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Abstract Diabetic kidney disease (DKD) is the main cause of deaths due to diabetes mellitus (DM). Due to the complexity of its onset, it is difficult to achieve accurate prevention and treatment. The classically activated macrophage (M1) polarization is a crucial proinflammatory mechanism of DKD, while the interaction and cascade effects of oxidative stress and inflammatory response remain to be elucidated. A urine proteomic analysis of patients with DM indicated that peroxiredoxin 2 (PRDX2) had the higher abundance in DKD. We recently found that PRDX of parasitic protozoa Entamoeba histolytica, which was similar to human PRDX2 in amino acid sequence and spatial structure, could activate the inflammatory response of macrophages through toll-like receptor 4 (TLR4). Hence, our study was designed to explore the role of PRDX2 in chronic inflammation during DKD. Combined with in vivo and in vitro experiments, results showed that the PRDX2 was positively correlated with DKD progression and upregulated by high glucose or recombinant tumor necrosis factor-α in renal tubular epithelial cells; Besides, recombinant PRDX2 could promote M1 polarization of macrophages, and enhance the migration as well as phagocytic ability of macrophages through TLR4. In summary, our study has explored the novel role of PRDX2 in DKD to provide a basis for further research on the diagnosis and treatment of DKD.

Abstract Net primary productivity (NPP) is an important parameter reflecting vegetation growth, and water is one of the necessary factors for vegetation growth. Investigating the mutual influence between NPP and water is significant for ensuring the stable development of the ecological environment. This study focuses on the Yangtze River Basin (YRB) as the research area, and based on medium-resolution imaging spectrometer (MODIS) data, climate data, and gravity recovery and climate experiment (GRACE) data, the spatiotemporal evolution characteristics of vegetation NPP and terrestrial water storage (TWS) in the YRB from 2000 to 2022 are explored and analyzes the mutual influence of NPP with climate factors and TWS. The results show that vegetation NPP (4.10 gC·m−2·a−1) and TWS (0.55 mm) in the YRB have exhibited an increasing trend from 2000 to 2022, with a strong correlation between the two, which is related to recent environmental policies. Analysis of the impact of climate factors on NPP reveals that temperature and TWS significantly positively impact NPP changes. Furthermore, comparisons between NPP and TWS indicate that changes in TWS substantially promote plant growth. In addition, the comparison between NPP and TWS indicates that changes in TWS have an important promoting effect on plant growth. Surface water (SWS) and soil water (SM) have a significant promoting effect on plant growth, but with a strong lag, while the consumption of groundwater (GWS) has been promoting plant growth without significant lag.

Abstract The crosstalk and balance regulation of Wnt-Notch have been known to be essential for cell fate decision and tissue regeneration, however, how this balance is maintained and how the Wnt-Notch pathways are connected with cell cycle regulation is still not clear. By analyzing the molecular alterations in mouse model with accelerated aging phenotypes due to loss of p21 function in a Werner syndrome background, we observed that Wnt3 and β-Catenin were down-regulated, while Notch1 and Hes1 were up-regulated. This disruption in Wnt-Notch signaling was accompanied by the loss of intestinal stem cell compartment, increase in Bmi1 positive cells, loss of Olfm4/Lgr5 positive cells, and reduced secretory Paneth cells and goblet cells in the intestinal crypts of p21TKO mice. BrdU incorporation, cleaved caspase 3, and Tunel assay results revealed the fast turnover of intestinal epithelia, which may result in abnormal stem cell mobilization and exhaustion of the stem cell reservoir in the intestinal crypts. We further identified shift of DREAM complex towards MMB complex due to the loss of p21 as the cause for faster turnover of intestinal epithelia. Importantly, we identified the E2F1 as the transcriptional regulator for Notch1, which linked the p21-DREAM/MMB/Rb-E2F1 pathway with Wnt-Notch pathway. The overexpression of p21 rescued the DREAM pathway, as well as the imbalance of Wnt-Notch pathway. In summary, our data identify p21 as an important factor in maintaining sequential mobilization, proliferation, and homeostasis of intestinal stem cells.

Abstract Background Uncertainty remains about the long-term effects of air pollutants (AP) on multiple diseases, especially subtypes of cardiovascular disease (CVD). We aimed to assess the individual and joint associations of fine particulate matter (PM2.5), along with its chemical components, nitrogen dioxide (NO2) and ozone (O3), with risks of 32 health conditions. Methods A total of 17,566 participants in Sichuan Province, China, were included in 2018 and followed until 2022, with an average follow-up period of 4.2 years. The concentrations of AP were measured using a machine-learning approach. The Cox proportional hazards model and quantile g-computation were applied to assess the associations between AP and CVD. Results Per interquartile range (IQR) increase in PM2.5 mass, NO2, O3, nitrate, ammonium, organic matter (OM), black carbon (BC), chloride, and sulfate were significantly associated with increased risks of various conditions, with hazard ratios (HRs) ranging from 1.06 to 2.48. Exposure to multiple air pollutants was associated with total cardiovascular disease (HR 1.75, 95% confidence intervals (CIs) 1.62–1.89), hypertensive diseases (1.49, 1.38–1.62), cardiac arrests (1.52, 1.30–1.77), arrhythmia (1.76, 1.44–2.15), cerebrovascular diseases (1.86, 1.65–2.10), stroke (1.77, 1.54–2.03), ischemic stroke (1.85, 1.61–2.12), atherosclerosis (1.77, 1.57–1.99), diseases of veins, lymphatic vessels, and lymph nodes (1.32, 1.15–1.51), pneumonia (1.37, 1.16–1.61), inflammatory bowel diseases (1.34, 1.16–1.55), liver diseases (1.59, 1.43–1.77), type 2 diabetes (1.48, 1.26–1.73), lipoprotein metabolism disorders (2.20, 1.96–2.47), purine metabolism disorders (1.61, 1.38–1.88), anemia (1.29, 1.15–1.45), sleep disorders (1.54, 1.33–1.78), renal failure (1.44, 1.21–1.72), kidney stone (1.27, 1.13–1.43), osteoarthritis (2.18, 2.00–2.39), osteoporosis (1.36, 1.14–1.61). OM had max weights for joint effects of AP on many conditions. Conclusions Long-term exposure to increased levels of multiple air pollutants was associated with risks of multiple health conditions. OM accounted for substantial weight for these increased risks, suggesting it may play an important role in these associations.

Sepsis frequently leads to life-threatening organ failure due to an in appropriate response by the body to bacterial, viral, and fungal infections. In recent years, there has been an increasing interest in using nanoparticles to develop biomarkers and drug delivery systems that have significantly improved the treatment of infectious diseases. Herein, we update the most recent development of nanoparticle-based therapeutics for sepsis treatment. This article begins with a brief overview of how sepsis is triggered and its associated diseases. It also explores the differences between traditional and modern treatment approaches. Afterward, the reasons for embracing nanotechnology-based therapies for sepsis are summarized, including their ability to reduce inflammation, provide antioxidant effects, regulate cell signaling pathways, manage reactive oxygen and nitrogen species (RONS) production, control autophagy and apoptosis, clear lipopolysaccharides (LPS) from the blood, inhibits the formation of cell-free DNA and cytokine storms. Furthermore, the special emphasis is on updating the use of nanotechnology-mediated drug delivery systems, such as nanoparticles, liposomes, and exosomes, in the treatment of sepsis caused by various microorganisms. Moreover, we also discuss polymer mediated therapy and some dynamic therapeutic aspects in septecemia disease. In addition, the article highlights the challenges and a limitation associated with using drug delivery for sepsis treatment and expresses the hope that this review will accelerate the development of more effective sepsis therapies and facilitate the transition from research to practical clinical application.

Abstract Cancer is measured as a major threat to human life and is a leading cause of death. Millions of cancer patients die every year, although a burgeoning number of researchers have been making tremendous efforts to develop cancer medicine to fight against cancer. Owing to the complexity and heterogeneity of cancer, lack of ability to treat deep tumor tissues, and high toxicity to the normal cells, it complicates the therapy of cancer. However, bacterial derivative-mediated drug delivery has raised the interest of researchers in overcoming the restrictions of conventional cancer chemotherapy. In this review, we show various examples of tumor-targeting bacteria and bacterial derivatives for the delivery of anticancer drugs. This review also describes the advantages and limitations of delivering anticancer treatment drugs under regulated conditions employing these tumor-targeting bacteria and their membrane vesicles. This study highlights the substantial potential for clinical translation of bacterial-based drug carriers, improve their ability to work with other treatment modalities, and provide a more powerful, dependable, and distinctive tumor therapy. Graphical Abstract

Objective The current study aims to elucidate the critical function of hepatocyte nuclear factor 1-beta (HNF1-β) in lupus nephritis (LN) by investigating its modulation of the Derlin-1/valosin-containing protein (VCP)/VCP-interacting membrane selenoprotein (VIMP) complex, endoplasmic reticulum (ER) stress and podocyte apoptosis.Methods In vitro and in vivo models of LN were established using glomerular podocytes treated with LN serum and MRL/lpr mice, respectively. The expression levels of HNF1-β were analysed in kidney tissues from patients with LN and MRL/lpr mice. To assess the effects of HNF1-β inhibition, an adeno-associated virus vector carrying HNF1-β short hairpin was administered to MRL/lpr mice. In vitro, glomerular podocytes were transfected with HNF1-β small interfering RNA (siRNA) or HNF1-β overexpression plasmids to explore their regulatory effects on the Derlin-1/VCP/VIMP complex and podocyte apoptosis. Dual-luciferase reporter assays and chromatin immunoprecipitation (ChIP) assays were performed to investigate the transcriptional activation of Derlin-1 and VCP promoters by HNF1-β.Results A significant decrease in HNF1-β levels was observed in kidney tissues from patients with LN while MRL/lpr mice exhibited an initial compensatory increase followed by a subsequent decrease in renal HNF1-β expression. Overexpression of HNF1-β transcriptionally upregulated Derlin-1 and VCP mitigating LN serum-induced ER stress and podocyte apoptosis. In contrast, HNF1-β inhibition exacerbated renal dysfunction and structural damage in MRL/lpr mice. Interestingly, HNF1-β inhibition transcriptionally repressed ERP44, leading to calcium ions (Ca²+) release-mediated disruption and inactivation of the Derlin-1/VCP/VIMP complex. This finding suggests that HNF1-β not only regulates the expression of key proteins in the Derlin-1/VCP/VIMP complex but also influences their assembly through Ca²+ release regulation.Conclusion This study provides novel insights into the regulatory mechanisms of HNF1-β in LN emphasising its impact on the Derlin-1/VCP/VIMP complex, ER stress and podocyte apoptosis. These findings have the potential to inform the development of new diagnostic tools and therapeutic strategies for LN.

As a new vegetation index, kernel normalized difference vegetation index (KNDVI) has great advantages in monitoring regional land degradation and vegetation status. However, the research on the spatial monitoring of rocky desertification based on KNDVI and feature space model has not been reported. In this study, the KNDVI, MSAVI, NDVI, EVI and BLI were introduced to establish four feature space monitoring index. After accuracy validation and comparisons, the optimal rocky desertification monitoring model was proposed and the spatio-temporal changes of rocky desertification had been analyzed. The time scale of this study was from 2018 to 2022, and the study area was about 3412 km2. The results showed that: (1) The rocky desertification monitoring model of KNDVI-BLI had the highest accuracy with R2=0.909 and RMSE of 0.392. (2) The rocky desertification in the western, northern and southeastern parts of Qixingguan District was more severe than other parts. (3) During 2018–2022, the rocky desertification showed an exacerbating trend in Qixingguan District. The area of extremely severe rocky desertification increased by 8.24 km2, while that of severe rocky desertification increased by 20.46 km2. The research results could provide a scientific and effective monitoring method for the control of rocky desertification.

The ovary is an important reproductive and endocrine organ for the continuation of the species and the homeostasis of the body's internal environment. Arsenic exposure is a global public health problem. However, the damage to the ovaries caused by exposure to arsenic-contaminated drinking water from neonatal mice period remains unclear. Here, we showed that arsenic exposure resulted in reduced granulosa cell proliferation, diminished ovarian reserve, decreased oogenesis, and endocrine disruption in mice. Mechanistically, arsenic exposure decreased the protein level of METTL3 in granulosa cells. The m6A modification levels of mitophagy regulated gene BNIP3 in 3’UTR region was decreased in arsenic exposed granulosa cells. Meanwhile, YTHDF2, which decays mRNA, bound to the 3′UTR region of BNIP3 was also decreased in arsenic exposed ovarian granulosa cells. Thus, BNIP3 mRNA becames more stable, and mitophagy was increased. The excessive mitophagy in granulosa cells led to endocrine disruption, follicular atresia and diminished ovarian reserve. In summary, our study reveals that METTL3-dependent m6A modification regulates granulosa cell mitophagy and follicular atresia by targeting BNIP3 which are induced by arsenic exposure.

Abstract Background Cancer stem cells (CSCs) play a vital role in the occurrence, maintenance, and recurrence of solid tumors. Although, miR-145-5p can inhibit CSCs survival, poor understanding of the underlying mechanisms hamperes further therapeutic optimization for patients. Lentivirus with remarkable transduction efficiency is the most commonly used RNA carrier in research, but has shown limited tumor-targeting capability. Methods We have applied liposome to decorate lentivirus surface thereby yielding liposome-lentivirus hybrid-based carriers, termed miR-145-5p-lentivirus nanoliposome (MRL145), and systematically analyzed their potential therapeutic effects on liver CSCs (LCSCs). Results MRL145 exhibited high delivery efficiency and potent anti-tumor efficacy under in vitro and in vivo. Mechanistically, the overexpressed miR-145-5p can significantly suppress the self-renewal, migration, and invasion abilities of LCSCs by targeting Collagen Type IV Alpha 3 Chain (COL4A3). Importantly, COL4A3 can promote phosphorylating GSK-3β at ser 9 (p-GSK-3β S9) to inactivate GSK3β, and facilitate translocation of β-catenin into the nucleus to activate the Wnt/β-catenin pathway, thereby promoting self-renewal, migration, and invasion of LCSCs. Interestingly, COL4A3 could attenuate the cellular autophagy through modulating GSK3β/Gli3/VMP1 axis to promote self-renewal, migration, and invasion of LCSCs. Conclusions These findings provide new insights in mode of action of miR-145-5p in LCSCs therapy and indicates that liposome-virus hybrid carriers hold great promise in miRNA delivery. Graphical abstract

Abstract Background Medical students frequently face challenges in academic adjustment, necessitating effective support and intervention. This study aimed to investigate the impact of stressful life events on medical students’ academic adjustment, focusing on the mediating roles of depression and anxiety. It also differentiated the impacts between at-risk students (those with academic failures) and their peers respectively. Methods This case-control study involved 320 at-risk medical students and 800 other students from a university in western China. Participants anonymously completed the scales of stressful life events, depression, anxiety, and academic adjustment. T-tests, ANOVA, Pearson correlation, and structural equation modeling were employed for statistical analysis. Results Depression and anxiety were significantly more prevalent in at-risk students (46.8% and 46.1%, respectively) than in controls (34.0% and 40.3%, respectively). Notably, at-risk students had poorer academic adjustment (t = 5.43, p

Abstract Salivary extracellular vesicles (EVs) have emerged as key tools for non-invasive diagnostics, playing a crucial role in the early detection and monitoring of diseases. These EVs surpass whole saliva in biomarker detection due to their enhanced stability, which minimizes contamination and enzymatic degradation. The review comprehensively discusses methods for isolating, enriching, quantifying, and characterizing salivary EVs. It highlights their importance as biomarkers in oral diseases like periodontitis and oral cancer, and underscores their potential in monitoring systemic conditions. Furthermore, the review explores the therapeutic possibilities of salivary EVs, particularly in personalized medicine through engineered EVs for targeted drug delivery. The discussion also covers the current challenges and future prospects in the field, emphasizing the potential of salivary EVs in advancing clinical practice and disease management.

Structural lithium batteries integrated with energy storage and mechanical load‐bearing capabilities hold great promise to revolutionize lightweight transport vehicles. However, the current development of structural batteries faces critical challenges in balancing the electrochemical and mechanical properties of the electrolytes. Herein, a super strong quasi‐solid composite polymer electrolyte (QCPE) is successfully fabricated by reinforcing polyelectrolyte with 3D in situ self‐assembled metal–organic framework‐modified glass fiber (MOF@GF) soaking a small amount of liquid electrolyte, which provides continuous ion conductive pathways for fast Li+ transport and contributes to the high ambient ionic conductivity of 1.47 × 10−3 S cm−1. The micropores and abundant polar functional groups selectively restrict the transport of anions to afford a homogeneous Li+ flux and a high Li+ transference number (0.56). Simultaneously, the MOF@GF provides more effective reinforcement and a remarkably high tensile strength of 48.6 MPa, and Young's modulus of 1.66 GPa is achieved. Furthermore, the lithium metal batteries fabricated with this QCPE exhibit a long, stable operation lifespan of 2000 h and excellent cycling performance with LiFePO4 and NCM811 cathodes. This design strategy generally opens a new avenue for structural batteries with high ionic conductivity and outstanding mechanical properties, which holds great promise for industrial translation.

Abstract Malaria genomic surveillance often estimates parasite genetic relatedness using metrics such as Identity-By-Decent (IBD), yet strong positive selection stemming from antimalarial drug resistance or other interventions may bias IBD-based estimates. In this study, we use simulations, a true IBD inference algorithm, and empirical data sets from different malaria transmission settings to investigate the extent of this bias and explore potential correction strategies. We analyze whole genome sequence data generated from 640 new and 3089 publicly available Plasmodium falciparum clinical isolates. We demonstrate that positive selection distorts IBD distributions, leading to underestimated effective population size and blurred population structure. Additionally, we discover that the removal of IBD peak regions partially restores the accuracy of IBD-based inferences, with this effect contingent on the population’s background genetic relatedness and extent of inbreeding. Consequently, we advocate for selection correction for parasite populations undergoing strong, recent positive selection, particularly in high malaria transmission settings.

In order to upgrade the utilization of flue gas desulfurization (FGD) gypsum, crystal modifier aluminum sulfate (Al2(SO4)3) was added into FGD gypsum to prepare calcined gypsum by calcining at normal pressure, and the effect of Al2(SO4)3 addition on the performance of calcined gypsum was studied. The results show that the addition of Al2(SO4)3 to FGD gypsum is slightly beneficial to promote the crystallization of hemihydrate gypsum (HH) along the a-axis direction. The Al2(SO4)3 addition also has a quick-setting effect on gypsum plaster during the hydration process, meanwhile inhibiting the growth of the (020) crystal plane of dihydrate gypsum (DH), then promoting uniform growth and aggregation along the c-axis. The close stacking makes hardened gypsum body dense and improves the strength of calcined gypsum. The strength of calcined gypsum prepared by calcining FGD gypsum with Al2(SO4)3 of 0.6 wt.% at 170 ℃ for 2 h is the highest. 2 h and 7 d flexural strength are 3.80 MPa and 7.20 MPa, and 2 h and 7 d compressive strength are 9.05 MPa and 19.23 MPa, respectively. In addition, 2 h flexural and compressive strength of the calcined gypsum with 0.6 ~ 1.0 wt.% of Al2(SO4)3 prepared at 170 ~ 180 ℃ for 2 h increase by 16 ~ 22 % and 20 ~ 33 %, respectively, which is very advantageous for the high value-added reuse of FGD gypsum for the preparation of high-quality calcined gypsum.

Global changes have led to significant changes in soil erosion on the Loess Plateau. Soil erosion leads to the degradation of land resources and a decline in soil fertility, adversely affecting agricultural production and the socioeconomic situation. Therefore, revealing the spatiotemporal evolution patterns of soil erosion in the Loess Plateau region and investigating the influencing factors that contribute to soil erosion are crucial for its management and restoration. In this study, the RUSLE monthly model and the Geodetector model were utilized to reveal the spatiotemporal trends of soil erosion in the Loess Plateau from 2000 to 2020 and to determine the dominant influencing factors in different periods. The main results are as follows: (1) From 2000 to 2020, the soil erosion in the Loess Plateau initially weakened and then intensified, indicating that precipitation and precipitation intensity have different effects on surface soil. (2) From 2000 to 2015, the area experiencing slight and mild erosion increased. This is attributed to the increase in vegetation coverage in the Loess Plateau region, which has alleviated soil erosion in the area. (3) From 2000 to 2020, zones of severe soil erosion were mainly located in the cities of Yan’an and Yulin and their surrounding areas. The gravity center of soil erosion shifted northwestward from Yan’an City overall, indicating an improvement in the soil erosion conditions in the Yan’an area. (4) The predominant level of soil erosion across different land-use types was slight erosion, accounting for over 40%. This may be a result of forestry ecological projects that effectively reduce soil loss. (5) In slope zones of 0–5°, slight erosion accounted for the largest area proportion. As the slope increased, the area proportion of severe and extremely severe erosion also increased. This is attributed to the protective role of vegetation on soil in gentle slope areas. (6) From 2000 to 2020, vegetation was the dominant single factor influencing the spatiotemporal changes in soil erosion, while the interactions between vegetation and land use had the largest explanatory power, indicating that changes in land-use types partially affect variations in vegetation coverage. Our research findings could provide important data support for soil erosion control and eco-environment restoration in the Loess Plateau region.

Previous studies are mostly conducted based on sparse time series and often ignore the dramatic changes in desertification during the year. Utilizing the Landsat and MODIS data sets from 2000 to 2020, this study applied the spatio-temporal fusion algorithm to obtain the images of the study area taken at similar times in August over the past 20 years. The optimal desertification remote sensing monitoring index of Gulang County was constructed based on the feature space model, and then the spatial and temporal evolution patterns and the driving mechanism of desertification in Gulang County were revealed by using a geographic detector. The research results were as follows: (1) The ESTARFM algorithm had better applicability in constructing long time series and similar time images with the correlation coefficient R2 = 0.83 between the results of the ESTARFM fusion model and the original image; (2) the SWCI-MSAVI feature space desertification monitoring index model based on point-to-point mode had the best applicability with an overall accuracy of 95.39% and a Kappa coefficient of 0.94; (3) from 2000 to 2020, the desertification showed an increasing trend, and the degree of desertification gradually intensified from south to north in Gulang County; (4) the dominant factors in various historical periods were different, which were mainly composed of precipitation, temperature and population density. The dominant interactive factors changed from alternating dominance of natural factors and human activity factors to the co-dominance of natural factors and human activity factors. The research results could provide decision-making support for precise prevention and control of desertification in arid–semi-arid regions.

ObjectiveEphedra, widely used in clinical practice as a medicinal herb, belongs to the genus Ephedra in the family Ephedraceae. However, the presence of numerous Ephedra varieties and variants requires differentiation for accurate identification.MethodsIn this study, we employed headspace gas chromatography mass spectrometry (HS-GC-MS), ultra-high performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF-MS), and global natural products social molecular networking (GNPS) for chemical component identification. Chemometric analysis was used to analyze the differential components. Metabolic analysis and Kyoto encyclopedia of genes and genomes (KEGG) enrichment were utilized to explore the synthesis pathways of different components.ResultA total of 83 volatile and 79 non-volatile components were identified in Ephedra species. Differential analysis revealed that among the eight Ephedra stems, 18 volatile and 19 non-volatile differential compounds were discovered, whereas Ephedra roots exhibited 21 volatile and 17 non-volatile markers. Volatile compounds were enriched in four synthetic pathways, while non-volatile components were enriched in five pathways among the differentiated components.ConclusionThis study is the first to conduct a comparative analysis of chemical components in different Ephedra species and parts. It provides a foundational reference for authenticating Ephedra herbs, evaluating medicinal resources, and comparing quality in future studies.

Untreated wastewater harbors dangerous pathogens, chemicals, and pollutants, posing grave public health threats. Nowadays, there is a rising demand for eco-friendly technologies for wastewater treatment. Recently, piezoelectric materials-based wastewater treatment technology has captured considerable interest among researchers because of its noninvasiveness and rapidity. Herein, a highly efficient piezoelectric composite material is designed with chitosan-incorporated bismuth ferrite (BFO) nanocrystals, to decompose pollutants and ablate bacteria in wastewater. On one hand, piezoelectric BFO has shown exclusive piezo-coefficient for ultrasound-mediated reactive oxygen species (ROS) production. On the other hand, chitosan depicts its biocompatible nature, which not only promotes cellular adhesion but also significantly elevates the ROS production capabilities of BFO under ultrasound. The synergistic effect of these two piezoelectric units in one composite entity shows an improved ROS production, eradicating ∼87.8% of Rhodamine B within 80 min under soft ultrasound treatment (rate constant, k ≈ 0.02866 min−1). After performing the scavenger experiment, it has been found that hydroxyl radicals are the dominating factor in this case. Further, the reusability of the composite piezocatalyst is confirmed through multiple cycles (five times) of the same experiment. The high polarizability of the composite material facilitates the generation of piezoelectric power through finger tapping (∼12.05 V), producing substantial instantaneous piezo-voltage. Moreover, the sample exhibits remarkable antibacterial activity, with nearly 99% bacterial eradication within 30 min. This indicates a significant advancement in utilizing biopolymeric composites incorporated with BFO for fabricating versatile devices with multidimensional applications.

Abstract Ribosomal RNA (rRNA) modifications, essential components of ribosome structure and function, significantly impact cellular proteomics and cancer biology. These chemical modifications transcend structural roles, critically shaping ribosome functionality and influencing cellular protein profiles. In this review, the mechanisms by which rRNA modifications regulate both rRNA functions and broader cellular physiological processes are critically discussed. Importantly, by altering the translational output, rRNA modifications can shift the cellular equilibrium towards oncogenesis, thus playing a key role in cancer development and progression. Moreover, a special focus is placed on the functions of mitochondrial rRNA modifications and their aberrant expression in cancer, an area with profound implications yet largely uncharted. Dysregulation in these modifications can lead to metabolic dysfunction and apoptosis resistance, hallmark traits of cancer cells. Furthermore, the current challenges and future perspectives in targeting rRNA modifications are highlighted as a therapeutic approach for cancer treatment. In conclusion, rRNA modifications represent a frontier in cancer research, offering novel insights and therapeutic possibilities. Understanding and harnessing these modifications can pave the way for breakthroughs in cancer treatment, potentially transforming the approach to combating this complex disease.

Background The health effects of particulate matter with an aerodynamic diameter ≤2.5 μm (PM2.5) might differ depending on compositional variations. Little is known about the joint effect of PM2.5 constituents on metabolic syndrome and cardiovascular disease (CVD). This study aims to evaluate the combined associations of PM2.5 components with CVD, identify the most detrimental constituent, and further quantify the mediation effect of metabolic syndrome. Methods and Results A total of 14 427 adults were included in a cohort study in Sichuan, China, and were followed to obtain the diagnosis of CVD until 2021. Metabolic syndrome was defined by the simultaneous occurrence of multiple metabolic disorders measured at baseline. The concentrations of PM2.5 chemical constituents within a 1‐km2 grid were derived based on satellite‐ and ground‐based detection methods. Cox proportional hazard models showed that black carbon, organic matter (OM), nitrate, ammonium, chloride, and sulfate were positively associated with CVD risks, with hazard ratios (HRs) ranging from 1.24 to 2.11 (all P

BackgroundThe Barthel Index (BI) is used to standardize the grading of assessments for clinical needs, insurance support, and long-term care resource allocation in China. However, its psychometric properties among nursing home residents remain unclear. Therefore, this study aims to assess and modify the psychometric properties of BI in nursing home residents.MethodsA total of 1,402 individuals undergoing evaluation in a nursing home facility in China were included in this study from November 2021 to November 2022. Correlations between items were examined to identify the potential multicollinearity concerns. The unidimensional item response theory (IRT) was used to validate and modify the single structure of BI. Furthermore, the logistic regression/IRT hybrid DIF detection method was conducted to assess differential item functioning (DIF) between the dementia group and the normal group.ResultsThe pairing of items 5 (“bowl control”) and 6 (“bladder control”) revealed a local dependence issue, leading to their consolidation. Items 56 (bowel and bladder control) and 9 (mobility) both displayed poor fit indices and underwent category collapsing. Through the application of the generalized partial credit model, the adjusted scale displayed better fit indices, demonstrating a robust discriminative power (DC >1.5) and orderly thresholds. Furthermore, non-uniform DIF was identified in item 2 (bathing) between the dementia group and the normal group.ConclusionThe modified BI demonstrated favorable psychometric properties and proved to be suitable for evaluating nursing home residents experiencing moderate functional impairment, which may provide a precise evaluation for long-term care resource allocation. Future studies could explore integrating supplementary measurements, such as objective indices, to assess a broader spectrum of functional statuses to potentially enhance the limited precision width observed in BI.

Abstract Objective Previous studies proved the effect of long-term exposure to air pollution or physical activity (PA) on the risk of systemic inflammation-induced multimorbidity (SIIM), while the evidence regarding their joint effects was rare, especially in low- and middle-income countries. Therefore, we aimed to examine the extent of interaction or joint relations of PA and air pollution with SIIM. Methods This study included 72,172 participants from China Multi-Ethnic Cohort.The average concentrations of ambient particulate matter pollutants (PM1, PM2.5, and PM10) were estimated using satellite-based random forest models. Self-reported information on a range of physical activities related to occupation, housework, commuting, and leisure activities was collected by an interviewer-administered questionnaire. A total of 11 chronic inflammatory systemic diseases were assessed based on self-reported lifetime diagnosis or medical examinations. SIIM was defined as having ≥ 2 chronic diseases related to systemic inflammation. Logistic regression models were used to assess the complex associations of air pollution particulate matter and PA with SIIM. Results We found positive associations between long-term air pollution particulates exposure and SIIM, with odds ratios (95%CI) of 1.07 (1.03 to 1.11), 1.18 (1.13 to 1.24), and 1.08 (1.05 to 1.12) per 10 µg/m3 increase in PM1, PM2.5, and PM10. No significant multiplicative interaction was found between ambient air pollutant exposure and PA on SIIM, whereas negative additive interaction was observed between long-term exposure to PM2.5 and PA on SIIM. The positive associations between low volume PA and SIIM were stronger among those exposed to high-level air pollution particulates. Compared with individuals engaged in high volume PA and exposed to low-level ambient air pollutants, those engaged in low volume PA and exposed to high-level ambient air pollutants had a higher risk of SIIM (OR = 1.49 in PM1 exposure, OR = 1.84 in PM2.5 exposure, OR = 1.19 in PM10 exposure). Conclusions Long-term (3 years average) exposure to PM1, PM2.5, and PM10 was associated with an increased risk of SIIM. The associations were modified by PA, highlighting PA’s importance in reducing SIIM for all people, especially those living in high-level air pollution regions.

Abstract The stability of coal pillar is extremely important to the control of rock strata movement and surface subsidence. It is of great significance for mining design to analyze the stability and failure characteristics of coal and rock pillars left after mining and to study the failure characteristics and rheological properties of coal and rock with different shapes. In this paper, based on uniaxial compression and rheological tests on rock samples, the rheological properties of rock samples with different shapes were discussed by using the nonlinear theoretical mechanics and damage theory, and the rheological mechanical characteristics of coarse yellow sandstone samples under the action of different free surface areas and the same loading contact area were investigated by means of experimental research, theoretical analysis and numerical simulation. The following conclusions were drawn: the failure characteristics and dynamic change process of rock samples with different shapes under the same loading contact area are obtained by uniaxial compression test and multi-stage rheological loading. The uniaxial compressive strengths of rock samples with the same loading contact surface area and different free surface areas are inversely proportional to their free surface areas. For the round sample, the stress level in the rheological test is obviously lower than the instantaneous peak uniaxial compression strength, while for the other samples, the stress level in the rheological test is close to the instantaneous peak uniaxial compression strength. For rock all these samples, both the ratio of steady-state rheological time to final failure time and the deformation degree decrease with the increase of free surface area.

Abstract Background Head and neck squamous cell carcinoma (HNSCC) is one of the most common malignant tumors globally. Understanding the molecular basis of tumor progression and drug resistance can offer innovative strategies to enhance clinical outcomes for HNSCC patients. Methods The cytoskeletal remodeling genes associated with cisplatin resistance were screened using a PCR array. The role of alpha-actinin 1 (ACTN1) in modulating cisplatin resistance and tumorigenesis in HNSCC was evaluated both in vitro and in vivo. Co-immunoprecipitation (Co-IP), IP-mass spectrometry (MS), western blotting, dual-luciferase assay, and bioinformatics analysis were performed to elucidate the underlying mechanisms involved. Results Our study identifies ACTN1 as a crucial contributor to cisplatin resistance and tumorigenesis in HNSCC, as evidenced across cellular, animal, and patient-derived xenograft models. From a clinical perspective, overexpression of ACTN1 significantly correlates with a suboptimal response to neoadjuvant chemotherapy and reduced overall survival in HNSCC patients. Mechanistically, ACTN1 predominantly activates β-catenin-mediated signaling by promoting the interaction between myosin heavy chain 9 (MYH9) and GSK-3β, leading to the ubiquitin-dependent degradation of GSK-3β. ACTN1 also interacts with integrin β1, subsequently activating the FAK/PI3K/AKT pathway, providing an additional avenue for the activation of β-catenin signaling. Our study also unveils that the β-catenin/c-Myc axis transcriptionally regulates ACTN1, thereby creating a positive feedback loop promoting HNSCC tumorigenesis and drug resistance. Conclusions These insights underscore the novel mechanisms that highlight ACTN1's pivotal role in driving HNSCC progression and resistance to chemotherapy, suggesting ACTN1 as a promising therapeutic target in HNSCC management.

AbstractPrevious studies were mostly conducted based on two-dimensional feature space to monitor salinization, while studies on dense long-term salinization monitoring based on three-dimensional feature space have not been reported. Based on Landsat TM/ETM+/OLI images and three-dimensional feature space method, this study introduced six typical salinization surface parameters, including NDVI, salinity index, MSAVI, surface albedo, iron oxide index, wetness index to construct eight different feature space monitoring index. The optimal soil salinization monitoring index model was proposed base on field observed data and then the evolution process of salinization in Yellow River Delta (YRD) were analyzed and revealed during 1984–2022. The salinization monitoring index model of MSAVI-Albedo-IFe2O3 feature space had the highest accuracy with R2 = 0.93 and RMSE = 0.678g/kg. The spatial distribution of salinization in YRD showed an increasing trend from inland southwest to coastal northeast and the salinization intensity showed an increasing trend during 1984–2022 due to the implements of agricultural measures such as planting salt-tolerant crops, microbial remediation and fertility improvement. The rate of salinization deterioration in the northeast part was greater than others. Zones of salinization improvement were mainly located in cultivated land of the southwest parts.

Abstract Objective Little is known about the magnitude of the relation of ambient fine particulate matter (PM2.5) constituents with hyperuricemia and serum uric acid (SUA) levels. Therefore, we aimed to assess the associations and to identify the most hazardous constituent. Methods This study included 72,840 participants from the China Multi-Ethnic Cohort. Annual average concentrations of PM2.5 mass and its major 7 constituents were matched to individuals by residential address. SUA levels exceeding 7.0 mg/dL (417 μmol/L) for men and 6.0 mg/dL (357 μmol/L) for women were considered to be hyperuricemia. Multiple logistic and linear regressions were performed on the association of single exposure to PM2.5 constituents with hyperuricemia and SUA, separately. The weighted quantile sum method was applied to examine the joint effect of PM2.5 constituents on hyperuricemia/SUA. Results Significant positive associations were discovered between PM2.5 constituents and SUA/hyperuricemia. For example, the odds ratio (95% confidence interval) of hyperuricemia for per standard deviation increase of PM2.5 mass, black carbon, organic matter, ammonium, and nitrate concentrations were 1.22 (1.12–1.32), 1.17 (1.08–1.27), 1.20 (1.10–1.31), 1.21 (1.11–1.31), and 1.28 (1.18–1.40), respectively. The joint exposure to PM2.5 constituents was significantly positively correlated with hyperuricemia (1.09, 1.05–1.14) and SUA (1.05, 1.03–1.06). And the weight of nitrate was the largest (0.668 for hyperuricemia, 0.586 for SUA). Conclusions Our findings suggest that long-term exposure to PM2.5 constituents is associated with increased SUA levels and a higher risk of hyperuricemia. In particular, nitrate seems to be the main contributor. This study may help prevent hyperuricemia by promoting the introduction of precise preventive measures. Graphical Abstract

Aiming at the problems of low processing efficiency, low groove shape accuracy and poor surface quality caused by grinding wheel wear in the grinding process of Cf/SiC composite grooves. In this paper, based on the motion mode of grinding wheel grinding, the wear volume formula of grinding wheels was analyzed, and the grinding wheel wear comparison experiment of different bond diamond grinding wheels grinding Cf/SiC composite grooves was carried out, and the more suitable kind of diamond grinding wheel for grinding Cf/SiC composite grooves was selected. From the experimental results, compared with the ceramic-bonded diamond wheel and resin-bonded diamond wheel, the grinding times of electroplated diamond wheel grinding Cf/SiC composites were increased by 20 and 104, respectively, and the surface roughness of the groove was most stable and the processing damage was smallest. Therefore, the best quality of grinding Cf/SiC composites groove was obtained by the electroplated diamond grinding wheel, and its life in grinding Cf/SiC composites was the longest. At the same time, the wear mechanism of the electroplated grinding wheel was explored, the wear on the bottom surface of the electroplated grinding wheel was more serious than that on the circumferential surface. The wear on the bottom surface was mainly wear and tear, and it gradually diffused along the inner diameter of the grinding wheel with the increasing grinding times.

Abstract Background Nuclear respiratory factor 1 (NRF1) is a transcription factor that participates in several kinds of tumor, but its role in hepatocellular carcinoma (HCC) remains elusive. This study aims to explore the role of NRF1 in HCC progression and investigate the underlying mechanisms. Results NRF1 was overexpressed and hyperactive in HCC tissue and cell lines and high expression of NRF1 indicated unfavorable prognosis of HCC patients. NRF1 promoted proliferation, migration and invasion of HCC cells both in vitro and in vivo. Mechanistically, NRF1 activated ERK1/2-CREB signaling pathway by transactivating lysophosphatidylcholine acyltransferase 1 (LPCAT1), thus promoting cell cycle progression and epithelial mesenchymal transition (EMT) of HCC cells. Meanwhile, LPCAT1 upregulated the expression of NRF1 by activating ERK1/2-CREB signaling pathway, forming a positive feedback loop. Conclusions NRF1 is overexpressed in HCC and promotes HCC progression by activating LPCAT1-ERK1/2-CREB axis. NRF1 is a promising therapeutic target for HCC patients.

The desertification of the China–Mongolia–Russia Economic Corridor (CMREC), one of the six major economic corridors in the Belt and Road Initiative, has posed a great challenge to the ecological environment protection and sustainable economic development of the region. In this work, two categories of feature space models based on point–point mode and point–line mode were constructed. The optimal feature space model was used to establish the spatial–temporal change patterns of desertification in the CMREC from 2001 to 2020, and then the dominant driving factors were quantitatively determined. The conclusions demonstrated the following: (1) the monitoring accuracy of the Albedo–MSAVI desertification model based on point–point mode was the highest, at 86.47%, followed by that of the TGSI–MSAVI model based on point–line mode, at 85.71%; (2) from 2001 to 2020, the spatial distribution of desertification in the China–Mongolia–Russia Economic Corridor region showed a decreasing trend radiating outwards from the Inner Mongolia Plateau and Gobi Desert; (3) the gravity center of desertification in Chinese parts in the CMREC migrated toward the northeast, while the Mongolia and Russia parts migrated toward the southwest and southeast, respectively; and (4) from 2001 to 2020, precipitation and land use change had the greatest impacts on the evolution patterns of desertification in China and Mongolia, while topography and land use contributed greatly to the change process of desertification in Russia. The research results could provide data support for desertification control in the CMREC.

Previous studies were mostly conducted based on sparse time series and different phenological images, which often ignored the dramatic changes in salinization evolution throughout the year. Based on Landsat and moderate-resolution-imaging spectroradiometer (MODIS) images from 2000 to 2020, this study applied the Enhanced Spatial and Temporal Adaptive Reflectance Fusion Model (ESTARFM) algorithm to obtain similar phenological images for the month of April for the past 20 years. Based on the random forest algorithm, the surface parameters of the salinization were optimized, and the feature space index models were constructed. Combined with the measured ground data, the optimal monitoring index model of salinization was determined, and then the spatiotemporal evolution patterns of salinization and its driving mechanisms in the Yellow River Delta were revealed. The main conclusions were as follows: (1) The derived long-time-series and similar phenological-fusion images enable us to reveal the patterns of change in the dramatic salinization in the year that we examined using the ESTARFM algorithm. (2) The NDSI-TGDVI feature space salinization monitoring index model based on point-to-point mode had the highest accuracy of 0.92. (3) From 2000 to 2020, the soil salinization in the Yellow River Delta showed an aggravating trend. The average value of salinization during the past 20 years was 0.65, which is categorized as severe salinization. The degree of salinization gradually decreased from the northeastern coastal area to the southwestern inland area. (4) The dominant factors affecting soil salinization in different historical periods varied. The research results could provide support for decision-making regarding the precise prevention and control of salinization in the Yellow River Delta.

Previous studies have primarily focused on the extraction of highland barley crops using single phenological images, which ignored the selection of the optimal phenological period for classification. Utilizing the multiple phenological images from Sentinel-2 to construct 25 features, including spectral, red edge, vegetation, and texture features, the recursive feature elimination algorithm and the random forest algorithm (RF) were employed to optimize feature datasets for different phenological stages, which were then used for the identification and classification of high-land barley by RF. The main results were as follows: (1) Information extraction based on feature optimization combinations yielded good overall classification accuracy, with classification accuracies for highland barley being 92.56% (jointing stage), 90.90% (heading stage), 90.74% (flowering stage), 91.55% (milk ripening stage), and 90.51% (maturity stage), respectively. (2) NDVIre1 had the highest importance score (0.1792) in the feature selection combination, indicating that the red edge index contributed significantly to crop information extraction and classification. (3) The five feature variables—GLCM_Mean, RVI, homogeneity, MAX, and GLCM_Correlation—showed stability and universality in the extraction of highland barley. These results demonstrated that the images that derived from the jointing and milk ripening phenological stages had the best applicability for highland barley extraction, and the optimized feature datasets that composed of NDVIre1 were conductive to detect and monitor of highland barley crops in the mountainous regions of northwest China.

The North China Plain (NCP) serves as a critical grain-producing region in China, playing a pivotal role in ensuring the nation’s food security. A comprehensive analysis of the carbon footprint (CF) related to the cultivation of major grain crops within this region and the proposal of strategies to reduce emissions through low-carbon production methods are crucial for advancing sustainable agricultural practices in China. This study employed the lifecycle assessment (LCA) method to estimate the CF of wheat, maize, and rice crops over a period from 2013 to 2022, based on statistical data collected from five key provinces and cities in the NCP: Beijing, Tianjin, Hebei, Shandong, and Henan. Additionally, the Logarithmic Mean Divisia Index (LMDI) model was utilized to analyze the influencing factors. The results indicated that the carbon footprints per unit area (CFA) of maize, wheat, and rice increased between 2013 and 2022. Rice had the highest carbon footprint per unit yield (CFY), averaging 1.1 kg CO2-eq kg−1, with significant fluctuations over time. In contrast, the CFY of wheat and maize remained relatively stable from 2013 to 2022. Fertilizers contributed the most to CF composition, accounting for 48.8%, 48.0%, and 25.9% of the total carbon inputs for wheat, maize, and rice, respectively. The electricity used for irrigation in rice production was 31.8%, which was much higher than that of wheat (6.8%) and maize (7.1%). The LMDI model showed that the labor effect was a common suppressing factor for the carbon emissions of maize, wheat, and rice in the NCP, while the agricultural structure effect and the economic development effect were common driving factors. By improving the efficiency of fertilizer and pesticide utilization, cultivating new varieties, increasing the mechanical operation efficiency, the irrigation efficiency, and policy support, the CF of grain crop production in the NCP can be effectively reduced. These efforts will contribute to the sustainable development of agricultural practices in the NCP and support China’s efforts to achieve its “double carbon” target.

Sea ice concentration (SIC) is an important dimension for characterising the geographical features of the pan-Arctic region. Trends in SIC bring new opportunities for human activities in the Arctic region. In this paper, we propose a deep learning technology-based sea ice concentration prediction model, SICFormer, which can realise end-to-end daily sea ice concentration prediction. Specifically, the model uses a 3D-Swin Transformer as an encoder and designs a decoder to reconstruct the predicted image based on PixelShuffle. This is a new model architecture that we have proposed. Single-day SIC data from the National Snow and Ice Data Center (NSIDC) for the years 2006 to 2022 are utilised. The results of 8-day short-term prediction experiments show that the average Mean Absolute Error (MAE) of the SICFormer model on the test set over the 5 years is 1.89%, the Root Mean Squared Error (RMSE) is 5.99%, the Mean Absolute Percentage Error (MAPE) is 4.32%, and the Nash–Sutcliffe Efficiency (NSE) is 0.98. Furthermore, the current popular deep learning models for spatio-temporal prediction are employed as a point of comparison given their proven efficacy on numerous public datasets. The comparison experiments show that the SICFormer model achieves the best overall performance.

Glioblastoma multiforme (GBM), a potential public health issue, is a huge challenge for the advanced scientific realm to solve. Chemodynamic therapy (CDT) based on the Fenton reaction emerged as a state-of-the-art therapeutic modality to treat GBM. However, crossing the blood–brain barrier (BBB) to reach the GBM is another endless marathon. In this review, the physiology of the BBB has been elaborated to understand the mechanism of crossing these potential barriers to treat GBM. Moreover, the designing of Fenton-based nanomaterials has been discussed for the production of reactive oxygen species in the tumor area to eradicate the cancer cells. For effective tumor targeting, biological nanomaterials that can cross the BBB via neurovascular transport channels have also been explored. To overcome the neurotoxicity caused by inorganic nanomaterials, the use of smart nanoagents having both enhanced biocompatibility and effective tumor targeting ability to enhance the efficiency of CDT are systematically summarized. Finally, the advancements in intelligent Fenton-based nanosystems for a multimodal therapeutic approach in addition to CDT are demonstrated. Hopefully, this systematic review will provide a better understanding of Fenton-based CDT and insight into GBM treatment.