Search results for: cell morphology prediction

Authors: Azza H. El-Medany, Hanan H. Hagar, Omnia A. Nayel, Jamila H. El-Medany

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In search for drugs that can target cancer cell micro-environment in as much as being able to halt malignant cellular transformation, the natural dietary phytochemical curcumin was currently assessed in DMH-induced colorectal cancer rat model. The study enrolled 50 animals divided into a control group (n=10) and DMH-induced colorectal cancer control group (n=20) (20mg/kg-body weight for 28 weeks) versus curcumin-treated group (n=20) (160 mg/kg suspension daily oral for further 8 weeks). Treatment by curcumin succeeded to significantly decrease the percent of ACF and tended to normalize back the histological changes retrieved in adenomatous and stromal cells induced by DMH. The drug also significantly elevated GSH and significantly reduced most of the accompanying biochemical elevations (namely MDA, TNF-α, TGF-β and COX2) observed in colonic carcinomatous tissue, induced by DMH, thus succeeding to revert that of MDA, COX2 and TGF-β back to near normal as justified by being non-significantly altered as compared to normal controls. The only exception was PAF that was insignificantly altered by the drug. When taken together, it could be concluded that curcumin possess the potentiality to halt some of the orchestrated cross-talk between cancerous transformation and its micro-environmental niche that contributes to cancer initiation, progression and metastasis in this experimental cancer colon model. Envisioning these merits to a drug with already known safety preferentiality, awaits final results of current ongoing clinical trials, before curcumin can be added to the new therapeutic armamentarium of anticancer therapy.

Keywords: curcumin, dimethyl hydralazine, aberrant crypt foci, malondialdehyde, reduced glutathione, cyclooxygenase-2, tumour necrosis factor-alpha, transforming growth factor-beta, platelet activating factor

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Authors: Kamal Ameis

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This study aims to further improve our understanding of the underlying mechanism of local injury that occurs after manual acupuncture needle manipulation, and that initiates the muscle regeneration process, which is essential for muscle maintenance and adaptation. Skeletal muscle is maintained by resident stem cells called muscle satellite cells. These cells are normally in quiescent state, but following muscle injury, they re-enter the cell cycle and execute a myogenic program resulting in muscle fiber regeneration. Our previous work in young rats demonstrated that acupuncture treatment induced injury that activated resident satellite (stem) cells, which leads to muscle regeneration. Skeletal muscle regeneration is an adaptive response to injury that requires a tightly orchestrated event between signaling pathways activated by growth factor and intrinsic regulatory program controlled by myogenic transcription factor. We identified several gene expressions uniquely important for muscle regeneration in response to acupuncture treatment at different time course using different biological techniques, including Immunocytochemistry, western blotting, and Real Time PCR. This study uses a novel but non-invasive model of injury induced by manual acupuncture to further our current understanding of regenerative mechanism of muscle stem cells. From a clinical perspective, this model of injury induced by manual acupuncture may be easily translatable into a clinical tool that can be used as an alternative to physical exercise for patients challenged by bed rest or forced inactivity. Finally, the knowledge gained from this research could be useful for studies of the local effects of various modalities of induced injury, such as the traditional method of healing by cupping (hijamah), which may enhanced muscle stem cells and muscle fiber regeneration.

Keywords: acupuncture, injury, regeneration, muscle stem cells

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Authors: Nasim Rasuli, Akram Ahmadi, Hossein Riahi, Zeinab Shariatmadari, Majid Ghorbani Nohooji, Pooyan Mehraban Joubani

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Cyanobacteria are one of the most promising sources of new biostimulants and have received much attention due to their diverse applications in biotechnology. These microorganisms enhance the growth and productivity of plants by producing plant growth stimulants and fixing atmospheric nitrogen. Thymus vulgaris L., a valuable medicinal plant from the Lamiaceae family, is widely distributed across the globe. essential oil of T. vulgaris is best characterized by the prominence of phenols, making them the key compounds in its composition. Lignin biosynthesis as a natural plant polyphenol plays a crucial role in promoting plant growth, strengthening cell walls, and increasing resistance to pathogens. In this study, the bioelicitor activity of five cyanobacterial suspensions including Anabaena torulosa ISB213, Nostoc calcicola ISB215, Nostoc ellipsosporum ISB217, Trichormus doliolum ISB214, and Oscillatoria sp. ISB2116 on the lignin content of the T. vulgaris L. was investigated. Pot experiments were performed by inoculation of a %2 algal extract to the soil of treated plants one week before planting and then every 20 days. After four months, the lignin content in the leaves of both treated and control plants was evaluated. The results demonstrated that the application of cyanobacteria significantly increased the lignin content in the leaves of treated plants compared to the control. The treatment with Oscillatoria sp. ISB216 and N. ellipsosporum ISB217 resulted in the highest lignin content, with an increase of 93.33% and 86.67%, respectively. These findings highlight the potential of cyanobacteria as bioelicitors, offering a viable alternative for enhancing the production of secondary metabolites in T. vulgaris. Consequently, this could contribute to the economic value of this medicinal plant.

Keywords: cyanobacteria, bioelicitor, thymus vulgaris, lignin

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Authors: Cyoung-Huei Huang, Chiu-Li Yeh, Man-Hui Pai, Sung-Ling Yeh

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This study evaluated the effect of different dietary n-6/n-3 polyunsaturated fatty acid (PUFA) ratios on modulating helper T (Th) and regulatory T (Treg) lymphocytes in mice with dextran sulfate sodium (DSS)-induced colitis. There were 3 control and 3 colitis groups in this study. Mice were fed for 24 d with an AIN-93G diet either with soybean oil (S), a mixture of soybean oil and low fish oil content (LF) or high fish oil content (HF). The ratio of n-6/n-3 PUFA in the LF diet was 4:1, and that in the HF diet was 2:1. The control groups drank distilled water while colitis groups provided 2% DSS in drinking water during day 15-19. All mice drank distilled water from day 20-24 for recovery and sacrificed on day 25. The results showed that colitis resulted in higher Th1, Th2, and Th17 and lower Treg percentages in the blood. Also, plasma haptoglobin and proinflammatory chemokines were elevated in colon lavage fluid. Colitic groups with fish oil had lower inflammatory mediators in the plasma and colon lavage fluid. Further, the percentages of Th1, Th2, and Th17 cells in the blood were lower, whereas Treg cell percentages were higher than those in the soybean oil group. The colitis group with n-6/n-3 PUFA ratio 2:1 had more pronounce effects than ratio 4:1. These results suggest that diets with an n-6/n-3 PUFA ratio of 2:1 or 4:1 regulate the Th/Treg balance and attenuate inflammatory mediator production in colitis. Compared to the n-6/n-3 PUFA ratio 4:1, the ratio of 2:1 was more effective in reducing inflammatory reactions in DSS-induced colitis.

Keywords: inflammatory bowel disease, n-3 polyunsaturated fatty acids, helper T lymphocyte, regulatory T lymphocyte

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Authors: Frida Carrillo Morales, Maria Maricela Carrasco Yépez, Saúl Rojas Hernández

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Naegleria fowleri is the causative agent of primary amebic meningoencephalitis, this disease is acute and fulminant that affects humans. It has been reported that despite the existence of therapeutic options against this disease, its mortality rate is 97%. Therefore, the need arises to have vaccines that confer protection against this disease and, in addition to developing adjuvants to enhance the immune response. In this regard, in our work group, we obtained a peptide designed from the membrane protein MP2CL5 of Naegleria fowleri called Smp145 that was shown to be immunogenic; however, it would be of great importance to enhance its immunological response, being able to co-administer it with a non-toxic adjuvant. Therefore, the objective of this work was to carry out the bioinformatic design of a peptide of the Naegleria fowleri membrane protein MP2CL5 conjugated with a non-toxic modified adjuvant from the native A1 structure of Cholera Toxin. For which different bioinformatics tools were used to obtain a model with a modification in amino acid 61 of the A1 subunit of the CT (CTA1), to which the Smp145 peptide was added and both molecules were joined with a 13-glycine linker. As for the results obtained, the modification in CTA1 bound to the peptide produces a reduction in the toxicity of the molecule in in silico experiments, likewise, the prediction in the binding of Smp145 to the receptor of B cells suggests that the molecule is directed in specifically to the BCR receptor, decreasing its native enzymatic activity. The stereochemical evaluation showed that the generated model has a high number of adequately predicted residues. In the ERRAT test, the confidence with which it is possible to reject regions that exceed the error values was evaluated, in the generated model, a high score was obtained, which determines that the model has a good structural resolution. Therefore, the design of the conjugated peptide in this work will allow us to proceed with its chemical synthesis and subsequently be able to use it in the mouse meningitis protection model caused by N. fowleri.

Keywords: immunology, vaccines, pathogens, infectious disease

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Authors: JiYoung Park, SueGoo Rhee, HyunAe Woo

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In liver regeneration, quiescent hepatocytes need to be primed to fully respond to growth factors such as hepatocyte growth factor. To understand the priming process, it is necessary to analyze patterns of gene expression that occur during liver regeneration after partial hepatectomy (PHx). Recently, tyrosine phosphorylation of signal transducer and activator of transcription 3 (pYSTAT3) has been shown to play an important role in initiating liver regeneration. In order to evaluate the role of pYSTAT3 on liver regeneration after PHx, we used an intrabody which can selectively inhibit pYSTAT3. In our previous studies, an intrabody had been shown that it bound specifically to the pYSTAT3. Adenovirus-mediated expression of the intrabody in HepG2 cells, as well as mouse liver, blocked both accumulation of pYSTAT3 in the nucleus and downstream target of pYSTAT3. In this study, PHx was performed on intrabody-expressing mice and the expression levels of liver regeneration-related genes were analyzed. We also measured liver/body weight ratios and the related cellular signaling pathways were analyzed. Acute phase response genes were reduced in an intrabody-expressing mice during liver regeneration than in control virus-injected mice. However, the time course of liver mass restoration in intrabody-expressing mice was similar to that observed in control virus-injected mice. We also observed that the expression levels of anti-apoptotic genes, such as Bcl2 and Bcl-xL were decreased in intrabody-expressing mice whereas the expression of cell cycle-related genes such as cyclin D1, and c-myc was increased. Liver regeneration after PHx was partially impaired by the selective inhibition of pYSTAT3 with a phosphorylation site-specific intrabody and these results indicated that pYSTAT3 might have limited role in liver mass recovery.

Keywords: STAT3, pYSTAT3, liver regeneration, intrabody

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Authors: Amit Keshav, Alok Sharma, Bidyut Mazumdar

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Colocasia esculenta leaves and roots are widely used in Asian countries, such as, India, Srilanka and Pakistan, as food and feed material. The root is high in carbohydrates and rich in zinc. The leaves and stalks are often traditionally preserved to be eaten in dry season. Leaf juice is stimulant, expectorant, astringent, appetizer, and otalgia. Looking at the medicinal uses of the plant leaves; phytochemicals were extracted from the plant leaves and were characterized using Fourier-transform infrared spectroscopy (FTIR) to find the functional groups. Phytochemical analysis of Colocasia esculenta (L.) leaf was studied using three solvents (methanol, chloroform, and ethanol) with soxhlet apparatus. Powder of the leaves was employed to obtain the extracts, which was qualitatively and quantitatively analyzed for phytochemical content using standard methods. Phytochemical constituents were abundant in the leave extract. Leaf was found to have various phytochemicals such as alkaloids, glycosides, flavonoids, terpenoids, saponins, oxalates and phenols etc., which could have lot of medicinal benefits such as reducing headache, treatment of congestive heart failure, prevent oxidative cell damage etc. These phytochemicals were identified using UV spectrophotometer and results were presented. In order to find the antioxidant activity of the extract, DPPH (2,2-diphenyl-1-picrylhydrazyl) method was employed using ascorbic acid as standard. DPPH scavenging activity of ascorbic acid was found to be 84%, whereas for ethanol it was observed to be 78.92%, for methanol: 76.46% and for chloroform: 72.46%. Looking at the high antioxidant activity, Colocasia esculenta may be recommended for medicinal applications. The characterizations of functional groups were analyzed using FTIR spectroscopy.

Keywords: antioxidant activity, Colocasia esculenta, leaves, characterization, FTIR

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Authors: Chhabi Nigam, S. Ramakrishnan

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This paper brings out the analysis of the airborne Synthetic Aperture Radar (SAR) data to study the impact of Doppler centroid on Image quality and geocoding accuracy from the perspective of Stripmap mode of data acquisition. Although in Stripmap mode of data acquisition radar beam points at 90 degrees broad side (side looking), shift in the Doppler centroid is invariable due to platform motion. In-accurate estimation of Doppler centroid leads to poor image quality and image miss-registration. The effect of Doppler centroid is analyzed in this paper using multiple sets of data collected from airborne platform. Occurrences of ghost (ambiguous) targets and their power levels have been analyzed that impacts appropriate choice of PRF. Effect of aircraft attitudes (roll, pitch and yaw) on the Doppler centroid is also analyzed with the collected data sets. Various stages of the RDA (Range Doppler Algorithm) algorithm used for image formation in Stripmap mode, range compression, Doppler centroid estimation, azimuth compression, range cell migration correction are analyzed to find the performance limits and the dependence of the imaging geometry on the final image. The ability of Doppler centroid estimation to enhance the imaging accuracy for registration are also illustrated in this paper. The paper also tries to bring out the processing of low squint SAR data, the challenges and the performance limits imposed by the imaging geometry and the platform dynamics on the final image quality metrics. Finally, the effect on various terrain types, including land, water and bright scatters is also presented.

Keywords: ambiguous target, Doppler Centroid, image registration, Airborne SAR

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Authors: Benbiao Song, Yan Gao, Zhuo Liu

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Geostatistical modeling is the key technic for reservoir characterization, the quality of geological models will influence the prediction of reservoir performance greatly, but few studies have been done to quantify the factors impacting geostatistical reservoir modeling accuracy. In this study, 16 fluvial prototype models have been established to represent different geological complexity, 6 cases range from 16 to 361 wells were defined to reproduce all those 16 prototype models by different methodologies including SIS, object-based and MPFS algorithms accompany with different constraint parameters. Modeling accuracy ratio was defined to quantify the influence of each factor, and ten realizations were averaged to represent each accuracy ratio under the same modeling condition and parameters association. Totally 5760 simulations were done to quantify the relative contribution of each factor to the simulation accuracy, and the results can be used as strategy guide for facies modeling in the similar condition. It is founded that data density, geological trend and geological complexity have great impact on modeling accuracy. Modeling accuracy may up to 90% when channel sand width reaches up to 1.5 times of well space under whatever condition by SIS and MPFS methods. When well density is low, the contribution of geological trend may increase the modeling accuracy from 40% to 70%, while the use of proper variogram may have very limited contribution for SIS method. It can be implied that when well data are dense enough to cover simple geobodies, few efforts were needed to construct an acceptable model, when geobodies are complex with insufficient data group, it is better to construct a set of robust geological trend than rely on a reliable variogram function. For object-based method, the modeling accuracy does not increase obviously as SIS method by the increase of data density, but kept rational appearance when data density is low. MPFS methods have the similar trend with SIS method, but the use of proper geological trend accompany with rational variogram may have better modeling accuracy than MPFS method. It implies that the geological modeling strategy for a real reservoir case needs to be optimized by evaluation of dataset, geological complexity, geological constraint information and the modeling objective.

Keywords: fluvial facies, geostatistics, geological trend, modeling strategy, modeling accuracy, variogram

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Authors: Meghdad Payan, Kostas Senetakis, Arman Khoshghalb, Nasser Khalili

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Dynamic properties of soils, especially at the range of very small strains, are of particular interest in geotechnical engineering practice for characterization of the behavior of geo-structures subjected to a variety of stress states. This study reports on the small-strain dynamic properties of sand-silt mixtures with particular emphasis on the effect of non-plastic fines content on the small strain shear modulus (Gmax), Young’s Modulus (Emax), material damping (Ds,min) and Poisson’s Ratio (v). Several clean sands with a wide range of grain size characteristics and particle shape are mixed with variable percentages of a silica non-plastic silt as fines content. Prepared specimens of sand-silt mixtures at different initial void ratios are subjected to sequential torsional and flexural resonant column tests with elastic dynamic properties measured along an isotropic stress path up to 800 kPa. It is shown that while at low percentages of fines content, there is a significant difference between the dynamic properties of the various samples due to the different characteristics of the sand portion of the mixtures, this variance diminishes as the fines content increases and the soil behavior becomes mainly silt-dominant, rendering no significant influence of sand properties on the elastic dynamic parameters. Indeed, beyond a specific portion of fines content, around 20% to 30% typically denoted as threshold fines content, silt is controlling the behavior of the mixture. Using the experimental results, new expressions for the prediction of small-strain dynamic properties of sand-silt mixtures are developed accounting for the percentage of silt and the characteristics of the sand portion. These expressions are general in nature and are capable of evaluating the elastic dynamic properties of sand-silt mixtures with any types of parent sand in the whole range of silt percentage. The inefficiency of skeleton void ratio concept in the estimation of small-strain stiffness of sand-silt mixtures is also illustrated.

Keywords: damping ratio, Poisson’s ratio, resonant column, sand-silt mixture, shear modulus, Young’s modulus

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Authors: Shidvash Vakilipour, Scott Ormiston, Masoud Mohammadi, Rouzbeh Riazi, Kimia Amiri, Sahar Barati

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Two-phase and multi-phase flows are common flow types in fluid mechanics engineering. Among the basic and applied problems of these flow types, two-phase parallel flow is the one that two immiscible fluids flow in the vicinity of each other. In this type of flow, fluid properties (e.g. density, viscosity, and temperature) are different at the two sides of the interface of the two fluids. The most challenging part of the numerical simulation of two-phase flow is to determine the location of interface accurately. In the present work, a coupled interface tracking algorithm is developed based on Arbitrary Lagrangian-Eulerian (ALE) approach using a cell-centered, pressure-based, coupled solver. To validate this algorithm, an analytical solution for fully developed two-phase flow in presence of gravity is derived, and then, the results of the numerical simulation of this flow are compared with analytical solution at various flow conditions. The results of the simulations show good accuracy of the algorithm despite using a nearly coarse and uniform grid. Temporal variations of interface profile toward the steady-state solution show that a greater difference between fluids properties (especially dynamic viscosity) will result in larger traveling waves. Gravity effect studies also show that favorable gravity will result in a reduction of heavier fluid thickness and adverse gravity leads to increasing it with respect to the zero gravity condition. However, the magnitude of variation in favorable gravity is much more than adverse gravity.

Keywords: coupled solver, gravitational force, interface tracking, Reynolds number to Froude number, two-phase flow

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Authors: Ghaleb Bin Huraib, Fahad Al Harthi, Misbahul Arfin, Abdulrahman Al-Asmari

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Atopic dermatitis (AD), also known as atopic eczema, is a chronic inflammatory skin disease characterized by severe itching and recurrent relapsing eczema-like skin lesions, affecting up to 20% of children and 10% of adults in industrialized countries. AD is a complex multifactorial disease, and its exact etiology and pathogenesis have not been fully elucidated. The aim of this study was to investigate the impact of gene polymorphisms of T helper cell subtype Th1 and Th2 cytokines, interferon-gamma (IFN-γ), interleukin-6 (IL-6) and transforming growth factor (TGF)-β1on AD susceptibility in a Saudi cohort. One hundred four unrelated patients with AD and 195 healthy controls were genotyped for IFN-γ (874A/T), IL-6 (174G/C) and TGF-β1 (509C/T) polymorphisms using ARMS-PCR and PCR-RFLP technique. The frequency of genotypes AA and AT of IFN-γ (874A/T) differed significantly among patients and controls (P 0.001). The genotype AT was increased while genotype AA was decreased in AD patients as compared to controls. AD patients also had higher frequency of T containing genotypes (AT+TT) than controls (P = 0.001). The frequencies of allele T and A were statistically different in patients and controls (P = 0.04). The frequencies of genotype GG and allele G of IL-6 (174G/C) were significantly higher while genotype GC and allele C were lower in AD patients than controls. There was no significant difference in the frequencies of alleles and genotypes of TGF-β1 (509C/T) polymorphism between patient and control groups. These results showed that susceptibility to AD is influenced by presence or absence of genotypes of IFN-γ (874A/T) and IL-6 (174G/C) polymorphisms. It is concluded that T-allele and T-containing genotypes (AT+TT) of IFN-γ (874A/T) and G-allele and GG genotype ofIL-6 (174G/C) polymorphisms are susceptible to AD in Saudis.On the other hand, the TGF-β1 (509C/T) polymorphism may not be associated with AD risk in Saudi population however further studies with large sample size are required to confirm these findings.

Keywords: atopic dermatitis, interferon-γ, interleukin-6, transforming growth factor-β1, polymorphism

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Authors: L. K. Nivedha, V. Maruthapandian, R. Kothandaraman

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Rechargeable zinc-air batteries (ZAB) are gaining significant research attention owing to their high energy density and copious zinc resources worldwide. However, the unsolved obstacles such as dendrites, passivation, depth of discharge and the lack of an efficient cathode catalyst restrict their practical application1. By and large, non-noble transition metal-based catalysts are well-reputed materials for catalysing oxygen reduction reaction (ORR) and oxygen evolution reaction (OER) with greater stability in alkaline medium2. Herein, we report the synthesis and application of Mn₃O4-NiFeLDH/Carbon composite as a cathode catalyst for rechargeable ZAB. The synergetic effects of the mixed transition metals (Mn/Ni/Fe) have aided in catalysing ORR and OER in alkaline electrolyte with a shallow potential gap of 0.7 V. The composite, by its distinctive physicochemical characteristics, shows an excellent OER activity with a current density of 1.5 mA cm⁻² at a potential of 1.6 V and a superior ORR activity with an onset potential of 0.8 V when compared with their counterparts. Nevertheless, the catalyst prefers a two-electron pathway for the electrochemical reduction of oxygen which results in a limiting current density of 2.5 mA cm⁻². The bifunctional activity of the Mn₃O₄-NiFeLDH/Carbon composite was utilized in developing rechargeable ZAB. The fully fabricated ZAB delivers an open circuit voltage of 1.4 V, a peak power density of 70 mW cm⁻², and a specific capacity of 800 mAh g⁻¹ at a current density of 20 mA cm⁻² with an average discharge voltage of 1 V and the cell is operable upto 50 mA cm-2. Rechargeable ZAB demonstrated over 110 h at 10 mA cm⁻². Further, the cause for the diminished charge-discharge performance experienced beyond the 100th cycle was investigated, and carbon corrosion was testified using Infrared spectroscopy.

Keywords: rechargeable zinc-air battery, oxygen evolution reaction, bifunctional catalyst, alkaline medium

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Authors: Awan A. Zaima, Tanvieer Ayesha, Mirshahi Shahsoltan, Pocard Marc, Mirshahi Massoud

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Brain-derived neurotrophic factor (BDNF) is described as a factor helping to support the survival of existing neurons by involving the growth and differentiation of new neurons and synapses. Cancer diagnosis impacts the mental health, and in consequences, depression arise eventually hinders recovery and disrupts the quality of life and surviving chances of patients. The focus of this study is to hint upon a prospective biomarker as a promising diagnostic tool for an early indicator/predictor of depression prevalence in cancer patients for better care and treatment options. The study aims to analyze peripheral biomarkers from neuro immune axis (BDNF, IL21 as a NK cell activator) using co-relation approach. Samples were obtained from random non cancer candidates and advanced peritoneum carcinomatosis patients with 25% pseudomyxoma, 21% Colon cancer,19% stomach cancer, 10% ovarian cancer, 8% appendices cancer, and 10% other area of peritoneum cancer patients. Both groups of the study were categorized by gender and age, with a range of 18 to 86 years old. Biomarkers were analyzed in collected plasma by performing multiplex sandwich ELISA system. Data were subjected to statistical analysis for the assessment of the correlation. Our results demonstrate that BNDF and IL 21 down regulated significantly in patient groupas compared to non-cancer candidates (ratio of patients/normalis 2.57 for BNDF and 1.32 for IL21). This preliminary investigation suggested that the neuro immune biomarkers are down regulated in carcinomatosis patients and can be associated with cancer expansion and cancer genesis. Further studies on larger cohort are necessary to validate this hypothesis.

Keywords: biomarkers, depression, peritoneum carcinoma, BNDF, IL21

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Authors: S. Hussain, N. Ahmad, S. Alam, M. Bezabhi, W. H. Hendriks, P. Yu, J. W. Cone

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The high content of lignin in cell walls is the major limiting factor in the digestion and utilisation of cereal crop residues by ruminants. The aim of this study was to evaluate the effectiveness of the white rot fungus, Pleurotus ostreatus (P. ostreatus), to degrade lignin and to enhance the rumen degradability of maize stover, rice straw, wheat straw and their mixture in equal proportion on a dry-matter (DM) basis. Four samples of each substrate were incubated aerobically in triplicate with P. ostreatus for 0 (Control), 21, 28 and 35 days under solid-state conditions (temperature, 24 ͦ C; humidity, 70± 5%). The changes in chemical composition, DM and nutrient losses, and rumen fermentation characteristics using in vitro DM digestibility (DMD) and the in vitro gas production (GP) technique were measured. The results showed that incubation with P. ostreatus decreased (P < 0.001) the contents of neutral detergent fibre and lignin with a concomitant increase (P < 0.001) in the contents of ash and crude protein. The losses of nutrients differed (P < 0.001) among the straw types, with rice straw and maize stover showing the largest (P < 0.05) lignin degradation compared to wheat and mixed straws. The DMD and 72-h cumulative GP increased (P < 0.001) consistently with increasing fungal incubation period and for all substrates the highest values of DMD and GP were measured after 35 days of incubation with P. ostreatus. The lignin degradation was strongly associated with hemicellulose degradation (r = 0.71) across the various straws. Results of the present study demonstrated that incubation of low-quality crop residues with P. ostreatus under solid-state conditions upgrades their feeding value by reducing the content of lignin and increasing the content of crude protein and ruminal degradation.

Keywords: crop residues, lignin degradation, maize stovers, wheat straws, white rot fungi

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Authors: Kottaridi Klimentia, Demopoulos Vasilis, Sidiropoulos Anastasios, Ihara Diego, Nikolaidis Vasileios, Antonopoulos Dimitrios

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Aflatoxins are highly poisonous and carcinogenic compounds produced by species of the genus Aspergillus spp. that can infect a variety of agricultural foods, including dried figs. Biological and environmental factors, such as population, pathogenicity, and aflatoxinogenic capacity of the strains, topography, soil, and climate parameters of the fig orchards, are believed to have a strong effect on aflatoxin levels. Existing methods for aflatoxin detection and measurement, such as high performance liquid chromatography (HPLC), and enzyme-linked immunosorbent assay (ELISA), can provide accurate results, but the procedures are usually time-consuming, sample-destructive, and expensive. Predicting aflatoxin levels prior to crop harvest is useful for minimizing the health and financial impact of a contaminated crop. Consequently, there is interest in developing a tool that predicts aflatoxin levels based on topography and soil analysis data of fig orchards. This paper describes the development of a risk assessment tool for the contamination of aflatoxin on dried figs, based on the location and altitude of the fig orchards, the population of the fungus Aspergillus spp. in the soil, and soil parameters such as pH, saturation percentage (SP), electrical conductivity (EC), organic matter, particle size analysis (sand, silt, clay), the concentration of the exchangeable cations (Ca, Mg, K, Na), extractable P, and trace of elements (B, Fe, Mn, Zn and Cu), by employing machine learning methods. In particular, our proposed method integrates three machine learning techniques, i.e., dimensionality reduction on the original dataset (principal component analysis), metric learning (Mahalanobis metric for clustering), and k-nearest neighbors learning algorithm (KNN), into an enhanced model, with mean performance equal to 85% by terms of the Pearson correlation coefficient (PCC) between observed and predicted values.

Keywords: aflatoxins, Aspergillus spp., dried figs, k-nearest neighbors, machine learning, prediction

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Authors: Pratikno Hidayat, Khamdan Cahyari

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Hydrogen is the ultimate choice of energy carriers in future. It contents high energy density (42 kJ/g), emits only water vapor during combustion and has high energy conversion up to 50% in fuel cell application. One of the promising methods to produce hydrogen is from organic waste through dark fermentation method. It utilizes sugar-rich organic waste as substrate and hydrogen-producing microorganisms to generate the hydrogen. Solid waste of sago processing industries in Indonesia is one of the promising raw materials for both producing biofuel hydrogen and mitigating the environmental impact due to the waste disposal. This research was meant to investigate the effect of chemical and biological pretreatment i.e. acid treatment and mushroom cultivation toward lignocellulosic waste of these sago industries. Chemical pretreatment was conducted through exposing the waste into acid condition using sulfuric acid (H2SO4) (various molar i.e. 0.2, 0.3, and 0.4 M and various duration of exposure i.e. 30, 60 and 90 minutes). Meanwhile, biological treatment was conducted through utilization of the solid waste as growth media of mushroom (Oyster and Ling-zhi) for 3 months. Dark fermentation was conducted at pH 5.0, temperature 27℃ and atmospheric pressure. It was noticed that chemical and biological pretreatment could improve hydrogen yield with the highest yield at 3.8 ml/g VS (31%v H2). The hydrogen production was successfully performed to generate high percentage of hydrogen, although the yield was still low. This result indicated that the explosion of acid chemical and biological method might need to be extended to improve degradability of the solid waste. However, high percentage of hydrogen was resulted from proper pretreatment of residual sludge of biogas plant to generate hydrogen-producing inoculum.

Keywords: hydrogen, sago waste, chemical, biological, dark fermentation, Indonesia

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Authors: Umamaheswari Shanmugam, Silvia Ronchi

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Software, artificial intelligence, and machine learning can improve healthcare through innovative and advanced technologies that can use the large amount and variety of data generated during healthcare services every day; one of the significant advantages of these new technologies is the ability to get experience and knowledge from real-world use and to improve their performance continuously. Healthcare systems and institutions can significantly benefit because the use of advanced technologies improves the efficiency and efficacy of healthcare. Software-defined as a medical device, is stand-alone software that is intended to be used for patients for one or more of these specific medical intended uses: - diagnosis, prevention, monitoring, prediction, prognosis, treatment or alleviation of a disease, any other health conditions, replacing or modifying any part of a physiological or pathological process–manage the received information from in vitro specimens derived from the human samples (body) and without principal main action of its principal intended use by pharmacological, immunological or metabolic definition. Software qualified as medical devices must comply with the general safety and performance requirements applicable to medical devices. These requirements are necessary to ensure high performance and quality and protect patients' safety. The evolution and the continuous improvement of software used in healthcare must consider the increase in regulatory requirements, which are becoming more complex in each market. The gap between these advanced technologies and the new regulations is the biggest challenge for medical device manufacturers. Regulatory requirements can be considered a market barrier, as they can delay or obstacle the device's approval. Still, they are necessary to ensure performance, quality, and safety. At the same time, they can be a business opportunity if the manufacturer can define the appropriate regulatory strategy in advance. The abstract will provide an overview of the current regulatory framework, the evolution of the international requirements, and the standards applicable to medical device software in the potential market all over the world.

Keywords: artificial intelligence, machine learning, SaMD, regulatory, clinical evaluation, classification, international requirements, MDR, 510k, PMA, IMDRF, cyber security, health care systems

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Authors: Kristina Amaleviciute, Ieva Jokubauskaite, Alvyra Slepetiene, Jonas Volungevicius, Inga Liaudanskiene

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The main task of this research was to investigate the chemical composition of the differently used soil in profiles. To identify the differences in the soil were investigated organic carbon (SOC) and its fractional composition: dissolved organic carbon (DOC), mobile humic acids (MHA) and C to N ratio of natural and anthropogenically affected Luvisols. Research object: natural and anthropogenically affected Luvisol, Akademija, Kedainiai, distr. Lithuania. Chemical analyses were carried out at the Chemical Research Laboratory of Institute of Agriculture, LAMMC. Soil samples for chemical analyses were taken from the genetics soil horizons. SOC was determined by the Tyurin method modified by Nikitin, measuring with spectrometer Cary 50 (VARIAN) in 590 nm wavelength using glucose standards. For mobile humic acids (MHA) determination the extraction procedure was carried out using 0.1 M NaOH solution. Dissolved organic carbon (DOC) was analyzed using an ion chromatograph SKALAR. pH was measured in 1M H2O. N total was determined by Kjeldahl method. Results: Based on the obtained results, it can be stated that transformation of chemical composition is going through the genetic soil horizons. Morphology of the upper layers of soil profile which is formed under natural conditions was changed by anthropomorphic (agrogenic, urbogenic, technogenic and others) structure. Anthropogenic activities, mechanical and biochemical disturbances destroy the natural characteristics of soil formation and complicates the interpretation of soil development. Due to the intensive cultivation, the pH values of the curve equals (disappears acidification characteristic for E horizon) with natural Luvisol. Luvisols affected by agricultural activities was characterized by a decrease in the absolute amount of humic substances in separate horizons. But there was observed more sustainable, higher carbon sequestration and thicker storage of humic horizon compared with forest Luvisol. However, the average content of humic substances in the soil profile was lower. Soil organic carbon content in anthropogenic Luvisols was lower compared with the natural forest soil, but there was more evenly spread over in the wider thickness of accumulative horizon. These data suggest that the organization of geo-ecological declines and agroecological increases in Luvisols. Acknowledgement: This work was supported by the National Science Program ‘The effect of long-term, different-intensity management of resources on the soils of different genesis and on other components of the agro-ecosystems’ [grant number SIT-9/2015] funded by the Research Council of Lithuania.

Keywords: agrogenization, dissolved organic carbon, luvisol, mobile humic acids, soil organic carbon

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Authors: Ercan Karadogan, Fatih Usta

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Auxetic materials have a negative Poisson’s ratio (NPR), which is not often found in nature. They are metamaterials that have potential applications in many engineering fields. Mechanical metamaterials are synthetically designed structures with unusual mechanical properties. These mechanical properties are dependent on the properties of the matrix structure. They have the following special characteristics, i.e., improved shear modulus, increased energy absorption, and intensive fracture toughness. Non-auxetic materials compress transversely when they are stretched. The system naturally is inclined to keep its density constant. The transversal compression increases the density to balance the loss in the longitudinal direction. This study proposes to improve the crushing performance of hybrid auxetic materials. The re-entrant honeycomb structure has been combined with a star honeycomb, an S-shaped unit cell, a double arrowhead, and a structurally hexagonal re-entrant honeycomb by 9 X 9 cells, i.e., the number of cells is 9 in the lateral direction and 9 in the vertical direction. The Finite Element (FE) and experimental methods have been used to determine the compression behavior of the developed hybrid auxetic structures. The FE models have been developed by using Abaqus software. The specimens made of polymer plastic materials have been 3D printed and subjected to compression loading. The results are compared in terms of specific energy absorption and strength. This paper describes the quasi-static crushing behavior of two types of hybrid lattice structures (auxetic + auxetic and auxetic + non-auxetic). The results show that the developed hybrid structures can be useful to control collapse mechanisms and present larger energy absorption compared to conventional re-entrant auxetic structures.

Keywords: auxetic materials, compressive behavior, metamaterials, negative Poisson’s ratio

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Authors: Jin Hwan Cheong, Mina Hwang, Myung Hoon Han, Je Il Ryu, Young ha Oh, Seong Ho Koh, Wu Duck Won, Byung Jin Ha

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Leucine-rich repeat-containing G-protein coupled receptor 5 (LGR5) has been reported to play critical roles in the proliferation of various cancer cells. However, the roles of LGR5 in brain tumors and the specific intracellular signaling proteins directly associated with it remain unknown. Expression of LGR5 was first measured in normal brain tissue, meningioma, and pituitary adenoma of humans. To identify the downstream signaling pathways of LGR5, siRNA-mediated knockdown of LGR5 was performed in SH-SY5Y neuroblastoma cells followed by proteomics analysis with 2-dimensional polyacrylamide gel electrophoresis (2D-PAGE). In addition, the expression of LGR5-associated proteins was evaluated in LGR5-inꠓhibited neuroblastoma cells and in human normal brain, meningioma, and pituitary adenoma tissue. Proteomics analysis showed 12 protein spots were significantly different in expression level (more than two-fold change) and subsequently identified by peptide mass fingerprinting. A protein association network was constructed from the 12 identified proteins altered by LGR5 knockdown. Direct and indirect interactions were identified among the 12 proteins. HSP 90-beta was one of the proteins whose expression was altered by LGR5 knockdown. Likewise, we observed decreased expression of proteins in the hnRNP subfamily following LGR5 knockdown. In addition, we have for the first time identified significantly higher hnRNP family expression in meningioma and pituitary adenoma compared to normal brain tissue. Taken together, LGR5 and its downstream sigꠓnaling play critical roles in neuroblastoma and brain tumors such as meningioma and pituitary adenoma.

Keywords: LGR5, neuroblastoma, meningioma, pituitary adenoma, hnRNP

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Authors: Ezeugwunne Ifeoma Priscilla, Charles Chinedum Onyenekwe, Joseph Eberendu Ahaneku, Rosemary Adanma Analike, Adesuwa Peace Eidangbe

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This study was designed to assess the effect of malaria parasitaemia on serum reproductive hormone levels of asymptomatic HIV adult subjects. A total of 271 participants aged between 17 and 58 ears were conveniently recruited. 135 asymptomatic HIV-infected subjects participated in the study; 67 of them had malaria parasitaemia. 136 HIV seropositive control subjects, 68 of them had malaria parasitaemia. Blood samples were collected from the participants for the determination of HIV status by immunoassay and immunochromatography. Enzyme-linked immunosorbent assay (ELISA) was used to assay for serum LH, FSH, Estrogen, testosterone, progesterone, prolactin, and PSA levels, CD4+T cell counts by Cyflow method, thick and thin films determination of malaria parasitaemia count and density by WHO. Student's t-tests and ANOVA were used to compare means. P<0.05 was considered statistically significant. The results showed significant differences in serum levels of LH, FSH, PSA, estrogen, progesterone, and testosterone amongst the groups at P<0.05, respectively. The serum levels of LH, FSH, and PSA were significantly higher in malaria-infected asymptomatic HIV subjects than in asymptomatic HIV subjects with malaria parasitaemia (P<0.05 in each case). Also, the serum levels of LH, FSH, PSA, estrogen, and progesterone were significantly higher in malaria-infected asymptomatic HIV subjects compared with malaria-infected HIV seronegative subjects (P<0.05, respectively). The mean MP counts and MP density were significantly higher in asymptomatic HIV subjects compared to HIV seronegative subjects (P<0.05, in each case). The mean serum levels of testosterone were significantly lower in both malaria-infected and malaria uninfected HIV seronegative subjects (P<0.05, in each case). In conclusion, Malaria and HIV co-infection might increase the burden of hypogonadism as well as primary testicular failure, hyperprogesteronaemia, elevated levels of estrogen, and PSA in adult males asymptomatic HIV subjects.

Keywords: malaria parasitaemia, HIV, CD4, reproductive hormones

Procedia PDF Downloads 142

Authors: Alessio Varotto, Lorenzo Freschi, Umberto Pasqual Laverdura, Anastasia Moschovi, Davide Pumiglia, Iakovos Yakoumis, Marta Feroci, Maria Luisa Grilli

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Dry reforming of Methane (DRM) is considered one of the most valuable technologies for green-house gas valorization thanks to the fact that through this reaction, it is possible to obtain syngas, a mixture of H₂ and CO in an H₂/CO ratio suitable for utilization in the Fischer-Tropsch process of high value-added chemicals and fuels. Challenges of the DRM process are the reduction of costs due to the high temperature of the process and the high cost of precious metals of the catalyst, the metal particles sintering, and carbon deposition on the catalysts’ surface. The aim of this study is to demonstrate the feasibility of the synthesis of catalysts using a leachate solution containing Pt coming directly from the recovery of spent diesel oxidation catalysts (DOCs) without further purification. An unusual perovskite support for DRM, the BaCe₁₋ₓ₋ᵧZrₓGdᵧO₃ (BCZG) perovskite, has been chosen as the catalyst support because of its high thermal stability and capability to produce oxygen vacancies, which suppress the carbon deposition and enhance the catalytic activity of the catalyst. BCZG perovskite has been synthesized by a sol-gel modified Pechini process and calcinated in air at 1100 °C. BCZG supports have been impregnated with a Pt-containing leachate solution of DOC, obtained by a mild hydrometallurgical recovery process, as reported elsewhere by some of the authors of this manuscript. For comparison reasons, a synthetic solution obtained by digesting commercial Pt-black powder in aqua regia was used for BCZG support impregnation. Pt nominal content was 2% in both BCZG-based catalysts formed by real and synthetic solutions. The structure and morphology of catalysts were characterized by X-Ray Diffraction (XRD) and Scanning Electron Microscopy (SEM). Thermogravimetric Analysis (TGA) was used to study the thermal stability of the catalyst’s samples. Brunauer-Emmett-Teller (BET) analysis provided a high surface area of the catalysts. H₂-TPR (Temperature Programmed Reduction) analysis was used to study the consumption of hydrogen for reducibility, and it was associated with H₂-TPD characterization to study the dispersion of Pt on the surface of the support and calculate the number of active sites used by the precious metal. Dry reforming of methane (DRM) reaction, carried out in a fixed bed reactor, showed a high conversion efficiency of CO₂ and CH4. At 850°C, CO₂ and CH₄ conversion were close to 100% for the catalyst obtained with the aqua regia-based solution of commercial Pt-black, and ~70% (for CH₄) and ~80 % (for CO₂) in the case of real HCl-based leachate solution. H₂/CO ratios were ~0.9 and ~0.70 in the first and latter cases, respectively. As far as we know, this is the first pioneering work in which a BCGZ catalyst and a real Pt-containing leachate solution were successfully employed for DRM reaction.

Keywords: dry reforming of methane, perovskite, PGM, recycled Pt, syngas

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Authors: Claire B. Salvedia, Enrico P. Supangco, Francisco B. Eligado, Renato Sa Vega, Antonio A. Rayos

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The study was conducted to evaluate the effect of probiotic feeding on weight gain, blood biochemical and hematological indices of crossbred dairy goat kids. Sixteen (16) crossbred Anglo-Nubian x Saanen dairy goat kids, 3 to 4 months old, ranging from 19 to 23kg were randomly assigned into four treatments fed with 5x109 cfu/ml probiotic supplements; Treatment 1 – control; Treatment 2 – lactic acid bacteria (L. plantarum BS and P. acidilactici 3G3); treatment 3 – S. cerevisiae 2030; Treatment 4 – multi-strain probiotics (L. plantarum BS, P. acidilactici 3G3, and S.cerevisiae 2030). Feed ration provided daily for each of the experimental animals were composed of 1kg mixed concentrate feed ((Leucaena leucocephala dried leaves and pollard), and 4 kg fresh Pennisetum purpureum and Gliciridia sepium leaves (50:50). The experimental feeding trial lasted for 9 weeks. Result revealed that treatments fed with probiotics had significantly (P≤0.05) higher weight gain compared to the control. Significant effect on plasma urea nitrogen (PUN) and triglyceride were noted during 30th and 60th day of probiotic feeding. White blood cell counts were significantly affected by probiotic feeding during the 60th day. Concentrations of glucose and cholesterol remained unchanged throughout the experimental period. The findings suggests, under the condition of the experiment, that live probiotic feeding could have a significant role in improving weight gain and metabolism of crossbred dairy goat kids.

Keywords: probiotics, weight gain, blood biochemical indices, crossbred dairy goat kids

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Authors: Swathi Ganesan, Nalinda Somasiri, Rebecca Jeyavadhanam, Gayathri Karthick

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The COVID-19 crisis presents a substantial and critical hazard to worldwide health. Since the occurrence of the disease in late January 2020 in the UK, the number of infected people confirmed to acquire the illness has increased tremendously across the country, and the number of individuals affected is undoubtedly considerably high. The purpose of this research is to figure out a predictive machine learning archetypal that could forecast COVID-19 cases within the UK. This study concentrates on the statistical data collected from 31st January 2020 to 31st March 2021 in the United Kingdom. Information on total COVID cases registered, new cases encountered on a daily basis, total death registered, and patients’ death per day due to Coronavirus is collected from World Health Organisation (WHO). Data preprocessing is carried out to identify any missing values, outliers, or anomalies in the dataset. The data is split into 8:2 ratio for training and testing purposes to forecast future new COVID cases. Support Vector Machines (SVM), Random Forests, and linear regression algorithms are chosen to study the model performance in the prediction of new COVID-19 cases. From the evaluation metrics such as r-squared value and mean squared error, the statistical performance of the model in predicting the new COVID cases is evaluated. Random Forest outperformed the other two Machine Learning algorithms with a training accuracy of 99.47% and testing accuracy of 98.26% when n=30. The mean square error obtained for Random Forest is 4.05e11, which is lesser compared to the other predictive models used for this study. From the experimental analysis Random Forest algorithm can perform more effectively and efficiently in predicting the new COVID cases, which could help the health sector to take relevant control measures for the spread of the virus.

Keywords: COVID-19, machine learning, supervised learning, unsupervised learning, linear regression, support vector machine, random forest

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Authors: Minghui Zhang, Sirine Fkaier, Sabri Fernana, Svetlana Kiseleva, Denis Kiselev

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The real-time identification of bacteria and fungi is difficult because they emit much weaker signals than pollen. In 2020, Plair developed Rapid-E+, which extends abilities of Rapid-E to detect smaller bioaerosols such as bacteria and fungal spores with diameters down to 0.3 µm, while keeping the similar or even better capability for measurements of large bioaerosols like pollen. Rapid-E+ enables simultaneous measurements of (1) time-resolved, polarization and angle dependent Mie scattering patterns, (2) fluorescence spectra resolved in 16 channels, and (3) fluorescence lifetime of individual particles. Moreover, (4) it provides 2D Mie scattering images which give the full information on particle morphology. The parameters of every single bioaerosol aspired into the instrument are subsequently analysed by machine learning. Firstly, pure species of microbes, e.g., Bacillus subtilis (a species of bacteria), and Penicillium chrysogenum (a species of fungal spores), were aerosolized in a bioaerosol chamber for Rapid-E+ training. Afterwards, we tested microbes under different concentrations. We used several steps of data analysis to classify and identify microbes. All single particles were analysed by the parameters of light scattering and fluorescence in the following steps. (1) They were treated with a smart filter block to get rid of non-microbes. (2) By classification algorithm, we verified the filtered particles were microbes based on the calibration data. (3) The probability threshold (defined by the user) step provides the probability of being microbes ranging from 0 to 100%. We demonstrate how Rapid-E+ identified simultaneously microbes based on the results of Bacillus subtilis (bacteria) and Penicillium chrysogenum (fungal spores). By using machine learning, Rapid-E+ achieved identification precision of 99% against the background. The further classification suggests the precision of 87% and 89% for Bacillus subtilis and Penicillium chrysogenum, respectively. The developed algorithm was subsequently used to evaluate the performance of microbe classification and quantification in real-time. The bacteria and fungi were aerosolized again in the chamber with different concentrations. Rapid-E+ can classify different types of microbes and then quantify them in real-time. Rapid-E+ enables classifying different types of microbes and quantifying them in real-time. Rapid-E+ can identify pollen down to species with similar or even better performance than the previous version (Rapid-E). Therefore, Rapid-E+ is an all-in-one instrument which classifies and quantifies not only pollen, but also bacteria and fungi. Based on the machine learning platform, the user can further develop proprietary algorithms for specific microbes (e.g., virus aerosols) and other aerosols (e.g., combustion-related particles that contain polycyclic aromatic hydrocarbons).

Keywords: bioaerosols, laser-induced fluorescence, Mie-scattering, microorganisms

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Authors: Siddharth Ahuja, T. M. Muruganandam

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An analytical investigation is performed to study the unsteady response of a one-dimensional, non-linear dynamic shock system to external downstream pressure perturbations in a supersonic flow in a varying area duct. For a given pressure ratio across a wind tunnel, the normal shock's location can be computed as per one-dimensional steady gas dynamics. Similarly, for some other pressure ratio, the location of the normal shock will change accordingly, again computed using one-dimensional gas dynamics. This investigation focuses on the small-time interval between the first steady shock location and the new steady shock location (corresponding to different pressure ratios). In essence, this study aims to shed light on the motion of the shock from one steady location to another steady location. Further, this study aims to create the foundation of the Unsteady Gas Dynamics field enabling further insight in future research work. According to the new pressure ratio, a pressure pulse, generated at the exit of the tunnel which travels and perturbs the shock from its original position, setting it into motion. During such activity, other numerous physical phenomena also happen at the same time. However, three broad phenomena have been focused on, in this study - Traversal of a Wave, Fluid Element Interactions and Wave Interactions. The above mentioned three phenomena create, alter and kill numerous waves for different conditions. The waves which are created by the above-mentioned phenomena eventually interact with the shock and set it into motion. Numerous such interactions with the shock will slowly make it settle into its final position owing to the new pressure ratio across the duct, as estimated by one-dimensional gas dynamics. This analysis will be extremely helpful in the prediction of inlet 'unstart' of the flow in a supersonic engine intake and its prominence with the incoming flow Mach number, incoming flow pressure and the external perturbation pressure is also studied to help design more efficient supersonic intakes for engines like ramjets and scramjets.

Keywords: analytical investigation, compression and expansion waves, fluid element interactions, shock trajectory, supersonic flow, unsteady gas dynamics, varying area duct, wave interactions

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Authors: Austin Jiang, Richard M. Salmon, Nicholas W. Morrell, Wei Li

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BMP10 is highly expressed in the developing heart and plays essential roles in cardiogenesis. BMP10 deletion in mice results in embryonic lethality due to impaired cardiac development. In adults, BMP10 expression is restricted to the right atrium, though ventricular hypertrophy is accompanied by increased BMP10 expression in a rat hypertension model. However, reports of BMP10 activity in the circulation are inconclusive. In particular it is not known whether in vivo secreted BMP10 is active or whether additional factors are required to achieve its bioactivity. It has been shown that high-affinity binding of the BMP10 prodomain to the mature ligand inhibits BMP10 signaling activity in C2C12 cells, and it was proposed that prodomain-bound BMP10 (pBMP10) complex is latent. In this study, we demonstrated that the BMP10 prodomain did not inhibit BMP10 signaling activity in multiple endothelial cells, and that recombinant human pBMP10 complex, expressed in mammalian cells and purified under native conditions, was fully active. In addition, both BMP10 in human plasma and BMP10 secreted from the mouse right atrium were fully active. Finally, we confirmed that active BMP10 secreted from mouse right atrium was in the prodomain-bound form. Our data suggest that circulating BMP10 in adults is fully active and that the reported vascular quiescence function of BMP10 in vivo is due to the direct activity of pBMP10 and does not require an additional activation step. Moreover, being an active ligand, recombinant pBMP10 may have therapeutic potential as an endothelial-selective BMP ligand, in conditions characterized by loss of BMP9/10 signaling.

Keywords: bone morphogenetic protein 10 (BMP10), endothelial cell, signal transduction, transforming growth factor beta (TGF-B)

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Authors: Kayode A. Olaniyi, Adeola A. Ogunleye, Tola M. Osifeko

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Electric Vehicles (EV) appear to be gaining increasing patronage as a feasible alternative to Internal Combustion Engine Vehicles (ICEVs) for having low emission and high operation efficiency. The EV energy storage systems are required to handle high energy and power density capacity constrained by limited space, operating temperature, weight and cost. The choice of strategies for energy storage evaluation, monitoring and control remains a challenging task. This paper presents review of various energy storage technologies and recent researches in battery evaluation techniques used in EV applications. It also underscores strategies for the hybrid energy storage management and control schemes for the improvement of EV stability and reliability. The study reveals that despite the advances recorded in battery technologies there is still no cell which possess both the optimum power and energy densities among other requirements, for EV application. However combination of two or more energy storages as hybrid and allowing the advantageous attributes from each device to be utilized is a promising solution. The review also reveals that State-of-Charge (SoC) is the most crucial method for battery estimation. The conventional method of SoC measurement is however questioned in the literature and adaptive algorithms that include all model of disturbances are being proposed. The review further suggests that heuristic-based approach is commonly adopted in the development of strategies for hybrid energy storage system management. The alternative approach which is optimization-based is found to be more accurate but is memory and computational intensive and as such not recommended in most real-time applications.

Keywords: battery state estimation, hybrid electric vehicle, hybrid energy storage, state of charge, state of health

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Authors: Mohammed Jarrar, Shalini Behl, Nadia Shaheen, Abeer Fatima, Reem Nasab

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Skin aging is a slow multifactorial process influenced by both internal as well as external factors. Ultra-violet radiations (UV), diet, smoking and personal habits are the most common environmental factors that affect skin aging. Fat contents and fibrous proteins as collagen and elastin are core internal structural components. The direct influence of UV on elastin integrity and health is crucial on aging of skin by time. The deposition of abnormal elastic material is a major marker in a photo-aged skin. Searching for compounds that may protect against cutaneous photo-damage is highly valued. Retinoids and Alpha Hydroxy Acids protective and or repairing effects of UV have been endorsed by some researchers. For consolidating a better understanding of anti and protective effects of such anti-aging agents, we evaluated the combinatory effects of various dosages of lactic acid and retinol on the dermal fibroblasts elastin levels exposed to UV. The UV exposed cells showed significant reduction in the elastin levels. A combination of drugs with a higher concentration of lactic acid (30-35 mM) and a lower concentration of retinol (10-15mg/mL) showed to work better in enhancing elastin concentration in UV exposed cells. We assume this enhancement could be the result of increased tropo-elastin gene expression stimulated by retinol and lactic acid probably repaired the UV irradiated damage by enhancing the amount and integrity of the elastin fibers.

Keywords: alpha hydroxy acid, elastin, retinol, ultraviolet radiations

Procedia PDF Downloads 342