Use Of Sources Research Articles

Navigating the infodemic through digital health literacy education in schools

Abstract Background High digital health literacy (DHL) can help to navigate the internet’s vast information landscape. This research explores the impact of learning DHL in schools on students’ DHL, and how it might mitigates confusion surrounding health-related information. Moreover, this research sheds light on how learning DHL in schools influences students’ inclinations towards specific sources of health information. Methods 1448 secondary school students aged 9-18 years participated in face-to-face interviews. Associations between learning digital health literacy (DHL) and students’ DHL, comprehension of health information, sense of being informed on health topics, and utilization of diverse health information sources were evaluated using the chi-squared test. Results The learning of DHL within school settings demonstrated a significant correlation with students’ overall DHL (X2 (6) = 120.99, p < .001). Those reporting high levels of DHL learning exhibited reduced confusion regarding health information (X2 (4) = 16.65, p = .002) and felt notably more informed (X2 (4) = 231.06, p < .001). Contrasted with peers who reported insufficient learning of DHL, students with high learning reported learning more about health from parents (X2 (2) = 55.28, p < .001), peer interactions (X2 (2) = 214.51, p < .001), online sources (X2 (2) = 78.54, p < .001), influencer content (X2 (2) = 68.46, p < .001), offline literature (X2 (2) = 24.32, p < .001), television (X2 (2) = 140.36, p < .001), and in school (X2 (2) = 205.53, p < .001). However, they were less reliant on physicians for health information (X2 (2) = 53.62, p < .001). Conclusions Integrating DHL into school curricula holds promise for enhancing students’ DHL and alleviating apprehensions regarding health-related information. Moreover, such educational initiatives have the potential to expand students’ repertoire of resources for accessing health information, encompassing both digital and non-digital sources.

Effects of plastic film mulching on soil microbial carbon metabolic activity and functional diversity at different maize growth stages in cool, semi-arid regions

IntroductionPlastic film mulching has been widely used to enhance soil hydrothermal conditions and increase crop yields in cool, semi-arid areas. However, its impact on soil microbial carbon metabolic activity and functional diversity during plant growth remains unclear despite their important roles in nutrient cycling and soil quality evaluation.MethodsThis study used the Biolog EcoPlate technique to investigate the dynamics and driving factors of soil microbial carbon metabolic activity and functional diversity at different maize growth stages following plastic film mulching.Results and discussionThe results revealed that film mulching significantly increased microbial carbon metabolic activities [represented by average well color development (AWCD)] by 300% at the seedling stage and by 26.8% at maturity but decreased it by 47.4% at the flowering stage compared to the control (without mulching). A similar trend was observed for the microbial functional diversity index. Redundancy analysis identified soil moisture (SM), soil temperature (ST), dissolved organic carbon (DOC), microbial biomass carbon (MBC), and bacteria amounts as the primary factors influencing changes in soil microbial carbon source utilization. The mulch treatment significantly increased SM at all growth stages, while its warming effect disappeared at the flowering stage. Soil DOC, MBC, and bacterial populations were notably higher under mulching at the seedling and maturity stages but lower at the flowering stage. Pearson correlation analysis showed that changes in SM, ST, DOC, MBC, and bacterial populations positively correlated with the utilization of all carbon source classes, AWCD, and functional diversity indexes after film mulching. Furthermore, maize grain yield and water use efficiency increased by 142 and 129%, respectively, following film mulching. In conclusion, plastic film mulching enhanced soil microbial carbon metabolic activity and functional diversity at the seedling and maturity stages, improving crop yields in cool, semi-arid areas. Furthermore, the decrease in soil carbon metabolic capacity at flowering stage highlights that supplementing soil carbon sources should be considered after continuous film mulching to sustain or enhance farmland productivity and soil quality.

Assessing the Damage to Environmental Pollution: Discerning the Impact of Environmental Technology, Energy Efficiency, Green Energy and Natural Resources

The existing literature covers the topic of environmental pollution, but there is a scarcity of research that specifically examines the factors contributing to financial losses caused by carbon emissions. In this perspective, this ongoing analysis provides an understanding of the impact of environmental technology, energy efficiency, renewable energy consumption, natural resources, and economic growth on carbon dioxide damage in Organization for Economic Cooperation and Development (OECD) countries from 2000 to 2021 using the “Method of Moments Quantile Regression (MMQR)”, and “Dumitrescu–Hurlin (D-H)” causality test. The findings from the MMQR revealed that environmental control technology, renewable energy consumption, and energy efficiency contribute to reducing carbon dioxide damage at different quantiles. It was also found that economic growth and natural resources contribute to the increase in carbon dioxide damage in various quantities. Additionally, a one-way causality result was obtained from environmental technology, energy efficiency, renewable energy consumption, natural resources, and economic growth towards carbon dioxide damage. These results indicate that policymakers in OECD nations should provide suggestions on the efficient utilization of renewable energy sources and environmentally friendly technologies to minimize carbon dioxide damage.

Single-Shot Fringe Projection Profilometry Based on LC-SLM Modulation and Polarization Multiplexing

Fringe projection profilometry (FPP) is extensively utilized for the 3D measurement of various specimens. However, traditional FPP typically requires at least three phase-shifted fringe patterns to achieve a high-quality phase map. In this study, we introduce a single-shot FPP method based on common path polarization interferometry. In our method, the projected fringe pattern is created through the interference of two orthogonal circularly polarized light beams modulated by a liquid crystal spatial light modulator (LC-SLM). A polarization camera is employed to capture the reflected fringe pattern, enabling the simultaneous acquisition of four-step phase-shifting fringe patterns. The system benefits from advanced anti-vibration capabilities attributable to the common path self-interference optical path design. Furthermore, the utilization of a low-coherence LED light source results in reduced noise levels compared to a laser light source. The experimental results demonstrate that our proposed method can yield 3D measurement outcomes with high accuracy and efficiency.

PV- Battery Based AC/DC Hybrid Multiport Power Routing System

The utilization of renewable energy sources has significantly increased as a result of growing environmental concerns and the depletion of traditional energy sources. One clean and sustainable energy source that has gained popularity among them is photovoltaic (PV) systems. Batteries and other energy storage devices are necessary to offer a steady and dependable power source, though, because PV energy is sporadic. Effective power flow control and a dependable power supply are demonstrated by the test results. By reducing dependency on traditional sources and supporting clean and sustainable energy, this adaptable and scalable solution is suitable for residential, commercial, and industrial environments. An AC/DC hybrid multiport power routing system based on PV batteries is shown in this project to solve this problem. The battery bank, power routing unit, and PV array that make up the suggested system. keywords: PV panels, batteries, inverters, and a microcontroller-based power routing unit.

Testing the Stability of NASICON Solid Electrolyte in Seawater Batteries

Rechargeable batteries play a crucial role in the utilization of renewable energy sources. Energy storage systems (ESSs) are designed to store renewable energy efficiently for immediate use. The market for energy storage systems heavily relies on lithium-ion batteries due to their high energy density, capacity, and competitiveness. However, the increasing cost and limited availability of lithium make long-term use challenging. As an alternative to Li-ion batteries, rechargeable seawater batteries are gaining attention due to their abundant and complementary sodium ion active materials. This study focuses on the preparation and characterization of Na3.0Zr2Si2PO12- and Na3.15Zr2Si2PO12-type ceramic membranes and testing their stability in seawater batteries used as solid electrolyte. From the surface analysis, it was observed that the Na3.15Zr2Si2PO12 powder showed a specific surface area of 2.94 m2/g compared to 2.69 m2/g for the Na3.0Zr2Si2PO12 powder. The measured NASICON samples achieved ionic conductivities between 7.42 × 10−5 and 4.4 × 10−4 S/cm compared to the NASICON commercial membrane with an ionic conductivity of 3.9 × 10−4 S/cm. Battery testing involved charging/discharging at various constant current values (0.6–2.0 mA), using Pt/C as the catalyst and seawater as the catholyte.

Molecular simulations of increased thermal energy storage in metal–organic heat carriers with R1234ze(E)/R32 mixtures combined with IRMOF-1

Metal-organic heat carrier (MOHC) nanofluids offer a promising solution to enhance the efficiency of Organic Rankine Cycle systems. In this study, we developed a computational model to assess the thermal energy storage capacity of MOHC nanofluids using a base fluid mixture of R1234ze(E) and R32 refrigerants. Through Grand Canonical Monte Carlo and molecular dynamics simulations, we examined the adsorption characteristics, desorption heat, and thermodynamic properties of MOHCs. Our findings reveal that R32 molecules are preferentially adsorbed in IRMOF-1 compared to R1234ze(E), with adsorption selectivity of R32 over R1234ze(E) increasing under higher adsorption pressures. When the temperature during the endothermic process surpasses the phase transition point of the base fluid, the latent heat of phase transition can be fully exploited to enhance energy storage. Moreover, the inclusion of IRMOF-1 nanoparticles significantly improves the energy storage properties of both R32 and R1234ze(E), as well as their mixtures. The energy storage enhancement provided by IRMOF-1 is particularly pronounced under high working pressures and low temperature differences. These insights offer valuable guidance for selecting appropriate base fluids in MOHC systems, thereby optimizing the utilization of low-grade energy sources.

Resource sharing of an infant gut microbiota synthetic community in combinations of human milk oligosaccharides.

Quickly after birth, the gut microbiota is shaped via species acquisition and resource pressure. Breastmilk, and more specifically, human milk oligosaccharides are a determining factor in the formation of microbial communities and the interactions between bacteria. Prominent human milk oligosaccharide degraders have been rigorously characterized, but it is not known how the gut microbiota is shaped as a complex community. Here, we designed BIG-Syc, a synthetic community of 13 strains from the gut of vaginally born, breastfed infants. BIG-Syc replicated key compositional, metabolic, and proteomic characteristics of the gut microbiota of infants. Upon fermentation of a 4 and 5 human milk oligosaccharide mix, BIG-Syc demonstrated different compositional and proteomic profiles, with Bifidobacterium infantis and Bifidobacterium bifidum suppressing one another. The mix of 5 human milk oligosaccharides resulted in a more diverse composition with dominance of B. bifidum, whereas that with 4 human milk oligosaccharides supported the dominance of B. infantis, in 4 of 6 replicates. Reintroduction of bifidobacteria to BIG-Syc led to their engraftment and establishment of their niche. Based on proteomics and genome-scale metabolic models, we reconstructed the carbon source utilization and metabolite and gas production per strain. BIG-Syc demonstrated teamwork as cross-feeders utilized simpler carbohydrates, organic acids, and gases released from human milk oligosaccharide degraders. Collectively, our results showed that human milk oligosaccharides prompt resource-sharing for their complete degradation while leading to a different compositional and functional profile in the community. At the same time, BIG-Syc proved to be an accurate model for the representation of intra-microbe interactions.

Unveiling the importance of heterotrophy for coral symbiosis under heat stress.

Global warming endangers reef-building corals as they lose their photosynthetic symbionts, which limits their ability to feed autotrophically. Consequently, heterotrophy, the capture of zooplankton, can become crucial for the energy budget of heat-stressed corals. However, it is difficult to assess the extent of the heterotrophic contribution in corals, as well as the dynamics of nutrient exchange between the host and its symbionts. In this pioneering study, we employed a suite of isotopic markers, including 13C- and 15N bulk tissue isotope measurements, compound-specific isotope analysis of amino acids (CSIA-AAs), and 13C- and 15N-labeled food incubations, to investigate nutrient acquisition and allocation in the coral Stylophora pistillata under controlled and heat-induced bleaching conditions. Bulk isotope values and inorganic carbon assimilation remained unchanged in the bleached corals compared to the control corals, overall indicating undisturbed autotrophic activity of the symbionts under heat stress. However, CSIA-AAs showed an increased dependence on heterotrophy for amino acid synthesis in both the host and the symbionts despite reduced assimilation of 15N-labeled food. Overall, these results suggest that although S. pistillata reduces its assimilation of heterotrophic food under heat stress, the acquisition of amino acids by the coral host and symbionts still relies on heterotrophy. This study emphasizes the importance of using multiple indicators to gain a comprehensive understanding of coral nutrition. It shows that coral dependence on heterotrophy is not only associated with a decline in autotrophic availability. Rather, it demonstrates the ability of S. pistillata to adapt its utilization of food sources to the prevailing environmental conditions.IMPORTANCEThis work highlights that every isotopic marker displays a piece of different information concerning the diet of the model coral S. pistillata. By combining all markers, we observed that although S. pistillata exhibited reduced heterotrophic assimilation under heat stress, amino acid acquisition and synthesis remained dependent on heterotrophy. The findings emphasize the adaptability of corals in utilizing different food sources, which is vital for their resilience and recovery in changing environmental conditions. This research underscores the complexity of coral symbiosis and highlights the need for multiple indicators to understand dietary dynamics comprehensively.

Application of a GIS-Based Multi-Criteria Decision-Making Approach to the Siting of Ocean Thermal Energy Conversion Power Plants: A Case Study of the Xisha Sea Area, China

In order to achieve the goals of carbon neutrality and reduced carbon emissions, China is increasingly focusing on the development and utilization of renewable energy sources. Among these, ocean thermal energy conversion (OTEC) has the advantages of small periodic fluctuations and large potential reserves, making it an important research field. With the development of the “Maritime Silk Road”, the Xisha Islands in the South China Sea will see a growing demand for electricity, providing the potential for OTEC development in this region. Optimal site selection of OTEC power plants is a prerequisite for developing thermal energy provision, affecting both the construction costs and future benefits of the power plants. This study establishes a scientific evaluation model based on the decision-making frameworks of geographic information systems (GISs) and multi-criteria decision-making (MCDM) methods, specifically the analytic hierarchy process (AHP) for assigning weights, the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) to reclassify the factors, and weighted linear combination (WLC) to compute the suitability index. In addition to commonly considered factors such as temperature difference and marine usage status, this study innovatively incorporates geological conditions and maximum offshore distances of cold seawater based on cost control. The final evaluation identifies three suitable areas for OTEC development near the Xuande Atoll and the Yongle Atoll in the Xisha Sea Area, providing valuable insights for energy developers and policymakers.

Preference for water sources and agricultural utilisation among rural households: a case of Akoko district of Ondo State, Nigeria

The increasing challenge of freshwater scarcity amid rising demand and diminishing availability has led to a critical issue threatening sustainable development, especially in rural areas of developing countries like Nigeria. Despite the abundance of studies on rural water use, gaps remain in understanding the interplay between socio-economic factors, and agricultural practices in shaping these preferences and utilisation. Thus, the study investigates the preference for water sources and their utilisation in agricultural activities among rural households in the Akoko district of Ondo State, Nigeria. Cross-sectional data from randomly sampled 240 rural households were collected with the aid of a questionnaire, and employed for the data analysis. Descriptive statistics, logit, and multinomial regressions were used for the data analysis. The findings revealed a dominant preference for rainwater and well water. Factors such as access to safe water sources, time spent, extension service, technology adoption, soil type, experience, and proximity to water sources significantly influence the choice of water source utilization in the area using multinomial logit regression. Again, the results from logit regression revealed that water source, technology adoption, soil type, fish farming, crop farming, farming experience, and distance to water sources significantly affect the use of water for agricultural purposes. Therefore, the policy should enhance water access, consider soil characteristics in agricultural planning, and facilitate knowledge transfer among farmers for optimal water use, recognizing the symbiotic relationship between water access and agricultural sustainability.

Automating Systematic Literature Reviews with Retrieval-Augmented Generation: A Comprehensive Overview

This study examines Retrieval-Augmented Generation (RAG) in large language models (LLMs) and their significant application for undertaking systematic literature reviews (SLRs). RAG-based LLMs can potentially automate tasks like data extraction, summarization, and trend identification. However, while LLMs are exceptionally proficient in generating human-like text and interpreting complex linguistic nuances, their dependence on static, pre-trained knowledge can result in inaccuracies and hallucinations. RAG mitigates these limitations by integrating LLMs’ generative capabilities with the precision of real-time information retrieval. We review in detail the three key processes of the RAG framework—retrieval, augmentation, and generation. We then discuss applications of RAG-based LLMs to SLR automation and highlight future research topics, including integration of domain-specific LLMs, multimodal data processing and generation, and utilization of multiple retrieval sources. We propose a framework of RAG-based LLMs for automating SRLs, which covers four stages of SLR process: literature search, literature screening, data extraction, and information synthesis. Future research aims to optimize the interaction between LLM selection, training strategies, RAG techniques, and prompt engineering to implement the proposed framework, with particular emphasis on the retrieval of information from individual scientific papers and the integration of these data to produce outputs addressing various aspects such as current status, existing gaps, and emerging trends.

Enhancing Energy Harvesting Efficiency from Ambient Sources through Advanced Materials and Nanotechnology

The utilization of ambient energy sources for powering small-scale electronic devices and sensors has garnered significant attention due to its potential for sustainable and autonomous operation. This research focuses on enhancing the efficiency of energy harvesting from ambient sources, such as vibrations, heat differentials, and electromagnetic fields, through the integration of advanced materials and nanotechnology into energy harvesting systems. The study begins with a comprehensive review of existing energy harvesting technologies, highlighting their limitations in terms of efficiency, scalability, and adaptability to various ambient energy sources. It identifies the key challenges faced in achieving high energy conversion rates and explores the potential of advanced materials and nanoscale structures to address these challenges. One aspect of the research involves the development and characterization of novel materials with superior energy conversion properties. This includes the synthesis of piezoelectric materials for vibration energy harvesting, thermoelectric materials for heat-to-electricity conversion, and nanomaterials for enhancing electromagnetic energy harvesting efficiency. Advanced characterization techniques, such as scanning electron microscopy (SEM) and X-ray diffraction (XRD), are employed to analyze the structural and electrical properties of these materials. Furthermore, the study investigates the design and fabrication of nanostructured energy harvesting devices optimized for specific ambient energy sources. This involves the integration of nanoscale components, such as nanostructured electrodes, into energy harvesting systems to improve energy capture and conversion rates. Finite element analysis (FEA) simulations and experimental testing are conducted to evaluate the performance and efficiency of these nano-enhanced energy harvesting devices under real-world conditions. The research also addresses the optimization of energy harvesting system parameters, including resonance tuning, impedance matching, and energy management circuits, to maximize energy extraction and utilization. Computational modeling techniques, such as multiscale modeling and finite element simulations, are utilized to optimize system configurations and improve overall energy harvesting efficiency. Overall, this research contributes to the advancement of energy harvesting technologies by leveraging advanced materials and nanotechnology, paving the way for sustainable and autonomous power generation from ambient energy sources for a wide range of applications.

Screening and functional characterization of isocitrate lyase AceA in the biofilm formation of Vibrio alginolyticus.

Biofilm is a well-known sessile lifestyle for bacterial pathogens, but a little is known about the mechanism on biofilm formation in Vibrio alginolyticus. In this study, we screened V. alginolyticus strains with strong biofilm formation ability from coastal seawater. The antibiotic resistance of the biofilm cells (BFs) was higher than that of the planktonic cells (PTs). To study the genes and pathways involved in biofilm formation, we performed transcriptome analysis of the BFs and PTs of V. alginolyticus R9. A total of 685 differentially expressed genes (DEGs) were upregulated, and 517 DEGs were downregulated in the BFs. The upregulated DEGs were significantly enriched in several pathways including glyoxylate and dicarboxylate metabolism, while the downregulated genes were significantly enriched in the flagellar assembly pathways. The key gene involved in glyoxylate shunt, aceA, was cloned, and ΔaceA mutant was constructed to determine the function of AceA in carbon source utilization, biofilm formation, and virulence. Real-time reverse transcription PCR showed that the expression of aceA was higher at the mature stage but lower at the disperse stage of biofilm formation, and the expression of the flagellar related genes was upregulated in ΔaceA. This is the first study to illustrate the global gene expression profile during the biofilm formation of V. alginolyticus, and isocitrate lyase AceA, the key enzyme involved in glyoxylate shunt, was shown to maintain biofilms accompanied by downregulation of flagellation but promoted dispersal of BFs at the late stage.IMPORTANCEBiofilms pose serious public problems, not only protecting the cells in it from environmental hazard but also affecting the composition and abundance of bacteria, algae, fungi, and protozoa. The important opportunistic pathogen Vibrio alginolyticus is extremely ubiquitously present in seawater, and it also exhibited a strong ability to form biofilm; thus, investigation on the biofilm formation of V. alginolyticus at molecular level is fundamental for the deeper exploration of the environmental concerns arose by biofilm. In this study, transcriptome analysis of biofilm cells (BFs) and planktonic cells (PTs) from V. alginolyticus was performed and AceA was screened to play an important role in biofilm formation. AceA was shown to maintain biofilms accompanied by downregulation of flagellation but promoted dispersal of BFs at the disperse stage. This method was helpful to further understand the ability and mechanism of V. alginolyticus biofilm formation and provide clues for prevention of V. alginolyticus infection.

Estimation of SAM for India: An Application for India’s Energy Transition Targets

The social accounting matrix (SAM) for India was historically constructed based on the input–output table (IOT). However, since 2011–2012, the Government of India has been publishing the supply–use table, instead of the IOT. While the erstwhile IOT, published by the Government of India, had the same number of products and industries, the supply–use table provides one ‘supply matrix’ and one ‘use matrix’, each of which is a rectangular table with 140 products and 66 industries (for 2018–2019). Converting the supply–use table to a square IOT and subsequently extending it to SAM require the utilisation of various data sources, numerous steps and adjustments. Despite the usefulness of both IO and SAM matrices in macroeconomic policy design, not much literature is available on these. This study aims to bridge the gap by constructing IOT and SAM for India from the supply–use table incorporating information from many other sources and describing the method of construction of the matrices. Our IO and SAM also focus on various energy sectors, including different sources of power generation, biomass and so on, and disaggregate energy-intensive sectors like cement or aluminium, considering the immense usefulness of the energy-extended macro-structure to the research of energy and environment policies. The study focuses on the construction of a 59 × 59 SAM for India, with the base year of 2021–2022 incorporating three factors of production and ten categories of households. As an application of the newly constructed SAM, we have analysed the employment implication of India’s Nationally Determined Contribution emission commitments. JEL Codes: E16, C67, D57

Thermal energy and thermo-economic analysis of PCM-TES for space heating based on low-temperature waste heat: An experimental and numerical study

Great potential for using low-temperature waste heat for energy savings has been revealed in recent years. In this study, a novel PCM-TES unit integrated into a fresh air system was proposed to effectively utilize low-temperature waste heat to address shortcomings of preheating outdoor air for space heating. An experimental setup was built to investigate the heat storage and release performance of proposed unit. Well-validated CFD simulations further parametrically studied PCM thermal characteristics to HTF’s velocity and temperature changes. Energy and thermo-economic analyses were employed to evaluate unit potentials across three Chinese cities with different climate zones. The results showed that charging process was completed in 142–253 min at water temperatures of 55–60 °C; discharging process efficiency increased by 36.10% as the air velocity increased from 2 to 4 m/s. EPI revealed that, theoretically, the system could handle up to 28.2% of the heating demand. Energy and economic analysis indicated the system’s significant potential in colder climates, with Harbin achieving average energy savings of 7.93% and 13.48% over Qingdao and Chongqing, respectively, and cost savings up to 67.65% and 229.61% compared to those cities. This study is expected to shed light on the utilization of low-temperature waste sources for indoor space heating.

Breaking the Pt Electron Symmetry and OH Spillover towards PtIr Active Center for Performance Modulation in Direct Ammonia Fuel Cell.

The growing interest in low-temperature direct ammonia fuel cells (DAFCs) arises from the utilization of a carbon-neutral ammonia source; however, DAFCs encounter significant electrode overpotentials due to the substantial energy barrier of the *NH2 to *NH dehydrogenation, compounded by the facile deactivation by *N on the Pt surface. In this work, a unique catalyst, Pt4Ir@AlOOH/NGr i.e., Pt4Ir/ANGr, is introduced composed of PtIr alloy nanoparticles controllably decorated on the pseudo-boehmite phase of AlOOH-supported nitrogen-doped reduced graphene (AlOOH/NGr) composite, synthesized via the polyol reduction method. The detailed studies on the structural and electronic properties of the catalyst by XAS and VB-XPS reveal the possible electronic modulations. The optimized Pt4Ir/ANGr composition exhibits a significantly improved onset potential and mass activity for AOR. The DFT study confirms the OHad species spillover by AlOOH and Pt4Ir (100) facilitates the conversion of the *NH2 to *NH with minimal energy barriers. Finally, testing of DAFC at the system level using a membrane electrode assembly (MEA) with Pt4Ir/ANGr as the anode catalyst, demonstrating the suitability of the catalyst for its practical applications. This study thus uncovers the potential of the Pt4Ir catalyst in synergy with ANGr, largely addressing the challenges in hydrogen transportation, storage, and safety within DAFCs.

Avoiding overflow metabolite formation in Komagataella phaffii fermentations to enhance recombinant protein production

BackgroundKomagataella phaffii (K. phaffii), formerly known as Pichia pastoris, is a widely utilized yeast for recombinant protein production. However, due to the formation of overflow metabolites, carbon yields may be reduced and product recovery becomes challenging. This study investigates the impact of oxygen availability, different glucose concentrations and feeding strategies on overflow metabolite formation and recombinant protein production in K. phaffii.ResultsHigh glucose concentrations in batch fermentation, as applied in literature, lead to substantial ethanol accumulation, adversely affecting biomass yield and product formation. Increasing dissolved oxygen setpoints does not significantly reduce ethanol formation, indicating that glucose surplus, rather than oxygen availability, drives overflow metabolism. Decreasing the initial glucose concentration to 5 g/L and adapting the feeding strategy of the fed-batch phase, effectively mitigates overflow metabolite formation, improving biomass yield by up to 9% and product concentration by 40% without increasing process time.ConclusionsThese findings underscore the importance of a suitable glucose-feeding strategy in K. phaffii fermentation processes and highlight the detrimental effects of overflow metabolites on productivity. By optimizing carbon source utilization, it is possible to enhance fermentation efficiency and recombinant protein production with K. phaffii.

Current Applications and Future Implications of Artificial Intelligence in Spine Surgery and Research: A Narrative Review and Commentary.

Narrative review. Artificial intelligence (AI) is being increasingly applied to the domain of spine surgery. We present a review of AI in spine surgery, including its use across all stages of the perioperative process and applications for research. We also provide commentary regarding future ethical considerations of AI use and how it may affect surgeon-industry relations. We conducted a comprehensive literature review of peer-reviewed articles that examined applications of AI during the pre-, intra-, or postoperative spine surgery process. We also discussed the relationship among AI, spine industry partners, and surgeons. Preoperatively, AI has been mainly applied to image analysis, patient diagnosis and stratification, decision-making. Intraoperatively, AI has been used to aid image guidance and navigation. Postoperatively, AI has been used for outcomes prediction and analysis. AI can enable curation and analysis of huge datasets that can enhance research efforts. Large amounts of data are being accrued by industry sources for use by their AI platforms, though the inner workings of these datasets or algorithms are not well known. AI has found numerous uses in the pre-, intra-, or postoperative spine surgery process, and the applications of AI continue to grow. The clinical applications and benefits of AI will continue to be more fully realized, but so will certain ethical considerations. Making industry-sponsored databases open source, or at least somehow available to the public, will help alleviate potential biases and obscurities between surgeons and industry and will benefit patient care.

Energy Consumption in Wheat-Rice Cropping System in Punjab

Energy consumption for crop production depends on the availability of energy sources and the capacity of the farmers. This study analyzed energy sources used by farmers for wheat and rice production and identified agricultural operations where energy consumption can be reduced so that operational costs in wheat-rice production system can be lowered. Data on energy use in wheat and rice cropping system was collected by interviewing the farmers using specially designed questionnaire. Relevant information pertaining to human labour use, sources of irrigation, number of irrigations to each crop, quantity of farm inputs, utilization of mechanical power sources and grain yield etc. were collected. The average output energy of grain, input energy, energy ratio and specific energy for wheat crop in the state of Punjab were 68347 MJ ha-1, 15644 MJ ha-1, 8.4 and 3.08 MJ kg-1, respectively. The average output energy of grain, input energy, energy ratio and specific energy for rice were 115888 MJ ha-1, 16438 MJ ha-1, 14.8 and 2.09 MJ kg-1, respectively. For wheat-rice cropping system, the average output energy of grain, input energy, energy ratio and specific energy were 184234.4 MJ ha-1, 32081.4 MJ ha-1, 11.7 and 2.48 MJ kg-1, respectively. Energy ratio (output energy to input energy ratio) of rice is higher than the wheat, indicating rice efficiently utilized energy resources to convert into output of the harvested crop. Similarly, lower specific energy (input energy to yield ratio) of rice as compared to wheat also indicates lower energy consumption to produce per unit of rice. This analysis clearly indicates that rice production is more energy efficient than wheat production in rice-wheat production system. Further, the energy ratio, specific energy and energy productivity of wheat-rice cropping system were estimated as 11.6 to 11.9, 2.44 to 2.51 MJ kg-1 and 0.40 to 0.41kg MJ-1, respectively. This study will be helpful to identify the agricultural operations and implementing suitable interventions for improving energy use efficiency.