Development and validation of a non-invasive method for quantifying amino acids in human saliva.

As an analytical matrix, saliva has superior characteristics than blood and urine. Saliva collection is, first and foremost, non-invasive, making it convenient, painless, and secure for more susceptible people. Second, it does not need professional training for medical personnel, resulting in cost-effectiveness and suitability for extensive collection in support of research. In this study, we developed a method and used it to quantify 13 salivary-free amino acid (SFAA) profiles to support the early clinical diagnosis of diseases using LC-MS/MS. Using an Intrada Amino Acid column (100 × 3 mm, 3 µm), chromatographic separation was accomplished with a binary gradient elution, and an electrospray ionisation source running in the positive ionisation mode was chosen for data collection using the multiple reaction monitoring (MRM) modes. Amino acids were extracted from saliva using acetonitrile. In the MRM mode, LODs and LOQs for ten amino acids were in the range of 0.06-2.50 µM and 0.19-7.58 µM, respectively, and those values were in the range of 1.00-3.00 µM and 3.00-8.50 µM, respectively, for three amino acids. Matrix-matched six-point calibration curves showed a linear correlation coefficient (r 2) of ≥0.998. Recovery experiments validated the method by spiking the control sample at three different concentration levels (5, 50 and 100 µM), and the accuracy level was 85-110%. Except for Thr and Ser, intra- (n = 3) and inter-day (n = 3) precision fell between 0.02 and 7.28. Salivary amino acids can serve as possible biomarkers for various malignancies, with fluctuations in body fluids being crucial for cancer diagnosis; therefore, examining amino acid patterns in saliva can assist in early cancer detection. LC-MS offers improved selectivity and sensitivity for non-derivatised amino acid analysis, surpassing conventional methods and offering proactive quality assurance, making it suitable for complicated sample matrices. These discoveries could be significant in investigating new pathways and cancer treatments and looking for possible AA biomarkers for other malignancies and diseases.

Global-to-Local Dependencies in Phosphorus Mass Flows and Markets: Pathways to Improving System Resiliency in Response to Exogenous Shocks.

Uneven global distribution of phosphate rock deposits and the supply chains to transport phosphorus (P) make P fertilizers vulnerable to exogenous shocks, including commodity market shocks; extreme weather events or natural disasters; and geopolitical instability, such as trade disputes, disruption of shipping routes, and war. Understanding bidirectional risk transmission (global-to-local and local-to-global) in P supply and consumption chains is thus essential. Ignoring P system interdependencies and associated risks could have major impacts on critical infrastructure operations and increase the vulnerability of global food systems. We highlight recent unanticipated events and cascading effects that have impacted P markets globally. We discuss the need to account for exogenous shocks in local assessments of P flows, policies, and infrastructure design choices. We also provide examples of how accounting for undervalued global risks to the P industry can hasten the transition to a sustainable P future. For example, leveraging internal P recycling loops, improving plant P use efficiency, and utilizing legacy soil P all enhance system resiliency in the face of exogenous shocks and long-term anticipated threats. Strategies applied at the local level, which are embedded within national and global policy systems, can have global-scale impacts in derisking the P supply chain.

Demystifying the association between economic development, transportation, tourism, renewable energy, and ecological footprint in Bay of Bengal Initiative for Multi-Sectoral Technical and Economic Cooperation region during globalization mode.

The Bay of Bengal Initiative for Multi-Sectoral Technical and Economic Cooperation (BIMSTEC) economies have yet to meaningfully contribute to accomplishing Sustainable Development Goals (SDG 7) affordable and clean energy, (SDG 8) decent work and economic growth, and (SDG 13) climate action. Dealing with this issue might require a shift or alteration of policy framework that is the major theme of this study. Consequently, this present research inspects the influence of economic growth, transportation, tourism sector development, and renewable energy on ecological footprint using panel time series from 1990 and 2019 for the BIMSTEC region. To evaluate this dynamic nexus between the mentioned environmental pollution drivers of ecological footprint, this study employed the augumented mean group (AMG) and common correlated effect mean group (CCEMG) regression estimators after detection of cross-sectional dependency. The empirical outcomes denote that economic growth and transportation sector of BIMSTEC countries increase the levels of ecological footprint. Conversely, tourism sector development, globalization, and renewable energy protect the ecological excellence in the region. Moreover, it is observed that a unidirectional causality exists from economic growth to ecological footprint, ecological footprint to transportation, tourism to ecological footprint, and globalization to ecological footprint, while bidirectional causality exists between renewable energy and ecological footprint. By observing the positive function of tourism, green energy, and globalization on sustainable environment progress, central authorities are capable to redesign policies concerning supportable efficient technologies and regulate globalization towards green programs and agenda to reduce global warming.