Assessing and Enhancing Robustness of Deep Learning Models with Corruption Emulation in Digital Pathology

Deep learning in digital pathology brings intelligence and automation as substantial enhancements to pathological analysis, the gold standard of clinical diagnosis. However, multiple steps from tissue preparation to slide imaging introduce various image corruptions, making it difficult for deep neural network (DNN) models to achieve stable diagnostic results for clinical use. In order to assess and further enhance the robustness of the models, we analyze the physical causes of the full-stack corruptions throughout the pathological life-cycle and propose an Omni-Corruption Emulation (OmniCE) method to reproduce 21 types of corruptions quantified with 5-level severity. We then construct three OmniCE-corrupted benchmark datasets at both patch level and slide level and assess the robustness of popular DNNs in classification and segmentation tasks. Further, we explore to use the OmniCE-corrupted datasets as augmentation data for training and experiments to verify that the generalization ability of the models has been significantly enhanced

The Mechanism of ATP-Dependent Allosteric Protection of Akt Kinase Phosphorylation

SummaryKinases use ATP to phosphorylate substrates; recent findings underscore the additional regulatory roles of ATP. Here, we propose a mechanism for allosteric regulation of Akt1 kinase phosphorylation by ATP. Our 4.7-μs molecular dynamics simulations of Akt1 and its mutants in the ATP/ADP bound/unbound states revealed that ATP occupancy of the ATP-binding site stabilizes the closed conformation, allosterically protecting pT308 by restraining phosphatase access and key interconnected residues on the ATP→pT308 allosteric pathway. Following ATP→ADP hydrolysis, pT308 is exposed and readily dephosphorylated. Site-directed mutagenesis validated these predictions and indicated that the mutations do not impair PDK1 and PP2A phosphatase recruitment. We further probed the function of residues around pT308 at the atomic level, and predicted and experimentally confirmed that Akt1H194R/R273H double mutant rescues pathology-related Akt1R273H. Analysis of classical Akt homologs suggests that this mechanism can provide a general model of allosteric kinase regulation by ATP; as such, it offers a potential avenue for allosteric drug discovery

Proton pump inhibitors may enhance the risk of digestive diseases by regulating intestinal microbiota

Proton pump inhibitors (PPIs) are the most used acid-inhibitory drugs, with a wide range of applications in the treatment of various digestive diseases. However, recently, there has been a growing number of digestive complications linked to PPIs, and several studies have indicated that the intestinal flora play an important role in these complications. Therefore, developing a greater understanding of the role of the gut microbiota in PPI-related digestive diseases is essential. Here, we summarize the current research on the correlation between PPI-related digestive disorders and intestinal flora and establish the altered strains and possible pathogenic mechanisms of the different diseases. We aimed to provide a theoretical basis and reference for the future treatment and prevention of PPI-related digestive complications based on the regulation of the intestinal microbiota

Modeling power flow in the induction cavity with a two dimensional circuit simulation

We have proposed a two dimensional (2D) circuit model of induction cavity. The oil elbow and azimuthal transmission line are modeled with one dimensional transmission line elements, while 2D transmission line elements are employed to represent the regions inward the azimuthal transmission line. The voltage waveforms obtained by 2D circuit simulation and transient electromagnetic simulation are compared, which shows satisfactory agreement. The influence of impedance mismatch on the power flow condition in the induction cavity is investigated with this 2D circuit model. The simulation results indicate that the peak value of load voltage approaches the maximum if the azimuthal transmission line roughly matches the pulse forming section. The amplitude of output transmission line voltage is strongly influenced by its impedance, but the peak value of load voltage is insensitive to the actual output transmission line impedance. When the load impedance raises, the voltage across the dummy load increases, and the pulse duration at the oil elbow inlet and insulator stack regions also slightly increase

Machine learning-based integration identifies the ferroptosis hub genes in nonalcoholic steatohepatitis

Abstract Background Ferroptosis, is characterized by lipid peroxidation of fatty acids in the presence of iron ions, which leads to cell apoptosis. This leads to the disruption of metabolic pathways, ultimately resulting in liver dysfunction. Although ferroptosis is linked to nonalcoholic steatohepatitis (NASH), understanding the key ferroptosis-related genes (FRGs) involved in NASH remains incomplete. NASH may be targeted therapeutically by identifying the genes responsible for ferroptosis. Methods To identify ferroptosis-related genes and develop a ferroptosis-related signature (FeRS), 113 machine-learning algorithm combinations were used. Results The FeRS constructed using the Generalized Linear Model Boosting algorithm and Gradient Boosting Machine algorithms exhibited the best prediction performance for NASH. Eight FRGs, with ZFP36 identified by the algorithms as the most crucial, were incorporated into in FeRS. ZFP36 is significantly enriched in various immune cell types and exhibits significant positive correlations with most immune signatures. Conclusion ZFP36 is a key FRG involved in NASH pathogenesis

Effects of Class IIa Bacteriocin-Producing Lactobacillus Species on Fermentation Quality and Aerobic Stability of Alfalfa Silage

The effects of two strains of class IIa bacteriocin-producing lactic acid bacteria, Lactobacillus delbrueckii F17 and Lactobacillus plantarum (BNCC 336943), or a non-bacteriocin Lactobacillus plantarum MTD/1 (NCIMB 40027), on fermentation quality, microbial counts, and aerobic stability of alfalfa silage were investigated. Alfalfa was harvested at the initial flowering stage, wilted to a dry matter concentration of approximately 32%, and chopped to 1 to 2 cm length. Chopped samples were treated with nothing (control, CON), Lactobacillus delbrueckii F17 (F17), Lactobacillus plantarum (BNCC 336943) (LPB), or Lactobacillus plantarum MTD/1 (NCIMB 40027) (LPN), each at an application rate of 1 × 106 colony-forming units/g of fresh weight. Each treatment was ensiled in quadruplicate in vacuum-sealed polyethylene bags packed with 500 g of fresh alfalfa per bag and ensiled at ambient temperature (25 ± 2 °C) for 3, 7, 14, 30, and 60 days. The samples were then subjected to an aerobic stability test after 60 days of ensiling. Compared with the CON silage, the inoculants reduced the pH after 14 days of ensiling. After 60 days, pH was lowest in the LPB-treated silage, followed by the F17 and LPN-treated silages. Inoculation of F17 increased concentrations of lactic acid in silages fermented for 7, 14, 30, and 60 days relative to other treatments, except for the LPN-treated silages ensiled for 30 and 60 days, in which the lactic acid concentrations were similar to that of F17 silage. Application of F17 and LPB decreased the number of yeast and mold relative to CON and LPN-treated silages. Compared with the CON silage, inoculant-treated silages had greater aerobic stability, water-soluble carbohydrate, and crude protein concentrations, and lower neutral detergent fiber, amino acid nitrogen, and ammonia nitrogen concentrations. The LPB-treated silage had the greatest aerobic stability followed by the F17-treated silage. Both class IIa bacteriocin producing inoculants improved alfalfa silage fermentation quality, reduced the growth of yeasts and molds, and improved the aerobic stability of the ensiled forage to a greater extent than the proven LPN inoculant. However, higher crude protein concentration and lower ammonia nitrogen concentration were observed in LPN-treated silage relative to other treatments

Effects of Varying Tobacco Rod Circumference on Cigarette Combustion: An Experimental Investigation

To study the effects of tobacco rod circumference on cigarette combustion status, cigarettes were made with three different circumferences of 24 mm, 20 mm, 17 mm and otherwise identical construction. Their combustion characteristics, including combustion coal volume, characteristic temperature distribution, heating rate, instantaneous burn rate, and yields of selected mainstream smoke chemicals, were systematically measured. The results indicated that the cigarettes with the lowest circumference of 17 mm showed higher combustion temperatures with a smaller coal volume. The maximum instantaneous burn rate was distinctly different for the three cigarettes, from 1.84 mm/s to 2.48 mm/s, when their circumference was reduced from 24 mm to 17 mm. The tobacco mass consumption per puff showed a negative trend when the circumference decreased. The majority of the chemical compounds (16 of 21) measured in mainstream smoke decreased when the circumference was reduced, except for formaldehyde, while the yields of the chemical compounds produced per weight of cut tobacco, consumed during puffing, showed an obverse trend

Computational Study of Ternary Devices: Stable, Low-Cost, and Efficient Planar Perovskite Solar Cells

Abstract Although perovskite solar cells with power conversion efficiencies (PCEs) more than 22% have been realized with expensive organic charge-transporting materials, their stability and high cost remain to be addressed. In this work, the perovskite configuration of MAPbX (MA = CH3NH3, X = I3, Br3, or I2Br) integrated with stable and low-cost Cu:NiO x hole-transporting material, ZnO electron-transporting material, and Al counter electrode was modeled as a planar PSC and studied theoretically. A solar cell simulation program (wxAMPS), which served as an update of the popular solar cell simulation tool (AMPS: Analysis of Microelectronic and Photonic Structures), was used. The study yielded a detailed understanding of the role of each component in the solar cell and its effect on the photovoltaic parameters as a whole. The bandgap of active materials and operating temperature of the modeled solar cell were shown to influence the solar cell performance in a significant way. Further, the simulation results reveal a strong dependence of photovoltaic parameters on the thickness and defect density of the light-absorbing layers. Under moderate simulation conditions, the MAPbBr3 and MAPbI2Br cells recorded the highest PCEs of 20.58 and 19.08%, respectively, while MAPbI3 cell gave a value of 16.14%