Notes

Selection for low-cadmium cultivars as well as cadmium subcellular distribution comparison involving 2 picked cultivars associated with eggplant (Solanum melongena D.).
In clinical practice, doctors often use attributes, e.g. morphological and appearance characteristics of a lesion, to aid disease diagnosis. Effectively modeling all relationships among attributes could boost the accuracy of medical image diagnosis. In this paper, we introduce a hybrid neuro-probabilistic reasoning algorithm for interpretable attribute-based medical image diagnosis. There are two parallel branches in our hybrid algorithm, a Bayesian network branch performing probabilistic causal relationship reasoning and a graph convolutional network branch performing more generic relational modeling and reasoning using a feature representation. Tight coupling between these two branches is achieved via a cross-network attention mechanism and the fusion of their classification results. We have successfully applied our hybrid reasoning algorithm to two challenging medical image diagnosis tasks. On the LIDC-IDRI benchmark dataset for benign-malignant classification of pulmonary nodules in CT images, our method achieves a new state-of-the-art accuracy of 95.36% and an AUC of 96.54%. Our method also achieves a 2.94% accuracy improvement on the in-house chest X-ray image dataset for tuberculosis diagnosis. Our ablation study indicates that our hybrid algorithm achieves a much more robust performance than a pure neural network architecture under very limited training data.Point cloud analysis without pose priors is very challenging in real applications, as the orientations of point clouds are often unknown. In this paper, we propose a brand new point-set learning framework PRIN, namely, Point-wise Rotation Invariant Network, focusing on rotation invariant feature extraction in point clouds analysis. We construct spherical signals by Density Aware Adaptive Sampling to deal with distorted point distributions in spherical space. Spherical Voxel Convolution and Point Re-sampling are proposed to extract rotation invariant features for each point. In addition, we extend PRIN to a sparse version called SPRIN, which directly operates on sparse point clouds. Both PRIN and SPRIN can be applied to tasks ranging from object classification, part segmentation, to 3D feature matching and label alignment. Results show that, on the dataset with randomly rotated point clouds, SPRIN demonstrates better performance than state-of-the-art methods without any data augmentation. We also provide thorough theoretical proof and analysis for point-wise rotation invariance achieved by our methods. The code to reproduce our results will be made publicly available.Most animals survive and thrive due to navigational behavior to reach their destinations. In order to navigate, it is important for animals to integrate information obtained from multisensory inputs and use that information to modulate their behavior. In this study, by using a virtual reality (VR) system for an insect, we investigated how the adult silkmoth integrates visual and wind direction information during female search behavior (olfactory behavior). According to the behavioral experiments using a VR system, the silkmoth had the highest navigational success rate when odor, vision, and wind information were correctly provided. However, the success rate of the search was reduced if the wind direction information provided was different from the direction actually detected. This indicates that it is important to acquire not only odor information but also wind direction information correctly. When the wind is received from the same direction as the odor, the silkmoth takes positive behavior; if the odor is detected but the wind direction is not in the same direction as the odor, the silkmoth behaves more carefully. This corresponds to a modulation of behavior according to the degree of complexity (turbulence) of the environment. We mathematically modeled the modulation of behavior using multisensory information and evaluated it using simulations. The mathematical model not only succeeded in reproducing the actual silkmoth search behavior but also improved the search success relative to the conventional odor-source search algorithm.In this paper, the influences of biochar on the anaerobic digestion of sulphate wastewater, including the COD removal rate, methane yield, intermediate products and the change of microbial community structure, were investigated. The results showed that sulphate could promote the anaerobic digestion with the SO42-/COD ratio increasing from 0 to 0.1, while the activity of MPB was inhibited, which led to the decrease of COD removal rate and methane yield with the SO42-/COD ratio increasing from 0.1 to 2. At 1 g biochar loading, 344.97 mL CH4/gCODremoval was obtained compared with the control group (220.70 CH4/gCODremoval) at 2 of SO42-/COD. Biochar could also reduce the secondary accumulation of NH4+-N and TVFA. Meanwhile, methanogenic microorganisms were selectively enriched especially for methanobacterium, methanosaeta and methanolinea, while the growth of SRB was inhibited with biochar addition.As the main exchanger of electroneutral NaCl absorption, sodium-hydrogen exchanger isoform 3 (NHE3) circulates in the epithelial brush border (BB) and intracellular compartments in a multi-protein complex. The size of the NHE3 complex changes during rapid regulation events. Recycling regulation of NHE3 in epithelial cells can be roughly divided into three stages. First, when stimulated by Ca2+, cGMP, and cAMP-dependent signaling pathways, NHE3 is converted from an immobile complex found at the apical microvilli (MV) into an easily internalized and mobile form that relocates to a compartment near the base of the MV. Second, NHE3 is internalized by clathrin and albumin-dependent pathways into cytoplasmic endosomal compartments, where the complex is reprocessed and reassembled. Finally, NHE3 is translocated from the recycling endosomes (REs) to the apex of epithelial cells, a process that can be stimulated by an increase in sodium-glucose cotransporter 1 (SGLT1) activity, epidermal growth factor receptor (EGFR) signaling, Ca2+ signaling, and binding to βPix and SH3 and multiple ankyrin repeat domains 2 (Shank2) proteins. This review describes the molecular steps and protein interactions involved in the recycling movement of NHE3 from the apex of epithelial cells, into vesicles, where it is reprocessed and reassembled, and returned to its original location on the plasma membrane, where it exerts its physiological function.The present ethnobotanical study unravelled the phenolic reservoir (UHPLC-MS/TQ-MS) and pharmacological activity (antioxidant and enzyme inhibitory activities) of an endemic plant, Achillea pseudoaleppica Hub.-Mor. (Asteraceae). mTOR inhibitor The effective antioxidant properties of ethanol and water extracts of A. pseudoaleppica leaves were determined by using six different in vitro bioanalytical methods including three reducing antioxidant methods and three radical scavenging antioxidant methods. In the other step of the study, the enzyme inhibitory effects of water and ethanol extracts of A. pseudoaleppica were determined against acetylcholinesterase (AChE), butyrylcholinesterase (BChE), α-amylase, and α-glucosidase enzymes. The ethanol extract was found to have effective inhibition potential for all four respected enzymes. The IC50 values of A. pseudoaleppica extract against AChE, BChE, α-amylase, and α-glucosidase enzymes were found to be 2.67 mg/mL, 4.55 mg/mL, 16.51 mg/mL, and 12.37 mg/mL, respectively. Also, UHPLC-MS/TQ-MS analyses revealed quinic acid as the most abundant phenolic compound of the water extract (31.12 ± 1.65 µg/mg) and ethanol extract (11.75 ± 0.82 µg/mg). In addition, the molecular docking interaction of the most abundant phenolic compound of A. pseudoaleppica (quinic acid) with AChE, BChE, α-amylase, and α-glucosidase target enzymes were evaluated using Chimera and AutoDock Vina softwares. In conclusion, the rich phenolic content and the potent antioxidant and enzyme inhibitory properties of A. pseudoaleppica extracts may support the widespread ethnobotanical use of the plant application.Communicated by Ramaswamy H. Sarma.The availability of electronic health record (EHR)-linked biobank data for research presents opportunities to better understand complex ocular diseases. Developing accurate computable phenotypes for ocular diseases for which gold standard diagnosis includes imaging remains inaccessible in most biobank-linked EHRs. The objective of this study was to develop and validate a computable phenotype to identify primary open-angle glaucoma (POAG) through accessing the Department of Veterans Affairs (VA) Computerized Patient Record System (CPRS) and Million Veteran Program (MVP) biobank. Accessing CPRS clinical ophthalmology data from VA Medical Center Eye Clinic (VAMCEC) patients, we developed and iteratively refined POAG case and control algorithms based on clinical, prescription, and structured diagnosis data (ICD-CM codes). Refinement was performed via detailed chart review, initially at a single VAMCEC (n = 200) and validated at two additional VAMCECs (n = 100 each). Positive and negative predictive values (PPV, NPV) were computed as the proportion of CPRS patients correctly classified with POAG or without POAG, respectively, by the algorithms, validated by ophthalmologists and optometrists with access to gold-standard clinical diagnosis data. The final algorithms performed better than previously reported approaches in assuring the accuracy and reproducibility of POAG classification (PPV >83% and NPV >97%) with consistent performance in Black or African American and in White Veterans. Applied to the MVP to identify cases and controls, genetic analysis of a known POAG-associated locus further validated the algorithms. We conclude that ours is a viable approach to use combined EHR-genetic data to study patients with complex diseases that require imaging confirmation.Alphaherpesvirus infection results in severe health consequences in a wide range of hosts. USPs are the largest subfamily of deubiquitinating enzymes that play critical roles in immunity and other cellular functions. To investigate the role of USPs in alphaherpesvirus replication, we assessed 13 USP inhibitors for PRV replication. Our data showed that all the tested compounds inhibited PRV replication, with the USP14 inhibitor b-AP15 exhibiting the most dramatic effect. Ablation of USP14 also influenced PRV replication, whereas replenishment of USP14 in USP14 null cells restored viral replication. Although inhibition of USP14 induced the K63-linked ubiquitination of PRV VP16 protein, its degradation was not dependent on the proteasome. USP14 directly bound to ubiquitin chains on VP16 through its UBL domain during the early stage of viral infection. Moreover, USP14 inactivation stimulated EIF2AK3/PERK- and ERN1/IRE1-mediated signaling pathways, which were responsible for VP16 degradation through SQSTM1/p62-mediated selective macroautophagy/autophagy. Ectopic expression of non-ubiquitinated VP16 fully rescued PRV replication. Challenge of mice with b-AP15 activated ER stress and autophagy and inhibited PRV infection in vivo. Our results suggested that USP14 was a potential therapeutic target to treat alphaherpesvirus-induced infectious diseases.
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