of the pathogenesis of ABR dysfunction-induced neuroinflammation and indicates that targeting platelet CD40L is beneficial for treating central nervous system (CNS) disorders associated with ABR dysfunction.

Identification of N- and C-3-Modified Laudanosoline Derivatives as Novel Influenza PAN Endonuclease Inhibitors.

Influenza PAN inhibitors are of particular importance in current efforts to develop a new generation of antiviral drugs due to the growing emergence of highly pathogenic influenza viruses and the resistance to existing antiviral inhibitors. Herein, we design and synthesize a set of 1,3-cis-N-substituted-1,2,3,4-tetrahydroisoquinoline derivatives to enhance their potency by further exploiting the pockets 3 and 4 in the PAN endonuclease based on the hit d,l-laudanosoline. Particularly, the lead compound 35 exhibited potent and broad anti-influenza virus effects with EC50 values ranging from 0.43 to 1.12 µM in vitro and good inhibitory activity in a mouse model. Mechanistic studies demonstrated that 35 could bind tightly to the PAN endonuclease of RNA-dependent RNA polymerase, thus blocking the viral replication to exert antiviral activity. Overall, our study might establish the importance of 1,2,3,4-tetrahydroisoquinoline-6,7-diol-based derivatives for the development of novel PAN inhibitors of influenza viruses.

Machine Learned Texture Prior From Full-Dose CT Database via Multi-Modality Feature Selection for Bayesian Reconstruction of Low-Dose CT.

In our earlier study, we proposed a regional Markov random field type tissue-specific texture prior from previous full-dose computed tomography (FdCT) scan for current low-dose CT (LdCT) imaging, which showed clinical benefits through task-based evaluation. Nevertheless, two assumptions were made for early study. One assumption is that the center pixel has a linear relationship with its nearby neighbors and the other is previous FdCT scans of the same subject are available. To eliminate the two assumptions, we proposed a database assisted end-to-end LdCT reconstruction framework which includes a deep learning texture prior model and a multi-modality feature based candidate selection model. A convolutional neural network-based texture prior is proposed to eliminate the linear relationship assumption. And for scenarios in which the concerned subject has no previous FdCT scans, we propose to select one proper prior candidate from the FdCT database using multi-modality features. Features from three modalities are used including the subjects' physiological factors, the CT scan protocol, and a novel feature named Lung Mark which is deliberately proposed to reflect the z-axial property of human anatomy. Moreover, a majority vote strategy is designed to overcome the noise effect from LdCT scans. Experimental results showed the effectiveness of Lung Mark. The selection model has accuracy of 84% testing on 1,470 images from 49 subjects. The learned texture prior from FdCT database provided reconstruction comparable to the subjects having corresponding FdCT. This study demonstrated the feasibility of bringing clinically relevant textures from available FdCT database to perform Bayesian reconstruction of any current LdCT scan.

Adaptation to low nitrogen and salt stresses in the desert poplar by effective regulation of nitrogen assimilation and ion balance.

As a main desert plant from arid regions of Central Asia, Populus euphratica always encounters with nitrogen shortage in its long life, apart from salt or drought stress. However, it remains unknown how this species responds to low nitrogen and combined stresses of low nitrogen and salinity. Thus, saplings of P. euphratica with uniform size were exposed to normal or low nitrogen condition (150 and 15 ppm ammonium nitrate separately) individually or in combination with salinity. Under low nitrogen conditions we found a positive effect on P. euphratica root growth, which could be associated to high level of nitrogen allocation to support root growth and effective regulation of nitrogen assimilation in comparison with the other poplar species reported before. Under salt stress the root growth of P. euphratica was significantly inhibited, with the side effects of oxidative stress, as saplings stored higher Na+ and Cl- contents in roots. Under the combined stressors of both salinity and low nitrogen, P. euphratica undergo a risky strategy, as stimulated root growth is accompanied by further oxidative stress.The concentrations of root K+ and whole plant NO3- were increased to support the tolerance of the combined stressors in P. euphratica, showing same characteristics with halophytes. Overall, our results provide evidence that the desert poplar can adapt to the salt stress/low nitrogen bundle, by effective regulation of nitrogen assimilation and ion homoeostasis.