DeepSub: Utilizing Deep Learning for Predicting the Number of Subunits in Homo-Oligomeric Protein Complexes.

The molecular weight (MW) of an enzyme is a critical parameter in enzyme-constrained models (ecModels). It is determined by two factors: the presence of subunits and the abundance of each subunit. Although the number of subunits (NS) can potentially be obtained from UniProt, this information is not readily available for most proteins. In this study, we addressed this gap by extracting and curating subunit information from the UniProt database to establish a robust benchmark dataset. Subsequently, we propose a novel model named DeepSub, which leverages the protein language model and Bi-directional Gated Recurrent Unit (GRU), to predict NS in homo-oligomers solely based on protein sequences. DeepSub demonstrates remarkable accuracy, achieving an accuracy rate as high as 0.967, surpassing the performance of QUEEN. To validate the effectiveness of DeepSub, we performed predictions for protein homo-oligomers that have been reported in the literature but are not documented in the UniProt database. Examples include homoserine dehydrogenase from Corynebacterium glutamicum, Matrilin-4 from Mus musculus and Homo sapiens, and the Multimerins protein family from M. musculus and H. sapiens. The predicted results align closely with the reported findings in the literature, underscoring the reliability and utility of DeepSub.

Dynamic effective connectivity in the cerebellar dorsal dentate nucleus and the cerebrum, cognitive impairment, and clinical correlates in patients with schizophrenia.

BACKGROUND: Schizophrenia (SZ) is characterized by disconnected cerebral networks. Recent studies have shown that functional connectivity between the cerebellar dorsal dentate nucleus (dDN) and cerebrum is correlated with psychotic symptoms, and processing speed in SZ patients. Dynamic effective connectivity (dEC) is a reliable indicator of brain functional status. However, the dEC between the dDN and cerebrum in patients with SZ remains largely unknown. METHODS: Resting-state functional MRI data, symptom severity, and cognitive performance were collected from 74 SZ patients and 53 healthy controls (HC). Granger causality analysis and sliding time window methods were used to calculate dDN-based dEC maps for all subjects, and k-means clustering was performed to obtain several dEC states. Finally, between-group differences in dynamic effective connectivity variability (dECV) and clinical correlations were obtained using two-sample t-tests and correlation analysis. RESULTS: We detected four dEC states from the cerebrum to the right dDN (IN states) and three dEC states from the right dDN to the cerebrum (OUT states), with SZ group having fewer transitions in the OUT states. SZ group had increased dECV from the right dDN to the right middle frontal gyrus (MFG) and left lingual gyrus (LG). Correlations were found between the dECV from the right dDN to the right MFG and symptom severity and between the dECV from the right dDN to the left LG and working memory performance. CONCLUSIONS: This study reveals a dynamic causal relationship between cerebellar dDN and the cerebrum in SZ and provides new evidence for the involvement of cerebellar neural circuits in neurocognitive functions in SZ.

Screening optimal candidates with operable, early-stage triple-negative breast cancer benefitting from capecitabine maintenance: A post-hoc analysis of the SYSUCC-001 study.

BACKGROUND: To explore whether specific clinicopathological covariates are predictive for a benefit from capecitabine maintenance in early-stage triple-negative breast cancer (TNBC) in the SYSUCC-001 phase III clinical trial. METHODS: Candidate covariates included age, menstrual status, type of surgery, postoperative chemotherapy regimen, Ki-67 percentage, histologic grade, primary tumor size, lymphovascular invasion, node status, and capecitabine medication. Their nonlinear effects were modeled by restricted cubic spline. The primary endpoint was disease-free survival (DFS). A survival prediction model was constructed using Cox proportional hazards regression analysis. RESULTS: All 434 participants (306 in development cohort and 128 in validation cohort) were analyzed. The estimated 5-year DFS in development and validation cohorts were 77.8 % (95 % CI, 72.9%-82.7 %) and 78.2 % (95 % CI, 70.9%-85.5 %), respectively. Age and node status had significant nonlinear effects on DFS. The prediction model constructed using four covariates (node status, lymphovascular invasion, capecitabine maintenance, and age) demonstrated satisfactory calibration and fair discrimination ability, with C-index of 0.722 (95 % CI, 0.662-0.781) and 0.764 (95 % CI, 0.668-0.859) in development and validation cohorts, respectively. Moreover, patient classification was conducted according to their risk scores calculated using our model, in which, notable survival benefits were reported in low-risk subpopulations. An easy-to-use online calculator for predicting benefit of capecitabine maintenance was also designed. CONCLUSIONS: The evidence-based prediction model can be readily assessed at baseline, which might help decision making in clinical practice and optimize patient stratification, especially for those with low-risk, capecitabine maintenance might be a potential strategy in the early-disease setting.

Baicalein inhibits biofilm formation of avian pathogenic Escherichia coli in vitro mainly by affecting adhesion.

Avian pathogenic Escherichia coli (APEC) is a widespread bacterium that causes significant economic losses to the poultry industry. APEC biofilm formation may result in chronic, persistent, and recurrent infections in clinics, making treatment challenging. Baicalein is a natural product that exhibits antimicrobial and antibiofilm activities. This study investigates the inhibitory effect of baicalein on APEC biofilm formation at different stages. The minimum inhibitory concentration (MIC) of baicalein on APEC was determined, and the growth curve of APEC biofilm formation was determined. The effects of baicalein on APEC biofilm adhesion, accumulation, and maturation were observed using optical microscopy, confocal laser scanning microscopy, and scanning electron microscopy. The biofilm inhibition rate of baicalein was calculated at different stages. The MIC of baicalein against APEC was 256 µg/mL. The process of APEC biofilm maturation takes approximately 48 h after incubation, with initial adhesion completed at 12 h, and cell accumulation finished at 24 h. Baicalein had a significant inhibitory effect on APEC biofilm formation at concentrations above 1 µg/mL (p < 0.01). Notably, baicalein had the highest rate of biofilm formation inhibition when added at the adhesion stage. Therefore, it can be concluded that baicalein is a potent inhibitor of APEC biofilm formation in vitro and acts, primarily by inhibiting cell adhesion. These findings suggests that baicalein has a potential application for inhibiting APEC biofilm formation and provides a novel approach for the prevention and control APEC-related diseases.

Investigating consumers' experiences with community supported agriculture: Convergent parallel design methods.

Community-supported agriculture (CSA) represents a collaborative model where local farms and community members form partnerships to facilitate the direct delivery of fresh produce from farms to consumers. This study primarily investigates the experiences of current CSA members, focusing on the key factors influencing their retention intentions. Employing a convergent parallel mixed methods approach, this study gathers and analyzes both quantitative data (such as factors affecting members' retention intentions) and qualitative data (derived from interviews reflecting members' perceptions of their CSA experiences). The integration of these datasets provides a comprehensive understanding of the factors that shape CSA membership dynamics. The research findings underscore that Convenience, Product Quality, and Positive Interactions are pivotal factors that contribute to members' Intentions to continue their CSA memberships. These insights are crucial for enhancing the services provided to CSA members and hold significant implications for the broader scope of CSA membership research. This study not only fills a critical gap in understanding the Chinese CSA context but also contributes to the global discourse on sustainable agriculture practices and community engagement.

Coffee leaf extract inhibits advanced glycation end products and their precursors: A mechanistic study.

Excessive accumulation of advanced glycation end products (AGEs) in the body is associated with diabetes and its complications. In this study, we aimed to explore the potential and mechanism of coffee leaf extract (CLE) in inhibiting the generation of AGEs and their precursors in an in vitro glycation model using bovine serum albumin and glucose (BSA-Glu) for the first time. High-performance liquid chromatography analysis revealed that CLE prepared with ultrasound pretreatment (CLE-U) contained higher levels of trigonelline, mangiferin, 3,5-dicaffeoylquinic acid, and γ-aminobutyric acid than CLE without ultrasound pretreatment (CLE-NU). The concentrations of these components, along with caffeine and rutin, were dramatically decreased when CLE-U or CLE-NU was incubated with BSA-Glu reaction mixture. Both CLE-U and CLE-NU exhibited a dose-dependent inhibition of fluorescent AGEs, carboxymethyllysine, fructosamine, 5-hydroxymethylfurfural, 3-deoxyglucosone, glyoxal, as well as protein oxidation products. Notably, CLE-U exhibited a higher inhibitory capacity compared to CLE-NU. CLE-U effectively quenched fluorescence intensity and increased the α-helix structure of the BSA-Glu complex. Molecular docking results suggested that the key bioactive compounds present in CLE-U interacted with the arginine residues of BSA, thereby preventing its glycation. Overall, this research sheds light on the possible application of CLE as a functional ingredient in combating diabetes by inhibiting the generation of AGEs.

Convergence in simulating global soil organic carbon by structurally different models after data assimilation.

Current biogeochemical models produce carbon-climate feedback projections with large uncertainties, often attributed to their structural differences when simulating soil organic carbon (SOC) dynamics worldwide. However, choices of model parameter values that quantify the strength and represent properties of different soil carbon cycle processes could also contribute to model simulation uncertainties. Here, we demonstrate the critical role of using common observational data in reducing model uncertainty in estimates of global SOC storage. Two structurally different models featuring distinctive carbon pools, decomposition kinetics, and carbon transfer pathways simulate opposite global SOC distributions with their customary parameter values yet converge to similar results after being informed by the same global SOC database using a data assimilation approach. The converged spatial SOC simulations result from similar simulations in key model components such as carbon transfer efficiency, baseline decomposition rate, and environmental effects on carbon fluxes by these two models after data assimilation. Moreover, data assimilation results suggest equally effective simulations of SOC using models following either first-order or Michaelis-Menten kinetics at the global scale. Nevertheless, a wider range of data with high-quality control and assurance are needed to further constrain SOC dynamics simulations and reduce unconstrained parameters. New sets of data, such as microbial genomics-function relationships, may also suggest novel structures to account for in future model development. Overall, our results highlight the importance of observational data in informing model development and constraining model predictions.

Unraveling the drivers for interannual variabilities of N2O fluxes from forests soils across climatic zones.

Forest soils are an important source of nitrous oxide (N2O), however, field observations of N2O emission have often exhibited large variabilities when compared with managed agricultural lands. In the last decade, the number of forest N2O studies has increased more than tenfold, but only a few of them have looked into the interannual flux variabilities from the regional scale. Here, we have collected 30 long-term N2O monitoring studies (≥ 2 years) based on a global database, and extracted variabilities (VARFlux) as well as relative variabilities (VAR%, in proportions) of annual N2O fluxes. The relationship of mean annual precipitation (MAP), mean annual temperature (MAT), and nitrogen (N) deposition with flux variabilities was examined to explore the underlying mechanisms for N2O emission on a long-term scale. Our results show that mean VARFlux is 0.43 kg N ha-1 yr-1 and VAR% is 28.68%. Across climatic zones, the subtropical forests have the largest annual N2O fluxes, as well as the largest fluctuations among annual budgets, while the tropics were the smallest. We found that the regulating factors for VARFlux and VAR% are fundamentally different, i.e., MAT and N input determine the annual fluxes as well as VARFlux while MAP and other limiting soil parameters determine VAR%. The relative contributions of different seasons to flux variabilities were also explored, indicating that N2O fluxes of warm and cool seasons are more responsible for the fluctuations in annual fluxes of the (sub)tropical and temperate forests, respectively. Overall, despite the limitation in interpretations due to few long-term studies from literature, this work highlights that significant interannual variabilities are common phenomena for N2O emission from different climatic zones forest soils; by unraveling the divergent drivers for VARFlux and VAR%, we have provided the possibility of improving N2O simulation models for constraining the heterogeneity of N2O emission processes from climatic zones forest soils.

ECMpy 2.0: A Python package for automated construction and analysis of enzyme-constrained models.

Genome-scale metabolic models (GEMs) have been widely employed to predict microorganism behaviors. However, GEMs only consider stoichiometric constraints, leading to a linear increase in simulated growth and product yields as substrate uptake rates rise. This divergence from experimental measurements prompted the creation of enzyme-constrained models (ecModels) for various species, successfully enhancing chemical production. Building upon studies that allocate macromolecule resources, we developed a Python-based workflow (ECMpy) that constructs an enzyme-constrained model. This involves directly imposing an enzyme amount constraint in GEM and accounting for protein subunit composition in reactions. However, this procedure demands manual collection of enzyme kinetic parameter information and subunit composition details, making it rather user-unfriendly. In this work, we've enhanced the ECMpy toolbox to version 2.0, broadening its scope to automatically generate ecGEMs for a wider array of organisms. ECMpy 2.0 automates the retrieval of enzyme kinetic parameters and employs machine learning for predicting these parameters, which significantly enhances parameter coverage. Additionally, ECMpy 2.0 introduces common analytical and visualization features for ecModels, rendering computational results more user accessible. Furthermore, ECMpy 2.0 seamlessly integrates three published algorithms that exploit ecModels to uncover potential targets for metabolic engineering. ECMpy 2.0 is available at https://github.com/tibbdc/ECMpy or as a pip package (https://pypi.org/project/ECMpy/).

Smartphone-assisted mobile fluorescence sensor for self-calibrated detection of anthrax biomarker, Cu2+, and cysteine in food analysis.

Dipicolinic acid (DPA), as a biomarker for Bacillus anthracis, is highly toxic at trace levels. Rapid and on-site quantitative detection of DPA is essential for maintaining food safety and public health. This work develops a dual-channel self-calibrated fluorescence sensor constructed by the YVO4:Eu and Tb-ß-diketone complex for rapid visual detection of DPA. This sensor exhibits high selectivity, fast response time, excellent detection sensitivity, and the detection limit is as low as 4.5 nM in the linear range of 0-16 µM. A smartphone APP and portable ultraviolet lamp can assemble a mobile fluorescence sensor for on-site analysis. Interestingly, adding Cu2+ ions can quench the fluorescence intensity of Tb3+. In contrast, the addition of cysteine can restore the fluorescence, allowing the accurate detection of Cu2+ ions and cysteine in environmental water and food samples. This work provides a portable sensor that facilitates real-time analysis of multiple targets in food and the environment.

Unveiling the Mechanism of the ChaiShao Shugan Formula Against Triple-Negative Breast Cancer.

Background: The ChaiShao Shugan Formula (CSSGF) is a traditional Chinese medicine formula with recently identified therapeutic value in triple-negative breast cancer (TNBC). This study aimed to elucidate the underlying mechanism of CSSGF in TNBC treatment. Methods: TNBC targets were analyzed using R and data were from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. The major ingredients and related protein targets of CSSGF were explored via the Traditional Chinese Medicine Systems Pharmacology database, and an ingredient-target network was constructed via Cytoscape to identify hub genes. The STRING database was used to construct the PPI network. GO and KEGG enrichment analyses were performed via R to obtain the main targets. The online tool Kaplan‒Meier plotter was used to identify the prognostic genes. Molecular docking was applied to the core target genes and active ingredients. MDA-MB-231 and MCF-7 cell lines were used to verify the efficacy of the various drugs. Results: A total of 4562 genes were screened as TNBC target genes. The PPI network consisted of 89 nodes and 845 edges. Our study indicated that quercetin, beta-sitosterol, luteolin and catechin might be the core ingredients of CSSGF, and EGFR and c-Myc might be the latent therapeutic targets of CSSGF in the treatment of TNBC. GO and KEGG analyses indicated that the anticancer effect of CSSGF on TNBC was mainly associated with DNA binding, transcription factor binding, and other biological processes. The related signaling pathways mainly involved the TNF-a, IL-17, and apoptosis pathways. The molecular docking data indicated that quercetin, beta-sitosterol, luteolin, and catechin had high affinity for EGFR, JUN, Caspase-3 and ESR1, respectively. In vitro, we found that CSSGF could suppress the expression of c-Myc or promote the expression of EGFR. In addition, we found that quercetin downregulates c-Myc expression in two BC cell lines. Conclusion: This study revealed the effective ingredients and latent molecular mechanism of action of CSSGF against TNBC and confirmed that quercetin could target c-Myc to induce anti-BC effects.

The relationship between the gut microbiota and oxidative stress in the cognitive function of schizophrenia: A pilot study in China.

Cognitive impairment is a core symptom of schizophrenia. The gut microbiota (GM) and oxidative stress may play important roles in the pathophysiological mechanisms of cognitive impairment. This study aimed to explore the relationship between GM and oxidative stress in the cognitive function of schizophrenia. GM obtained by 16S RNA sequencing and serum superoxide dismutase (SOD) levels from schizophrenia patients (N = 68) and healthy controls (HCs, N = 72) were analyzed. All psychiatric symptoms were assessed using the Positive and Negative Syndrome Scale (PANSS). Cognitive function was assessed using the MATRICS Consensus Cognitive Battery (MCCB). Correlation analysis was used to explore the relationship between GM, SOD, and cognitive function. Machine learning models were used to identify potential biomarkers. Compared to HCs, the relative abundances of Collinsella, undefined Ruminococcus, Lactobacillus, Eubacterium, Mogibacterium, Desulfovibrio, Bulleidia, Succinivibrio, Corynebacterium, and Atopobium were higher in patients with schizophrenia, but Faecalibacterium, Anaerostipes, Turicibacter, and Ruminococcus were lower. In patients with schizophrenia, the positive factor, general factor, and total score of MCCB positively correlated with Lactobacillus, Collinsella, and Lactobacillus, respectively; SOD negatively correlated with Eubacterium, Collinsella, Lactobacillus, Corynebacterium, Bulleidia, Mogibacterium, and Succinivibrio, but positively correlated with Faecalibacterium, Ruminococcus, and MCCB verbal learning index scores; Faecalibacterium and Turicibacter were positively correlated with MCCB visual learning index scores and speed of processing index scores, respectively. Our findings revealed a correlation between SOD and GM and confirmed that cognitive dysfunction in patients with schizophrenia involves abnormal SOD levels and GM changes.

Mycorrhizal type and tree diversity affect foliar elemental pools and stoichiometry.

Species-specific differences in nutrient acquisition strategies allow for complementary use of resources among plants in mixtures, which may be further shaped by mycorrhizal associations. However, empirical evidence of this potential role of mycorrhizae is scarce, particularly for tree communities. We investigated the impact of tree species richness and mycorrhizal types, arbuscular mycorrhizal fungi (AM) and ectomycorrhizal fungi (EM), on above- and belowground carbon (C), nitrogen (N), and phosphorus (P) dynamics. Soil and soil microbial biomass elemental dynamics showed weak responses to tree species richness and none to mycorrhizal type. However, foliar elemental concentrations, stoichiometry, and pools were significantly affected by both treatments. Tree species richness increased foliar C and P pools but not N pools. Additive partitioning analyses showed that net biodiversity effects of foliar C, N, P pools in EM tree communities were driven by selection effects, but in mixtures of both mycorrhizal types by complementarity effects. Furthermore, increased tree species richness reduced soil nitrate availability, over 2 yr. Our results indicate that positive effects of tree diversity on aboveground nutrient storage are mediated by complementary mycorrhizal strategies and highlight the importance of using mixtures composed of tree species with different types of mycorrhizae to achieve more multifunctional afforestation.

Characterization of kombucha prepared from black tea and coffee leaves: A comparative analysis of physiochemical properties, bioactive components, and bioactivities.

The utilization of coffee leaves in kombucha production has intrigued researchers; however, the lack of understanding regarding the characteristics of coffee leaf kombucha (CK) and its differentiation from black tea kombucha (BK) has impeded its application in the beverage industry. Therefore, this study aimed to characterize and compare the physiochemical properties, phytochemical compositions, antioxidant activity, and α-glucosidase inhibitory ability of kombucha prepared from the leaves of Coffea arabica (CK) and black tea (Camellia sinensis, BK) and their extracts (CT and BT). After fermentation, pH and the contents of total sugars, reducing sugars, and free amino acids of BK and CK were decreased, whereas the levels of total acids and organic acids, such as gluconic, lactic, and acetic acid were increased. Notably, the concentration of vitamin C in CK was 48.9% higher than that in BK. HPLC analysis exhibited that 5-caffeoylquinic acid in CT was significantly decreased by 48.0% in CK, whereas the levels of 3-caffeoylquinic acid and 4-caffeoylquinic acid were significantly increased after fermentation. The content of caffeine was significantly (p < 0.05) reduced by 9.5% and 22.0% in BK and CK, respectively, whereas the theobromine level was significantly increased in CK. Notably, CK has superior total phenolic and flavonoid contents and antioxidant activity than BK, whereas BK possesses higher α-glucosidase inhibitory capacity. Electronic nose analysis demonstrated that sulfur-containing organics were the main volatiles in both kombuchas, and fermentation significantly increased their levels. Our study indicates that coffee leaves are a promising resource for preparing kombucha. PRACTICAL APPLICATION: This article investigates the differences in physicochemical properties, bioactive constituents, antioxidant activity, and α-glucosidase inhibitory activity of kombucha preparation from black tea and coffee leaves. We have found that after fermentation BK had brighter soup color and higher α-glucosidase inhibitory capacity, whereas CK had higher levels of total phenols, flavonoids, vitamin C, and antioxidants and lower contents of sugars. This study provides valuable information for the preparation of CK with high-quality attributes and antioxidant activity.

Prevalence and predictive value of sarcopenia in surgically treated cholangiocarcinoma: a comprehensive review and meta-analysis.

Background: Sarcopenia, marked by a reduction in skeletal muscle mass and function, is a condition that can manifest in elderly patients with cancer and has been recognized as a possible adverse factor affecting the survival of individuals diagnosed with malignant tumors. This systematic review and meta-analysis aimed to examine the prevalence of sarcopenia in individuals with cholangiocarcinoma while concurrently investigating the potential correlations between the presence of sarcopenia and various critical factors, including survival outcomes and postoperative complications. Methods: A comprehensive search was conducted across multiple databases, including EMBASE, PubMed, Web of Science, Cochrane Library, and CNKI, employing keywords such as sarcopenia, cholangiocarcinoma, and prognosis. This research explored the prognostic value of sarcopenia on the survival of cholangiocarcinoma. The findings of this meta-analysis were presented using forest plots and a summarized effects model. The Newcastle-Ottawa Scale (NOS) was employed to evaluate the quality of the studies included in the analysis. Results: A total of 33 articles from five databases were in in the quantitative analysis. A comprehensive meta-analysis revealed that the overall prevalence of sarcopenia among individuals diagnosed with cholangiocarcinoma was43%. Moreover, the analysis revealed a significant and noteworthy correlation between sarcopenia and key clinical parameters such as overall survival (OS), Recurrence-Free Survival (RFS), and Disease-Free Survival (DFS) in patients with cholangiocarcinoma. Subgroup analysis revealed that, when categorized by various ethnicities, diagnostic techniques, and tumor locations, sarcopenia consistently retained its status as a negative predictive factor. Furthermore, sarcopenia has emerged as a risk factor for postoperative complications. All included studies had an NOS score greater than 5, indicating a high quality of evidence. Conclusion: The results suggest that sarcopenia is significantly related to survival outcomes and postoperative complications in cholangiocarcinoma. Appropriate diagnosis and treatment of sarcopenia should be implemented to improve the prognosis of individuals with cholangiocarcinoma. Systematic Review Registration: https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42023479866, identifier CRD42023479866.

A clinical update of compound heterozygosity for hemoglobin Hekinan II [a27(B8)Glu-Asp; HBA1: c.84G>T] variant in China.

BACKGROUND: Hemoglobin (Hb) Hekinan II (A27; Glu-Asp) is an α-chain variant, and its interaction with the common Southeast Asian (--SEA/) α-thalassemia (α-thal) deletion is rarely reported. This study provides a clinical update of Hb Hekinan II associated with (--SEA/) α-thal. METHODS: A total of 11 simple heterozygotes and 20 composite heterozygotes for Hb Hekinan II and (--SEA/) α-thal were included based on molecular diagnosis. RESULTS: Hb Hekinan II exhibited a significant increase in hemoglobin, mean corpuscular volume, and mean corpuscular hemoglobin content, but a decrease in red blood cell level compared with α+ thalassemia deletion. Compared with (--SEA/) α-thal, composite heterozygotes for Hb Hekinan II and (--SEA/) α-thal showed similar erythrocyte parameters. Both heterozygotes with and without (--SEA/) α-thal showed low Hb A2 level. Hb Hekinan II showed abnormal performance in high-performance liquid chromatography but not in capillary electrophoresis. CONCLUSION: Hb Hekinan II is a benign Hb variant. The heterozygotes exhibit clinically asymptomatic coinheritance with (--SEA/) α-thal having comparable hematological phenotype to simple (--SEA/) α-thal. The combination of hematological and molecular analysis helped to improve the detection rate of this rare variant.

Size, distribution, and vulnerability of the global soil inorganic carbon.

Global estimates of the size, distribution, and vulnerability of soil inorganic carbon (SIC) remain largely unquantified. By compiling 223,593 field-based measurements and developing machine-learning models, we report that global soils store 2305 ± 636 (±1 SD) billion tonnes of carbon as SIC over the top 2-meter depth. Under future scenarios, soil acidification associated with nitrogen additions to terrestrial ecosystems will reduce global SIC (0.3 meters) up to 23 billion tonnes of carbon over the next 30 years, with India and China being the most affected. Our synthesis of present-day land-water carbon inventories and inland-water carbonate chemistry reveals that at least 1.13 ± 0.33 billion tonnes of inorganic carbon is lost to inland-waters through soils annually, resulting in large but overlooked impacts on atmospheric and hydrospheric carbon dynamics.

Portable luminescent fiber- and glove-based nanosensor for multicolor visual detection of tetracycline in food samples.

An intelligent fluorescent nanoprobe (lignite-CDs-Eu) was constructed by an effective and facile method based on lignite-derived carbon dots (CDs) and lanthanide europium ions (Eu3+), which exhibited high sensitivity, low detection limit (13.35 nM) and visual color variation (from blue to red) under ultraviolet light towards tetracycline (TC) detection. Significantly, portable and economical sensors were developed using lignite-CDs-Eu immobilized fiber material of filter paper and wearable glove with the aid of color extracting and image processing application (APP) in the smartphone. Facile, fast and real-time visual detection of TC in food samples was realized. Moreover, logic gate circuit was also designed to achieve intelligent and semi-quantitative inspection of TC. To some extent, this study extended the cross-application of intelligent computer software in food analytical science, and provided a certain reference for the development of small portable detection sensors which were suitable for convenience and non-professional use in daily life.

The aging behavior of degradable plastic polylactic acid under the interaction of environmental factors.

Microplastics leaching from aging biodegradable plastics pose potential environmental threats. This study used response surface methodology (RSM) to investigate the impact of temperature, light, and humidity on the aging characteristics of polylactic acid (PLA). Key evaluation metrics included the C/O ratio, functional groups, crystallinity, surface topography, and mechanical properties. Humidity was discovered to have the greatest effect on the ageing of PLA, followed by light and temperature. The interactions between temperature and light, as well as humidity and sunlight, significantly impact the aging of PLA. XPS analysis revealed PLA underwent aging due to the cleavage of the ester bond (O-C=O), resulting in the addition of C=O and C-O. The aging process of PLA was characterized by alterations in surface morphology and augmentation in crystallinity, resulting in a decline in both tensile strength and elongation. These findings might offer insights into the aging behavior of degradable plastics under diverse environmental conditions.

Variations in the Prevalence of Anemia of Varying Severity Among Urban Non-Pregnant Women - China, 2021.

What is already known about this topic?: Anemia is a significant public health issue affecting women globally. Prior studies in China predominantly concentrated on anemia in pregnant or reproductive-age women, leaving a gap in available data concerning anemia in non-pregnant women of all age groups in China. What is added by this report?: In 2021, the prevalence of anemia and moderate to severe anemia among women aged 18 years and older in urban China was 14.8% and 5.7%, respectively. Anemia prevalence exhibited significant variations based on factors such as age, body mass index (BMI), geographic location, and socioeconomic status. What are the implications for public health practice?: The strategy for addressing anemia should account for non-pregnant women aged 30-49 years and those aged 70 years and older, taking into consideration differences related to socioeconomic development and geography.