Integration of STING activation and COX-2 inhibition via steric-hindrance effect tuned nanoreactors for cancer chemoimmunotherapy.

Integrating immunotherapy with nanomaterials-based chemotherapy presents a promising avenue for amplifying antitumor outcomes. Nevertheless, the suppressive tumor immune microenvironment (TIME) and the upregulation of cyclooxygenase-2 (COX-2) induced by chemotherapy can hinder the efficacy of the chemoimmunotherapy. This study presents a TIME-reshaping strategy by developing a steric-hindrance effect tuned zinc-based metal-organic framework (MOF), designated as CZFNPs. This nanoreactor is engineered by in situ loading of the COX-2 inhibitor, C-phycocyanin (CPC), into the framework building blocks, while simultaneously weakening the stability of the MOF. Consequently, CZFNPs achieve rapid pH-responsive release of zinc ions (Zn2+) and CPC upon specific transport to tumor cells overexpressing folate receptors. Accordingly, Zn2+ can induce reactive oxygen species (ROS)-mediated cytotoxicity therapy while synchronize with mitochondrial DNA (mtDNA) release, which stimulates mtDNA/cGAS-STING pathway-mediated innate immunity. The CPC suppresses the chemotherapy-induced overexpression of COX-2, thus cooperatively reprogramming the suppressive TIME and boosting the antitumor immune response. In xenograft tumor models, the CZFNPs system effectively modulates STING and COX-2 expression, converting "cold" tumors into "hot" tumors, thereby resulting in ≈ 4-fold tumor regression relative to ZIF-8 treatment alone. This approach offers a potent strategy for enhancing the efficacy of combined nanomaterial-based chemotherapy and immunotherapy.

The causal effect of atopic dermatitis on lung cancer: A Mendelian randomization study.

BACKGROUND: Growing evidence has shown that atopic dermatitis (AD) may decrease lung cancer (LC) risk. However, the causality between the two diseases is inconsistent and controversial. Therefore, we explored the causal relationship between AD and different histological subtypes of LC by using the Mendelian randomization (MR) method. MATERIALS AND METHODS: We conducted the MR study based on summary statistics from the genome-wide association studies (GWAS) of AD (10,788 cases and 30,047 controls) and LC (29,266 cases and 56,450 controls). Instrumental variables (IVs) were obtained after removing SNPs associated with potential confounders. We employed inverse-variance weighted (IVW), MR-Egger, and weighted median methods to pool estimates, and performed a comprehensive sensitivity analysis. RESULTS: The results of the IVW method suggested that AD may decrease the risk of developing lung adenocarcinoma (LUAD) (OR = 0.91, 95% CI: 0.85-0.97, P = 0.007). Moreover, no causality was identified between AD and overall LC (OR = 0.96, 95% CI: 0.91-1.01, P = 0.101), lung squamous cell carcinoma (LUSC) (OR = 1.04, 95% CI: 0.96-1.036, P = 0.324), and small cell lung carcinoma (SCLC) (OR = 0.95, 95% CI: 0.82-1.10, P = 0.512). A comprehensive sensitivity test showed the robustness of our results. CONCLUSION: The present study indicates that AD may decrease the risk of LUAD in the European population, which needs additional investigations to identify the potential molecular mechanisms.

Application of Artificial Intelligence in the Headache Field.

PURPOSE OF REVIEW: Headache disorders are highly prevalent worldwide. Rapidly advancing capabilities in artificial intelligence (AI) have expanded headache-related research with the potential to solve unmet needs in the headache field. We provide an overview of AI in headache research in this article. RECENT FINDINGS: We briefly introduce machine learning models and commonly used evaluation metrics. We then review studies that have utilized AI in the field to advance diagnostic accuracy and classification, predict treatment responses, gather insights from various data sources, and forecast migraine attacks. Furthermore, given the emergence of ChatGPT, a type of large language model (LLM), and the popularity it has gained, we also discuss how LLMs could be used to advance the field. Finally, we discuss the potential pitfalls, bias, and future directions of employing AI in headache medicine. Many recent studies on headache medicine incorporated machine learning, generative AI and LLMs. A comprehensive understanding of potential pitfalls and biases is crucial to using these novel techniques with minimum harm. When used appropriately, AI has the potential to revolutionize headache medicine.

Solid-State Surface-Anchoring Strategy to Prepare Anti-Sintering Supported Metal Cluster Catalysts.

Due to the unique geometric and electronic structures, supported metal clusters with sizes below 3 nm have appealed to great interest in heterogeneous catalysis. However, these supported ultrasmall metal clusters would endure severe particle coalescences under high reaction temperatures. Herein, based on the technology of ball-milling processing, we propose a solid-state "surface-anchoring" strategy to synthesize thermally stabilized Al2O3-supported Ni nanoclusters. Interestingly, when the theoretical Ni loading weight was 1 wt %, highly dispersed Ni species were found where no Ni nanoparticles would be seen after 500 °C calcination. Until the Ni loading weight increased to 5 wt % and the calcination temperature increased to 750 °C, the Ni nanoparticles became significant but still with a size of only about 6.8 nm. With the small Ni nanoparticles, the final 5-Ni-Al2O3-OAm-750 sample worked well as methane dry reforming catalysts with excellent anticoking performance during a 500 h stability test.

Ser/Thr protein kinase Stk1 phosphorylates the key transcriptional regulator AlgR to modulate virulence and resistance in Pseudomonas aeruginosa.

Pseudomonas aeruginosa is one of the leading causes of nosocomial infections worldwide and has emerged as a serious public health threat, due in large part to its multiple virulence factors and remarkable resistance capabilities. Stk1, a eukaryotic-type Ser/Thr protein kinase, has been shown in our previous work to be involved in the regulation of several signalling pathways and biological processes. Here, we demonstrate that deletion of stk1 leads to alterations in several virulence- and resistance-related physiological functions, including reduced pyocyanin and pyoverdine production, attenuated twitching motility, and enhanced biofilm production, extracellular polysaccharide secretion, and antibiotic resistance. Moreover, we identified AlgR, an important transcriptional regulator, as a substrate for Stk1, with its phosphorylation at the Ser143 site catalysed by Stk1. Intriguingly, both the deletion of stk1 and the mutation of Ser143 of AlgR to Ala result in similar changes in the above-mentioned physiological functions. Furthermore, assays of algR expression in these strains suggest that changes in the phosphorylation state of AlgR, rather than its expression level, underlie changes in these physiological functions. These findings uncover Stk1-mediated phosphorylation of AlgR as an important mechanism for regulating virulence and resistance in P. aeruginosa.

Constructing Dynamic Cross-Linking Networks as Durable Bifunctional Coating for Highly Stable Zinc Anodes.

The serious dendrite growth and H2O-induced side reactions on the Zn electrode lead to a significant fading in the cycling performance, hindering the development of commercial applications of aqueous Zn-ion batteries (AZIBs). Herein, a novel bifunctional network coating of dynamically cross-linking sodium alginate with trehalose has been rationally constructed on the Zn anode (Zn@AT). Firstly, the AT coating possesses abundant zinophilic oxygen-containing functional groups, which are able to induce uniform Zn2+ ion flux. Secondly, the AT coating as a solid barrier can effectively inhibit H2O-induced side reactions by lowering the activity of H2O molecules. More specially, based on the dynamic cross-linking, AT network coating is endowed with self-healing capacity during cycling for durable battery operation. Consequentially, Zn@AT anodes in symmetric cells can cycle stably for 2787 h at 2 mA cm-2/2 mAh cm-2, and even achieve a significantly long cycle performance of 1087 h at large charge/discharge depths of 10 mA cm-2/10 mAh cm-2. Moreover, the Zn@AT//MnO2 full cell shows excellent specific capacity of 175 mAh g-1 after 400 cycles. This study lights an effective strategy to enhance the durability of Zn electrodes in AZIBs.

Activation of pyramidal neurons in the infralimbic cortex alleviates LPS-induced depressive-like behavior in mice.

The infralimbic (IL) cortex dysfunction has been implicated in major depressive disorder (MDD), yet the precise cellular and molecular mechanisms remain poorly understood. In this study, we investigated the role of layer V pyramidal neurons in a mouse model of MDD induced by repeated lipopolysaccharide (LPS) administration. Our results demonstrate that three days of systemic LPS administration induced depressive-like behavior and upregulated mRNA levels of interleukin-1ß (IL-1ß), tumor necrosis factor-alpha (TNF-α), and transforming growth factor-ß (TGF-ß) in the IL cortex. Electrophysiological recordings revealed a significant decrease in the intrinsic excitability of layer V pyramidal neurons in the IL following systemic LPS exposure. Importantly, chemogenetic activation of IL pyramidal neurons ameliorated LPS-induced depressive-like behavior. Additionally, LPS administration significantly increased microglial activity in the IL, as evidenced by a greater number of Ionized calcium binding adaptor molecule-1 (IBA-1)-positive cells. Morphometric analysis further unveiled enlarged soma, decreased branch numbers, and shorter branch lengths of microglial cells in the IL cortex following LPS exposure. Moreover, the activation of pyramidal neurons by clozapine-N-oxide increased the microglia branch length but did not change branch number or cytosolic area. These results collectively suggest that targeted activation of pyramidal neurons in the IL cortex mitigates microglial response and ameliorates depressive-like behaviors induced by systemic LPS administration. Therefore, our findings offer potential therapeutic targets for the development of interventions aimed at alleviating depressive symptoms by modulating IL cortical circuitry and microglial activity.

Disrupted dynamic brain functional connectivity in male cocaine use disorder: Hyperconnectivity, strongly-connected state tendency, and links to impulsivity and borderline traits.

Cocaine use is a major public health problem with serious negative consequences at both the individual and societal levels. Cocaine use disorder (CUD) is associated with cognitive and emotional impairments, often manifesting as alterations in brain functional connectivity (FC). This study employed resting-state functional magnetic resonance imaging (rs-fMRI) to examine dynamic FC in 38 male participants with CUD and 31 matched healthy controls. Using group spatial independent component analysis (group ICA) combined with sliding window approach, we identified two recurring distinct connectivity states: the strongly-connected state (state 1) and weakly-connected state (state 2). CUD patients exhibited significant increased mean dwell and fraction time in state 1, and increased transitions from state 2 to state 1, demonstrated significant strongly-connected state tendency. Our analysis revealed abnormal FC patterns that are state-dependent and state-shared in CUD patients. This study observed hyperconnectivity within the default mode network (DMN) and between DMN and other networks, which varied depending on the state. Furthermore, after adjustment for multiple comparisons, we found significant correlations between these altered dynamic FCs and clinical measures of impulsivity and borderline personality disorder. The disrupted FC and repetitive effects of precuneus and angular gyrus across correlations suggested that they might be the important hub of neural circuits related behaviorally and mentally in CUD. In summary, our study highlighted the potential of these disrupted FC as neuroimaging biomarkers and therapeutic targets, and provided new insights into the understanding of the neurophysiologic mechanisms of CUD.

Effect of Pore Structure Heterogeneity of Sandstone Reservoirs on Porosity-Permeability Variation by Using Single-Multi-Fractal Models.

Pore structure heterogeneity affects sandstone porosity and permeability and thus sandstone gas productivity. A total of 17 sandstone samples collected from the northwestern margin of the Junggar Basin in Xinjiang Province are investigated in this study. The pore-fracture system distribution of target sandstones is studied by high-pressure mercury injection tests. On this basis, single- and multi-fractal models are used to characterize pore structure heterogeneity, and the applicability of four models (Menger model, Sierpinski model, Thermodynamic model, multifractal model) to characterize pore and fracture distribution heterogeneity are discussed. Moreover, a correlation between fractal dimension, pore structure parameters, and variation coefficient of porosity-permeability is discussed based on overburden permeability test results. The results are as follows. (1) D S (fractal dimension of Sierpinski model) shows a significant correlation with pore volume percentage, so the Sierpinski model could better characterize fracture distribution heterogeneity quantitatively. Multifractal dimensions are consistent with those of Sierpinski and Thermodynamic models, which indicates that the single- and multiple-fractal models are consistent. (2) The porosity and permeability decrease as a power function with higher confining pressure. The porosity and permeability behavior changes at a critical conversion pressure value. For a confining pressure lower than this critical value, the porosity and permeability decrease largely. For confining pressures higher than this critical value, the porosity and permeability vary less. In contrast, permeability has a larger variation rate and is more obviously affected by confining pressure. (3) Pore compression space is affected by the permeability variation coefficient. Compressibility, porosity, and permeability variation coefficient have no relationship with pore structure parameters since compressibility is affected by pore structure, mineral composition, and other factors in sandstone samples.

FBP1 orchestrates keratinocyte proliferation/differentiation and suppresses psoriasis through metabolic control of histone acetylation.

Keratinocyte proliferation and differentiation in epidermis are well-controlled and essential for reacting to stimuli such as ultraviolet light. Imbalance between proliferation and differentiation is a characteristic feature of major human skin diseases such as psoriasis and squamous cell carcinoma. However, the effect of keratinocyte metabolism on proliferation and differentiation remains largely elusive. We show here that the gluconeogenic enzyme fructose-1,6-bisphosphatase 1 (FBP1) promotes differentiation while inhibits proliferation of keratinocyte and suppresses psoriasis development. FBP1 is identified among the most upregulated genes induced by UVB using transcriptome sequencing and is elevated especially in upper epidermis. Fbp1 heterozygous mice exhibit aberrant epidermis phenotypes with local hyperplasia and dedifferentiation. Loss of FBP1 promotes proliferation and inhibits differentiation of keratinocytes in vitro. Mechanistically, FBP1 loss facilitates glycolysis-mediated acetyl-CoA production, which increases histone H3 acetylation at lysine 9, resulting in enhanced transcription of proliferation genes. We further find that the expression of FBP1 is dramatically reduced in human psoriatic lesions and in skin of mouse imiquimod psoriasis model. Fbp1 deficiency in mice facilitates psoriasis-like skin lesions development through glycolysis and acetyl-CoA production. Collectively, our findings reveal a previously unrecognized role of FBP1 in epidermal homeostasis and provide evidence for FBP1 as a metabolic psoriasis suppressor.

IRE1α Mediates the Hypertrophic Growth of Cardiomyocytes Through Facilitating the Formation of Initiation Complex to Promote the Translation of TOP-Motif Transcripts.

BACKGROUND: Cardiomyocyte growth is coupled with active protein synthesis, which is one of the basic biological processes in living cells. However, it is unclear whether the unfolded protein response transducers and effectors directly take part in the control of protein synthesis. The connection between critical functions of the unfolded protein response in cellular physiology and requirements of multiple processes for cell growth prompted us to investigate the role of the unfolded protein response in cell growth and underlying molecular mechanisms. METHODS: Cardiomyocyte-specific inositol-requiring enzyme 1α (IRE1α) knockout and overexpression mouse models were generated to explore its function in vivo. Neonatal rat ventricular myocytes were isolated and cultured to evaluate the role of IRE1α in cardiomyocyte growth in vitro. Mass spectrometry was conducted to identify novel interacting proteins of IRE1α. Ribosome sequencing and polysome profiling were performed to determine the molecular basis for the function of IRE1α in translational control. RESULTS: We show that IRE1α is required for cell growth in neonatal rat ventricular myocytes under prohypertrophy treatment and in HEK293 cells in response to serum stimulation. At the molecular level, IRE1α directly interacts with eIF4G and eIF3, 2 critical components of the translation initiation complex. We demonstrate that IRE1α facilitates the formation of the translation initiation complex around the endoplasmic reticulum and preferentially initiates the translation of transcripts with 5' terminal oligopyrimidine motifs. We then reveal that IRE1α plays an important role in determining the selectivity and translation of these transcripts. We next show that IRE1α stimulates the translation of epidermal growth factor receptor through an unannotated terminal oligopyrimidine motif in its 5' untranslated region. We further demonstrate a physiological role of IRE1α-governed protein translation by showing that IRE1α is essential for cardiomyocyte growth and cardiac functional maintenance under hemodynamic stress in vivo. CONCLUSIONS: These studies suggest a noncanonical, essential role of IRE1α in orchestrating protein synthesis, which may have important implications in cardiac hypertrophy in response to pressure overload and general cell growth under other physiological and pathological conditions.

Controllable silver release for efficient treatment of drug-resistant bacterial-infected wounds.

The use of traditional Ag-based antibacterial agents is usually accompanied by uncontrollable silver release, which makes it difficult to find a balance between antibacterial performance and biosafety. Herein, we prepared a core-shell system of ZIF-8-derived amorphous carbon-coated Ag nanoparticles (Ag@C) as an ideal research model to reveal the synergistic effect and structure-activity relationship of the structural transformation of carbon shell and Ag core on the regulation of silver release behavior. It is found that Ag@C prepared at 600 °C (AC6) exhibits the best ion release kinetics due to the combination of relatively simple shell structure and lower crystallinity of Ag core, thereby exerting stronger antibacterial properties (> 99.999%) at trace doses (20 µg mL-1) compared with most other Ag-based materials. Meanwhile, the carbon shell prevents the metal Ag from being directly exposed to the organism and thus endows AC6 with excellent biocompatibility. In animal experiments, AC6 can effectively promote wound healing by inactivating drug-resistant bacteria while regulating the expression of TNF-α and CD31. This work provides theoretical support for the scientific design and clinical application of controllable ion-releasing antibacterial agents.

Hospital-treated infectious diseases, infection burden and risk of Parkinson disease: An observational and Mendelian randomization study.

BACKGROUND: Experimental and cross-sectional evidence has suggested a potential role of infection in the ethology of Parkinson's disease (PD). We aim to examine the longitudinal association of infections with the incidence of PD and to explore whether the increased risk is limited to specific infection type rather than infection burden. METHODS: Based on the UK Biobank, hospital-treated infectious diseases and incident PD were ascertained through record linkage to national hospital inpatient registers. Infection burden was defined as the sum of the number of infection episodes over time and the number of co-occurring infections. The polygenic risk score (PRS) for PD was calculated. The genome-wide association studies (GWAS) used in two-sample Mendelian Randomization (MR) were obtained from observational cohort participants of mostly European ancestry. RESULTS: Hospital-treated infectious diseases were associated with an increased risk of PD (adjusted HR [aHR] 1.35 [95 % CI 1.20-1.52]). This relationship persisted when analyzing new PD cases occurring more than 10 years post-infection (aHR 1.22 [95 % CI 1.04-1.43]). The greatest PD risk was observed in neurological/eye infection (aHR 1.72 [95 % CI 1.32-2.34]), with lower respiratory tract infection (aHR 1.43 [95 % CI 1.02-1.99]) ranked the second. A dose-response association was observed between infection burden and PD risk within each PD-PRS tertile (p-trend < 0.001). Multivariable MR showed that bacterial and viral infections increase the PD risk. CONCLUSIONS: Both observational and genetic analysis suggested a causal association between infections and the risk of developing PD. A dose-response relationship between infection burden and incident PD was revealed.

Metal-doped carbon dots for biomedical applications: From design to implementation.

Carbon dots (CDs), as a new kind of fluorescent nanomaterials, show great potential for application in several fields due to their unique nano-size effect, easy surface functionalization, controllable photoluminescence, and excellent biocompatibility. Conventional preparation methods for CDs typically involve top-down and bottom-up approaches. Doping is a major step forward in CDs design methodology. Chemical doping includes both non-metal and metal doping, in which non-metal doping is an effective strategy for modulating the fluorescence properties of CDs and improving photocatalytic performance in several areas. In recent years, Metal-doped CDs have aroused the interest of academics as a promising nano-doping technique. This approach has led to improvements in the physicochemical and optical properties of CDs by altering their electron density distribution and bandgap capacity. Additionally, the issues of metal toxicity and utilization have been addressed to a large extent. In this review, we categorize metals into two major groups: transition group metals and rare-earth group metals, and an overview of recent advances in biomedical applications of these two categories, respectively. Meanwhile, the prospects and the challenges of metal-doped CDs for biomedical applications are reviewed and concluded. The aim of this paper is to break through the existing deficiencies of metal-doped CDs and fully exploit their potential. I believe that this review will broaden the insight into the synthesis and biomedical applications of metal-doped CDs.

Gaining insights into the responses of individual yeast cells to ethanol fermentation using Raman tweezers and chemometrics.

Saccharomyces cerevisiae is the most common microbe used for the industrial production of bioethanol, and it encounters various stresses that inhibit cell growth and metabolism during fermentation. However, little is currently known about the physiological changes that occur in individual yeast cells during ethanol fermentation. Therefore, in this work, Raman spectroscopy and chemometric techniques were employed to monitor the metabolic changes of individual yeast cells at distinct stages during high gravity ethanol fermentation. Raman tweezers was used to acquire the Raman spectra of individual yeast cells. Multivariate curve resolution-alternating least squares (MCR-ALS) and principal component analysis were employed to analyze the Raman spectra dataset. MCR-ALS extracted the spectra of proteins, phospholipids, and triacylglycerols and their relative contents in individual cells. Changes in intracellular biomolecules showed that yeast cells undergo three distinct physiological stages during fermentation. In addition, heterogeneity among yeast cells significantly increased in the late fermentation period, and different yeast cells may respond to ethanol stress via different mechanisms. Our findings suggest that the combination of Raman tweezers and chemometrics approaches allows for characterizing the dynamics of molecular components within individual cells. This approach can serve as a valuable tool in investigating the resistance mechanism and metabolic heterogeneity of yeast cells during ethanol fermentation.

Optical characterization of a fiber Fabry-Perot cavity: precision measurement of intra-cavity loss, transmittance, and reflectance.

We propose and demonstrate a method for characterizing the individual mirror parameters of a fiber Fabry-Perot cavity (FFPC). By measuring the reflection and transmission spectra of the FFPC with an incident laser propagating from the two mirrors of the FFPC and considering several normal or unique losses, the transmittance, reflectance, and intra-cavity loss of the individual mirrors can be determined. Due to the intrinsic limitation of cavity length, traditional powerful methods, such as the cavity ring-down technique, are not applicable to FFPCs for characterizing the parameters of individual mirrors. This scheme provides a dependable method for assessing FFPC mirrors and provides a significant capability for the implementation of strong-coupling cavity quantum electrodynamics based on FFPCs.

Highly Stable and Selective Ni/ZrO2 Nanofiber Catalysts for Efficient CO2 Methanation.

Ni-based oxides are promising catalysts for CO2 methanation. However, Ni-based catalysts also have some unresolved issues and drawbacks in practical applications. The activity and selectivity of Ni-based catalysts in CO2 methanation at low temperatures still need to be improved. Here, Ni/ZrO2 nanofibers with high surface areas (up to 101.2 m2/g) were prepared by electrospinning methods. The Ni/ZrO2-ES (also named as 66Ni/ZrO2) catalyst showed excellent catalytic performance in CO2 methanation (the CO2 conversion = 81% and CH4 selectivity = 99% at 350 °C) and excellent stability for 100 h, which was better than most reported Ni/ZrO2 catalysts. However, the comparison sample Ni/ZrO2-CP prepared by the coprecipitation method had poor catalytic performance (the CO2 conversion = 54% and CH4 selectivity = 90% at 350 °C). Within 100 h, the CO2 conversion decreased to 30% and the CH4 selectivity decreased to 52%. Both EPR and O1S XPS confirmed that Ni/ZrO2 nanofibers can form more reactive oxygen species vacancies, and CO2-TPD confirmed that nanofibers had more CO2 adsorption sites compared with the control sample Ni/ZrO2-CP. In situ DRIFTS analysis showed that bidentate carbonate and monodentate carbonate were key intermediates in CO2 methanation. The catalytic performance of Ni/ZrO2 nanofiber catalysts would be attributed to higher dispersion of Ni species on the surface of nanofibers, high specific surface area (101.2 m2/g), more oxygen vacancies, more CO2 adsorption sites, and the synergistic effect between Ni nanoparticles and ZrO2 nanofibers. This work may inspire the rational design of Ni/ZrO2 nanofiber catalysts with rich oxygen vacancies for low-temperature CO2 methanation.

An Improved Migratory Birds Optimization Algorithm for Closed- Loop Supply Chain Network Planning in a Fuzzy Environment.

Recycling of used products can provide substantial economic and environmental benefits for supply chain players. However, many factors associated with the design of closed-loop supply chain networks are uncertain in their nature, including demand, opening cost of facilities, capacity of opened facilities, transportation cost, and procurement cost. Therefore, this study proposes a novel fuzzy programming model for closed-loop supply chain network design, which directly relies on the fuzzy ranking method based on a credibility measure. The objective of the presented optimization model aims at minimizing the total cost of the network when selecting the facility locations and transportation routes between the nodes of the network. Based on the problem characteristics, a Migratory Birds Optimization Algorithm with a new product source encoding scheme is developed as a solution approach. The inspiration for the product source coding method originates from the label information of raw material supplier and manufacturing factories on product packaging, as well as the information of each logistics node on the delivery order. This novel encoding method aims to address the limitations of four traditional encoding methods: Prüfer number based encoding, spanning tree based encoding, forest data structure based encoding, and priority based encoding, thereby increasing the likelihood of heuristic algorithms finding the optimal solution. Thirty-five illustrative examples are developed to evaluate the proposed algorithm against the exact optimization method (LINGO) and a Genetic Algorithm, Ant Colony Optimization, Simulated Annealing, which are recognized as well-known metaheuristic algorithms. The results from extensive experiments show that the proposed algorithm is able to provide optimal and good-quality solutions within acceptable computational time even for large-scale numerical examples. The suitability of the model is confirmed through a meticulous sensitivity analysis. This analysis involves adjusting the confidence level incrementally from 50% to 100%, in 5% intervals, with respect to the model's uncertain parameters. Consequently, it yields valuable managerial insights. The outcomes of this research are expected to provide scientific support for related supply chain enterprises and stakeholders.

Divergent impacts of fertilization regimes on below-ground prokaryotic and eukaryotic communities in the Tibetan Plateau.

Chemical nutrient amendment by human activities can lead to environmental impacts contributing to global biodiversity loss. However, the comprehensive understanding of how below- and above-ground biodiversity shifts under fertilization regimes in natural ecosystems remains elusive. Here, we conducted a seven-year field experiment (2011-2017) and examined the effects of different fertilization on plant biodiversity and soil belowground (prokaryotic and eukaryotic) communities in the alpine meadow of the Tibetan Plateau, based on data collected in 2017. Our results indicate that nitrogen addition promoted total plant biomass but reduced the plant species richness. Conversely, phosphorus enrichment did not promote plant biomass and exhibited an unimodal pattern with plant richness. In the belowground realm, distinct responses of soil prokaryotic and eukaryotic communities were observed under fertilizer application. Specifically, soil prokaryotic diversity decreased with nitrogen enrichment, correlating with shifts in soil pH. Similarly, soil eukaryotic diversity decreased with increased phosphorous inputs, aligning with the equilibrium between soil available and total phosphorus. We also established connections between these soil organism communities with above-ground plant richness and biomass. Overall, our study contributes to a better understanding of the sustainable impacts of human-induced nutrient enrichment on the natural environment. Future research should delve deeper into the long-term effects of fertilization on soil health and ecosystem functioning, aiming to achieve a balance between agricultural productivity and environmental conservation.