Iterative Design of Near-Infrared Fluorescent Probes for Early Diagnosis of Alzheimer's Disease by Targeting Aß Oligomers.

Amyloid-ß oligomers (AßOs), crucial toxic proteins in early Alzheimer's disease (AD), precede the formation of Aß plaques and cognitive impairment. In this context, we present our iterative process for developing novel near-infrared fluorescent (NIRF) probes specifically targeting AßOs, aimed at early AD diagnosis. An initial screening identified compound 18 as being highly selective for AßOs. Subsequent analysis revealed that compound 20 improved serum stability while retaining affinity for AßOs. The most promising iteration, compound 37, demonstrated exceptional qualities: a high affinity for AßOs, emission in the near-infrared region, and good biocompatibility. Significantly, ex vivo double staining indicated that compound 37 detected AßOs in AD mouse brain and in vivo imaging experiments showed that compound 37 could differentiate between 4-month-old AD mice and age-matched wild-type mice. Therefore, compound 37 has emerged as a valuable NIRF probe for early detection of AD and a useful tool in exploring AD's pathological mechanisms.

Cluster Analysis of Cortical Amyloid Burden for Identifying Imaging-driven Subtypes in Mild Cognitive Impairment.

Over the past decade, Alzheimer's disease (AD) has become increasingly severe and gained greater attention. Mild Cognitive Impairment (MCI) serves as an important prodromal stage of AD, highlighting the urgency of early diagnosis for timely treatment and control of the condition. Identifying the subtypes of MCI patients exhibits importance for dissecting the heterogeneity of this complex disorder and facilitating more effective target discovery and therapeutic development. Conventional method uses clinical measurements such as cognitive score and neurophysical assessment to stratify MCI patients into two groups with early MCI (EMCI) and late MCI (LMCI), which shows their progressive stages. However, such clinical method is not designed to de-convolute the heterogeneity of the disorder. This study uses a data-driven approach to divide MCI patients into a novel grouping of two subtypes based on an amyloid dataset of 68 cortical features from positron emission tomography (PET), where each subtype has a homogeneous cortical amyloid burden pattern. Experimental evaluation including visual two-dimensional cluster distribution, Kaplan-Meier plot, genetic association studies, and biomarker distribution analysis demonstrates that the identified subtypes performs better across all metrics than the conventional EMCI and LMCI grouping.

Learning With Noisy Labels Over Imbalanced Subpopulations.

Learning with noisy labels (LNL) has attracted significant attention from the research community. Many recent LNL methods rely on the assumption that clean samples tend to have a "small loss." However, this assumption often fails to generalize to some real-world cases with imbalanced subpopulations, that is, training subpopulations that vary in sample size or recognition difficulty. Therefore, recent LNL methods face the risk of misclassifying those "informative" samples (e.g., hard samples or samples in the tail subpopulations) into noisy samples, leading to poor generalization performance. To address this issue, we propose a novel LNL method to deal with noisy labels and imbalanced subpopulations simultaneously. It first leverages sample correlation to estimate samples' clean probabilities for label correction and then utilizes corrected labels for distributionally robust optimization (DRO) to further improve the robustness. Specifically, in contrast to previous works using classification loss as the selection criterion, we introduce a feature-based metric that takes the sample correlation into account for estimating samples' clean probabilities. Then, we refurbish the noisy labels using the estimated clean probabilities and the pseudo-labels from the model's predictions. With refurbished labels, we use DRO to train the model to be robust to subpopulation imbalance. Extensive experiments on a wide range of benchmarks demonstrate that our technique can consistently improve state-of-the-art (SOTA) robust learning paradigms against noisy labels, especially when encountering imbalanced subpopulations. We provide our code in https://github.com/chenmc1996/LNL-IS.

Deep Trans-Omic Network Fusion for Molecular Mechanism of Alzheimer's Disease.

Background: There are various molecular hypotheses regarding Alzheimer's disease (AD) like amyloid deposition, tau propagation, neuroinflammation, and synaptic dysfunction. However, detailed molecular mechanism underlying AD remains elusive. In addition, genetic contribution of these molecular hypothesis is not yet established despite the high heritability of AD. Objective: The study aims to enable the discovery of functionally connected multi-omic features through novel integration of multi-omic data and prior functional interactions. Methods: We propose a new deep learning model MoFNet with improved interpretability to investigate the AD molecular mechanism and its upstream genetic contributors. MoFNet integrates multi-omic data with prior functional interactions between SNPs, genes, and proteins, and for the first time models the dynamic information flow from DNA to RNA and proteins. Results: When evaluated using the ROS/MAP cohort, MoFNet outperformed other competing methods in prediction performance. It identified SNPs, genes, and proteins with significantly more prior functional interactions, resulting in three multi-omic subnetworks. SNP-gene pairs identified by MoFNet were mostly eQTLs specific to frontal cortex tissue where gene/protein data was collected. These molecular subnetworks are enriched in innate immune system, clearance of misfolded proteins, and neurotransmitter release respectively. We validated most findings in an independent dataset. One multi-omic subnetwork consists exclusively of core members of SNARE complex, a key mediator of synaptic vesicle fusion and neurotransmitter transportation. Conclusions: Our results suggest that MoFNet is effective in improving classification accuracy and in identifying multi-omic markers for AD with improved interpretability. Multi-omic subnetworks identified by MoFNet provided insights of AD molecular mechanism with improved details.

Physiological, molecular, and environmental insights into plant nitrogen uptake, and metabolism under abiotic stresses.

Nitrogen (N) as an inorganic macronutrient is inevitable for plant growth, development, and biomass production. Many external factors and stresses, such as acidity, alkalinity, salinity, temperature, oxygen, and rainfall, affect N uptake and metabolism in plants. The uptake of ammonium (NH4 +) and nitrate (NO3 -) in plants mainly depends on soil properties. Under the sufficient availability of NO3 - (>1 mM), low-affinity transport system is activated by gene network NRT1, and under low NO3 - availability (<1 mM), high-affinity transport system starts functioning encoded by NRT2 family of genes. Further, under limited N supply due to edaphic and climatic factors, higher expression of the AtNRT2.4 and AtNRT2.5T genes of the NRT2 family occur and are considered as N remobilizing genes. The NH4 + ion is the final form of N assimilated by cells mediated through the key enzymes glutamine synthetase and glutamate synthase. The WRKY1 is a major transcription factor of the N regulation network in plants. However, the transcriptome and metabolite profiles show variations in N assimilation metabolites, including glycine, glutamine, and aspartate, under abiotic stresses. The overexpression of NO3 - transporters (OsNRT2.3a and OsNRT1.1b) can significantly improve the biomass and yield of various crops. Altering the expression levels of genes could be a valuable tool to improve N metabolism under the challenging conditions of soil and environment, such as unfavorable temperature, drought, salinity, heavy metals, and nutrient stress.

A signaling cascade mediating fruit trait development via phosphorylation-modulated nuclear accumulation of JAZ repressor.

It is generally accepted that jasmonate-ZIM domain (JAZ) repressors act to mediate jasmonate (JA) signaling via CORONATINE-INSENSITIVE1 (COI1)-mediated degradation. Here, we report a cryptic signaling cascade where a JAZ repressor, FvJAZ12, mediates multiple signaling inputs via phosphorylation-modulated subcellular translocation rather than the COI1-mediated degradation mechanism in strawberry (Fragaria vesca). FvJAZ12 acts to regulate flavor metabolism and defense response, and was found to be the target of FvMPK6, a mitogen-activated protein kinase that is capable of responding to multiple signal stimuli. FvMPK6 phosphorylates FvJAZ12 at the amino acid residues S179 and T183 adjacent to the PY residues, thereby attenuating its nuclear accumulation and relieving its repression for FvMYC2, which acts to control the expression of lipoxygenase 3 (FvLOX3), an important gene involved in JA biosynthesis and a diverse array of cellular metabolisms. Our data reveal a previously unreported mechanism for JA signaling and decipher a signaling cascade that links multiple signaling inputs with fruit trait development.

Efficiency of Protective Interventions on Irinotecan-Induced Diarrhea: A Systematic Review and Meta-Analysis.

BACKGROUND: Irinotecan is widely used in the treatment of various solid tumors, but the adverse effects from it, especially diarrhea, limit its use. Several clinical trials of prophylactic treatment of irinotecan-induced diarrhea (IID) have been ongoing, and some of the data are controversial. This encouraged us to conduct a meta-analysis of the effects of interventions on preventing IID. METHOD: This systematic review was conducted based on the PRISMA statement. We performed literature searches from PubMed, Web of Science, Embase, and Cochrane Library. The number registered in PROSPERO is CRD42022368633. After searching 1034 articles in the database and references, 8 studies were included in this meta-analysis. RESULT: The RR of high-grade diarrhea and all-grade diarrhea were 0.31 (I2 = 51%, 95% CI: 0.14-0.69; P = .004) and .76 (I2 = 65%, 95% CI: 0.62-0.93; P < .008) respectively, thus the use of intervention measures for preventing IID is effective, and the risk reduction of high-grade diarrhea was more significant. Subgroup analysis revealed that the monotherapy group (RR: 0.48, 95% CI: 0.21-1.13, I2 = 0%) and combination therapy group (RR: 0.14, 95% CI: 0.06-0.32, I2 = 0%) in the risk of high-grade diarrhea had no significant heterogeneity within the groups, and traditional herbal medicines (Kampo medicine Hangeshashin-to, PHY906 and hot ironing with Moxa Salt Packet on Tianshu and Shangjuxu) were effective preventive measures (RR:0.20, 95% CI: 0.07-0.60, I2 = 0%). The Jadad scores for traditional herbal medicines studies were 3, and the follow-up duration was only 2 to 6 weeks. CONCLUSION: This systematic review and meta-analysis suggest that preventive treatments significantly reduced the risk of high-grade and all-grade diarrhea, confirming the efficacy in the incidence and severity of IID, among which traditional herbal medicines (baicalin-containing) provided a protective effect in reducing the severity of IID. However, the traditional herbal medicines studies were of low quality. Combined irinotecan therapy can obtain better preventive effects than monotherapy of IID. These would be helpful for the prevention of IID in clinical practice.

The genetic regulatory architecture and epigenomic basis for age-related changes in rattlesnake venom.

Developmental phenotypic changes can evolve under selection imposed by age- and size-related ecological differences. Many of these changes occur through programmed alterations to gene expression patterns, but the molecular mechanisms and gene-regulatory networks underlying these adaptive changes remain poorly understood. Many venomous snakes, including the eastern diamondback rattlesnake (Crotalus adamanteus), undergo correlated changes in diet and venom expression as snakes grow larger with age, providing models for identifying mechanisms of timed expression changes that underlie adaptive life history traits. By combining a highly contiguous, chromosome-level genome assembly with measures of expression, chromatin accessibility, and histone modifications, we identified cis-regulatory elements and trans-regulatory factors controlling venom ontogeny in the venom glands of C. adamanteus. Ontogenetic expression changes were significantly correlated with epigenomic changes within genes, immediately adjacent to genes (e.g., promoters), and more distant from genes (e.g., enhancers). We identified 37 candidate transcription factors (TFs), with the vast majority being up-regulated in adults. The ontogenetic change is largely driven by an increase in the expression of TFs associated with growth signaling, transcriptional activation, and circadian rhythm/biological timing systems in adults with corresponding epigenomic changes near the differentially expressed venom genes. However, both expression activation and repression contributed to the composition of both adult and juvenile venoms, demonstrating the complexity and potential evolvability of gene regulation for this trait. Overall, given that age-based trait variation is common across the tree of life, we provide a framework for understanding gene-regulatory-network-driven life-history evolution more broadly.

Synthesis of Spiro Polycyclic N-Heterocycles and Indolecarbazoles via Merging Oxidative Coupling and Cascade Palladium-Catalyzed Intramolecular Oxidative Cyclization.

We report a step-economic strategy for the direct synthesis of spiro polycyclic N-heterocycles and indolecarbazole-fused naphthoquinones by merging oxidative coupling and cascade palladium-catalyzed intramolecular oxidative cyclization. In the protocol, bi-indolylnaphthoquinones were first synthesized by oxidative coupling of indoles and naphthoquinones. Subsequent cascade palladium-catalyzed intramolecular oxidative cyclization of bi-indolylnaphthoquinones gave spiro polycyclic N-heterocycles and indolecarbazoles. The intramolecular oxidative cyclization approach could also be realized by the presence or absence of iron catalysts under standard conditions. This protocol is featured with moderate to excellent yields, a wide substrate scope, and divergent structures of products.

Strong Interactions between Au Nanoparticles and BiVO4 Photoanode Boosts Hole Extraction for Photoelectrochemical Water Splitting.

Strong metal-support interaction (SMSI) is widely proposed as a key factor in tuning catalytic performances. Herein, the classical SMSI between Au nanoparticles (NPs) and BiVO4 (BVO) supports (Au/BVO-SMSI) is discovered and used innovatively for photoelectrochemical (PEC) water splitting. Owing to the SMSI, the electrons transfer from V4+ to Au NPs, leading to the formation of electron-rich Au species (Auδ-) and strong electronic interaction (i.e., Auδ--Ov-V4+), which readily contributes to extract photogenerated holes and promote charge separation. Benefitted from the SMSI effect, the as-prepared Au/BVO-SMSI photoanode exhibits a superior photocurrent density of 6.25 mA cm-2 at 1.23 V versus the reversible hydrogen electrode after the deposition of FeOOH/NiOOH cocatalysts. This work provides a pioneering view for extending SMSI effect to bimetal oxide supports for PEC water splitting, and guides the interfacial electronic and geometric structure modulation of photoanodes consisting of metal NPs and reducible oxides for improved solar energy conversion efficiency.

Full-length transcriptome profiling of Acanthopanax gracilistylus provides new insight into the kaurenoic acid biosynthesis pathway.

Acanthopanax gracilistylus is a deciduous plant in the family Araliaceae, which is commonly used in Chinese herbal medicine, as the root bark has functions of nourishing the liver and kidneys, removing dampness and expelling wind, and strengthening the bones and tendons. Kaurenoic acid (KA) is the main effective substance in the root bark of A. gracilistylus with strong anti-inflammatory effects. To elucidate the KA biosynthesis pathway, second-generation (DNA nanoball) and third-generation (Pacific Biosciences) sequencing were performed to analyze the transcriptomes of the A. gracilistylus leaves, roots, and stems. Among the total 505,880 isoforms, 408,954 were annotated by seven major databases. Sixty isoforms with complete open reading frames encoding 11 key enzymes involved in the KA biosynthesis pathway were identified. Correlation analysis between isoform expression and KA content identified a total of eight key genes. Six key enzyme genes involved in KA biosynthesis were validated by real-time quantitative polymerase chain reaction. Based on the sequence analysis, the spatial structure of ent-kaurene oxidase was modeled, which plays roles in the three continuous oxidations steps of KA biosynthesis. This study greatly enriches the transcriptome data of A. gracilistylus and facilitates further analysis of the function and regulation mechanism of key enzymes in the KA biosynthesis pathway. Supplementary Information: The online version contains supplementary material available at 10.1007/s12298-024-01436-7.

Antigen-Clustered Nanovaccine Achieves Long-Term Tumor Remission by Promoting B/CD 4 T Cell Crosstalk.

Current cancer vaccines using T cell epitopes activate antitumor T cell immunity through dendritic cell/macrophage-mediated antigen presentation, but they lack the ability to promote B/CD4 T cell crosstalk, limiting their anticancer efficacy. We developed antigen-clustered nanovaccine (ACNVax) to achieve long-term tumor remission by promoting B/CD4 T cell crosstalk. The topographic features of ACNVax were achieved using an iron nanoparticle core attached with an optimal number of gold nanoparticles, where the clusters of HER2 B/CD4 T cell epitopes were conjugated on the gold surface with an optimal intercluster distance of 5-10 nm. ACNVax effectively trafficked to lymph nodes and cross-linked with BCR, which are essential for stimulating B cell antigen presentation-mediated B/CD4 T cell crosstalk in vitro and in vivo. ACNVax, combined with anti-PD-1, achieved long-term tumor remission (>200 days) with 80% complete response in mice with HER2+ breast cancer. ACNVax not only remodeled the tumor immune microenvironment but also induced a long-term immune memory, as evidenced by complete rejection of tumor rechallenge and a high level of antigen-specific memory B, CD4, and CD8 cells in mice (>200 days). This study provides a cancer vaccine design strategy, using B/CD4 T cell epitopes in an antigen clustered topography, to achieve long-term durable anticancer efficacy through promoting B/CD4 T cell crosstalk.

Theoretical study of filtered and amplified PRBS phase modulation for SBS suppression in a 2.5†kW, 10†GHz monolithic fiber amplifier.

We report a theoretical and experimental study on stimulated Brillouin scattering (SBS) suppression in a monolithic fiber amplifier with filtered and amplified pseudo-random binary sequence (PRBS) phase modulation. Theoretically, we use a time-dependent three-wave coupled nonlinear system considering both active fiber and passive fiber to describe the acoustic phonon, laser, and Stokes characteristics in a fiber amplifier. The SBS threshold power after filtered PRBS phase modulation is numerically evaluated to obtain the optimal parameters, and the time-averaged distributions of the counter-pump power, laser power, and Stokes power at different positions along the fiber length of the fiber system are simulated. Also, we established a four-stage fiber amplifier system to verify our theory. The configuration of the fiber amplifier system includes a filtered and amplified PRBS phase-modulated single-frequency fiber laser, a three-stage pre-amplifier, and a counter-pumping main stage, subsequently. 2.5 kW output power with an FWHM linewidth of 9.63 GHz is accomplished by a domestic ytterbium-doped double-clad fiber with core/cladding diameters of 20.2/400  µm. The reflectivity of the main stage is 0.049‰ at the maximum output power, which indicates the proposed architecture is under the SBS threshold. The experiments verify the accuracy of the theoretical model, which provides a reliable reference for evaluating the SBS suppression capability of the high-power narrow-linewidth fiber amplifier phase modulated by the filtered and amplified PRBS signal.

[Occurrence Characteristic and Risk Assessment of Microplastics in Sishui River (Xingyang Section)].

Urban rivers are the main receptors and transporters of microplastic pollution. Understanding the occurrence and environmental risk of microplastics in urban rivers can provide theoretical basis for further control of microplastic pollution. The Sishui River, a tributary of the Yellow River, was selected as the research object. A total of nine water samples were collected from sewage outlets of the Sishui River (Xingyang section). The microplastics in the collected samples were characterized by their sizes, shapes, and colors using a microscope. It was found that microplastics were mostly in the form of transparent fibers and fragments in the water body of sewage outlets, of which the size below 500 µm was relatively high. In addition, PET and PE polymers were identified as the main types using a laser infrared imager. The correlation analysis showed that there was a significant correlation between the PET and PE, indicating that they were similar in origin. The results of the environmental risk assessment showed that the type of microplastics was the main factor affecting the assessment results, whereas the risk values of six sewage samples containing PVC were high. However, the value of pollution load index revealed a low risk level of pollutants in the study area.

Predictive performance of the variation rate of the driving pressure on the outcome of invasive mechanical ventilation in patients with acute respiratory distress syndrome.

PURPOSE: To assess the value of the driving pressure variation rate (ΔP%) in predicting the outcome of weaning from invasive mechanical ventilation in patients with acute respiratory distress syndrome. METHODS: In this case-control study, a total of 35 patients with moderate-severe acute respiratory distress syndrome were admitted to the intensive care unit between January 2022 and December 2022 and received invasive mechanical ventilation for at least 48 h were enrolled. Patients were divided into successful weaning group and failed weaning group depending on whether they could be removed from ventilator support within 14 days. Outcome measures including driving pressure, PaO2:FiO2, and positive end-expiratory pressure, etc. were assessed every 24 h from day 0 to day 14 until successful weaning was achieved. The measurement data of non-normal distribution were presented as median (Q1, Q3), and the differences between groups were compared by Wilcoxon rank sum test. And categorical data use the Chi-square test or Fisher's exact test to compare. The predictive value of ΔP% in predicting the outcome of weaning from the ventilator was analyzed using receiver operating characteristic curves. RESULTS: Of the total 35 patients included in the study, 17 were successful vs. 18 failed in weaning from a ventilator after 14 days of mechanical ventilation. The cut-off values of the median ΔP% measured by Operator 1 vs. Operator 2 in the first 4 days were ≥ 4.17% and 4.55%, respectively (p < 0.001), with the area under curve of 0.804 (sensitivity of 88.2%, specificity of 64.7%) and 0.770 (sensitivity of 88.2%, specificity of 64.7%), respectively. There was a significant difference in mechanical ventilation duration between the successful weaning group and the failure weaning group (8 (6, 13) vs. 12 (7.5, 17.3), p = 0.043). The incidence of ventilator-associated pneumonia in the successful weaning group was significantly lower than in the failed weaning group (0.2‰ vs. 2.3‰, p = 0.001). There was a significant difference noted between these 2 groups in the 28-day mortality (11.8% vs. 66.7%, p = 0.003). CONCLUSION: The median ΔP% in the first 4 days of mechanical ventilation showed good predictive performance in predicting the outcome of weaning from mechanical ventilation within 14 days. Further study is needed to confirm this finding.

ZmARF1 positively regulates low phosphorus stress tolerance via modulating lateral root development in maize.

Phosphorus (P) deficiency is one of the most critical factors for plant growth and productivity, including its inhibition of lateral root initiation. Auxin response factors (ARFs) play crucial roles in root development via auxin signaling mediated by genetic pathways. In this study, we found that the transcription factor ZmARF1 was associated with low inorganic phosphate (Pi) stress-related traits in maize. This superior root morphology and greater phosphate stress tolerance could be ascribed to the overexpression of ZmARF1. The knock out mutant zmarf1 had shorter primary roots, fewer root tip number, and lower root volume and surface area. Transcriptomic data indicate that ZmLBD1, a direct downstream target gene, is involved in lateral root development, which enhances phosphate starvation tolerance. A transcriptional activation assay revealed that ZmARF1 specifically binds to the GC-box motif in the promoter of ZmLBD1 and activates its expression. Moreover, ZmARF1 positively regulates the expression of ZmPHR1, ZmPHT1;2, and ZmPHO2, which are key transporters of Pi in maize. We propose that ZmARF1 promotes the transcription of ZmLBD1 to modulate lateral root development and Pi-starvation induced (PSI) genes to regulate phosphate mobilization and homeostasis under phosphorus starvation. In addition, ZmERF2 specifically binds to the ABRE motif of the promoter of ZmARF1 and represses its expression. Collectively, the findings of this study revealed that ZmARF1 is a pivotal factor that modulates root development and confers low-Pi stress tolerance through the transcriptional regulation of the biological function of ZmLBD1 and the expression of key Pi transport proteins.

Boosting synergism of chemo- and immuno-therapies via switching paclitaxel-induced apoptosis to mevalonate metabolism-triggered ferroptosis by bisphosphonate coordination lipid nanogranules.

Conventional chemotherapy based on cytotoxic drugs is facing tough challenges recently following the advances of monoclonal antibodies and molecularly targeted drugs. It is critical to inspire new potential to remodel the value of this classical therapeutic strategy. Here, we fabricate bisphosphonate coordination lipid nanogranules (BC-LNPs) and load paclitaxel (PTX) to boost the chemo- and immuno-therapeutic synergism of cytotoxic drugs. Alendronate in BC-LNPs@PTX, a bisphosphonate to block mevalonate metabolism, works as both the structure and drug constituent in nanogranules, where alendronate coordinated with calcium ions to form the particle core. The synergy of alendronate enhances the efficacy of paclitaxel, suppresses tumor metastasis, and alters the cytotoxic mechanism. Differing from the paclitaxel-induced apoptosis, the involvement of alendronate inhibits the mevalonate metabolism, changes the mitochondrial morphology, disturbs the redox homeostasis, and causes the accumulation of mitochondrial ROS and lethal lipid peroxides (LPO). These factors finally trigger the ferroptosis of tumor cells, an immunogenic cell death mode, which remodels the suppressive tumor immune microenvironment and synergizes with immunotherapy. Therefore, by switching paclitaxel-induced apoptosis to mevalonate metabolism-triggered ferroptosis, BC-LNPs@PTX provides new insight into the development of cytotoxic drugs and highlights the potential of metabolism regulation in cancer therapy.

Life cycle environmental impact assessment of natural gas distributed energy system.

Natural gas distributed energy is recognized as a pivotal means to enhance energy efficiency and mitigate carbon dioxide emissions through localized energy cascading. Positioned as a key option for advancing the Sustainable Development Goals, this system optimizes energy utilization near end-users. While maximizing energy efficiency, it is imperative to address potential environmental challenges. A thorough, comprehensive environmental assessment, facilitated by the life cycle assessment method, proves instrumental in meeting this standard. Employing this method enables an intuitive grasp of the environmental strengths and weaknesses inherent in natural gas distributed energy within the power structure. This insight serves as a foundation for informed project decision-making, fostering the growth of the industry. We selected six environmental impact assessment categories based on the CML 2001 method, and conducted the life cycle analysis across four stages. China's inaugural natural gas distributed energy demonstration project was chosen as a model case, and an environmental impact assessment inventory was established, utilizing survey data and literature for comprehensive data collection and analysis. Results from case testing yield environmental impact assessment outcomes, with a specific sensitivity analysis for stages with notable environmental impact factors. The study underscores that the operation phase has the highest environmental impact, comprising 78.37% of the total combined environmental impact, followed by the fuel production phase. Comparative analyses with coal-fired and conventional natural gas power generation, based on dimensionless literature data, reveal that abiotic resources depletion potential is the primary contributor to the environmental impact of 1 kWh of electricity product, constituting 52.76% of the total impact value, followed by global warming potential. Concrete strategies have been outlined for decision-making in both the operational and planning phases of natural gas distributed energy projects. The strengthening of policies is pinpointed towards grid connection and scale expansion.

Unraveling crop enzymatic browning through integrated omics.

Enzymatic browning reactions, triggered by oxidative stress, significantly compromise the quality of harvested crops during postharvest handling. This has profound implications for the agricultural industry. Recent advances have employed a systematic, multi-omics approach to developing anti-browning treatments, thereby enhancing our understanding of the resistance mechanisms in harvested crops. This review illuminates the current multi-omics strategies, including transcriptomic, proteomic, and metabolomic methods, to elucidate the molecular mechanisms underlying browning. These strategies are pivotal for identifying potential metabolic markers or pathways that could mitigate browning in postharvest systems.