Occurrence of microplastics in the headwaters of Yellow River on the Tibetan Plateau: Source analysis and ecological risk assessment.

The widespread occurrence of Microplastics (MPs) has aroused increasing concerns. However, the fate of MPs in remote areas remains poorly understood. Here, the spatial distribution, potential sources, and environmental risks of MPs were analyzed in the headstream of the Yellow River on the eastern Tibetan Plateau. The average MP abundances are (464.3 ± 200.9) items /m3 and (63.6 ± 34.7) items /kg in the water and sediment, respectively, with both majority polymer is polypropylene (PP) (water: 28.7 %; sediment: 25.2 %). The structural equation modeling and conditional fragmentation model were used in this study to analyze the source and impact factors of riverine MPs. According to the models, MPs were influenced by water quality parameters and anthropogenic activities. Furthermore, the source analysis through MP characteristics and statistical analysis showed that the main sources of MPs include domestic sewage, plastic waste disposal, and the use of agricultural plastic film. Moreover, the differences in MP sources along the river were distinguished by the conditional fragmentation model. The potential ecological risks of MPs were evaluated, resulting in relatively medium-to-low levels. Our findings will serve as important references for improving the understanding of the plateau environmental impacts of MP distribution in the headwaters of large rivers.

Injectable Nanorobot-Hydrogel Superstructure for Hemostasis and Anticancer Therapy of Spinal Metastasis.

Surgery remains the standard treatment for spinal metastasis. However, uncontrolled intraoperative bleeding poses a significant challenge for adequate surgical resection and compromises surgical outcomes. In this study, we develop a thrombin (Thr)-loaded nanorobot-hydrogel hybrid superstructure by incorporating nanorobots into regenerated silk fibroin nanofibril hydrogels. This superstructure with superior thixotropic properties is injected percutaneously and dispersed into the spinal metastasis of hepatocellular carcinoma (HCC) with easy bleeding characteristics, before spinal surgery in a mouse model. Under near-infrared irradiation, the self-motile nanorobots penetrate into the deep spinal tumor, releasing Thr in a controlled manner. Thr-induced thrombosis effectively blocks the tumor vasculature and reduces bleeding, inhibiting tumor growth and postoperative recurrence with Au nanorod-mediated photothermal therapy. Our minimally invasive treatment platform provides a novel preoperative therapeutic strategy for HCC spinal metastasis effectively controlling intraoperative bleeding and tumor growth, with potentially reduced surgical complications and enhanced operative outcomes.

Environmental fate of microplastics in high-altitude basins: the insights into the Yarlung Tsangpo River Basin.

Microplastics (MPs) have been found in remote high-altitude areas, but the main source and migration process remained unclear. This work explored the characteristics and potential sources of MPs in the Yarlung Tsangpo River Basin. The average abundances of MPs in water, sediment, and soil samples were 728.26 ± 100.53 items/m3, 43.16 ± 5.82 items/kg, and 61.92 ± 4.29 items/kg, respectively, with polypropylene and polyethylene as the main polymers. The conditional fragmentation model revealed that the major source of MPs lower than 4000 m was human activities, while that of higher than 4500 m was atmospheric deposition. Community analysis was further conducted to explore the migration process and key points of MPs among different compartments in the basin. It was found that Lhasa (3600 m) and Shigatse (4100 m) were vital sources of MPs inputs in the midstream and downstream, respectively. This work would provide new insights into the fate of MPs in high-altitude areas.

Exosomal circHIF1A derived from hypoxic-induced carcinoma-associated fibroblasts promotes hepatocellular carcinoma cell malignant phenotypes and immune escape.

Hypoxia is a hallmark of solid tumors. Cancer-associated fibroblasts (CAFs) are an important component of the tumor microenvironment, and CAF-derived exosomes are involved in cancer genesis and progression. Here, this work investigated the role and mechanism of exosomal circHIF1A derived from hypoxia-induced CAFs in hepatocellular carcinoma (HCC) tumorigenesis. CAFs isolated from fresh HCC tissues were incubated in normoxia or hypoxia condition (N/CAFs or H/CAFs), and then the exosomes from N/CAFs or H/CAFs were isolated for functional analysis. Cell proliferation, migration and invasion were analyzed by cell counting kit-8, colony formation, and transwell assays. Immune evasion was evaluated by measuring the cytotoxicity and viability of CD8+T cells. qRT-PCR and western blotting analyses were used for the level measurement of genes and proteins. The binding between Hu antigen R (HuR) and circHIF1A or Programmed death ligand 1 (PD-L1) was analyzed by RNA immunoprecipitation assay. Functionally, we found that CAFs, especially CAFs under hypoxic stress (H/CAFs), promoted the proliferation, migration, invasion and EMT progression in HCC cells, as well as induced immune escape by suppressing CD8+T cell cytotoxicity and activity in an exosome-dependent manner. H/CAFs-derived exosomes showed highly expressed circHIF1A, and could secrete circHIF1A into HCC cells via exosomes. The oncogenic effects of H/CAFs-secreted exosomes were abolished by circHIF1A knockdown. Mechanistically, circHIF1A interacted with HuR to stabilize PD-L1 expression in HCC cells. Meanwhile, circHIF1A silencing suppressed HCC cell proliferation, mobility and immune escape by regulating PD-L1 expression. In all, exosomal circHIF1A derived from hypoxic-induced CAFs promoted the proliferation, migration, invasion, EMT progression and immune escape in HCC cells by up-regulating PD-L1 expression in a HuR-dependent manner.

Chromosome-level genome assembly and population genomics reveals crucial selection for subgynoecy development in chieh-qua.

Chieh-qua is an important cucurbit crop and very popular in South China and Southeast Asia. Despite its significance, its genetic basis and domestication history are unclear. In this study, we have successfully generated a chromosome-level reference genome assembly for the chieh-qua 'A36' using a hybrid assembly strategy that combines PacBio long reads and Illumina short reads. The assembled genome of chieh-qua is approximately 953.3 Mb in size and is organized into 12 chromosomes, with contig N50 of 6.9 Mb and scaffold N50 of 68.2 Mb. Notably, the chieh-qua genome is comparable in size to the wax gourd genome. Through gene prediction analysis, we have identified a total of 24 593 protein-coding genes in the A36 genome. Additionally, approximately 56.6% (539.3 Mb) of the chieh-qua genome consists of repetitive sequences. Comparative genome analysis revealed that chieh-qua and wax gourd are closely related, indicating a close evolutionary relationship between the two species. Population genomic analysis, employing 129 chieh-qua accessions and 146 wax gourd accessions, demonstrated that chieh-qua exhibits greater genetic diversity compared to wax gourd. We also employed the GWAS method to identify related QTLs associated with subgynoecy, an interested and important trait in chieh-qua. The MYB59 (BhiCQ0880026447) exhibited relatively high expression levels in the shoot apex of four subgynoecious varieties compared with monoecious varieties. Overall, this research provides insights into the domestication history of chieh-qua and offers valuable genomic resources for further molecular research.

Establishment and verification of a prognostic model based on coagulation and fibrinolysis-related genes in hepatocellular carcinoma.

BACKGROUND: Studies have shown that coagulation and fibrinolysis (CFR) are correlated with Hepatocellular carcinoma (HCC) progression and prognosis. We aim to build a model based on CFR-correlated genes for risk assessment and prediction of HCC patient. METHODS: HCC samples were selected from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases respectively. The Molecular Signatures Database (MSigDB) was used to select the CFR genes. RiskScore model were established by single sample gene set enrichment analysis (ssGSEA), weighted correlation network analysis (WGCNA), multivariate Cox regression analysis, LASSO regression analysis. RESULTS: PCDH17, PGF, PDE2A, FAM110D, FSCN1, FBLN5 were selected as the key genes and designed a RiskScore model. Those key genes were Differential expressions in HCC cell and patients. Overexpression PDE2A inhibited HCC cell migration and invasion. The higher the RiskScore, the lower the probability of survival. The model has high AUC values in the first, third and fifth year prediction curves, indicating that the model has strong prediction performance. The difference analysis of clinicopathological features found that a great proportion of high clinicopathological grade samples showed higher RiskScore. RiskScore were positively correlated with immune scores and TIDE scores. High levels of immune checkpoints and immunomodulators were observed in high RiskScore group. High RiskScore groups may benefit greatly from taking traditional chemotherapy drugs. CONCLUSIONS: We screened CFR related genes to design a RiskScore model, which could accurately evaluate the prognosis and survival status of HCC patients, providing certain value for optimizing the clinical treatment of cancer in the future.

A multivariate analysis of microplastics in soils along the headwaters of Yangtze river on the Tibetan Plateau.

Microplastics (MPs) are among the most widespread anthropogenic pollutants of natural environments, while limited research has focused on the fate of MPs in soils along the Plateau rivers. In this study, we investigated MPs in soils along the source areas of the Yangtze River on the Qinghai-Tibet Plateau. The results showed mean MP abundance values of (89.4 ± 51.0) and (64.4 ± 24.5) items/kg of dry soils around the tributary and mainstream areas, respectively. Film, transparent colors, and polyethylene were common shape, color, and compositions, respectively. The correlation analysis and PCA revealed that MP abundance was related to soil heavy metals (Cr and Ni) and nutrients (TOC and TP) (p < 0.05). Structural equation modeling also revealed that population density was the dominant driving factor contributing to MPs, with a total effect coefficient of 0.45. In addition, the conditional fragmentation model further distinguished the differences in MP sources from upstream to downstream along the Jinsha River. The significant sources of MPs in the bare land and grasslands from the upper reaches of the Jinsha River included traffic, tourism, and atmospheric transport. In contrast, MP transport during farming activities mainly contributed to MPs in the agricultural soil in the lower reaches.

An effective strategy for assembling the sex-limited chromosome.

BACKGROUND: Most currently available reference genomes lack the sequence map of sex-limited (such as Y and W) chromosomes, which results in incomplete assemblies that hinder further research on sex chromosomes. Recent advancements in long-read sequencing and population sequencing have provided the opportunity to assemble sex-limited chromosomes without the traditional complicated experimental efforts. FINDINGS: We introduce the first computational method, Sorting long Reads of Y or other sex-limited chromosome (SRY), which achieves improved assembly results compared to flow sorting. Specifically, SRY outperforms in the heterochromatic region and demonstrates comparable performance in other regions. Furthermore, SRY enhances the capabilities of the hybrid assembly software, resulting in improved continuity and accuracy. CONCLUSIONS: Our method enables true complete genome assembly and facilitates downstream research of sex-limited chromosomes.

Associations between Life's Essential 8 and abdominal aortic calcification among US Adults: a cross-sectional study.

BACKGROUND: Cardiovascular health (CVH) and abdominal aortic calcification (AAC) are closely linked to cardiovascular disease (CVD) and related mortality. However, the relationship between CVH metrics via Life's Essential 8 (LE8) and AAC remains unexplored. METHODS: The study analyzed data from the 2013-2014 National Health and Nutrition Examination Survey (NHANES) cohort, which included adults aged 40 or above. The research used the LE8 algorithm to evaluate CVH. Semi-quantitative AAC-24 scoring techniques were employed to assess AAC, categorized into no calcification, mild to moderate calcification, and severe calcification. RESULTS: The primary analysis involved 2,478 participants. Following adjustments for multiple factors, the LE8 score exhibited a significant association with ACC risk (Mild-moderate ACC: 0.87, 95% CI: 0.81,0.93; Severe ACC: 0.77, 95% CI: 0.69,0.87, all P < 0.001), indicating an almost linear dose-response relationship. Compared to the low CVH group, the moderate CVH group showed lower odds ratios (OR) for mild-moderate and severe calcification (OR = 0.78, 95% CI: 0.61-0.99, P = 0.041; OR = 0.68, 95% CI: 0.46-0.99, P = 0.047, respectively). Moreover, the high CVH group demonstrated even lower ORs for mild-moderate and severe calcification (OR = 0.46, 95% CI: 0.31, 0.69, P < 0.001; OR = 0.29, 95% CI: 0.14, 0.59, P = 0.001, respectively). Interactions were found between chronic kidney disease (CKD) condition, history of CVD, marital status and CVH metrics to ACC. Participants without CKD exhibited a more pronounced negative association between the CVH metric and both mild-moderate and severe ACC. Those lacking a history of CVD, and never married/widowed/divorced/separated showed a stronger negative association between the CVH metric and severe ACC. CONCLUSIONS: The novel CVH metrics demonstrated an inverse correlation with the risk of AAC. These findings suggest that embracing improved CVH levels may assist in alleviating the burden of ACC.

Predicting Elimination of Small-Molecule Drug Half-Life in Pharmacokinetics Using Ensemble and Consensus Machine Learning Methods.

Half-life is a significant pharmacokinetic parameter included in the excretion phase of absorption, distribution, metabolism, and excretion. It is one of the key factors for the successful marketing of drug candidates. Therefore, predicting half-life is of great significance in drug design. In this study, we employed eXtreme Gradient Boosting (XGboost), randomForest (RF), gradient boosting machine (GBM), and supporting vector machine (SVM) to build quantitative structure-activity relationship (QSAR) models on 3512 compounds and evaluated model performance by using root-mean-square error (RMSE), R2, and mean absolute error (MAE) metrics and interpreted features by SHapley Additive exPlanation (SHAP). Furthermore, we developed consensus models through integrating four individual models and validated their performance using a Y-randomization test and applicability domain analysis. Finally, matched molecular pair analysis was used to extract the transformation rules. Our results revealed that XGboost outperformed other individual models (RMSE = 0.176, R2 = 0.845, MAE = 0.141). The consensus model integrating all four models continued to enhance prediction performance (RMSE = 0.172, R2 = 0.856, MAE = 0.138). We evaluated the reliability, robustness, and generalization ability via Y-randomization test and applicability domain analysis. Meanwhile, we utilized SHAP to interpret features and employed matched molecular pair analysis to extract chemical transformation rules that provide suggestions for optimizing drug structure. In conclusion, we believe that the consensus model developed in this study serve as a reliable tool to evaluate half-life in drug discovery, and the chemical transformation rules concluded in this study could provide valuable suggestions in drug discovery.

Toward Low-Carbon Rice Production in China: Historical Changes, Driving Factors, and Mitigation Potential.

Under the "Double Carbon" target, the development of low-carbon agriculture requires a holistic comprehension of spatially and temporally explicit greenhouse gas (GHG) emissions associated with agricultural products. However, the lack of systematic evaluation at a fine scale presents considerable challenges in guiding localized strategies for mitigating GHG emissions from crop production. Here, we analyzed the county-level carbon footprint (CF) of China's rice production from 2007 to 2018 by coupling life cycle assessment and the DNDC model. Results revealed a significant annual increase of 74.3 kg CO2-eq ha-1 in the average farm-based CF (FCF), while it remained stable for the product-based CF (PCF). The CF exhibited considerable variations among counties, ranging from 2324 to 20,768 kg CO2-eq ha-1 for FCF and from 0.36 to 3.81 kg CO2-eq kg-1 for PCF in 2018. The spatiotemporal heterogeneities of FCF were predominantly influenced by field CH4 emissions, followed by diesel consumption and soil organic carbon sequestration. Scenario analysis elucidates that the national total GHG emissions from rice production could be significantly reduced through optimized irrigation (48.5%) and straw-based biogas production (18.0%). Moreover, integrating additional strategies (e.g., advanced crop management, optimized fertilization, and biodiesel application) could amplify the overall emission reduction to 76.7% while concurrently boosting the rice yield by 11.8%. Our county-level research provides valuable insights for the formulation of targeted GHG mitigation policies in rice production, thereby advancing the pursuit of carbon-neutral agricultural practices.

Standardization of monitoring data reassesses spatial distribution of aquatic microplastics concentrations worldwide.

Microplastics are found in continental and oceanic waters worldwide, but their spatial distribution shows an intricate pattern. Their driving factors remain difficult to identify and widely discussed due to insufficient and unstandardized monitoring data. Here, based on in situ experiments and hundreds of river samples from the Qinghai-Tibet Plateau, we formulate a model to standardize aquatic microplastic measurements. The model was applied to existing data on a global scale. These data are standardized to a 20 µm mesh size, resulting in a new spatial distribution of aquatic microplastic densities, with average concentrations of 554.93 ± 1352.42 items/m3 in Europe, 2558.90 ± 4799.62 in North America and 1741.94 ± 3225.09 in Asia. Excessive contaminations (microplastic concentration > 104 items/m3) are in the Yangtze River, the Charleston Harbor Estuary, the Bodega Bay and the Winyah Bay. We show that, based on these standardized concentrations, new driving factors could be used to predict the global or regional microplastic distribution in continental waters, such as the Human Development Index with a correlation of 75.86% on a global scale, the nighttime lights with a correlation of 37.26 ± 0.30% in Europe and 39.02 ± 0.54% in Asia, and the Mismanagement Plastic Waste with a correlation of 61.21 ± 19.86% in North America. Mapping standardized concentrations of aquatic microplastics enables a better comparison of contamination levels between regions and reveals more accurate hotspots to better adapt remediation efforts and future plastic pollution scenarios.

Association of the triglyceride-glucose index with all-cause and cardiovascular mortality in patients with cardiometabolic syndrome: a national cohort study.

OBJECTIVE: This study aimed to evaluate the association of triglyceride-glucose (TyG) index with all-cause and cardiovascular mortality risk among patients with cardiometabolic syndrome (CMS). METHODS: We performed a cohort study of 5754 individuals with CMS from the 2001-2018 National Health and Nutrition Examination Survey. The TyG index was calculated as Ln [fasting triglycerides (mg/dL) × fasting glucose (mg/dL)/2]. Multivariate Cox proportional hazards regression models assessed the associations between TyG index and mortality . Non-linear correlations and threshold effects were explored using restricted cubic splines and a two-piecewise Cox proportional hazards model. RESULTS: Over a median follow-up of 107 months, 1201 all-cause deaths occurred, including 398 cardiovascular disease-related deaths. The multivariate Cox proportional hazards regression model showed a positive association between the TyG index and all-cause and cardiovascular mortality. Each one-unit increase in the TyG index was associated with a 16% risk increase in all-cause mortality (HR: 1.16, 95% CI 1.03, 1.31, P = 0.017) and a 39% risk increase in cardiovascular mortality (HR: 1.39, 95% CI 1.14, 1.71, P = 0.001) after adjusting for confounders. The restricted cubic splines revealed a U-shaped association between the TyG index and all-cause (P for nonlinear < 0.001) and cardiovascular mortality (P for nonlinear = 0.044), identifying threshold values (all-cause mortality: 9.104; cardiovascular mortality: 8.758). A TyG index below these thresholds displayed a negative association with all-cause mortality (HR: 0.58, 95% CI 0.38, 0.90, P = 0.015) but not with cardiovascular mortality (HR: 0.39, 95% CI 0.12, 1.27, P = 0.119). Conversely, a TyG index exceeding these thresholds was positively associated with all-cause and cardiovascular mortality (HR: 1.35, 95% CI 1.17, 1.55, P < 0.001; HR: 1.54, 95% CI 1.25, 1.90, P < 0.001, respectively). Notably, a higher TyG index (≥ threshold values) was significantly associated with increased mortality only among individuals aged under 55 compared to those with a lower TyG index (< threshold values). CONCLUSIONS: The TyG index demonstrated a U-shaped correlation with all-cause and cardiovascular mortality in individuals with CMS. The thresholds of 9.104 and 8.758 for all-cause and cardiovascular mortality, respectively, may be used as intervention targets to reduce the risk of premature death and cardiovascular disease.

Effect of Ticagrelor versus Clopidogrel on All-Cause and Cardiovascular Mortality in Acute Coronary Syndrome Patients with Hyperuricemia.

BACKGROUND AND OBJECTIVE: The relationship between hyperuricemia and mortality in patients with acute coronary syndrome (ACS) is considerably controversial. Additionally, the strategy of dual antiplatelet therapy (DAPT) has not been evaluated in patients with ACS with hyperuricemia. This study aims to evaluate the impact of hyperuricemia on the prognosis of ACS and explore the efficacy of ticagrelor compared with clopidogrel in patients with hyperuricemia. METHODS: The study enrolled 4319 patients divided into hyperuricemia (HUA, n = 1060) and normouricemia (NUA, n = 3259) groups. The inverse probability of treatment weighting (IPTW)-adjusted Cox regression analysis was used to evaluate the impact of ticagrelor versus clopidogrel on all-cause and cardiovascular mortality. RESULTS: Hyperuricemia significantly increased the risk of all-cause death compared with patients with NUA at 7 days [adjusted hazard ratio (HR): 4.292, 95% confidence interval (CI) 1.727-10.67]; P = 0.002), 14 days (adjusted HR: 2.871, 95% CI 1.326-6.219; P = 0.0074), 30 days (adjusted HR: 2.168, 95% CI 1.056-4.453; P = 0.035), 3 months (adjusted HR: 2.018, 95% CI 1.152-3.533; P = 0.0144) and 1 year (adjusted HR: 1.702, 95% CI 1.137-2.548; P = 0.009). No significant difference was found between ticagrelor and clopidogrel in 1-year all-cause mortality [7.0% versus 5.5%, adjusted HR: 1.114 (95% CI 0.609-2.037), P = 0.725] among patients with concomitant hyperuricemia. CONCLUSION: Hyperuricemia was independently related to an increased risk of all-cause and cardiovascular death in patients with ACS undergoing PCI. At 1-year follow-up, there were no significant differences between ticagrelor and clopidogrel concerning all-cause and cardiovascular death in patients with hyperuricemia.

DeepRisk network: an AI-based tool for digital pathology signature and treatment responsiveness of gastric cancer using whole-slide images.

BACKGROUND: Digital histopathology provides valuable information for clinical decision-making. We hypothesized that a deep risk network (DeepRisk) based on digital pathology signature (DPS) derived from whole-slide images could improve the prognostic value of the tumor, node, and metastasis (TNM) staging system and offer chemotherapeutic benefits for gastric cancer (GC). METHODS: DeepRisk is a multi-scale, attention-based learning model developed on 1120 GCs in the Zhongshan dataset and validated with two external datasets. Then, we assessed its association with prognosis and treatment response. The multi-omics analysis and multiplex Immunohistochemistry were conducted to evaluate the potential pathogenesis and spatial immune contexture underlying DPS. RESULTS: Multivariate analysis indicated that the DPS was an independent prognosticator with a better C-index (0.84 for overall survival and 0.71 for disease-free survival). Patients with low-DPS after neoadjuvant chemotherapy responded favorably to treatment. Spatial analysis indicated that exhausted immune clusters and increased infiltration of CD11b+CD11c+ immune cells were present at the invasive margin of high-DPS group. Multi-omics data from the Cancer Genome Atlas-Stomach adenocarcinoma (TCGA-STAD) hint at the relevance of DPS to myeloid derived suppressor cells infiltration and immune suppression. CONCLUSION: DeepRisk network is a reliable tool that enhances prognostic value of TNM staging and aid in precise treatment, providing insights into the underlying pathogenic mechanisms.

Single-Component Dual-Functional Autoboost Strategy by Dual Photodynamic and Cyclooxygenase-2 Inhibition for Lung Cancer and Spinal Metastasis.

Coloading adjuvant drugs or biomacromolecules with photosensitizers into nanoparticles to enhance the efficiency of photodynamic therapy (PDT) is a common strategy. However, it is difficult to load positively charged photosensitizers and negatively charged adjuvants into the same nanomaterial and further regulate drug release simultaneously. Herein, a single-component dual-functional prodrug strategy is reported for tumor treatment specifically activated by tumor microenvironment (TME)-generated HOCl. A representative prodrug (DHU-CBA2) is constructed using indomethacin grafted with methylene blue (MB). DHU-CBA2 exhibited high sensitivity toward HOCl and achieved simultaneous release of dual drugs in vitro and in vivo. DHU-CBA2 shows effective antitumor activity against lung cancer and spinal metastases via PDT and cyclooxygenase-2 (COX-2) inhibition. Mechanistically, PDT induces immunogenic cell death but stimulates the gene encoding COX-2. Downstream prostaglandins E2 and Indoleamine 2,3 dioxygenase 1 (IDO1) mediate immune escape in the TME, which is rescued by the simultaneous release of indomethacin. DHU-CBA2 promotes infiltration and function of CD8+ T cells, thus inducing a robust antitumor immune response. This work provides an autoboost strategy for a single-component dual-functional prodrug activated by TME-specific HOCl, thereby achieving favorable tumor treatment via the synergistic therapy of PDT and a COX-2 inhibitor.

Strategies to Promote the Journey of Nanoparticles Against Biofilm-Associated Infections.

Biofilm-associated infections are one of the most challenging healthcare threats for humans, accounting for 80% of bacterial infections, leading to persistent and chronic infections. The conventional antibiotics still face their dilemma of poor therapeutic effects due to the high tolerance and resistance led by bacterial biofilm barriers. Nanotechnology-based antimicrobials, nanoparticles (NPs), are paid attention extensively and considered as promising alternative. This review focuses on the whole journey of NPs against biofilm-associated infections, and to clarify it clearly, the journey is divided into four processes in sequence as 1) Targeting biofilms, 2) Penetrating biofilm barrier, 3) Attaching to bacterial cells, and 4) Translocating through bacterial cell envelope. Through outlining the compositions and properties of biofilms and bacteria cells, recent advances and present the strategies of each process are comprehensively discussed to combat biofilm-associated infections, as well as the combined strategies against these infections with drug resistance, aiming to guide the rational design and facilitate wide application of NPs in biofilm-associated infections.

PPAR γ activation in chondrocytes alleviates glucocorticoid-induced oxidative stress, mitochondrial impairment, and pyroptosis via autophagic flow enhancement.

Osteoarthritis (OA) is a progressive age-related disease characterised by pathological changes in the synovium, articular cartilage, and subchondral bone, significantly reducing the patients' quality of life. This study investigated the role of glucocorticoids, specifically dexamethasone, in OA progression, with a particular focus on their effects on chondrocytes. Although glucocorticoids are commonly used for OA pain relief, our research demonstrated that high concentrations of dexamethasone may accelerate OA progression by enhancing the ability of reactive oxygen species to inhibit chondrocyte autophagy, resulting in cell death and accelerated cartilage degeneration. Despite reports on the acceleration of pathogenesis and cartilage damage in some patients of OA taking corticosteroids, the mechanism behind the same has not been investigated. This necessitates an investigation of the concentration-dependent changes in the cartilage cells upon dexamethasone administration. In addition, the protective effect of PPAR γ on chondrocytes can prevent the decrease in chondrocyte autophagy and delay cartilage degeneration. Therefore, our study suggests that the therapeutic use of glucocorticoids in OA treatment should be more nuanced considering their potential detrimental effects. Future investigations should focus on the mechanisms underlying the glucocorticoid-mediated modulation of cell death processes, which could provide insights into new therapeutic strategies for OA treatment.

Genome-wide association study for stalk lodging resistance related traits in maize (Zea mays L.).

BACKGROUND: The stalk traits stalk diameter, stalk length, rind penetrometer resistance and dry matter content are important indicators for measuring lodging resistance. RESULTS: In this study, 377 inbred lines were used as the basic materials, and four stalk-related traits including stalk diameter, stalk length, rind penetrometer resistance and dry matter content of the third segment of maize, were investigated at the tasseling, grain filling, and maturity stages. 461,053 high-quality SNPs which were obtained by whole genome resequencing were used for genome-wide association study. As a result of mixed linear model analysis (P < 9.77 × 10-6), 29 significant SNPs related to traits were detected, accounting for 7.19% -15.03% of phenotypic variation, among which 4, 1, 4 and 20 SNPs were found related to rind penetrometer resistance, stalk diameter, stalk length, and dry matter content respectively. Most candidate genes are related to plant element structure, signal transduction mechanisms, inorganic ion transport and metabolism, nucleotide transport and metabolism, and transporter enzyme families. Comparing mixed linear model with generalized linear model, a total of 12 candidate genes were detected repeatedly, during which the candidate gene Zm00001d014449 were detected 5 times, with a phenotypic variation interpretation rate of 9.95% -10.84%. This gene is mainly expressed in cells with active cell division and tissue differentiation, and is involved in the formation of stalk vascular bundles and the synthesis of cell walls. Another candidate gene, Zm00001d005300, encodes the transcription factor MYB44, which regulates the dependence of salt stress signal phosphorylation, can effectively inhibit the accumulation of destructive reactive oxygen species, and has a certain resistance to non-biotic stress. In addition, this study also found that 10 unknown functional genes can be further Functional verification. CONCLUSIONS: This study helps to deepen the understanding of the genetic basis of traits related to maize stalk lodging resistance, and provides theoretical guidance for future maize lodging resistance breeding.