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Medical imaging is a crucial component of any modern healthcare system, and image classification is a key technique of Computer-Aided Diagnosis (CADx) system that provides accurate detection and treatment for various diseases. With the increasing use of digital medical images, there is a growing concern for their security and protection against unauthorized access, tampering, and copying. However, the impact of watermarking on the accuracy of image classification models, particularly in medical imaging, remains an undiscovered area of research. To the best of our knowledge, this work is one of the pioneering attempts in the field that examines the impact of watermarking on image classification accuracy with deep learning. Within this context, brain tumor and histopathologic cancer datasets are utilized. A Light-weight Conventional Neural Netwok (CNN) is developed, and several CNN models, such as ResNet-50, VGG16, VGG19, DarkNet-19, and AlexNet, are specially tailored to achieve accurate classification. Following the evaluation of the classification performance, a new watermarking scheme based on the Redundant Discrete Wavelet transform (RDWT), Multiresolution Singular Value Decomposition (MSVD), and Arnold Cat Map (ACM) is applied to the images, the classification accuracy of the watermarked testing-sets is subsequently re-evaluated. Results indicated that the proposed watermarking scheme is highly robust as the Normalized Correlation (NC) exceeded 0.9 and up to 1 for some attacks, and imperceptibility is well maintained at optimal levels as the Peak-Signal-to-Noise Ratio (PSNR) ranged from 66 dB and up to a maximum value of nearly 68 dB. Additionally, analyzing the effect of watermarking on classification accuracy indicated that the effect is found to be minimal, and ranged from 0% to 0.15% at most.

BackgroundEpilepsy-associated dysbiosis in gut microbiota has been previously described, but the mechanistic roles of the gut microbiome in epileptogenesis among children with cerebral palsy (CP) have yet to be illustrated.MethodsUsing shotgun metagenomic sequencing coupled with untargeted metabolomics analysis, this observational study compared the gut microbiome and metabolome of eight children with non-epileptic cerebral palsy (NECP) to those of 13 children with cerebral palsy with epilepsy (CPE). Among children with CPE, 8 had drug-sensitive epilepsy (DSE) and five had drug-resistant epilepsy (DRE). Characteristics at enrollment, medication history, and 7-day dietary intake were compared between groups.ResultsAt the species level, CPE subjects had significantly lower abundances of Bacteroides fragilis and Dialister invisus but higher abundances of Phascolarctobacterium faecium and Eubacterium limosum. By contrast, DRE subjects had a significantly higher colonization of Veillonella parvula. Regarding microbial functional pathways, CPE subjects had decreased abundances of pathways for serine degradation, quinolinic acid degradation, glutamate degradation I, glycerol degradation, sulfate reduction, and nitrate reduction but increased abundances of pathways related to ethanol production. As for metabolites, CPE subjects had higher concentrations of kynurenic acid, 2-oxindole, dopamine, 2-hydroxyphenyalanine, 3,4–dihydroxyphenylglycol, L-tartaric acid, and D-saccharic acid; DRE subjects had increased concentrations of indole and homovanilic acid.ConclusionsIn this study, we found evidence of gut dysbiosis amongst children with cerebral palsy and epilepsy in terms of gut microbiota species, functional pathways, and metabolites. The combined metagenomic and metabolomic analyses have shed insights on the potential roles of B. fragilis and D. invisus in neuroprotection. The combined analyses have also provided evidence for the involvement of GMBA in the epilepsy-related dysbiosis of kynurenine, serotonin, and dopamine pathways and their complex interplay with neuroimmune and neuroendocrinological pathways.

SPI1 fusion genes in T-cell acute lymphoblastic leukemia (T-ALL) are commonly found with co-occurring NRAS mutations. Here, the authors show that the combination of these oncogenes is necessary to drive T-ALL in a murine model and that the oncogenic activity of the SPI1 fusion is dependent on β-catenin.

PurposeRefractive surgery has been in use for a long time and is evolving at a fast pace with several new corneal procedures being used for the correction of presbyopia. The purpose of this article is to give a comprehensive review of the literature to evaluate the outcome and success of different corneal refractive surgical procedures in presbyopic patients.MethodsWe performed a comprehensive search on PubMed to identify published reports of the various procedures utilized in the past and present to correct presbyopia. The outcomes of these procedures were recorded.Results and conclusionWe found that varying rates of success have been reported with these procedures. The results of our exhaustive search are presented in this report for review.

Global food security and sustainability can be enhanced with increased production and use of hemp seed (Cannabis sativa L.) that not only provides healthy sources of protein and oil, but the whole plant can be used for fiber, especially new applications including high-performance textiles. There is limited knowledge of the variation in hemp seed for health and consumer traits, such as the complex plant polysaccharides comprising dietary fiber. To fill this gap, seed from 20 hemp cultivars and advanced breeding lines were analyzed for a variety of traits including complex carbohydrates, protein, lipids, heart percent, phytate and lignin. The analyses revealed different polysaccharides in hull and heart fractions, with hulls varying in cellulose (22.0–36.7%) and xylan (5.7–17.1%) whereas heart fractions contained xyloglucan and pectin, and comprised different proportions of heart and hull. Staining revealed that cellulose and lignin are localized in hull not heart tissue. Protein content of hemp seed ranged from 19.5 to 26.9% and Coomassie staining showed that cells of hemp hearts contain numerous protein bodies but few starch granules. Analysis of selected lines confirmed that hemp hearts are low in starch (

Among the histamine receptors, growing evidence points to the histamine H3 receptor as a pharmacological candidate to counteract the autonomic neuropathy associated with diabetes. The study aimed to evaluate the effect of PF00868087 (also known as ZPL-868), a CNS-sparing histamine H3 receptor antagonist, on the autonomic neuropathy of the intestinal tract associated with diabetes. Diabetes was induced in male BALB/c mice by a single high dose of streptozotocin (150 mg/kg). Colorectal specimens from control and diabetic mice, randomized to vehicle or PF0086087 (10, 30, 100 mg/kg/day by oral gavage for 14 days), were processed for morphological and immunohistochemical analysis. A significant overproduction of mucus in the intestinal mucosa of diabetic mice compared to the controls was observed. PF0086087 at the highest dose prevented mucin overproduction. The immunohistochemistry analysis demonstrated that diabetes causes a decrease in the inhibitory component of enteric motility, measured as the percentage of neuronal nitric oxide synthase-positive neurons (p < 0.05) and a parallel increase in the excitatory component evaluated as substance P-positive fibres (p < 0.01). PF0086087 dose-dependently prevented these pathophysiological events. In conclusion, PF0086087 may be an essential tool in preventing nitrergic dysfunction in the myenteric plexus of the distal colon and diabetes-induced gastrointestinal complications.

Abstract In this study, a speaker identification system is considered consisting of a feature extraction stage which utilizes both power normalized cepstral coefficients (PNCCs) and Mel frequency cepstral coefficients (MFCC). Normalization is applied by employing cepstral mean and variance normalization (CMVN) and feature warping (FW), together with acoustic modeling using a Gaussian mixture model-universal background model (GMM-UBM). The main contributions are comprehensive evaluations of the effect of both additive white Gaussian noise (AWGN) and non-stationary noise (NSN) (with and without a G.712 type handset) upon identification performance. In particular, three NSN types with varying signal to noise ratios (SNRs) were tested corresponding to street traffic, a bus interior, and a crowded talking environment. The performance evaluation also considered the effect of late fusion techniques based on score fusion, namely, mean, maximum, and linear weighted sum fusion. The databases employed were TIMIT, SITW, and NIST 2008; and 120 speakers were selected from each database to yield 3600 speech utterances. As recommendations from the study, mean fusion is found to yield overall best performance in terms of speaker identification accuracy (SIA) with noisy speech, whereas linear weighted sum fusion is overall best for original database recordings.

This paper presents a novel security architecture for protecting the integrity of iris images and templates using watermarking and visual cryptography (VC). The proposed scheme offers a complete protection framework for the iris biometrics which consists of two stages: the first stage is for iris image protection, while the second is for the iris template. First, for protecting the iris image, a watermark text which carries personal information is embedded in the middle band frequency region of the iris image using a novel watermarking algorithm that randomly interchanges multiple middle band pairs of the discrete cosine transform. Second, for iris template protection, the binary iris template is divided into two shares using VC, where one share is stored in the database and the other is kept with the user on a smart card. In addition, the SHA-2 hash function is utilized to maintain the integrity of the stored iris template in both the database and smart card. The experimental and comparison results on the CASIA V4 and UBIRIS V1 iris databases demonstrate that the proposed framework preserves the privacy of the iris images and templates and retains robustness to malicious attacks, while it does not have a discernible effect on the recognition performance.

The demonstration of the structure–properties relationship of shape-dependent photocatalysts remains a challenge today. Herein, one-dimensional (1-D)-like titania (TiO2), as a model photocatalyst, has been synthesized under a strong magnetic field in the presence of a magnetically responsive liquid crystal as the structure-aligning agent to demonstrate the relationship between a well-aligned structure and its photocatalytic properties. The importance of the 1-D-like TiO2 and its relationship with the electronic structures that affect the electron–hole recombination and the photocatalytic activity need to be clarified. The synthesis of 1-D-like TiO2 with liquid crystal as the structure-aligning agent was carried out using the sol–gel method under a magnetic field (0.3 T). The mixture of liquid crystal, 4′-pentyl-4-biphenylcarbonitrile (5CB), tetra-n-butyl orthotitanate (TBOT), 2-propanol, and water, was subjected to slow hydrolysis under a magnetic field. The TiO2–5CB took a well-aligned whiskerlike shape when the reaction mixture was placed under the magnetic field, while irregularly shaped TiO2–5CB particles were formed when no magnetic field was applied. It shows that the strong interaction between 5CB and TBOT during the hydrolysis process under a magnetic field controls the shape of titania. The intensity of the emission peaks in the photoluminescence spectrum of 1-D-like TiO2–5CB was lowered compared with the TiO2–5CB synthesized without the magnetic field, suggesting the occurrence of electron transfer from 5CB to the 1-D-like TiO2–5CB during ultraviolet irradiation. Apart from that, direct current electrical conductivity and Hall effect studies showed that the 1-D-like TiO2 composite enhanced electron mobility. Thus, the recombination of electrons and holes was delayed due to the increase in electron mobility; hence, the photocatalytic activity of the 1-D-like TiO2 composite in the oxidation of styrene in the presence of aqueous hydrogen peroxide under UV irradiation was enhanced. This suggests that the 1-D-like shape of TiO2 composite plays an important role in its photocatalytic activity.

A laboratory based microflotation rig termed efficient FLOtation of Algae Technology (eFLOAT) was used to optimise parameters for harvesting microalgal biomass from eutrophic water systems. This was performed for the dual objectives of remediation (nutrient removal) and resource recovery. Preliminary experiments demonstrated that chitosan was more efficient than alum for flocculation of biomass and the presence of bacteria could play a positive role and reduce flocculant application rates under the natural conditions tested. Maximum biomass removal from a hyper-eutrophic water retention pond sample was achieved with 5 mg·L−1 chitosan (90% Chlorophyll a removal). Harvesting at maximum rates showed that after 10 days, the bacterial diversity is significantly increased with reduced cyanobacteria, indicating improved ecosystem functioning. The resource potential within the biomass was characterized by 9.02 μg phosphate, 0.36 mg protein, and 103.7 μg lipid per mg of biomass. Fatty acid methyl ester composition was comparable to pure cultures of microalgae, dominated by C16 and C18 chain lengths with saturated, monounsaturated, and polyunsaturated fatty acids. Finally, the laboratory data was translated into a full-size and modular eFLOAT system, with estimated costs as a novel eco-technology for efficient algal bloom harvesting.