Cell System Research Articles

A STAND-ALONE HYBRID POWER SYSTEM BASED ON PV ENERGY AND HYDROGEN FUEL CELLS WITH ENERGY STORAGE SYSTEMS

This article is focused on the construction of a stand-alone residential 5-kW hybrid power system to feed different domestic loads at a typical house in Thi-Qar City, Iraq, including lighting loads, Table fan, Smartphone charger, TV, Microwave and Cooler. The stand-alone residential 5-kW hybrid power system consists of PV generator, PEMFC, storage batteries, Electrolyzer and hydrogen tank. The battery and hydrogen subsystem, composed of a fuel cell (FC), electrolyzer, and hydrogen storage tank, act as energy storage and support systems. The research in steps includes the design of the hybrid system. A program has been used in MATLAB to size system components in order to match the load of the site in the most cost-effective way. Evaluation of the economic feasibility of the same hybrid system when using a solar tracking system for photovoltaic cells. The simulation results demonstrate the hybrid system's ability to supply the required electrical energy to the loads, as well as the increase in hydrogen production when using the solar tracking system, which makes it possible to store excess hydrogen in the long term for later use when the photovoltaic energy decreases according to the seasons of the year.

Effect of Sub- Chronic Administration of Omeprazole on Hematological and Biochemical Parameters in Fischer Male Rats

Long-term use of proton pump inhibitors (PPIs) is believed to have various potential adverse events. Omeprazole is a part of PPIs most commonly prescribed worldwide; it irreversibly binds to the H+-K+ ATPase enzyme system in the gastric parietal cells to reduce the secretion of H+ ions into the lumen of the stomach. The main objective of the current work is to assess the adverse effects of omeprazole medication on certain hematological and biochemical parameters in rats who were on treatment for three months. We conducted a comparative cross-sectional study between March 2024 and July 2024. 20 male Fischer rats (Albino) aged two months, weighting (200-250g) was obtained from the animal house located in the Libyan center for medical research, in the city of Alzawia, and were enrolled in this study. Rats were divided into two groups, the first group was the control (Normal saline group) (n=10), second was administered 40mg/kg omeprazole via IP route (n=10) once daily. Complete blood count and biochemical parameters were measured for both groups. The treatment group had remarkably significant reductions in the number of red blood cells (RBCs) (p<0.001) and the platelets indices. Omeprazole elevated the cholesterol level (p<0.001) and triglyceride (p<0.001) as well as low-density lipoprotein (p<0.01). However, no impact was found with high density lipoprotein (HDL) (p>0.05). Blood urea levels (p<0.001) were significantly increased in the treatment group treated with omeprazole medication. The results also showed that the treatment group had a significant decline in calcium levels (p<0.001) than that of the control group. Prolonged use of omeprazole might result in adverse effects on hematological profile, particularly RBCs and their indices leading to the development of anemia in patients on this medication. Furthermore, it might result in disturbances in biochemical profile, levels of minerals, and vitamins as consequences of affected absorption.

Impact of Substrates, Volatile Fatty Acids, and Microbial Communities on Biohydrogen Production: A Systematic Review and Meta-Analysis

Hydrogen is becoming recognized as a clean and sustainable energy carrier, with microbial fermentation and electrolysis serving critical roles in its production. This paper provides a thorough meta-analysis of BioH2 production across diverse substrates, microbial populations, and experimental settings. Statistical techniques, including ANOVA, principal component analysis (PCA), and heatmaps, were used to evaluate the influence of various parameters on the hydrogen yield. The mean hydrogen generation from the reviewed studies was 168.57 ± 52.09 mL H2/g substrate, with food waste and glucose demonstrating considerably greater hydrogen production than mixed food waste (p < 0.05). The inhibition of methanogens with inhibitors like 2-bromoethanesulfonate (BES) and chloramphenicol (CES) enhanced hydrogen production by as much as 25%, as demonstrated in microbial electrolysis cell systems. PCA results highlighted Clostridium spp., Thermotoga spp., and Desulfovibrio spp. as the most dominant microbial species, with Clostridium spp. contributing up to 80% of the YH2 in fermentation systems. The study highlights synergistic interactions between dominant and less dominant microbial species under optimized environmental conditions (pH 5.5–6.0, 65 °C), emphasizing their complementary roles in enhancing H2 production. Volatile fatty acid regulation, particularly acetate and butyrate accumulation, correlated positively with hydrogen production (r = 0.75, p < 0.01). These findings provide insights into optimizing biohydrogen systems through microbial consortia management and substrate selection, offering a potential way for scalable and efficient H2 production.

Self-Tuning Oxygen Excess Ratio Control for Proton Exchange Membrane Fuel Cells Under Dynamic Conditions

Reasonable and effective control of a cathode air supply system is conducive to improving the dynamic response, operating efficiency, and reliability of fuel cell systems. This paper proposes a novel data-driven adaptive oxygen excess ratio (OER) control strategy based on online parameter identification for fuel cell systems. The proposed control scheme employs a second-order active disturbance rejection controller (ADRC) derived from the proportional-integral-derivative tuning rule to effectively deal with model uncertainties and external disturbances. Online parameter identification continuously translates the cathode air supply system into the second-order model, enabling the real-time adaptation of controller parameters to varying operating conditions. Simulation results demonstrate that the OER control strategy proposed significantly improves voltage stability and system efficiency under dynamic conditions compared to traditional methods. The innovation of this paper is that, based on consideration of the nonlinear slow time-varying characteristics of a PEMFC and the frequent disturbance of load current, adaptive control under system dynamic conditions can be considered. Combining the parameter identification scheme, an adaptive online self-tuning scheme is designed for the identified system model, which avoids the tediousness of a complex modeling process and has promotion value in practical applications.

A deep learning approach to predict differentiation outcomes in hypothalamic-pituitary organoids

We use three-dimensional culture systems of human pluripotent stem cells for differentiation into pituitary organoids. Three-dimensional culture is inherently characterized by its ability to induce heterogeneous cell populations, making it difficult to maintain constant differentiation efficiency. That is why the culture process involves empirical aspects. In this study, we use deep-learning technology to create a model that can predict from images of organoids whether differentiation is progressing appropriately. Our models using EfficientNetV2-S or Vision Transformer, employing VENUS-coupled RAX expression, predictively class bright-field images of organoids into three categories with 70% accuracy, superior to expert-observer predictions. Furthermore, the model obtained by ensemble learning with the two algorithms can predict RAX expression in cells without RAX::VENUS, suggesting that our model can be deployed in clinical applications such as transplantation.

Enhancing Energy Efficiency & Productivity With Solar Cells For Wifi Operations In Mining Are-as Pt Antareja Mahada Makmur Jobsite Mifa Ber-saudara (2024)

This improvement aims to evaluate the effectiveness of the use of solar cell systems in improving energy efficiency and WiFi network productivity in coal mining environments. The research method involves the installation of solar cell systems and the measurement of energy performance and productivity before and after implementation. The implementation of solar cell systems on WiFi networks in mining environments can improve energy efficiency and productivity. This study aims to analyze the influence of the implementation of solar cell systems on fossil energy use and environmental impact. The results show that the implementation of the solar cell system can reduce the use of fossil energy by 75% and reduce greenhouse gas emissions by 60%. The implementation of the solar cell system can also increase productivity by 25%. Therefore, the implementation of a solar cell system on a WiFi network in a mining operational environment is highly recommended. The results showed a significant improvement in the energy efficiency and stability of the WiFi network, which had a positive impact on operational productivity. The results of the study show that the use of solar cells can significantly reduce the consumption of electricity/fossil energy, as well as increase the availability of WiFi networks to support PT AMM's operational support activities. The implication of this study is the great potential of the use of solar energy to improve operational efficiency and reduce environmental impact.

Vector coding and place coding in hippocampus share a common directional signal

Vector coding is a major mechanism by which neural systems represent an animal’s location in both global and local, item-based reference frames. Landmark vector cells (LVCs) in the hippocampus complement classic place cells by encoding vector relationships between the organism and specific landmarks. How these place- and vector-coding properties interact is not known. We recorded place cells and LVCs using calcium imaging of the CA1 region of freely moving rats during cue-card rotation studies. Place fields rotated around the center of the platform to follow the cue rotation, whereas the fields of simultaneously recorded LVCs rotated by the same amount around the nearby landmarks. Some neurons demonstrated conjunctive coding of both classic place field properties and LVC properties. These results demonstrate that CA1 neurons employ a common directional input, presumably provided by the head direction cell system, to encode animals’ locations in both world-centered and landmark-centered reference frames.

Co-culture system of breast cancer and normal cells to investigate inflammation: using doxorubicin encapsulated in adipose-derived exosomes.

Doxorubicin (DOX) chemotherapy for breast cancer is an effective treatment option, but it also has disadvantages. Exosomes (EXOs) have safely and successfully transported DOX and reduced its adverse effects; however, its use is still being explored. In this study, a co-culture system of malignant and non-malignant breast cells was used to generate an in vitro model reflecting the in vivo cellular microenvironment, and the effects of this treatment were investigated by examining inflammatory genes. Extracellular matrices (EXOs) were extracted from mesenchymal stem cells derived from human adipose tissue by ultracentrifugation. Later, Western blotting, dynamic light scattering (DLS) and transmission electron microscopy methods were used to examine the properties of the EXO. DOX was encapsulated in the EXOs by sonication and the loading rate was measured by spectrophotometry. In the current study, a co-culture system was used to investigate the cytotoxic effects of free DOX and DOX encapsulated in EXOs (EXO-DOX) on various breast cell lines, including MCF-7, MCF-10A, MDA-MB-231, and A-MSC. Additionally, the expression levels of inflammatory cytokines (IL-1β, IL-6, IL-10, and TNF-α) were examined. Methylthiazolyldiphenyl-tetrazolium bromide assay demonstrated that free DOX showed the highest cytotoxicity against MCF-10A cells, followed by MCF-7 cells. Conversely, EXO-DOX indicated a greater effect on MCF-7 cells and had a lower IC50 compared to MDA-MB-231 cells. Free DOX significantly downregulated the expression of pro-inflammatory cytokines (IL-1β, IL-6, and TNF-α), particularly in MCF-7 and MCF-10A cells, while concurrently upregulating IL-10 expression. EXO-DOX induced a more significant alteration in cytokine expression than the control and free DOX treatment groups. The co-culture system revealed a synergistic effect of free DOX on cancer cells while simultaneously mitigating the toxic effects of DOX on normal cells. This study suggests that EXO-DOX has promising potential as a targeted drug delivery system that could potentially improve therapeutic efficacy and minimize off-target toxicity.

Construction and Isolation of Recombinant Vaccinia Virus by Homologous Recombination Using Fluorescent Protein Markers.

Genetic modification of vaccinia virus (VACV) is a fundamental and valuable research technique in elucidating the function of VACV genes, as well as the development as vaccine vectors for other infectious diseases, oncolytic therapeutics for cancers, and protein expression systems in mammalian cells. Because of the large size of poxvirus genome and noninfectious feature of the naked viral DNA, construction of recombinant VACV relies on intracellular homologous recombination between transfected DNA and replicating viral DNA in infected cells occurred in VACV infected cells. The efficiency of homologous recombination event for vaccinia virus is relatively low, and recombinant viruses only account for 0.1% of progeny viruses. Therefore, fluorescent protein markers are often included in the transfected DNA to facilitate the selection and screening of recombined viruses. Here we provide a detailed procedure for the design, generation, isolation, and detection of recombinant VACV by homologous recombination using fluorescent protein markers.

The Observation of Performance Trends by Numerical Simulation with Different Parameters in a Nonlinear Reversible Solid Oxide Cell System

The reversible solid oxide cell model is established by COMSOL Multiphysics® (version 5.4) software under multi-physics coupling. According to the governing equation, the simulations were conducted based on the same parameters for many control groups numerically. At the same time, a comparison of these results was involved. For the air electrode in SOFC mode, the performance of the fuel cell will increase with the increase in the porosity. For the fuel electrode in SOFC mode, the increase is much greater than the impact of the porosity. The design parameters compared in this simulation are used to simulate and analyze and predict fuel cell performance under different conditions. The design parameters related to the electrode microstructure are defined in this model as: porosity (electrode porosity), pore size (electrode internal average pore size), and permeability (electrode internal permeability).

Elevated levels of peripheral and central nervous system immune markers reflect innate immune dysregulation in autism spectrum disorder

BackgroundEvidence suggests dysregulated immune functions in the pathophysiology of Autism spectrum disorder (ASD), although specific immune mechanisms are yet to be identified. MethodsWe assessed circulating levels of 25 immune/neuroinflammatory markers in a large ASD sample (n = 151) and matched controls (n = 72) using linear models. In addition, we performed global brain transcriptomics analyses of relevant immune-related genes. We also assessed the expression and function of factors and pathway elements of the inflammasome system in peripheral blood mononuclear cells (PBMC) isolated from ASD and controls using in vitro methods. ResultsWe found higher circulating levels of IL-18 and adhesion factors (ICAM-1, MADCAM1) in individuals with ASD relative to controls. Consistent with this, brain levels of ICAM1 mRNA were also higher in ASD compared to controls. Furthermore, we found higher expression/activity of Caspase-1 and the inflammasome sensor NLRP3 in PBMCs in ASD, both at baseline and following inflammatory challenge. This corresponded with higher levels of secreted IL-18, IL-1β, and IL-8, as well as increased expression of adhesion factors following inflammasome activation in ASD PBMC cultures. Inhibition of the NLRP3-inflammasome rescued the observed immune phenotype in ASD in vitro. ConclusionOur results suggest a role for inflammasome dysregulation in ASD pathophysiology.

Mincle Maintains M1 Polarization of Macrophages and Contributes to Renal Aging Through the Syk/NF-κB Pathway.

Kidney is a classic organ undergoing senescence, and chronic inflammation has an important effect in cellular senescence. Mincle has been shown to be vital for maintaining the M1 phenotype of macrophages, but its role in regulating renal aging has yet to be explored. Young (2 months of age) and old (24 months of age) mice were used to analyze the changes of kidney damage during natural aging. Mice were subcutaneously injected with D-galactose (D-gal) to establish a renal aging model, and miR-6948-3p mimic and Mincle siRNA were administered via the tail vein every 3 days. Aged kidney and experimental aging kidney were characterized by decreased renal function and structural damage, and upregulated expression of senescence-related proteins and SPAP components. The ratio of M1 macrophages was increased in the aged kidney, and Mincle accumulated in the aged kidney macrophages. Administration of miR-6948-3p mimic or Mincle siRNA alleviated D-gal-induced renal senescence. LPS was used to induce M1 polarization of bone marrow-derived macrophages, and a coculture system of M1 macrophages and mouse renal tubular epithelial cells (TCMK-1) was established. Mincle was upregulated in LPS-induced M1 macrophages in vitro, and silencing Mincle in M1 macrophages attenuated M1 macrophage-induced TCMK-1 cell senescence. Mechanistically, Mincle was regulated by miR-6948-3p and maintained the M1 phenotype of macrophages through the Syk/NF-κB pathway. In conclusion, Mincle, posttranscriptionally suppressed by miR-6948-3p, modulated renal senescence by maintaining the phenotype of M1 macrophages through the Syk/NF-κB pathway.

Comprehensive Performance Evaluation and Advanced Exergy Analysis of the Low-Temperature Proton Exchange Membrane Fuel Cell and Spray Flash Desalination Coupled System

This study introduces an innovative integrated system comprising steam methanol-reforming, low-temperature proton exchange membrane fuel cell, and spray flash desalination. Through thorough performance and advanced exergy analyses of the system, crucial areas for enhancing components were identified. The findings demonstrate that raising the reforming temperature or increasing hydrogen utilization rates can notably enhance system efficiency. Furthermore, the LCOE increased by only 0.152＄/kWh, while CO2 emissions remained unchanged. Conventional exergy analysis reveals that exergy destruction attributed to fuel cell amount to 27.6% (13.26 kW) of total exergy destruction. Advanced exergy analyses indicate that fuel cell contribute significantly (10.23 kW) to endogenous exergy destruction, primarily due to internal factors. Furthermore, the order of contribution to the total exergy destruction within the system is identified as follows: LT-PEMFC, Combustor, and Reformer. These findings suggest that prioritizing the LT-PEMFC in efforts to enhance system efficiency is essential, followed by the burner and subsequently the reformer. These results highlighted the potential of the integrated system and suggested approaches for improving system efficiency and boosting component performance. Furthermore, the findings provided novel insights for advanced research on integrated systems that combined low-temperature proton exchange membrane fuel cell.

Investigation of vapor liquid equilibria for HFO-1336mzz(E) + HFC-1234ze(E) binary system by a novel developed cyclic-analytical apparatus

Hydrofluoroolefins (HFOs), which have excellent thermophysical properties and environmental performance, are considered as the most promising environmentally friendly alternatives to the currently used refrigerants. The vapor-liquid equilibrium (VLE) properties of fluids are the basis for the design and optimization of chemical separation and refrigeration systems. In this work, a high-precision and visual VLE experimental apparatus was developed based on the cyclic-analytical method. which mainly includes thermostatic bath, VLE cell, temperature and pressure measurement system, and gas chromatograph, etc. The expanded uncertainties of temperature, pressure, and composition measurement are 0.06 K, 0.0086 MPa, and 0.056 mole fraction, respectively. By measuring the VLE data of the known binary system and comparing it with the literature, the reliability and accuracy of the experimental apparatus were verified. The VLE data of HFO-1336mzz(E) + HFC-1234ze(E) were measured in the temperature range of 293.15 to 358.15 K. The experimental data were correlated with the Peng Robinson (PR) equation of state (EoS) combined with Mathias-Copeman alpha function (MC) and van der Waals (vdW) mixing rule (PRMC-vdW model) in order to adjust the binary interaction parameters (BIP). The VLE data was also compared with the PPR78 predictive model. The VLE investigation provides a basis for further research on the cycle performance of the mixed working fluid.

Performance Test of a Hydrogen-powered Solid Oxide Fuel Cell System and its Simulation for Vehicle Propulsion Application

Performance Test of a Hydrogen-powered Solid Oxide Fuel Cell System and its Simulation for Vehicle Propulsion Application

Optimizing Energy Efficiency and Emission Reduction: Leveraging the Power of Machine Learning in an Integrated Compressed Air Energy Storage-Solid Oxide Fuel Cell System

This research introduces a cutting-edge energy system that combines a solid oxide fuel cell (SOFC) with compressed air energy storage (CAES) to generate compressed air, electrical power, and heat. The system's performance was assessed and enhanced using regression-based machine learning models, concentrating on three main process variables: temperature, current density, and utilization factor. The machine learning models achieved impressive accuracy, with R-squared values greater than 98%, demonstrating their effectiveness in predicting system performance. The results from multi-objective optimization indicated that the ideal conditions for maximizing energy storage, efficiency, and minimizing emissions include a temperature of 973 K, a current density of 6,000 A/m2, and a utilization factor of 0.74. At these optimal parameters, the system reached an energy storage capacity of 28.12 cm3, an efficiency of 64.19%, and emissions of 274.04 kg/MWh. These results underscore the potential of the integrated SOFC-CAES system to tackle significant energy and environmental issues by enhancing energy efficiency, lowering emissions, and offering a sustainable approach to power generation. The findings from this study contribute to the development of hybrid energy systems and facilitate the transition to more sustainable and resilient energy frameworks.

Photo-Oxidation of Various Organic Compounds, Including Pollutants, by Europium (III) in Fuel Cell Systems

The ongoing anthropogenic climate crisis necessitates a reassessment of numerous technical domains, including the energy sector. An alternative to conventional fuel cells is provided by photo fuel cells, which possess at least one photoactive electrode (e.g., TiO2). However, it should be noted that such fuel cells are often constrained in terms of the range of potential fuels that can be utilized. Considering prior research on the distinctive photochemistry of europium, it was hypothesized hypothesis that a photocell based on the photo-oxidation of diverse organic compounds by trivalent europium might be theoretically feasible. As demonstrated in multiple experiments, it is feasible to construct and operate a fuel cell utilizing these diverse, straightforward substrates. In this context, peak powers of up to 14 μW have already been observed with the fuel cell described. It is noteworthy that an average electrical power of up to 6.28 μW was observed over a period of 168 h (7 days). Furthermore, it was demonstrated that simple alcohols (ethanol) could be completely oxidized with trivalent europium under suitable conditions. From various studies with different ethanol concentrations, it could be seen that a certain amount of water was needed to break down simple alcohols and organic compounds in general.

Laticifers as in vivo plant cell factories for therapeutic proteins

The demand for therapeutic proteins is growing annually. Novel approaches for the production of these molecules on a large scale are necessary, especially in plants. Plant laticifers could help provide an in vivo cell system for protein production expression that can reduce costs of production and downstream processing.

Quantitative analysis of fluid heat transfer behavior in a proton exchange membrane water electrolysis cell

The development of heat transfer models for proton exchange membrane water electrolysis (PEMWE) cells is necessary to enhance their efficiency, durability, and safety. Although modeling efforts have indicated that the heat transfer to fluids is significant, the magnitude of the heat transfer and mechanism have not been adequately studied. To fill this knowledge gap, we quantified the amounts of heat transferred in a thermally insulated cell and associated system. We found that heat transfer to the inflow water accounted for the majority of heat transfer to the fluids, and the rise of the membrane (CCM + PTL) temperature was due mainly to deterioration of the distribution of water at high current density. The sensible heat transfer and the resistive heat were directly proportional to each other, and the quantity of latent heat transfer could be influenced by resistive heating and kinetic factors. This study was the first to provide detailed experimental insights into the factors that mainly affect heat transfer to fluids in PEM water electrolysis cells.

Multi-objective hierarchical energy management strategy for fuel cell/battery hybrid power ships

The energy management strategy and the local controller in the ship energy management system are interconnected, impacting the performance of the hybrid propulsion system. To achieve the efficient operation of the hydrogen fuel cell (FC) and battery hybrid power system, based on the modelling and analysis of the hybrid power system, a nonlinear model predictive control (NMPC) based energy management strategy is proposed, and a dynamic virtual impedance droop controller and a classical proportional-integral (PI) controller are designed as local controllers. By simulating the designed random load conditions, pulse load conditions, and actual sailing conditions using hardware-in-the-loop (HiLs) technology, six different energy management strategies and their comprehensive performance with local controllers are compared and analysed. Comparing performance in terms of energy consumption, operating pressure, control accuracy, real-time performance, and robustness, it has been proven that the energy management strategy based on NMPC, coupled with a PI controller, is superior to other strategies overall. It can balance hydrogen consumption and the stable operation of the hybrid power system. Compared to existing energy management strategies, the proposed NMPC+PI strategy can reduce hydrogen consumption by 7.00 % and 40.29 %, and FC operating pressure by 44.96 % and 49.88 %, respectively, under both designed navigation conditions and actual navigation conditions.