Three-Dimensional Stochastic Characterization of Shale SEM Images

Sole and co-exposure toxicity of commercial formulations ethoprophos and bispyribac-sodium to Oreochromis niloticus: Assessment of oxidative stress, genotoxicity, and gill ultrastructure

Aquatic organisms are simultaneously exposed to multiple hazardous chemicals that can be released into water bodies. The current study aimed to evaluate the effect of sublethal concentration (1/50 96 h-LC50) of two formulated pesticides: ethoprophos, bispyribac-sodium, and their combination for 1, 2, 3, and 4 weeks on oxidative stress, genotoxic response, and gill morphology in Nile tilapia. This study is the first to demonstrate the toxic effects of ethoprophos and bispyribac-sodium mixture on the commercial important species, Oreochromis niloticus. The results showed that the 96 h-LC50 values of ethoprophos and bispyribac-sodium were 4.8 and 0.064 mg/L, respectively. Additionally, exposure to individual or combined pesticides induced a significant increase in the level of malondialdehyde (MDA), glutathione S-transferase (GST), and 8-hydroxy-2-deoxyguanosine (8-OHdG), as well as a notable decline in reduced glutathione (GSH), superoxide dismutase (SOD), catalase (CAT), and glutathione peroxidase (GPx) levels at all time of exposure. Furthermore, there were alterations in ultrastructure of the gill samples, including erosive lesions on the primary and secondary lamellae, fusion of microridges, and excessive mucus secretions on the epithelium. The data clearly demonstrate that the negative effects of the tested compounds are time-dependent and are more severe in combination than in a single compound. Collectively, our results indicated that the interaction of ethoprophos and bispyribac-sodium might be largely synergistic and provide new insights into the molecular mechanisms of fish confronting these substances.

Methane Adsorption and Transport in Tortuous Slit-like Nanochannels: A Molecular Simulation Study

Tortuosity is a crucial characteristic of porous materials, such as the shale matrix where shale gas is stored. The presence of tortuous nanochannels significantly affects the adsorption and transport of nanoflows. In this research, we use molecular dynamics simulation (MD) to study the adsorption and transport properties of shale gas (methane) in a curved slit-like nanochannel constructed from bent graphene sheets. Our findings reveal that the curvature of the tortuous channel influences methane adsorption: convex surfaces exhibit stronger adsorption, while concave surfaces exhibit weaker adsorption; the discrepancy is amplified by the nanoflow. Additionally, nanoflow velocity is heterogeneously distributed within the curved channel, with higher tangential flow velocities observed near the entrance and the outer surface. We also identify a "bouncing effect", where the nanoflow not only moves tangentially along the channel but also bounces between the inner and outer walls. Furthermore, methane in narrower channels exhibits higher tangent flow velocity and higher bouncing frequency but smaller flux, whereas larger curvature results in shorter channel length and smaller tortuosity, but the transport tangent velocity and flux are both reduced. The findings of this study can help in the better understanding of shale gas nanoflow properties in tortuous media and provide insights for simulating more general nonstraight nanoflows.

Characterization and antioxidant activity of nano-formulated berberine and cyperus rotundus extracts with anti-inflammatory effects in mastitis-induced rats

Bovine mastitis caused by infectious pathogens, mainly Staphylococcus aureus (S. aureus) and Escherichia coli (E. coli), constitutes a major destructive challenge for the dairy industry and public health. Berberine chloride (BER) and Cyperus rotundus possess a broad spectrum of anti-inflammatory, antioxidant, antibacterial, and antiproliferative activities; however, their bioavailability is low. This research aimed first to prepare an ethanolic extract of Cyperus rotundus rhizomes (CRE) followed by screening its phytochemical contents, then synthesis of BER and CRE loaded chitosan nanoparticles (NPs) (BER/CH-NPs and CRE/CH-NPs), afterward, the analysis of their loading efficiency in addition to the morphological and physicochemical characterization of the formulated NPs employing Scanning Electron Microscopy (SEM), Zeta Potential (ZP), Fourier Transform Infrared Spectroscopy (FTIR), Differential Scanning Calorimetry (DSC) and X-Ray Diffraction (XRD) assessments compared to their crude forms to evaluate the enhancement of bioavailability and stability. Isolation of bacterial strains from the milk of mastitic cows, used for induction of mammary gland (MG) inflammation in female albino rats, and a preliminary investigation of the prophylactic oral doses of the prepared NPs against S. aureus-induced mastitis in female rats. The minimal inhibitory concentration (MIC) of BER/CH-NPs and CRE/CH-NPs is 1 mg/kg b.w. BER/CH-NPs and CRE/CH-NPs alone or in combination show significant (P ≤ 0.05) DPPH radical scavenging activity (69.2, 88.5, and 98.2%, respectively) in vitro. Oral administration of BER/CH-NPs and CRE/CH-NPs to mastitis rats significantly (P ≤ 0.05) attenuated TNF-α (22.1, 28.6 pg/ml), IL-6 (33.4, 42.9 pg/ml), IL-18 (21.7, 34.7 pg/ml), IL-4 (432.9, 421.6 pg/ml), and MPO (87.1, 89.3 pg/ml) compared to mastitis group alongside the improvement of MG histopathological findings without any side effect on renal and hepatic functions. Despite promising results with BER and CRE nanoparticles, the study is limited by small-scale trials, a focus on acute administration, and partially explored nanoparticle-biological interactions, with no economic or scalability assessments. Future research should address these limitations by expanding trial scopes, exploring interactions further, extending study durations, and assessing economic and practical scalability. Field trials and regulatory compliance are also necessary to ensure practical application and safety in the dairy industry. In conclusion, the in vitro and in vivo results proved the antioxidant and anti-inflammatory efficacy of BER/CH-NPs and CRE/CH-NPs in low doses with minimal damage to the liver and kidney functions, supposing their promising uses in mastitis treatment.

Anticandidal activity of a wild Bacillus subtilis NAM against clinical isolates of pathogenic Candida albicans

Background

Resistance to antifungal medications poses a significant obstacle in combating fungal infections. The development of novel therapeutics for Candida albicans is necessary due to the increasing resistance of candidiasis to the existing medications. The utilization of biological control is seen as a more advantageous and less hazardous strategy therefore the objective of this study is to identify the antifungal properties of Bacillus subtilis against pathogenic C. albicans.

Results

We conducted a study to evaluate the antifungal properties of three bacterial isolates against the human pathogen Candida albicans. One of the bacterial isolates exhibited a potent antifungal activity against this fungal pathogen. This bacterium was identified as Bacillus subtilis based on the 16Sr RNA gene sequence. It exhibited inhibitory efficacy ranging from 33.5 to 44.4% against 15 Candida isolates. The optimal incubation duration for achieving the maximum antifungal activity was determined to be 48 h, resulting in a mean inhibition zone diameter of 29 ± 0.39 mm. The Potato Dextrose agar (PDA) medium was the best medium for the most effective antifungal activity. Incubation temperature of 25oC and medium pH value of 8.0 were the most favorable conditions for maximum antagonistic activity that resulted fungal growth inhibition of 40 ± 0.16 and 36 ± 0.94 mm respectively. Furthermore, the addition of 10.5 mg/ml of bacterial filtrate to C. albicans colonies resulted in 86.51%. decrease in the number of germinated cells. The fungal cell ultrastructural responses due to exposure to B. subtilis filtrate after 48 h were investigated using transmission electron microscopy (TEM). It revealed primary a drastic abnormality that lead to cellular disintegration including folding and lysis of the cell wall, total collapse of the yeast cells, and malformed germ tube following the exposure to the filtrate. However, the control culture treatment had a characteristic morphology of the normal fungal cells featuring a consistently dense central region, a well-organized nucleus, and a cytoplasm containing several components of the endomembrane system. The cells were surrounded by a uniform and intact cell wall.

Conclusion

The current study demonstrates a notable antifungal properties of B. subtilis against C. albicans as a result of production of bioactive components of the bacterial exudate. This finding could be a promising natural antifungal agent that could be utilized to combat C. albicans.

Shale Gas Nanofluid in the Curved Carbon Nanotube: A Molecular Dynamics Simulation Study

Curved nanochannels are prevalent in porous and tortuous materials, with shale matrices being a noteworthy example. The tortuosity of shale matrices significantly influences the behavior of shale gas, holding crucial implications for gas recovery engineering. In this study, we employ molecular dynamics simulation (MD) to investigate the impact of curvature and radius in tortuous nanochannel formed by a curved single-walled carbon nanotube (SWCNT) on the adsorption and transport properties of methane gas fluid. Our findings reveal that the inner half surface of the SWCNT, characterized by negative curvature, exhibits enhanced methane adsorption. Methane in straighter and narrower channels displays higher flow velocities, while wider channels exhibit higher flow flux. The nonzero flow velocity alters adsorption strength, causing the outer half to surpass the inner half. Tangent and vertical velocities of the flow are heterogeneously distributed in the channel, with the outer half having higher tangent velocities. Additionally, a vertical velocity pulse near the entrance induces turbulent vortex flow, slowing down the tangent flow velocity. This research contributes to a deeper understanding of shale gas properties in matrices with bent and curved channels, offering insights into nanofluids in carbon nanotubes and porous media featuring curved nanochannels.

Three-dimensional reconstruction of granular porous media based on deep generative models

Reconstruction of microstructure in granular porous media, which can be viewed as granular assemblies, is crucial for studying their characteristics and physical properties in various fields concerned with the behavior of such media, including petroleum geology and computational materials science. In spite of the fact that many existing studies have investigated grain reconstruction, most of them treat grains as simplified individuals for discrete reconstruction, which cannot replicate the complex geometrical shapes and natural interactions between grains. In this work, a hybrid generative model based on a deep-learning algorithm is proposed for high-quality three-dimensional (3D) microstructure reconstruction of granular porous media from a single two-dimensional (2D) slice image. The method extracts 2D prior information from the given image and generates the grain set as a whole. Both a self-attention module and effective pattern loss are introduced in a bid to enhance the reconstruction ability of the model. Samples with grains of varied geometrical shapes are utilized for the validation of our method, and experimental results demonstrate that our proposed approach can accurately reproduce the complex morphology and spatial distribution of grains without any artificiality. Furthermore, once the model training is complete, rapid end-to-end generation of diverse 3D realizations from a single 2D image can be achieved.

Prodigiosin-Functionalized Probiotic Ghosts as a Bioinspired Combination Against Colorectal Cancer Cells

Lactobacillus acidophilus ghosts (LAGs) with the unique safety of a probiotic, inherent tropism for colon cells, and multiple bioactivities offer promise as drug carriers for colon targeting. Our objective was to evaluate LAGs functionalized with prodigiosin (PG), apoptotic secondary bacterial metabolite, as a bioinspired formulation against colorectal cancer (CRC). LAGs were prepared by a chemical method and highly purified by density gradient centrifugation. LAGs were characterized by microscopic and staining techniques as relatively small-sized uniform vesicles (≈1.6 µm), nearly devoid of cytoplasmic and genetic materials and having a negatively charged intact envelope. PG was highly bound to LAGs envelope, generating a physiologically stable bioactive entity (PG-LAGs), as verified by multiple microscopic techniques and lack of PG release under physiological conditions. PG-LAGs were active against HCT116 CRC cells at both the cellular and molecular levels. Cell viability data highlighted the cytotoxicity of PG and LAGs and LAGs-induced enhancement of PG selectivity for HCT116 cells, anticipating dose reduction for PG and LAGs. Molecularly, expression of the apoptotic caspase 3 and P53 biomarkers in HCT116 intracellular proteins was significantly upregulated while that of the anti-apoptotic Bcl-2 (B-cell lymphoma 2) was downregulated by PG-LAGs relative to PG and 5-fluorouracil. PG-LAGs provide a novel bacteria-based combination for anticancer biomedicine.

Eco-friendly postharvest irradiation strategy with 131I isotope for environmental management of populations of migratory locust, Locusta migratoria

PURPOSE

Irradiation of food is promising for control of pests to minimize postharvest losses of yields and thus improvement of food safety, shelf life of produce. It is a method of choice that induces a series of lethal biochemical and molecular changes culminating into the engagement of a downstream cascade to cause abnormalities in irradiated pests. In this study, the effects of iodine-131 (131I) isotope radiation on the male gonad development of the migratory locust, Locusta migratoria, were evaluated.

MATERIALS AND METHODS

Newly emerged adult male locusts, less than one-day-old, were divided into two groups, control and irradiated. Locusts in the control group (n = 20 insects) didn't drink irradiated water and were reared under normal environmental conditions for one week. Locusts in the irradiated group (n = 20 insects) were exposed to irradiated water at a dose of 30 mCi and they were subsequently observed until they drank the whole quantity.

RESULTS

At the end of the experiment, scanning and electron microscopic examination of testes obtained from irradiated locusts revealed several major abnormalities, including malformed nuclei of spermatozoa, irregular plasma membranes, shrinkage of testicular follicles, vacuolated cytoplasm, disintegrated nebenkern and agglutinations of spermatids. Flow cytometry analysis revealed that 131I radiation induced both early and late apoptosis, but not necrosis, in testicular tissues. Testes of irradiated insects also exhibited a burst in reactive oxygen species (ROS), as indicated by significant elevation in amounts of malondialdehyde (MDA), a marker for peroxidation of lipids. In contrast, irradiation coincided with significant reductions in activities of enzymatic antioxidant biomarkers. Relative to controls, a three-fold upregulation of expression of mRNA of heat shock protein, Hsp90, was observed in testicular tissue of irradiated locusts. 131I-irradiated insects exhibited genotoxicity, as indicated by significant increases in various indicators of DNA damage by the comet assay, including tail length (7.80 ± 0.80 µm; p < .01), olive tail moment (40.37 ± 8.08; p < .01) and tail DNA intensity % (5.1 ± 0.51; p < .01), in testicular cells compared to the controls.

CONCLUSION

This is the first report on elucidation of I131-irradiation-mediated histopathological, biochemical and molecular mechanisms in gonads of male L. migratoria. Herein, the findings underscore the utility of 131I radiation as an eco-friendly postharvest strategy for management of insect pests and in particular for control of populations of L. migratoria.

Eugenol; Effective Anthelmintic Compound against Foodborne Parasite Trichinella spiralis Muscle Larvae and Adult

Trichinosis is a foodborne parasitic infection that results from ingestion of raw or under-cooked pork meat infected by parasitic nematode Trichinella spiralis with cosmopolitan distribution. Anthelmintic drugs are used to eliminate intestinal adult parasites and larvae as well as tissue-migrating newborn and in-turn encysted larvae. However, eliminating the infection or averting it from transmission is rarely possible using anthelmintic groups of benzimidazole derivatives. Eugenol (EO) is the main extracted constituent of clove oil (80−90%) and is responsible for its aroma. Therefore, this study aims to investigate the effect of eugenol on both adult and muscle larvae of Trichinella spiralis in vitro. IC50 for different concentrations of eugenol were calculated for both muscle larvae (187.5 µM) and adults (190.4 µM) to determine the accurate dose range. Both the nematode stages were cultured in the commonly used RPMI-1640 media in 24-well plates. Different concentrations of eugenol (122, 305, 609, 1218, and 3045 µM) were administered in different groups of larvae/adults. The parasitological parameters were monitored after 1, 3, 6, 10, 24 h for each EO concentration in concomitant with the control groups. Reference chemotherapeutic anthelminthic drug “albendazole” (at dose 377 µM) was experimentally grouped in triplicates as positive control and the untreated as negative control, respectively. Mortality was observed where time-dependent adult stages were less susceptible than muscle larvae. Eugenol achieved 100% efficacy against T. spiralis larvae and killed the total larvae after 10 and 24 h at concentrations of 1218 and 3045 µM, the same as albendazole’s effect on the positive control group. In regard to adults, resembling muscle larvae (ML), a significant effect of both concentrations at p < 0.0001 was obtained, and the concentration × time interaction was significant at p < 0.0001. Furthermore, the treated/untreated adult and muscle larvae were collected and processed for scanning electron microscopy (SEM). Massive destruction of parasite burden was observed, especially at high concentrations (1218 and 3045 µM). In addition, complete and mild loss in cuticular striation in both the treated and positive controls were confirmed by SEM, respectively, in comparison to the control untreated group.

Characterization of Orange Peel Extract and Its Potential Protective Effect against Aluminum Chloride-Induced Alzheimer's Disease

Alzheimer's disease (AD) is a devastating neurodegenerative disorder without a cure. Hence, developing an effective treatment or protective agent is crucial for public health. The present study aims to characterize orange peel extract (OPE) through in vitro and in silico studies. Furthermore, it examines the protective effect of OPE against experimentally-induced Alzheimer's disease in rats. The total phenolic and flavonoid content of OPE was 255.86 ± 1.77 and 52.06 ± 1.74 (mg/100 g), respectively. Gallic acid, the common polyphenol in OPE detected by HPLC was 3388.60 μg/100 g. OPE antioxidant IC₅₀ was 67.90 ± 1.05, 60.48 ± 0.91, and 63.70 ± 0.30 by DPPH, ABTS and Hydroxyl radical scavenging activity methods, respectively. In vitro anti-acetylcholinesterase (AChE) IC₅₀ was 0.87 ± 0.025 mg/mL for OPE and 2.45 ± 0.001 mg/mL for gallic acid. Molecular docking analysis for human AChE (4EY7) with donepezil, gallic acid, and acetylcholine showed binding energy ΔG values of -9.47, -3.72, and -5.69 Kcal/mol, respectively. Aluminum chloride injection (70 mg/Kg/day for 6 weeks) induced Alzheimer's-like disease in male rats. OPE (100 and 200 mg/kg/d) and gallic acid (50 mg/kg/d) were administered orally to experimental animals for 6 weeks in addition to aluminum chloride injection (as protective). OPE was found to protect against aluminum chloride-induced neuronal damage by decreasing both gene expression and activity of acetylcholinesterase (AChE) and a decrease in amyloid beta (Aβ42) protein level, thiobarbituric acid-reactive substances (TBARS), and nitric oxide (NO), and increased reduced glutathione (GSH) level and activity of the antioxidant enzymes in the brain tissues. Additionally, gene expressions for amyloid precursor protein (APP) and beta secretase enzyme (BACE1) were downregulated, whereas those for presinilin-2 (PSEN2) and beta cell lymphoma-2 (BCL2) were upregulated. Furthermore, the reverse of mitochondrial alternation and restored brain ultrastructure might underlie neuronal dysfunction in AD. In conclusion, our exploration of the neuroprotective effect of OPE in vivo reveals that OPE may be helpful in ameliorating brain oxidative stress, hence protecting from Alzheimer's disease progression.

Green synthesis of chitosan nanoparticles, optimization, characterization and antibacterial efficacy against multi drug resistant biofilm-forming Acinetobacter baumannii

Chitosan nanoparticles (CNPs) are promising versatile cationic polymeric nanoparticles, which have received growing interest over last few decades. The biocompatibility, biodegradability, environmental safety and non-toxicity of the chitosan nanoparticles makes it preferred for a wide range of biological applications including agriculture, medical and pharmaceutical fields. In this study, CNPs were biosynthesized by aqueous extract of Eucalyptus globulus Labill fresh leaves as bio-reductant. Box-Behnken design in 29 experimental runs was used for optimization of different factors affecting the production of CNPs. The maximum yield of CNPs was 9.91 mg/mL at pH of 4.5, chitosan concentration of 1%, incubation time of 60 min and temperature of 50 °C. The crystallinity, particle size and morphology of the biosynthesized CNPs were characterized. The CNPs possess a positively charged surface of 31.1 mV. The SEM images of the CNPs confirms the formation of spherical form with smooth surface. The TEM images show CNPs were spherical in shape and their size range was between 6.92 and 10.10 nm. X-ray diffraction indicates the high degree of CNPs crystallinity. FTIR analysis revealed various functional groups of organic compounds including NH, NH2, C-H, C-O, C-N, O-H, C-C, C-OH and C-O-C. The thermogravimetric analysis results revealed that CNPs are thermally stable. The antibacterial activity of CNPs was determined against pathogenic multidrug-resistant bacteria, Acinetobacter baumannii. The diameters of the inhibition zones were 12, 16 and 30 mm using the concentrations of 12.5, 25 and 50 mg/mL; respectively. When compared to previous studies, the biosynthesized CNPs produced using an aqueous extract of fresh Eucalyptus globulus Labill leaves have the smallest particle sizes (with a size range between 6.92 and 10.10 nm). Consequently, it is a promising candidate for a diverse range of medical applications and pharmaceutical industries.

Improved recurrent generative model for reconstructing large-size porous media from two-dimensional images

Modeling the three-dimensional (3D) structure from a given 2D image is of great importance for analyzing and studying the physical properties of porous media. As an intractable inverse problem, many methods have been developed to address this fundamental problems over the past decades. Among many methods, the deep learning-(DL) based methods show great advantages in terms of accuracy, diversity, and efficiency. Usually, the 3D reconstruction from the 2D slice with a larger field-of-view is more conducive to simulate and analyze the physical properties of porous media accurately. However, due to the limitation of reconstruction ability, the reconstruction size of most widely used generative adversarial network-based model is constrained to 64^{3} or 128^{3}. Recently, a 3D porous media recurrent neural network based method (namely, 3D-PMRNN) (namely 3D-PMRNN) has been proposed to improve the reconstruction ability, and thus the reconstruction size is expanded to 256^{3}. Nevertheless, in order to train these models, the existed DL-based methods need to down-sample the original computed tomography (CT) image first so that the convolutional kernel can capture the morphological features of training images. Thus, the detailed information of the original CT image will be lost. Besides, the 3D reconstruction from a optical thin section is not available because of the large size of the cutting slice. In this paper, we proposed an improved recurrent generative model to further enhance the reconstruction ability (512^{3}). Benefiting from the RNN-based architecture, the proposed model requires only one 3D training sample at least and generates the 3D structures layer by layer. There are three more improvements: First, a hybrid receptive field for the kernel of convolutional neural network is adopted. Second, an attention-based module is merged into the proposed model. Finally, a useful section loss is proposed to enhance the continuity along the Z direction. Three experiments are carried out to verify the effectiveness of the proposed model. Experimental results indicate the good reconstruction ability of proposed model in terms of accuracy, diversity, and generalization. And the effectiveness of section loss is also proved from the perspective of visual inspection and statistical comparison.

Imidacloprid-induced pathophysiological damage in the midgut of Locusta migratoria (Orthoptera: Acrididae) in the field

Neonicotinoids are modern insecticides widely used in agriculture worldwide. Their impact on target (nervous system) and non-target (midgut) tissues has been well studied in beneficial insects including honeybees under controlled conditions. However, their detailed effects on pest insects on the field are missing to date. Here, we have studied the effects of the neonicotinoid imidacloprid on the midgut of the pest insect Locusta migratoria caught in the field. We found that in the midgut of imidacloprid-exposed locusts the activity of enzymes involved in reactive oxygen metabolism was perturbed. By contrast, the activity of P450 enzymes that have been shown to be activated in a detoxification response and that were also reported to produce reactive oxygen species was elevated. Probably as a consequence, markers of oxidative stress including protein carbonylation and lipid peroxidation accumulated in midgut samples of these locusts. Histological analyses revealed that their midgut epithelium is disorganized and that the brush border of the epithelial cells is markedly reduced. Indeed, microvilli are significantly shorter, misshapen and possibly non-functional in imidacloprid-treated locusts. We hypothesize that imidacloprid induces oxidative stress in the locust midgut, thereby changing the shape of midgut epithelial cells and probably in turn compromising their physiological function. Presumably, these effects reduce the survival rate of imidacloprid-treated locusts and the damage they cause in the field.

Photorhabdus and Xenorhabdus as Symbiotic Bacteria for Bio-Control Housefly (Musca domestica L.)

&lt;b&gt;Background and Objective:&lt;/b&gt; The housefly poses a threat to the public health of humans and domestic animals since it can carry and transmit pathogens. Despite there are many attempts to control this insect, most of them depend on conventional pesticides. Thus, the current study aimed to evaluate the efficacy of whole-cell suspension, cell-free supernatant and crude cells of the symbiotic bacteria &lt;i&gt;Photorhabdus&lt;/i&gt; sp. and &lt;i&gt;Xenorhabdus&lt;/i&gt; sp., as bio-control agents for housefly stages. &lt;b&gt;Materials and Methods:&lt;/b&gt; The &lt;i&gt;Photorhabdus&lt;/i&gt; sp. and &lt;i&gt;Xenorhabdus&lt;/i&gt; sp., were isolated from the entomopathogenic nematodes, &lt;i&gt;Heterorhabditis indica&lt;/i&gt; and &lt;i&gt;Steinernema feltiae&lt;/i&gt;, respectively. The phenotypic, as well as the enzymatic characterizations of both bacteria, were determined. In addition, histopathological changes of the alimentary canal of &lt;i&gt;M. domestica&lt;/i&gt; adults treated with whole-cell suspensions (at 3×10&lt;sup&gt;8 &lt;/sup&gt;cells mL&lt;sup&gt;&lt;/sup&gt;&lt;sup&gt;1&lt;/sup&gt;) of both bacteria were carefully examined using transmission electron microscopy. &lt;b&gt;Results:&lt;/b&gt; The results showed that both symbiotic bacteria significantly suppressed larvae, pupae and adults of &lt;i&gt;M. domestica&lt;/i&gt;, particularly when they were applied as whole-cell suspensions. For example, the highest concentration of whole-cell suspension, cell-free supernatant and crude cells of &lt;i&gt;Photorhabdus&lt;/i&gt; sp., induced larval mortalities by 94.7, 64.0 and 45.3%, while those of &lt;i&gt;Xenorhabdus&lt;/i&gt; sp., induced larval mortalities by 58.7, 46.7 and 30.7% at 96 hrs, respectively. The results also showed that whole-cell suspensions of both symbiotic bacteria caused severe histopathological changes in the ultrastructure of the treated adults' alimentary canal. &lt;b&gt;Conclusion:&lt;/b&gt; Both symbiotic bacteria can be effectively used, particularly the whole-cell suspension, as bio-control agents against the housefly either in the larval or adult stage.

Vitamin B12 as a Cholinergic System Modulator and Blood Brain Barrier Integrity Restorer in Alzheimer's Disease

So far, the cholinergic hypothesis of Alzheimer's disease (AD) remains the fundamental explanation for the complex etiopathology of AD. However, therapeutics raising synaptic acetylcholine (Ach) or having cholinergic receptors agonistic activity had shown limited clinical efficacy, possibly, due to lacking capability to aggregate cholinergic receptors within the degenerated cholinergic neurons. Vitamin-B12 (B12) is an epigenetic modifier. It has a specific CNS transport system via the cubam receptors. The later enclose a cholinergic aggregator; agrin protein, suggesting that B12 administration may cause cholinergic receptors aggregation. Further, B12 involvement in homocysteine (Hcy) metabolism may restore blood brain barrier (BBB) integrity disrupted by elevated Hcy levels in AD. Here in, using a pharmacological model of cholinergic amnesia, three different B12 doses were compared to the standard of care; donepezil (DON) regarding cholinergic system modulation, and Hcy metabolic pathways. Further, AD-associated cerebro-vascular pathology was assessed by morphometric analyses of cerebro-vasculature morphology and ultrastructure using scanning and transmission electron-microscopes, respectively. Consequent effect on key AD-hallmarks and behavioral cognitive tests was also examined. The highest B12-tested dose (B12-HD) showed the greatest hippocampal cholinergic modulation with dose-dependent preferential upregulation of one cholinergic receptor over the other. Altered Hcy metabolism was proved to be a consequence of cholinergic disruption that was variably reversed by different B12 doses. In spite of equipotent effect of DON and B12-HD therapies in decreasing β-amyloid synthesis, B12-HD-treated group revealed the greatest restoration of BBB integrity indicating superior capability of β-amyloid clearance. Therefore, B12-HD therapy may represent a promising AD-modifying agent with extra-ability over conventional cholinergic modulators to aggregate cholinergic receptors.

Multiscale modeling of gas flow behaviors in nanoporous shale matrix considering multiple transport mechanisms

This study proposes a multiscale model combining molecular simulation and the lattice Boltzmann method (LBM) to explore gas flow behaviors with multiple transport mechanisms in nanoporous media of shale matrix. The gas adsorption characteristics in shale nanopores are first investigated by molecular simulations, which are then integrated and upscaled into the LBM model through a local adsorption density parameter. In order to adapt to high Knudsen number and nanoporous shale matrix, a multiple-relaxation-time pore-scale LBM model with a regularization procedure is developed. The combination of bounce-back and full diffusive boundary condition is adopted to take account of gas slippage and surface diffusion induced by gas adsorption. Molecular simulation results at the atomic scale show that gas adsorption behaviors are greatly affected by the pressure and pore size of the shale organic nanopore. At the pore scale, the gas transport behaviors with multiple transport mechanisms in nanoporous shale matrix are explored by the developed multiscale model. Simulation results indicate that pressure exhibits more significant influences on the transport behaviors of shale gas than temperature does. Compared with porosity, the average pore size of nanoporous shale matrix plays a more significant role in determining the apparent permeability of gas transport. The roles of the gas adsorption layer and surface diffusion in shale gas transport are discussed. It is observed that under low pressure, the gas adsorption layer has a positive influence on gas transport in shale matrix due to the strong surface diffusion effect. The nanoporous structure with the anisotropy characteristic parallel to the flow direction can enhance gas transport in shale matrix. The obtained results may provide underlying and comprehensive understanding of gas flow behaviors considering multiple transport mechanisms in shale matrix. Also, the proposed multiscale model can be considered as a powerful tool to invesigate the multiscale and multiphysical flow behaviors in porous media.

Digital Rock Reconstruction with User-Defined Properties Using Conditional Generative Adversarial Networks

Uncertainty is ubiquitous with multiphase flow in subsurface rocks due to their inherent heterogeneity and lack of in-situ measurements. To complete uncertainty analysis in a multi-scale manner, it is a prerequisite to provide sufficient rock samples. Even though the advent of digital rock technology offers opportunities to reproduce rocks, it still cannot be utilized to provide massive samples due to its high cost, thus leading to the development of diversified mathematical methods. Among them, two-point statistics (TPS) and multi-point statistics (MPS) are commonly utilized, which feature incorporating low-order and high-order statistical information, respectively. Recently, generative adversarial networks (GANs) are becoming increasingly popular since they can reproduce training images with excellent visual and consequent geologic realism. However, standard GANs can only incorporate information from data, while leaving no interface for user-defined properties, and thus may limit the representativeness of reconstructed samples. In this study, we propose conditional GANs for digital rock reconstruction, aiming to reproduce samples not only similar to the real training data, but also satisfying user-specified properties. In fact, the proposed framework can realize the targets of MPS and TPS simultaneously by incorporating high-order information directly from rock images with the GANs scheme, while preserving low-order counterparts through conditioning. We conduct three reconstruction experiments, and the results demonstrate that rock type, rock porosity, and correlation length can be successfully conditioned to affect the reconstructed rock images. The randomly reconstructed samples with specified rock type, porosity and correlation length will contribute to the subsequent research on pore-scale multiphase flow and uncertainty quantification.

Combining State of the Art Opensource and Proprietary Machine Learning Technologies to Build a Data Analysis Pipeline for Gasoline Particulate Filters using X-ray Microscopy, Focused Ion Beam-Scanning Electron Microscopy and Transmission Electron Microscopy

The performance of a particulate filter is determined by multi-scale properties that span the macro, meso and atomic scale. Traditionally, the primary role of a GPF is to reduce solid particles and liquid droplets. At the macroscale, transport of gas through a filter’s channels and interconnecting pores act as main transport arteries for catalytically active sites. At the mesoscale, the micropore structure is important for ensuring that there are enough active sites that are accessible for the gas to reach the catalyst nanoparticles. Whereas at the atomic scale, the structure of the catalyst material determines the performance and selectivity within the filter. Understanding all length scales requires a correlative approach but this is often quite difficult to achieve due to the number of software packages a scientist has to deal with. We demonstrate how current state of the art approaches in the field can be combined into a streamlined pipeline to characterise particulate filters by digitally reconstructing the sample, analysing it at high throughput, and eventually used as an input for gas flow simulations and better product design.

Three-dimensional reconstruction of porous media using super-dimension-based adjacent block-matching algorithm

As porous media play an essential role in a variety of industrial applications, it is essential to understand their physical properties. Nowadays, the super-dimensional (SD) reconstruction algorithm is used to stochastically reconstruct a three-dimensional (3D) structure of porous media from a given two-dimensional image. This algorithm exhibits superiority in accuracy compared with classical algorithms because it learns information from the real 3D structure. However, owing to the short development time of the SD algorithm, it also has some limitations, such as inexact porosity characterization, long run time, blocking artifacts, and suboptimal accuracy that may be improved. To mitigate these limitations, this study presents the design of a special template that contains two parts of data (i.e., adjacent blocks and a central block); the proposed method matches adjacent blocks during reconstruction and assigns the matched central block to the area to be reconstructed. Furthermore, we design two important mechanisms during reconstruction: one for block matching and the other for porosity control. To verify the effectiveness of the proposed method compared with an existing SD method, both methods were tested on silica particle material and three homogeneous sandstones with different porosities; meanwhile, we compared the proposed method with a multipoint statistics method and a simulated annealing method. The reconstructed results were then compared with the target both visually and quantitatively. The experimental results indicate that the proposed method can overcome the aforementioned limitations and further improve the accuracy of existing methods. This method achieved 4-6 speedup factor compared with the traditional SD method.

Nature-Inspired Optimization Algorithms for the 3D Reconstruction of Porous Media

One of the most challenging problems that are still open in the field of materials science is the 3D reconstruction of porous media using information from a single 2D thin image of the original material. Such a reconstruction is only feasible subject to some important assumptions that need to be made as far as the statistical properties of the material are concerned. In this study, the aforementioned problem is investigated as an explicitly formulated optimization problem, with the phase of each porous material point being decided such that the resulting 3D material model shows the same statistical properties as its corresponding 2D version. Based on this problem formulation, herein for the first time, several traditional (genetic algorithms—GAs, particle swarm optimization—PSO, differential evolution—DE), as well as recently proposed (firefly algorithm—FA, artificial bee colony—ABC, gravitational search algorithm—GSA) nature-inspired optimization algorithms were applied to solve the 3D reconstruction problem. These algorithms utilized a newly proposed data representation scheme that decreased the number of unknowns searched by the optimization process. The advantages of addressing the 3D reconstruction of porous media through the application of a parallel heuristic optimization algorithm were clearly defined, while appropriate experiments demonstrating the greater performance of the GA algorithm in almost all the cases by a factor between 5%–84% (porosity accuracy) and 3%–15% (auto-correlation function accuracy) over the PSO, DE, FA, ABC, and GSA algorithms were undertaken. Moreover, this study revealed that statistical functions of a high order need to be incorporated into the reconstruction procedure to increase the reconstruction accuracy.

Reconstruction of porous media from extremely limited information using conditional generative adversarial networks

Porous media are ubiquitous in both nature and engineering applications. Therefore, their modeling and understanding is of vital importance. In contrast to direct acquisition of three-dimensional (3D) images of this type of medium, obtaining its subregion (s) such as 2D images or several small areas can be feasible. Therefore, reconstructing whole images from limited information is a primary technique in these types of cases. Given data in practice cannot generally be determined by users and may be incomplete or only partially informed, thus making existing reconstruction methods inaccurate or even ineffective. To overcome this shortcoming, in this study we propose a deep-learning-based framework for reconstructing full images from their much smaller subareas. In particular, conditional generative adversarial network is utilized to learn the mapping between the input (a partial image) and output (a full image). To ensure the reconstruction accuracy, two simple but effective objective functions are proposed and then coupled with the other two functions to jointly constrain the training procedure. Because of the inherent essence of this ill-posed problem, a Gaussian noise is introduced for producing reconstruction diversity, thus enabling the network to provide multiple candidate outputs. Our method is extensively tested on a variety of porous materials and validated by both visual inspection and quantitative comparison. It is shown to be accurate, stable, and even fast (∼0.08 s for a 128×128 image reconstruction). The proposed approach can be readily extended by, for example, incorporating user-defined conditional data and an arbitrary number of object functions into reconstruction, while being coupled with other reconstruction methods.

Enhancing images of shale formations by a hybrid stochastic and deep learning algorithm

Accounting for the morphology of shale formations, which represent highly heterogeneous porous media, is a difficult problem. Although two- or three-dimensional images of such formations may be obtained and analyzed, they either do not capture the nanoscale features of the porous media, or they are too small to be an accurate representative of the media, or both. Increasing the resolution of such images is also costly. While high-resolution images may be used to train a deep-learning network in order to increase the quality of low-resolution images, an important obstacle is the lack of a large number of images for the training, as the accuracy of the network's predictions depends on the extent of the training data. Generating a large number of high-resolution images by experimental means is, however, very time consuming and costly, hence limiting the application of deep-learning algorithms to such an important class of problems. To address the issue we propose a novel hybrid algorithm by which a stochastic reconstruction method is used to generate a large number of plausible images of a shale formation, using very few input images at very low cost, and then train a deep-learning convolutional network by the stochastic realizations. We refer to the method as hybrid stochastic deep-learning (HSDL) algorithm. The results indicate promising improvement in the quality of the images, the accuracy of which is confirmed by visual, as well as quantitative comparison between several of their statistical properties. The results are also compared with those obtained by the regular deep learning algorithm without using an enriched and large dataset for training, as well as with those generated by bicubic interpolation.

A core-scale reconstructing method for shale

Characterization of shale cores with low and anisotropic permeability is complicated, due to the presence of multiscale pore structure and thin layers, and defies conventional methods. To accurately reproduce the morphology of multiscale pore structure of the shale core, a novel core-scale reconstructing method is proposed to reconstruct 3D digital-experimental models by means of the combination of SEM, EDS images, nitrogen adsorption and pressure pulse decay experiment result. In this method, the multiscale and multicomponent reconstructing algorithm is introduced to build the representative multiscale model for each layer, which can describe the complex 3D structures of nano organic pores, micro-nano inorganic pores, micro slits and several typical minerals. Especially, to reproduce the realistic morphology for shale, the optimization algorithm based on simulated annealing algorithm uses the experimental data as constrain conditions to adjust and optimize the model for each layer. To describe the bedding characteristics of the shale core, bedding fractures are constructed by analysis of the mineral distribution in the interface of two layers, and then the representative models for different layers are integrated together to obtain the final core-scale digital-experimental model. Finally, the model is validated by computing its morphological and flow properties and comparing them with those of the actual 3D shale sample. This method provide a way for systematically and continuously describe the multiscale and anisotropic pore structure (from nm-cm) of the shale core, and will be helpful for understanding the quality of the shale reservoir.

Kerogen Swelling and Confinement: Its implication on Fluid Thermodynamic Properties in Shales

Type I kerogen was isolated from Green River Shale and characterized using SEM, TGA, DSC, and nitrogen adsorption. The swelling behavior of this kerogen with decane was analyzed using traditional test-tube swelling experiment and Dynamic Light Scattering. The TGA and DSC were used to analyze the thermodynamic behavior of decane that was sorbed in the kerogen and show that kerogen suppresses the boiling point of decane due to the effect of confinement. However, the suppression is larger when oil (a multicomponent mixture) was used, possibly due to the combined effect of differential uptake of components by kerogen (kerogen prefers and sorbs polars and aromatics more than saturates, leading to splitting of oil into a sorbed and a free phase) and confinement in nano pores. Test-tube swelling, TGA, and DSC experiments were also performed on pyridine(polar-aromatic)-swelled kerogen. The combined and individual contributions from the two effects (the effect of confinement and differential uptake of hydrocarbon components) on properties of liquid in contact with kerogen, are studied in this work. Molecular Dynamics (MD) simulations revealed the variation in the swelling of type II kerogen in the presence of same amount of different liquids (differential swelling of kerogen).

Isolation, characterization, optimization, immobilization and batch fermentation of bioflocculant produced by Bacillus aryabhattai strain PSK1

Among others, isolate PSK1 was selected and identified by 16 S rDNA sequencing as Bacillus aryabhattai. Growth optimization of PSK1 and physicochemical parameters affected bioflocculant production was carried out by Plackett-Burman design and resulted in increasing in the activity by 4.5%. Bioflocculant production by entrapped and adsorbed immobilized microbial cells was performed using different techniques and revealed enhancement in the activity in particular with pumice adsorption. HPLC analysis of sugars and amino acids composition, FTIR and the effect of different factors on the purified PSK1 biopolymer such as presence of cations, thermal stability, pH range and clay concentration was carried out. Scanning electron microscopy (SEM) of free, immobilized cells, PSK1 bioflocculant and formed flocs were performed. The results revealed that bioflocculant PSK1 is mainly glycoprotein consists of glucose and rhamnose with a large number of amino acids in which arginine and phenylalanine were the major. SEM analysis demonstrated that PSK1 have a clear crystalline rod shaped structure. FTIR spectrum reported the presence of hydroxyl and amino groups which are preferred in flocculation process. PSK1 was soluble in water and insoluble in all other tested organic solvents, while it was thermally stable from 40 to 80 °C. Among examined cations, CaCl₂ was the best coagulant. The maximum flocculation activity of the PSK1 recorded at 50 °C (92.8%), pH 2.0 (94.56%) with clay concentration range 5-9 g/l. To obtain a large amount of PSK1 bioflocculant with high flocculating activity, batch fermentation was employed. The results recorded ∼6 g/l yield after 24 h of fermentation.

New insights on the complex dynamics of two-phase flow in porous media under intermediate-wet conditions

Multiphase flow in porous media is important in a number of environmental and industrial applications such as soil remediation, CO₂ sequestration, and enhanced oil recovery. Wetting properties control flow of immiscible fluids in porous media and fluids distribution in the pore space. In contrast to the strong and weak wet conditions, pore-scale physics of immiscible displacement under intermediate-wet conditions is less understood. This study reports the results of a series of two-dimensional high-resolution direct numerical simulations with the aim of understanding the pore-scale dynamics of two-phase immiscible fluid flow under intermediate-wet conditions. Our results show that for intermediate-wet porous media, pore geometry has a strong influence on interface dynamics, leading to co-existence of concave and convex interfaces. Intermediate wettability leads to various interfacial movements which are not identified under imbibition or drainage conditions. These pore-scale events significantly influence macro-scale flow behaviour causing the counter-intuitive decline in recovery of the defending fluid from weak imbibition to intermediate-wet conditions.