Nutrient deficiency patterns and all-cause and cardiovascular mortality in older adults with hypertension: a latent class analysis.

BACKGROUND: Previous researches examining the impact of dietary nutrition on mortality risk have mainly focused on individual nutrients, however the interaction of these nutrients has not been considered. The purpose of this study was to identify of nutrient deficiencies patterns and analyze their potential impact on mortality risk in older adults with hypertension. METHODS: We included participants from the National Health and Nutrition Examination Survey (NHANES) study. The latent class analysis (LCA) was applied to uncover specific malnutrition profiles within the sample. Risk of the end points across the phenogroups was compared using Kaplan-Meier analysis and Cox proportional hazard regression model. Multinomial logistic regression was used to determine the influencing factors of specific malnutrition profiles. RESULTS: A total of 6924 participants aged 60 years or older with hypertension from NHANES 2003-2014 was followed until December 31, 2019 with a median follow-up of 8.7 years. Various nutrients included vitamin A, vitamin B1, vitamin B12, vitamin C, vitamin D, vitamin E, vitamin K, fiber, folate, calcium, magnesium, zinc, copper, iron, and selenium, and LCA revealed 4 classes of malnutrition. Regarding all-cause mortality, "Nutrient Deprived" group showed the strongest hazard ratio (1.42 from 1.19 to 1.70) compared with "Adequate Nutrient" group, followed by "Inadequate Nutrient" group (1.29 from 1.10 to 1.50), and "Low Fiber, Magnesium, and Vit E" group (1.17 from 1.02 to 1.35). For cardiovascular mortality, "Nutrient Deprived" group showed the strongest hazard ratio (1.61 from 1.19 to 2.16) compared with "Adequate Nutrient" group, followed by "Low Fiber, Magnesium, and Vit E" group (1.51 from 1.04 to 2.20), and "Inadequate Nutrient" group (1.37 from 1.03 to 1.83). CONCLUSIONS: The study revealed a significant association between nutrients deficiency patterns and the risk of all-cause and cardiovascular mortality in older adults with hypertension. The findings suggested that nutrients deficiency pattern may be an important risk factor for mortality in older adults with hypertension.

Impact of Nanoparticle Additions on Life Cycle Assessment (LCA) of Ceramic Tiles Production.

The ceramic tile industry, with significant energy and material demands in its manufacturing processes, has employed technological innovations in energy efficiency, advanced equipment and tile thickness reduction to address these challenges. This study aimed to assess the impact of Ag2O, CuFe2O4, Fe3O4, and SiO2 nanoparticles (0%, 1%, and 5% by weight) on the mechanical strength, water absorption, and apparent thermal conductivity of ceramic tiles, as well as their capacity to reduce energy and raw material consumption. This reduction translates into a decrease in environmental impacts, which have been evaluated through life cycle assessment (LCA) methodology applied to the manufacturing processes. Nanoparticles (Ag2O, CuFe2O4, Fe3O4, and SiO2) were initially screened on TF clay (0%, 1%, 5% w/w), and the most effective were applied to CR1 and CR2 clays (0%, 1%, 5% w/w). Findings indicated a 32% increase in temperature gradient and a 16% improvement in flexural strength with the addition of Fe3O4 nanoparticle at 1% (w/w) in TF clay. Furthermore, there was a potential 48% reduction in energy consumption, and up to 16% decrease in tile weight or thickness without affecting the flexural strength property of the test tiles. LCA results demonstrated that the addition of Fe3O4 nanoparticle has potential reductions of up to 20% in environmental impacts. This study suggests that nanoparticle addition offers a viable alternative for reducing energy and material consumption in the ceramic tile industry. Future research should focus on assessing the economic impact of transitioning to a sustainable business model in the ceramic tile industry with nanoparticles addition.

Management of excavated soil and dredging spoil waste from construction and demolition within the EU: Practices, impacts and perspectives.

Excavated soil and rock (ESR) and dredging spoils (DDS) account for 23 % of the total EU waste generation in 2020. This study performs a life cycle assessment and life cycle costing to quantify the potential environmental and cost savings resulting from increasing the level of ESR and DDS prepared for reuse and recycled in comparison to the business-as-usual practice. Scenarios for the waste management pathways based on the status quo, technical feasibility or normative impositions are assessed, including the potential contribution to achieving the European Green Deal goals. Results show that promoting preparing for reuse and recycling could lead to non-negligible GHG reductions (up to 3.6 Mt. CO2 eq.) and economic savings (EUR 12.3 billion) annually. Depending upon the scenario, 0.2 % to 1 % of the net annual GHG emissions reductions sought by the European Green Deal could be facilitated by scaling up improved circular management of ESR and DDS at the EU level. Finally, the study highlights the main barriers to scaling up to more circular (i.e., preparing for reuse and recycling) and better performing management options in Europe. The results provide new insights for the European Green Deal and circular economy policymaking for CDW.

Performance of high-efficiency UV-C LEDs in water disinfection: Experimental, life cycle assessment, and economic analysis of different operational scenarios.

The widespread use of low or medium pressure mercury lamps in UV-C water disinfection should consider recent advances in UV-C LED lamps that offer a more sustainable approach and avoid its main drawbacks. The type of water and the mode of operation are critical when deciding on the treatment technology to be used. Therefore, this study investigates the potential application of UV-C LED disinfection technology in terms of kinetics, environmental assessment, and economic analysis for two scenarios: the continuous disinfection of a wastewater treatment plant (WWTP), and disinfection of harvested rainwater (RWH) in a residential household that operates intermittently. Experiments are conducted using both the new UV-C LED system and the conventional mercury lamp to disinfect real wastewater. Removal of total coliforms and Escherichia coli bacteria, with concentrations of approximately 105 and 104 CFU per 100 mL has been followed to assess the performance of both types of UV-C lamps. The experimental study provides kinetic parameters that have been further used in the environmental assessment conducted from a life cycle perspective. Additionally, considering the significant role of electricity consumption, a preliminary economic analysis has been conducted. The results indicate that first-order kinetic constants of pathogens removal with UV-C LEDs achieve 1.4 times higher values than Hg lamp. Regarding the environmental and economic assessment, for disinfection systems operating continuously, LEDs result in environmental impacts 5 times higher than Hg lamp in most categories, indicating that Hg lamps offer a viable option both from economic and environmental point of view. However, for installations with intermittent operation, LEDs emerge as the most competitive alternative, due to their ability to be turned on and off without affecting their lifespan. This study shows that UV-C LED lamps hold promise to replace conventional mercury lamps in a near future.

Four Unique Genetic Variants in Three Genes Account for 62.7% of Early-Onset Severe Retinal Dystrophy in Chile: Diagnostic and Therapeutic Consequences.

Leber congenital amaurosis (LCA)/early-onset severe retinal dystrophy (EOSRD) stand as primary causes of incurable childhood blindness. This study investigates the clinical and molecular architecture of syndromic and non-syndromic LCA/EOSRD within a Chilean cohort (67 patients/60 families). Leveraging panel sequencing, 95.5% detection was achieved, revealing 17 genes and 126 variants (32 unique). CRB1, LCA5, and RDH12 dominated (71.9%), with CRB1 being the most prevalent (43.8%). Notably, four unique variants (LCA5 p.Glu415*, CRB1 p.Ser1049Aspfs*40 and p.Cys948Tyr, RDH12 p.Leu99Ile) constituted 62.7% of all disease alleles, indicating their importance for targeted analysis in Chilean patients. This study underscores a high degree of inbreeding in Chilean families affected by pediatric retinal blindness, resulting in a limited mutation repertoire. Furthermore, it complements and reinforces earlier reports, indicating the involvement of ADAM9 and RP1 as uncommon causes of LCA/EOSRD. These data hold significant value for patient and family counseling, pharmaceutical industry endeavors in personalized medicine, and future enrolment in gene therapy-based treatments, particularly with ongoing trials (LCA5) or advancing preclinical developments (CRB1 and RDH12).

Effects of physical activity patterns on myopia among children and adolescents: A latent class analysis.

BACKGROUND: The daily physical activity (PA) patterns of children and adolescents are intricate and ambiguous, with varying effects on myopia resulting from different combinations of PA. This study aims to scrutinize the spectrum of PA patterns among children and adolescents and assess their impact on myopia. METHODS: Data sourced from the 2014 National Student Physical Fitness Survey (Tianjin segment) encompassed PA records and visual acuity measurements of participants. Latent Class Analysis and a generalized linear model were employed to investigate the relationship between PA categories and visual acuity across different educational stages. RESULTS: The study comprised 6465 primary and middle school students, among whom 50.13% were male. PA patterns were categorized into high (27.16%), medium (29.88%) and low visual acuity regulation groups (13.97%) and the nonmainstream group (28.99%). Following adjustments for sex, age, region and BMI, the medium visual acuity regulation group exhibited a lower risk of myopia (OR = 0.617, 95% CI = 0.424-0.897, p = 0.012; OR = 0.654, 95% CI = 0.438-0.976, p = 0.038) compared to the nonmainstream group among junior and senior middle school students. CONCLUSION: The efficacy of diverse PA patterns in mitigating myopia risk varies across educational stages and is influenced by sex-specific factors. It is imperative to advance myopia management strategies by emphasizing tailored PA interventions, discerning between PA patterns and delivering timely guidance and interventions tailored to distinct educational stages and sexes.

Latent class analysis and longitudinal development trajectory study of psychological distress in patients with stroke: a study protocol.

Background: Psychological distress affects the treatment and rehabilitation of patients with stroke, affects their long-term functional exercise and quality of life, and increases the risk of stroke recurrence and even death. This is a multi-dimensional and multi-level mental health problem and a dynamic process variable that shows a dynamic development trend with time. However, previous studies have been insufficient to deeply study the change mechanism of psychological distress, and there remains a lack of forward-looking longitudinal studies to analyze its change trajectory. This study aimed to investigate potential categories and how psychological distress changes over time and to examine conversion probability in these transformation processes. Methods: This prospective longitudinal mixed-method study investigated the potential categories and change trajectories of distress in patients with stroke. A total of 492 participants from three hospitals were recruited for quantitative analysis. Latent class analysis and latent transition analysis (LCA/LTA) were used to identify meaningful subgroups, transitions between those classes across time, and baseline demographic features that help predict and design tailored interventions. Discussion: A comprehensive understanding of the potential category and transformation processes of psychological distress over time, including the impact of the sense of demographic data on the role of shame and loneliness, can lead to the development of psychological distress treatment tailored to the unique needs of patients with stroke. Thus, this study can promote more effective and successful treatment outcomes, reduce the stigma surrounding disease issues among patients, and encourage them to use psychological consultation.

Developing a dynamic life cycle assessment framework for buildings through integrating building information modeling and building energy modeling program.

The construction and building sector is one of the largest contributors to the global carbon emissions. Therefore, it is imperative to accurately assess the carbon emissions of buildings throughout the life cycle. Many studies conducted life cycle assessment (LCA) of buildings to evaluate carbon emissions. However, due to the lack of dynamic data, most studies adopted the static LCA methodology, which neglected the dynamic variations during life cycle stages of a building. Unlike previous studies that collected static data from questionnaires and documents, the present study aims to establish a novel dynamic life cycle assessment (D-LCA) framework for buildings by incorporating the building information modeling (BIM) and the building energy modeling program (BEMP) into the static LCA. First, a static LCA is established as the baseline scenario that covers the "cradle-to-grave" life cycle stages. A BIM model is established using Revit to obtain the inventory of building materials. The Designer Simulation Toolkit (DeST) is used as a BEMP to simulate the operating energy consumption of the studied building, taking into account changes in energy mix, climate change, and occupant behavior. At the same time, the DeST results are further used as a data input for dynamic scenarios. The D-LCA framework is applied to a high-rise commercial building in China. This study found that the difference between static and dynamic scenarios was up to 66.7 %, mainly reflected in the dynamic energy consumption during the operation phase, indicating the inaccuracy of traditional static LCA. Therefore, a D-LCA by integrating BIM and BEMP can facilitate dynamic modeling and improve the accuracy and reliability of LCA for buildings.

Pyrolytic urban mining of waste printed circuit boards: an enviro-economic analysis.

E-waste, a global environmental concern resulting from supply chain inefficiency, also offers the opportunity to recover valuable materials, including general and rare earth metals. Waste printed circuit boards (WPCBs) are integral components of e-waste that contains substantial amounts of precious metals, making them a valuable waste category. Pyrolysis has emerged as a promising method for material recovery from WPCBs. Hence, pyrolytic urban mining of WPCBs offers an excellent avenue for resource recovery, redirecting valuable materials back into the supply chain. Under the current study, experimental investigation has been conducted to explore the recovery of materials from WPCBs through pyrolysis followed by process simulation, economic analysis, and life cycle assessment (LCA). An Aspen Plus simulation was conducted to model the pyrolysis of WPCBs and subsequent product recovery using a non-equilibrium kinetic model, which represents a unique approach in this study. Another distinct aspect is the comprehensive assessment of environmental and economic sustainability. The economic analysis has been carried out using Aspen economic analyzer whereas the LCA of WPCB pyrolysis has been conducted using the SimaPro software. The experimental investigation reveals yield of solid residues are about 75-84 wt.%, liquid yields of 6-13 wt.%, and gas yields of 4-21 wt.%, which is in well agreement with the Aspen Plus simulation results. The economic analysis for an e-waste pyrolysis plant with an annual feed rate of 2000 t reveals that the total capital cost of a pyrolysis plant is nearly $51.3 million, whereas the total equipment cost is nearly $2.7 million and the total operating cost is nearly $25.6 million. The desired rate of return is 20% per year and the payback period is 6 years with a profitability index of 1.25. From the LCA, the major impact categories are global warming, fossil resource scarcity, ozone formation in human health, ozone formation in terrestrial ecosystems, fine particulate matter formation, and water consumption. The findings of this study can serve as a guideline for e-waste recyclers, researchers, and decision-makers in establishing circular economy.

Energy from waste biomass: an LCA study on a biofuel cell at early design stage.

Diversifying energy sources and managing waste biomass are two pressing contemporary issues. The new technology proposed in this study aims to address both by converting waste biomass into energy and fertilizer through the use of a biofuel cell (BFC). The purpose of this study is to assess the environmental impacts associated with this innovative technology through a Life Cycle Assessment (LCA). To achieve the goal, the production and use of the cell were modelled, considering both laboratory-scale operations and industrial-scale approximations. The study explored alternative scenarios, such as sensitivity analyses involving different acids and bases, renewable energy sources, and heat recovery. Comparisons with conventional biomass waste treatments (anaerobic digestion and composting) demonstrated that the BFC technology remains competitive. To further improve the BFC's environmental footprint, efforts should focus on reducing energy requirements and enhancing nutrient recovery during scale-up. These insights are crucial for advancing sustainable waste treatment technologies and maximizing the potential of discarded biomass in an environmentally friendly manner.

Modelling environmental life cycle performance of alternative marine power configurations with an integrated experimental assessment approach: A case study of an inland passenger barge.

There is pressure on the global shipping industry to move towards greener propulsion and fuel technologies to reduce greenhouse gas emissions. Hydrogen and electricity are both recognised as pathways to achieve a net-zero. However, in the evaluation of the environmental performance of these alternative marine power configurations, conventional life cycle assessment (LCA) methods have limitations reflecting the varied nature of ship design and operational modes. The integration of LCA with experimental assessment could remedy the shortcoming of conventional approaches to data generation. The system energy demand data in this study was generated based on specific ship design and directly fed into life cycle assessment. To demonstrate the effectiveness and potential the approach was applied to a case study of inland waterway vessel. Suitable hybrid PV/electricity/diesel and hydrogen powered fuel cell systems for the case vessel were modelled; and hydrodynamic testing and dynamic system simulation was undertaken to provide ship performance data under various operational/environmental profiles. Lifecycle assessment (LCA) indicated hydrogen and electrical propulsion technologies have the potential for 85.7 % and 56.2 % emissions reduction against an MGO base case, respectively. The results highlight that implementation of both technologies is highly dependent on energy production pathways. Hydrogen systems reliant on fossil feedstocks risk an increase in emissions of up to 6.3 % against the MGO base case. Sensitivity analysis indicated an electrical system with electricity production from 79.5 % renewables could achieve savings of 82.2 % in GHG emissions compared to the MGO base case. Crucially, the results demonstrate a further development of the LCA approach which can enable a more accurate environmental performance evaluation of alternative marine power configurations considering specific ship design and operational characteristics. Ultimately this addition makes the results more meaningful for commercial operations and decision making in the selection of alternative marine power systems to support the transition to net-zero.

Are contaminated soil and groundwater remediation with nanoscale zero-valent iron sustainable? An analysis of case studies.

Nanoscale zero valent iron (nZVI) is globally the main nanomaterial used in contaminated site remediation. This study aims to evaluate the sustainability of using nZVI in the nanoremediation of contaminated sites and to determine the factors that affect the sustainability of the use of nZVI in remediation. Five case studies of nZVI use on a pilot scale were selected. Life cycle analysis tools were used to evaluate environmental, economic, social impacts, and sustainability. The functional unit of the life cycle analyses was 1.00 m3 of remediated soil and groundwater. Case study of Brazil was the least sustainable, while case study of United States was the most sustainable. Only the modification of the functional unit results in variations in the sustainability index. Different factors influence the sustainability of nZVI in remediation, the main factor being the amount of nZVI used in the processes. Finally, this work contributes significantly to the state-of-the-art sustainable use of nZVI in remediation. This is a pioneering study in the detailed and comprehensive assessment of the sustainability of the use of nZVI in remediation. Through the analysis of case studies, it is possible to determine the main factors that influence the sustainability of the nZVI remediation life cycle.

A life cycle assessment of the laboratory-scale oxidative liquefaction as the chemical recycling method of the end-of-life wind turbine blades.

According to the latest reports, estimated values of 50,000-66 000 t of end-of-life wind turbine blades (WTB) are expected to be decommissioned in Europe in 2025-2030, posing a significant threat from the environmental and waste management perspectives. This study aims to present the preliminary Life Cycle Assessment (LCA) with sensitivity and uncertainty analysis of the lab-scale oxidative liquefaction process of the WTB, as the original method to recover the high-quality glass fibers with simultaneous production of the secondary chemicals: phenols, ketones, acids, and fatty acids, from the oxidation of the epoxy resin from the polymer matrix. The LCA is based on the experimental results of the oxidative liquefaction process carried out on a laboratory scale using a Parr 500 ml batch reactor, at two different conditions sets for the functional unit (FU) of 1 kg of treated WTB. Each of the analyzed scenarios resulted in higher impact indicators compared to the landfilling. The highest quality fibers were obtained at 350 °C and 40 wt % H2O2 content resulted in 5.52 ± 1.20 kgCO2 eq Climate change impact and 97.8 ± 20.6 MJ of Resource use, fossil per kg of recycled WTB. The lowest quality fiber recovered in char, yet well separated from the matrix obtained at 250 °C and the lowest H2O2 content resulted in 0.0953 ± 0.487 kgCO2 eq Climate change impact and 8.84 ± 7.90 MJ of Resource use, fossil per kg of recycled WTB. The hot spot and sensitivity analysis indicated, that the oxidizer for the process - hydrogen peroxide, when acquired as a shelf product causes a significant burden on the whole process, with sensitivity ratios on the total impact indicators varying across the categories from 0.56 to 0.99. Substitution of H2O2 with theoretical 0-input oxidizer allowed to significantly lower environmental load of the recycling process, which in all of the analyzed scenarios presented environmental benefits compared to landfilling with recovery of the glass fiber and secondary chemicals.

Combining Fleetwide AviTeam Aviation Emission Modeling with LCA Perspectives for an Alternative Fuel Impact Assessment.

Reducing aviation emissions is important as they contribute to air pollution and climate change. Several alternative aviation fuels that may reduce life cycle emissions have been proposed. Comparative life cycle assessments (LCAs) of fuels are useful for inspecting individual fuels, but systemwide analysis remains difficult. Thus, systematic properties like fleet composition, performance, or emissions and changes to them under alternative fuels can only be partially addressed in LCAs. By integrating the geospatial fuel and emission model, AviTeam, with LCA, we can assess the mitigation potential of a fleetwide use of alternative aviation fuels on 210 000 shorter haul flights. In an optimistic case, liquid hydrogen (LH2) and power-to-liquid fuels, when produced with renewable electricity, may reduce emissions by about 950 GgCO2eq when assessed with the GWP100 metric and including non-CO2 impacts for all flights considered. Mitigation potentials range from 44% on shorter flights to 56% on longer flights. Alternative aviation fuels' mitigation potential is limited because of short-lived climate forcings and additional fuel demand to accommodate LH2 fuel. Our results highlight the importance of integrating system models into LCAs and are of value to researchers and decision-makers engaged in climate change mitigation in the aviation and transport sectors.

Life cycle assessment and cost analysis of an innovative automatic system for sorting municipal solid waste: A case study at Milan Malpensa airport.

With the recent advancement in artificial intelligence, there are new opportunities to adopt smart technologies for the sorting of materials at the beginning of the recycling value chain. An automatic bin capable of sorting the waste among paper, plastic, glass & aluminium, and residual waste was installed in public areas of Milan Malpensa airport, a context where the separate collection is challenging. First, the airport waste composition was assessed, together with the efficiency of the manual sorting performed by passengers among the conventional bins: paper, plastic, glass & aluminium, and residual waste. Then, the environmental (via the life cycle assessment - LCA) and the economic performances of the current system were compared to those of a system in which the sorting is performed by the automatic bin. Three scenarios were evaluated: i) all waste from public areas, despite being separately collected, is sent to incineration with energy recovery, due to the inadequate separation quality (S0); ii) recyclable fractions are sent to recycling according to the actual level of impurities in the bags (S0R); iii) fractions are sorted by the automatic bin and sent to recycling (S1). According to the results, the current separate collection shows a 62 % classification accuracy. Focusing on LCA, S0 causes an additional burden of 12.4 mPt (milli points) per tonne of waste. By contrast, S0R shows a benefit (-26.4 mPt/t) and S1 allows for a further 33 % increase of benefits. Moreover, the cost analysis indicates potential savings of 24.3 €/t in S1, when compared to S0.

Utilizing social determinants of health to identify most vulnerable neighborhoods-Latent class analysis and GIS map.

OBJECTIVES: Public Health officials are often challenged to effectively allocate limited resources. Social determinants of health (SDOH) may cluster in areas to cause unique profiles related to various adverse life events. The authors use the framework of unintended teen pregnancies to illustrate how to identify the most vulnerable neighborhoods. METHODS: This study used data from the U.S. American Community Survey, Princeton Eviction Lab, and Connecticut Office of Vital Records. Census tracts are small statistical subdivisions of a county. Latent class analysis (LCA) was employed to separate the 832 Connecticut census tracts into four distinct latent classes based on SDOH, and GIS mapping was utilized to visualize the distribution of the most vulnerable neighborhoods. GEE Poisson regression model was used to assess whether latent classes were related to the outcome. Data were analyzed in May 2021. RESULTS: LCA's results showed that class 1 (non-minority non-disadvantaged tracts) had the least diversity and lowest poverty of the four classes. Compared to class 1, class 2 (minority non-disadvantaged tracts) had more households with no health insurance and with single parents; and class 3 (non-minority disadvantaged tracts) had more households with no vehicle available, that had moved from another place in the past year, were low income, and living in renter-occupied housing. Class 4 (minority disadvantaged tracts) had the lowest socioeconomic characteristics. CONCLUSIONS: LCA can identify unique profiles for neighborhoods vulnerable to adverse events, setting up the potential for differential intervention strategies for communities with varying risk profiles. Our approach may be generalizable to other areas or other programs. KEY MESSAGES: What is already known on this topic Public health practitioners struggle to develop interventions that are universally effective. The teen birth rates vary tremendously by race and ethnicity. Unplanned teen pregnancy rates are related to multiple social determinants and behaviors. Latent class analysis has been applied successfully to address public health problems. What this study adds While it is the pregnancy that is not planned rather than the birth, access to pregnancy intention data is not available resulting in a dependency on teen birth data for developing public health strategies. Using teen birth rates to identify at-risk neighborhoods will not directly represent the teens at risk for pregnancy but rather those who delivered a live birth. Since teen birth rates often fluctuate due to small numbers, especially for small neighborhoods, LCA may avoid some of the limitations associated with direct rate comparisons. The authors illustrate how practitioners can use publicly available SDOH from the Census Bureau to identify distinct SDOH profiles for teen births at the census tract level. How this study might affect research, practice or policy These profiles of classes that are at heightened risk potentially can be used to tailor intervention plans for reducing unintended teen pregnancy. The approach may be adapted to other programs and other states to prioritize the allocation of limited resources.

A raising alarm on the current global electronic waste situation through bibliometric analysis, life cycle, and techno-economic assessment: a review.

Electronic waste (E-waste) production worldwide is increasing three times faster than the growth of the global population, and it is predicted that the total volume of E-waste will reach 74 million tonnes by 2030. United Nations warned that unless emissions of heat-trapping gases are drastically reduced, humanity will face catastrophic climate change. We created a bibliometric analysis and discussed the life cycle and techno-economic assessments of the current E-waste situation. We found trending E-waste topics, particularly those related to industrial facilities implementing a circular economy framework and improving the recycling methods of lithium-ion batteries, and this was linked to the topic of electric vehicles. Other research themes included bioleaching, hydrometallurgy, reverse logistics, heavy metal life cycle assessment, and sustainability. These topics can interest industrial factories and scientists interested in these fields. Also, throughout techno-economic assessments, we highlighted several economic and investment opportunities to benefit stakeholders from E-waste recycling. While the rate of E-waste is increasing, consumer education on the proper E-waste management strategies, a collaboration between international organizations with the industrial sector, and legislation of robust E-waste regulations may reduce the harmful effect on humans and the environment and increase the income to flourish national economies.

Development and application of a sensitive liquid chromatography-tandem mass spectrometry method for the quantitative analysis of 11 free fatty acids in human serum using a derivatisation strategy.

A stable isotope dilution-liquid chromatography-tandem mass spectrometry method based on a derivatisation strategy involving an N,N'-carbonylimidazole solution (CDI) with 4-(dimethylamino)-benzenemethanamine was developed for the determination of 11 free fatty acids (FFAs) in human blood samples. Serum samples were subjected to liquid‒liquid extraction and centrifuged, and the supernatant was collected for a two-step derivatisation reaction with a CDI and 4-(dimethylamino)-aniline acetonitrile solution. The derivatised solution was separated on a ACQUITY UPLC HSS T3 column (2.1 × 50 mm, 1.8 µm) column with a mobile phase consisting of water-acetonitrile in gradient elution and then detected by tandem mass spectrometry using electrospray ionisation (ESI) and multiple reaction monitoring (MRM) in positive ion mode and quantified using the isotope internal standard method. The effects of the derivatisation reaction time, temperature and concentration of derivatisation reagents on the response values of the analytes were investigated. The optimal conditions were as follows: 1.0 mg mL-1 CDI acetonitrile solution at 25 °C for 25 min, followed by a reaction with a 1.0 mg mL-1 4-(dimethylamino)-benzenemethanamine acetonitrile solution at 70 °C for 30 min. Under the optimal conditions, the limits of detection (LODs) of the 11 FFAs were in the range of 3.0-14.0 ng mL-1; the limits of quantification (LOQs) were in the range of 8.0-45.0 ng mL-1; and the mean recoveries ranged from 83.4 to 112.8%, with intraday and interday precisions ranging from 0.7 to 9.1% and 3.7-9.5%, respectively. The experimental method is simple in terms of the pretreatment operation, accurate and reliable, and can be applied to the sensitive determination of FFAs in human blood samples.

Dataset for the life-cycle assessment of the Basque Y high-speed rail line in Spain.

This dataset presents a detailed description of the data and information used in the life-cycle assessment (LCA) of the Basque Y HSR line, which is a high-performance line for mixed traffic still under construction in 2023 (190 km). The LCI data presented in this paper support the original research carried out on whether the construction of the Basque Y HSR line infrastructure is justified in terms of reducing environmental impacts and energy consumption [1]. Life-cycle inventory (LCI) data related to the construction and maintenance phases of the infrastructure was collected using Google Earth tool following the information from stakeholder AHT gelditu [2], including the length of each item (bridges, tunnels, earthworks, railway tracks); and complemented with data obtained from the LCA carried out by Tuchschmid et al. [3]. LCI data associated with the operation phase of the infrastructure was built on passenger data for the years 2020, 2030, 2040 and 2049 available in ADIF [4], and freight data for the period of 2023-2050 available in the report by ADIF and the Basque Government [5]. Environmental impacts for transport modes were obtained from the ecoinvent v3.7 database [6,7] and processed with openLCA software [8]. Life-cycle impact assessment (LCIA) results gathered in the dataset include Global Warming (GWP100a), Cumulative Energy Demand and total emissions for PM10, SO2, NOX and NMVOC. Access to the explanation of these data allows any reader to reproduce the calculations of the main project and may be used as a baseline for future studies on transport economics too.

Study on plasma metabolomics profiling of depression in Chinese community-dwelling older adults based on untargeted LC/GC‒MS.

Depression is a serious psychiatric illness that causes great inconvenience to the lives of elderly individuals. However, the diagnosis of depression is somewhat subjective. Nontargeted gas chromatography (GC)/liquid chromatography (LC)-mass spectrometry (MS) was used to study the plasma metabolic profile and identify objective markers for depression and metabolic pathway variation. We recruited 379 Chinese community-dwelling individuals aged ≥ 65. Plasma samples were collected and detected by GC/LC‒MS. Orthogonal partial least squares discriminant analysis and a heatmap were utilized to distinguish the metabolites. Receiver operating characteristic curves were constructed to evaluate the diagnostic value of these differential metabolites. Additionally, metabolic pathway enrichment was performed to reveal metabolic pathway variation. According to our standard, 49 people were included in the depression cohort (DC), and 49 people age- and sex-matched individuals were included in the non-depression cohort (NDC). 64 metabolites identified via GC‒MS and 73 metabolites identified via LC‒MS had significant contributions to the differentiation between the DC and NDC, with VIP values > 1 and p values < 0.05. Three substances were detected by both methods: hypoxanthine, phytosphingosine, and xanthine. Furthermore, 1-(sn-glycero-3-phospho)-1D-myo-inositol had the largest area under the curve (AUC) value (AUC = 0.842). The purine metabolic pathway is the most important change in metabolic pathways. These findings show that there were differences in plasma metabolites between the depression cohort and the non-depression cohort. These identified differential metabolites may be markers of depression and can be used to study the changes in depression metabolic pathways.