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Abstract The ATR kinase, which coordinates cellular responses to DNA replication stress, is also essential for the proliferation of normal unstressed cells. Although its role in the replication stress response is well defined, the mechanisms by which ATR supports normal cell proliferation remain elusive. Here, we show that ATR is dispensable for the viability of G0-arrested naïve B cells. However, upon cytokine-induced proliferation, Atr-deficient B cells initiate DNA replication efficiently, but by mid-S phase they display dNTP depletion, fork stalling, and replication failure. Nonetheless, productive DNA replication and dNTP levels can be restored in Atr-deficient cells by suppressing origin firing, such as partial inhibition of CDC7 and CDK1 kinase activities. Together, these findings indicate that ATR supports the proliferation of normal unstressed cells by tempering the pace of origin firing during the early S phase to avoid exhaustion of dNTPs and importantly also other replication factors.

ATR kinase is a key regulator of chromosome integrity. Here the authors by analysing the phenotype of a mouse model expressing a kinase-dead ATR, reveal the effect of ATR inhibition compared to ATR loss and its consequences for meiosis, DNA replication, checkpoint activation and genome instability .

Non-homologous end-joining is the key pathway for repairing double-stranded DNA breaks in mammalian cells. Here the authors show that PAXX promotes the accumulation of KU at DNA breaks and is essential for end-joining in cells lacking XLF.

Missense mutations in ATM kinase, a master regulator of DNA damage responses, are found in many cancers, but their impact on ATM function and implications for cancer therapy are largely unknown. Here we report that 72% of cancer-associated ATM mutations are missense mutations that are enriched around the kinase domain. Expression of kinase-dead ATM (AtmKD/-) is more oncogenic than loss of ATM (Atm-/-) in mouse models, leading to earlier and more frequent lymphomas with Pten deletions. Kinase-dead ATM protein (Atm-KD), but not loss of ATM (Atm-null), prevents replication-dependent removal of Topo-isomerase I-DNA adducts at the step of strand cleavage, leading to severe genomic instability and hypersensitivity to Topo-isomerase I inhibitors. Correspondingly, Topo-isomerase I inhibitors effectively and preferentially eliminate AtmKD/-, but not Atm-proficientor Atm-/- leukemia in animal models. These findings identify ATM kinase-domain missense mutations as a potent oncogenic event and a biomarker for Topo-isomerase I inhibitor based therapy.

Abstract The current study was to explore the prevalence and risk factors elements of pre-frailty and frailty among patients undergoing hemodialysis (HD) in central China. A cross-sectional, multi-institutional investigation was conducted. From March to May 2024, using the convenience sampling method, a total of 408 HD patients from four hospitals in Xiangyang, China, were recruited for this study. The participants’ demographics, lifestyle factors, factors related to dialysis treatment, the FRAIL scale, psychological resilience, and medical coping modes were assessed using a questionnaire. Multi-categorical logistic regression was performed to examine factors associated with pre-frailty and frailty in this population. Furthermore, to evaluate the independent relationship between frailty and psychological resilience, multiple regression analysis was used to adjust potential confounders and obtain odds ratios (OR) and 95% confidence intervals (CI). Pearson correlation analysis was used for correlation analysis among various scales. Among the 408 participants, the prevalence of pre-frailty and frailty among participants for all ages was 26.2% and 38.5%. Multivariate logistic regression analysis showed that smoking status, falls, heart disease, and psychological resilience are all associated with pre-frailty and frailty. The Pearson correlation analysis showed that resignation was positively related to frailty and negatively related to psychological resilience in patients. Confrontation and avoidance were positively related to psychological resilience. Frailty was negatively related to psychological resilience. Psychological resilience was independently linearly associated with pre-frailty (OR 0.49, 95% CI 0.32–0.75, p

Abstract Sponges harbour complex microbiomes and as ancient metazoans and important ecosystem players are emerging as powerful models to understand the evolution and ecology of symbiotic interactions. Metagenomic studies have previously described the functional features of sponge symbionts, however, little is known about the metabolic interactions and processes that occur under different environmental conditions. To address this issue, we construct here constraint-based, genome-scale metabolic networks for the microbiome of the sponge Stylissa sp. Our models define the importance of sponge-derived nutrients for microbiome stability and discover how different organic inputs can result in net heterotrophy or autotrophy of the symbiont community. The analysis further reveals the key role that a newly discovered bacterial taxon has in cross-feeding activities and how it dynamically adjusts with nutrient inputs. Our study reveals insights into the functioning of a sponge microbiome and provides a framework to further explore and define metabolic interactions in holobionts.

Abstract Low-light image enhancement aims to enhance the visibility and contrast of low-light images while eliminating complex degradation issues such as noise, artifacts, and color distortions. Most existing low-light image enhancement methods either focus on quality while neglecting computational efficiency or have limited learning and generalization capabilities. To address these issues, we propose a Bilateral Enhancement Network with signal-to-noise ratio fusion, called BiEnNet, for lightweight and generalizable low-light image enhancement. Specifically, we design a lightweight Bilateral enhancement module with SNR (Signal-to-Noise Ratio) Fusion (BSF), which serves the SNR map of the input low-light image as the interpolation weights to dynamically fuse global brightness features and local detail features extracted from a bilateral network and achieve differentiated enhancement across different regions. To improve the network’s generalization ability, we propose a Luminance Normalization (LNM) module for preprocessing and a Dual-Exposure Processing (DEP) module for post-processing. LNM divides the channels of input features into luminance-related channels and luminance independent channels, and reduces the inconsistency of the degradation distribution of input low-light images by only normalizing the luminance-related channels. DEP learns overexposure and underexposure corrections simultaneously by employing the ReLU activation function, inverting operation, and residual network, which can improve the robustness of enhancement effects under different exposure conditions while reducing network parameters. Experiments on the LOL-V1 dataset shows BiEnNet significantly increased PSNR by 8.6 $$\%$$ and SSIM by 3.6 $$\%$$ compared to FLW-Net, reduced parameters by 98.78 $$\%$$ , and improved computational speed by 52.64 $$\%$$ compared to the classical KIND.

Abstract Wazwaz Kaur Boussinesq (WKB) equation can effectively simulate the behavior of water waves in shallow water, including the nonlinear effect and dispersion phenomenon of waves, which is of great significance for understanding the dynamic process of ocean, river and other water bodies. To enrich the wave equation theory, the (3+1)-dimensional integer order derivative of WKB equation is changed to the fractional one with beta derivative. The current work deals with the fractional (3+1)-dimensional WKB equation for discussing its chaotic behavior and establishing some new analytic solutions. The chaotic properties of the equation are verified by the trend of evolution along with time, Lyapunov exponents and initial sensitivity analysis. And then complete discrimination system for polynomial method is applied to derive some trigonometric, hyperbolic, Jacobi elliptic and other solutions. The graphical demonstrations are provided for part of these solutions. From these visualized graphs, the solitary, periodic and quasi-periodic wave are shown and the effect of fractional derivatives on the equation can be seen intuitively.

Abstract This study aims to investigate the potential relationships between the systemic immune-inflammation index (SII) and body mass index (BMI), waist circumference, and the prevalence of obesity. A cross-sectional analysis was conducted on 7,645 individuals aged 20 and above from the NHANES 2017–2020. Multivariate linear regression analyses were conducted to evaluate the association of the logarithmically transformed SII (lgSII) with BMI and waist circumference. Additionally, multivariable logistic regression was utilized to explore the relationship between lgSII and the prevalence of obesity. Fitted smoothing curves and threshold-effect analysis were applied to elucidate nonlinear relationships. In the fully adjusted model, a positive relationship was observed between lgSII and BMI, waist circumference, and obesity prevalence (β = 3.13, 95% CI 2.10–4.16; β = 7.81, 95% CI 5.50–10.13; OR = 1.44, 95% CI 1.12–1.86). The variables of gender, age, race, education, marital status, poverty income ratio (PIR), energy intake, sleep disorder, smoking status, and alcohol use did not significantly modify the positive association between lgSII and obesity. However, physical activity appeared to influence the positive correlation between lgSII and obesity. Using a two-segment linear regression model, an inverted U-shaped relationship was observed between lgSII and both BMI and waist circumference. Furthermore, lgSII demonstrated a linear positive correlation with obesity prevalence. When stratified by physical activity, lgSII showed a non-significant negative correlation with obesity in the physically active group. Our findings underscore a robust association between the logarithmically transformed SII and BMI, waist circumference, and the prevalence of obesity.

The phenomenon of transforming natural marine space into proliferative capital holds global significance in modern modes of production. Under China’s socialist market economy, the property rights system and resource allocation methods have created a unique approach to the capitalization of marine space. Drawing on concepts related to the capitalization of space and land, this paper develops the idea of the capitalization of marine space. It is a process where the right to use the sea area is transferred by the rights holders through methods such as transfer, lease, or shares and is ultimately put into production as a means of production to realize the creation of capital value and surplus value. Using the mariculture industry on Guanglu Island in Changhai County as a case, this analysis delves into the process and mechanisms of the capitalization of marine space in China, the world’s leading mariculture nation, while considering the material agency of marine space. The research results show that: ① The specific realization process of marine space capitalization in the mariculture industry has gone through three stages: from natural marine space to marine space resources, from marine space resources to marine space assets, and the participation of marine space assets in creating value and surplus value. ② The material agency of marine space determines the feasibility of the capitalization of marine space and is also the decisive subject in shaping the specific practice of capitalization. The survival and profit needs of mariculture fishermen and enterprises drive the realization of the capitalization of marine space. China’s central and local governments participate in realizing the capitalization of marine space with the relevant institutional policies and norms aimed at economic development.

Abstract In 2015, we launched the mesoSPIM initiative, an open-source project for making light-sheet microscopy of large cleared tissues more accessible. Meanwhile, the demand for imaging larger samples at higher speed and resolution has increased, requiring major improvements in the capabilities of such microscopes. Here, we introduce the next-generation mesoSPIM (“Benchtop”) with a significantly increased field of view, improved resolution, higher throughput, more affordable cost, and simpler assembly compared to the original version. We develop an optical method for testing detection objectives that enables us to select objectives optimal for light-sheet imaging with large-sensor cameras. The improved mesoSPIM achieves high spatial resolution (1.5 µm laterally, 3.3 µm axially) across the entire field of view, magnification up to 20×, and supports sample sizes ranging from sub-mm up to several centimeters while being compatible with multiple clearing techniques. The microscope serves a broad range of applications in neuroscience, developmental biology, pathology, and even physics.

Orius nagaii is a highly effective natural enemy for controlling thrips, tetranychids, aphids, and various Lepidoptera pests. Nevertheless, the molecular mechanisms underlying its interactions with host pests remain unclear. Screening for optimal reference genes is a prerequisite for using reverse transcription–quantitative polymerase chain reaction (RT-qPCR) to investigate the interrelationship. Here, ten commonly used reference genes (Act, GAPDH, β-Tub, EF1-α, RPS10, RPS15, RPL6, RPL13, RPL32, and HSP90) were selected, and their expression stability across developmental stages, tissues, temperatures, and host conditions were evaluated using RefFinder, which uses multiple analytical approaches (NormFinder, geNorm, the ΔCt method, and BestKeeper). The findings suggested that the most reliable normalization can be achieved by selecting the two reference genes for all conditions, with the optimal pairs being RPS10 and RPL32 for the developmental stage, RPS10 and RPS15 for tissue, RPS10 and RPS15 for the host, and EF1-α and RPL13 for temperature. Also, the best and least stable reference genes were chosen to compare the relative transcript levels of the TBX1 in various tissues, which exhibited considerable variation. Our findings will significantly enhance the reliability of RT-qPCR and provide a foundation for further research on the expression patterns of crucial genes that are implicated in the interaction between O. nagaii and its host pests.

Abstract The tumour microenvironment is infiltrated by immunosuppressive cells, such as regulatory T cells (Tregs), which contribute to tumour escape and impede immunotherapy outcomes. Soluble fibrinogen-like protein 2 (sFGL2), a Treg effector protein, inhibits immune cell populations, via receptors FcγRIIB and FcγRIII, leading to downregulation of CD86 in antigen presenting cells and limiting T cell activation. Increased FGL2 expression is associated with tumour progression and poor survival in several different cancers, such as glioblastoma multiforme, lung, renal, liver, colorectal, and prostate cancer. Querying scRNA-seq human cancer data shows FGL2 is produced by cells in the tumour microenvironment (TME), particularly monocytes and macrophages as well as T cells and dendritic cells (DCs), while cancer cells have minimal expression of FGL2. We studied the role of FGL2 exclusively produced by cells in the TME, by leveraging Fgl2 knockout mice. We tested two murine models of cancer in which the role of FGL2 has not been previously studied: epithelial ovarian cancer and melanoma. We show that absence of FGL2 leads to a more activated TME, including activated DCs (CD86+, CD40+) and T cells (CD25+, TIGIT+), as well as demonstrating for the first time that the absence of FGL2 leads to more activated natural killer cells (DNAM-1+, NKG2D+) in the TME. Furthermore, the absence of FGL2 leads to prolonged survival in the B16F10 melanoma model, while the absence of FGL2 synergizes with oncolytic virus to prolong survival in the ID8-p53 −/− Brca2 −/− ovarian cancer model. In conclusion, targeting FGL2 is a promising cancer treatment strategy alone and in combination immunotherapies.

Abstract Telomere length (TL) shortening is a pivotal indicator of biological aging and is associated with many human diseases. The genetic determinates of human TL have been widely investigated, however, most existing studies were conducted based on adult tissues which are heavily influenced by lifetime exposure. Based on the analyses of terminal restriction fragment (TRF) length of telomere, individual genotypes, and gene expressions on 166 healthy placental tissues, we systematically interrogate TL-modulated genes and their potential functions. We discover that the TL in the placenta is comparatively longer than in other adult tissues, but exhibiting an intra-tissue homogeneity. Trans-ancestral TL genome-wide association studies (GWASs) on 644,553 individuals identify 20 newly discovered genetic associations and provide increased polygenic determination of human TL. Next, we integrate the powerful TL GWAS with placental expression quantitative trait locus (eQTL) mapping to prioritize 23 likely causal genes, among which 4 are functionally validated, including MMUT, RRM1, KIAA1429, and YWHAZ. Finally, modeling transcriptomic signatures and TRF-based TL improve the prediction performance of human TL. This study deepens our understanding of causal genes and transcriptomic determinants of human TL, promoting the mechanistic research on fine-grained TL regulation.

Abstract E-cadherin is an essential cell‒cell adhesion protein that mediates canonical cadherin-catenin complex formation in epithelial lateral membranes. Ankyrin-G (AnkG), a scaffold protein linking membrane proteins to the spectrin-based cytoskeleton, coordinates with E-cadherin to maintain epithelial cell polarity. However, the molecular mechanisms governing this complex formation and its relationships with the cadherin-catenin complex remain elusive. Here, we report that AnkG employs a promiscuous manner to encapsulate three discrete sites of E-cadherin by the same region, a dynamic mechanism that is distinct from the canonical 1:1 molar ratio previously described for other AnkG or E-cadherin-mediated complexes. Moreover, we demonstrate that AnkG-binding-deficient E-cadherin exhibited defective accumulation at the lateral membranes and show that disruption of interactions resulted in cell polarity malfunction. Finally, we demonstrate that E-cadherin is capable of simultaneously anchoring to AnkG and β-catenin, providing mechanistic insights into the functional orchestration of the ankyrin-spectrin complex with the cadherin-catenin complex. Collectively, our results show that complex formation between E-cadherin and AnkG is dynamic, which enables the maintenance of epithelial cell polarity by ensuring faithful targeting of the adhesion molecule-scaffold protein complex, thus providing molecular mechanisms for essential E-cadherin-mediated complex assembly at cell‒cell junctions.

Abstract Giardia duodenalis is a gastrointestinal protozoan ubiquitous in nature. It is a confirmed zoonotic pathogen, and cattle are considered a source of giardiasis outbreaks in humans. This study aimed to evaluate the prevalence and multilocus genotype (MLG) of G. duodenalis in dairy cattle in Central Inner Mongolia. This study was based on the small subunit ribosomal RNA (SSU rRNA), glutamate dehydrogenase (gdh), triosephosphate isomerase (tpi), and beta-giardin (bg) genes of G. duodenalis. DNA extraction, polymerase chain reaction (PCR), and sequence analysis were performed on 505 dairy cattle fecal samples collected in 2021 from six sampling sites and four age groups in Central Inner Mongolia to determine the prevalence and MLG distribution of G. duodenalis. The PCR results of SSU rRNA revealed that the overall prevalence of G. duodenalis was 29.5% (149/505) and that the overall prevalence of the diarrhea and nondiarrhea samples was 31.5% (46/146) and 28.5% (103/359), respectively; the difference was not significant (p > 0.05). SSU rRNA sequence analysis revealed that G. duodenalis assemblage E (91.1%, 133/146) was primarily detected and that assemblage A (8.9%, 13/146) was detected in 13 samples. The G. duodenalis—positive samples were PCR amplified and sequenced for gdh, tpi, and bg, from which 38, 47, and 70 amplified sequences were obtained, respectively. A combination of G. duodenalis assemblages A and E were detected in seven samples. Multilocus genotyping yielded 25 different assemblage E MLGs, which formed six subgroups. To the best of our knowledge, this is the first report regarding G. duodenalis infection in dairy cattle in Inner Mongolia, China. This study revealed that Inner Mongolian cattle pose a risk of giardiasis transmission to humans and that the distribution of local cattle G. duodenalis assemblage E MLGs is diverse. The findings of this study can bridge the knowledge gap in the molecular epidemiological investigation of giardiasis in Central Inner Mongolia.

BackgroundIn recent years, remarkable progress has been made in the use of machine learning, especially in analyzing prognosis survival data. Traditional prediction models cannot identify interrelationships between factors, and the predictive accuracy is lower. This study aimed to construct Bayesian network models using the tree augmented naïve algorithm in comparison with the Cox proportional hazards model.MethodsA Bayesian network model and a Cox proportional hazards model were constructed to analyze the prognostic factors of endometrial cancer. In total, 618 original cases obtained from the Surveillance, Epidemiology, and End Results database were used to construct the Bayesian network model, which was compared with the traditional Cox proportional hazards model by analyzing prognostic factors. External validation was performed using a dataset from The First Affiliated Hospital of Shandong First Medical University.ResultsThe predictive accuracy, area under the receiver operating characteristic curve, and concordance index for the Bayesian network model were 74.68%, 0.787, and 0.72, respectively, compared to 68.83%, 0.723, and 0.71, respectively, for the Cox proportional hazards model. Tumor size was the most important factor for predicting survival, followed by lymph node metastasis, distant metastasis, chemotherapy, lymph node resection, tumor stage, depth of invasion, tumor grade, histological type, age, primary tumor site, radiotherapy and surgical sequence, and radiotherapy.ConclusionThe findings indicate that the Bayesian network model is preferable to the Cox proportional hazards model for predicting survival in patients with endometrial cancer.

BackgroundDelirium is a common complication among intensive care unit (ICU) patients that is linked to negative clinical outcomes. However, adherence to the Clinical Practice Guidelines for the Prevention and Management of Pain, Agitation/Sedation, Delirium, Immobility, and Sleep Disruption in Adult Patients in the ICU (PADIS guidelines), which recommend the use of the ABCDEF bundle, is sub-optimal in routine clinical care. To address this issue, AI-AntiDelirium, a nurse-led artificial intelligence-assisted prevention and management tool for delirium, was developed by our research team. Our pilot study yielded positive findings regarding the use of AI-AntiDelirium in preventing patient ICU delirium and improving activities of daily living and increasing intervention adherence by health care staff.MethodsThe proposed large-scale pragmatic, open-label, parallel-group, cluster randomized controlled study will assess the impact of AI-AntiDelirium on the incidence of ICU delirium and delirium-related outcomes. Six ICUs in two tertiary hospitals in China will be randomized in a 1:1 ratio to an AI-AntiDelirium or a PADIS guidelines group. A target sample size of 1,452 ICU patients aged 50 years and older treated in the ICU for at least 24 hours will be included. The primary outcome evaluated will be the incidence of ICU delirium and the secondary outcomes will be the duration of ICU delirium, length of ICU and hospital stay, ICU and in-hospital mortality rates, patient cognitive function, patient activities of daily living, and ICU nurse adherence to the ABCDEF bundle.DiscussionIf this large-scale trial provides evidence of the effectiveness of AI-AntiDelirium, an artificial intelligence-assisted system tool, in decreasing the incidence of ICU delirium, length of ICU and hospital stay, ICU and in-hospital mortality rates, patient cognitive function, and patient activities of daily living while increasing ICU nurse adherence to the ABCDEF bundle, it will have a profound impact on the management of ICU delirium in both research and clinical practice.Clinical trial registrationChiCTR1900023711 (Chinese Clinical Trial Registry).

Summary: LINC00116 encodes a microprotein first identified as Mitoregulin (MTLN), where it was reported to localize to the inner membrane of mitochondria to regulate fatty acid oxidation and oxidative phosphorylation. These initial discoveries were followed by reports with differing findings about its molecular functions and submitochondrial localization. To clarify the apparent discrepancies, we constructed multiple orthogonal methods of determining the localization of MTLN, including split GFP-based reporters that enable efficient and reliable topology analyses for microproteins. These methods unequivocally demonstrate MTLN primarily localizes to the outer membrane of mitochondria, where it interacts with enzymes of fatty acid metabolism including CPT1B and CYB5B. Loss of MTLN causes the accumulation of very long-chain fatty acids (VLCFAs), especially docosahexaenoic acid (DHA). Intriguingly, loss of MTLN protects mice against western diet/fructose-induced insulin-resistance, suggests a protective effect of VLCFAs in this context. MTLN thus serves as an attractive target to control the catabolism of VLCFAs.

The aphidophagous gall midge, Aphidoletes aphidimyza (Rondani) (Diptera: Cecidomyiidae), a dominant natural enemy of aphids, has been used as a biological control agent in many countries to control aphids in greenhouses. To identify key factors that induce diapause in A. aphidimyza, we evaluated the effects of photoperiod and temperature on the incidence of diapause in A. aphidimyza under laboratory conditions. The results showed that temperature and photoperiod had significant impacts on development and diapause in A. aphidimyza. Low temperatures and a short photoperiod inhibited development, while high temperatures and a long photoperiod promoted development. Temperatures above 20 °C and a photoperiod greater than 14 h prevented diapause in A. aphidimyza. However, the highest diapause rate was recorded at under 15 °C and 10L:14D photoperiod conditions. At 15 °C, the first to third larvae were sensitive to a short photoperiod at any stage, and a short photoperiod had a cumulative effect on diapause induction. The longer the larvae received short light exposure, the higher the diapause rate appeared to be. Transcriptome sequencing analysis at different stages of diapause showed that differentially expressed genes were mainly enriched in the glucose metabolism pathway. Physiological and biochemical analyses showed that diapausing A. aphidimyza reduced water content; accumulated glycogen, trehalose, sorbitol, and triglycerides; and gradually reduced trehalose and triglyceride contents in the body with the extension of diapause time. Glycogen may be used as a source of energy, but sorbitol is usually used as a cryoprotectant. This study provided results on aspects of diapause in A. aphidimyza, providing data and theoretical support for promoting its commercial breeding and in-depth research on the molecular mechanisms underlying diapause regulation.

This study identified and characterized the gene encoding recep tor-type guanylate cyclase-22-like (GCY-22; OnGCY) from the pirate bug Orius nagaii, an important biological control agent. The full-length cDNA of the GCY of O. nagaii was obtained by rapid amplification of cDNA ends (RACE); it had a total length of 4888 base pairs (bp), of which the open reading frame (ORF) was 3750 bp, encoding a polypeptide of 1249 amino acid residues. The physicochemical properties of OnGCY were predicted and analyzed by using relevant ExPASy software, revealing a molecular formula of C6502H10122N1698O1869S57, molecular weight of ~143,811.57 kDa, isoelectric point of 6.55, and fat index of 90.04. The resulting protein was also shown to have a signal peptide, two transmembrane regions, and a conserved tyrosine kinase (tyrkc). Silencing OnGCY by RNA interference significantly inhibited ovarian development and decreased fertility in female O. nagaii in the treated versus the control group. Additionally, OnGCY silencing significantly decreased the expression levels of other GCY and Vg genes. Thus, these results clarify the structure and biological function of OnGCY, which has an important role in insect fecundity. The results also provide a reference for agricultural pest control and future large-scale breeding of biological control agents.

Abstract KMT2C and KMT2D are the most frequently mutated epigenetic genes in human cancers. While KMT2C is identified as a tumor suppressor in acute myeloid leukemia (AML), the role of KMT2D remains unclear in this disease, though its loss promotes B cell lymphoma and various solid cancers. Here, it is reported that KMT2D is downregulated or mutated in AML and its deficiency, through shRNA knockdown or CRISPR/Cas9 editing, accelerates leukemogenesis in mice. Hematopoietic stem and progenitor cells and AML cells with Kmt2d loss have significantly enhanced ribosome biogenesis and consistently, enlarged nucleolus, increased rRNA and protein synthesis rates. Mechanistically, it is found that KMT2D deficiency leads to the activation of the mTOR pathway in both mouse and human AML cells. Kmt2d directly regulates the expression of Ddit4, a negative regulator of the mTOR pathway. Consistent with the abnormal ribosome biogenesis, it is shown that CX‐5461, an inhibitor of RNA polymerase I, significantly restrains the growth of AML with Kmt2d loss in vivo and extends the survival of leukemic mice. These studies validate KMT2D as a de facto tumor suppressor in AML and reveal an unprecedented vulnerability to ribosome biogenesis inhibition.

S-methyl methionine (SMM) is a key molecule in production of dimethylsulfoniopropionate (DMSP), an important marine anti-stress compound, with roles in global nutrient cycling. Here, the authors determine the mechanism of SMM synthesis and uncover unexpected roles for SMM in archaea, CPR bacteria and animals.

Coal mining and ecological restoration activities significantly affect land surfaces, particularly vegetation. Long-term quantitative analyses of vegetation disturbance and restoration are crucial for effective mining management and ecological environmental supervision. In this study, using the Google Earth Engine and all available Landsat images from 1987 to 2020, we employed the Landsat-based Detection of Trends in Disturbance and Recovery (LandTrendr) algorithm and Support Vector Machine (SVM) to conduct a comprehensive analysis of the year, intensity, duration, and pattern of vegetation disturbance and restoration in the Heidaigou and Haerwusu open-pit coal mines (H-HOCMs) in the Jungar Coalfield of China. Our findings indicate that the overall accuracy for extractions of disturbance and restoration events in the H-HOCMs area is 83% and 84.5%, respectively, with kappa coefficients of 0.82 for both. Mining in Heidaigou has continued since its beginning in the 1990s, advancing toward the south and then eastward directions, and mining in the Haerwusu has advanced from west to east since 2010. The disturbance magnitude of the vegetation greenness in the mining area is relatively low, with a duration of about 4–5 years, and the restoration magnitude and duration vary considerably. The trajectory types show that vegetation restoration (R, 44%) occupies the largest area, followed by disturbance (D, 31%), restoration–disturbance (RD, 16%), disturbance–restoration (DR, 8%), restoration–disturbance–restoration (RDR), and no change (NC). The LandTrendr algorithm effectively detected changes in vegetation disturbance and restoration in H-HOCMs. Vegetation disturbance and restoration occurred in the study area, with a cumulative disturbance-to-restoration ratio of 61.79% since 1988. Significant restoration occurred primarily in the external dumps and continued ecological recovery occurred in the surrounding area.

Abstract Due to the huge toxicity of co-contaminated soil with PAHs and heavy metals and the complexity of their remediation, it is thus critical to take effective remediation actions to remove heavy metals and PAHs simultaneously from the co-contaminated soil. Biosurfactant-enhanced soil washing (BESW) were investigated in this study for remediation of soil co-contaminated with phenanthrene (PHE) and cadmium (Cd). The co-existence of PHE and Cd caused the change of the structure of soil and rhamnolipid micelle, which lead to different removal rate of PHE and Cd from co-contaminated soil compared with single contaminated soil. The results of FT-IR and NMR showed that PHE entered micelles of rhamnolipid and Cd formed the complexation with the external carboxyl groups of rhamnolipid micelle. We also found that pH, concentration of rhamnolipid solution, temperature and ionic strength had influence on co-contaminated soil remediation. The effects of above mentioned four factors on co-contaminated soil remediation in BESW processes were analyzed by using Taguchi design of experiment method. Taguchi based Grey Relational Analysis was conducted to identify the optimal remediation conditions, which included pH = 9, concentration of rhamnolipid = 5 g/L, temperature = 15 °C and ionic strength = 0.01 M. Under the optimal conditions for BESW, removal rates of cadmium and phenanthrene reached 72.4% and 87.8%, respectively in co-contaminated soil.

Salt lakes on the Tibetan Plateau (TP) are rich in lithium (Li), boron (B) and other mineral resources, and accurate assessment of the mineral content and spatial distribution of the brine in those salt lakes is important to guide the development and utilization of their mineral resources. There are few studies estimating the mineral content of salt lakes on the TP due to the lack of in situ investigation data. This study introduced an intelligent prediction model combining a feature selection algorithm with a machine learning algorithm using Sentinel-2 satellite data to estimate the Li, B, and TDS contents of Bieruoze Co and Guopu Co lakes on the TP. First, to enrich the spectral information, four mathematical transformations (reciprocal, logarithmic, reciprocal of logarithm, and first-order derivative) were applied to the original bands. Then, feature selection was performed using the genetic algorithm (GA) to select the optimal input variables for the model. Finally, prediction models were constructed by partial least squares regression (PLSR), multiple linear regression (MLR), and random forest (RF). The results showed that: 1) The spectral mathematical transformation provided rich spectral information for the mineral content estimation. 2) The performance of the estimation model constructed by the feature optimization method using GA was better than that of the estimation model constructed based on all spectral bands. Based on GA for feature optimization, the MAPE of GA-RF for estimating Li, B and TDS contents on the testing set was reduced by 77.52%, 28.54% and 36.79%, respectively. 3) Compared with the GA-MLR and GA-PLSR models, GA-RF estimated Li (R2=0.99, RMSE=1.15 mg L-1, MAPE=3.00%), B (R2=0.97, RMSE=10.65 mg L-1, MAPE=2.73%), and TDS (R2=0.93, RMSE=0.60 g L-1, MAPE=1.82%) all obtained the optimal performance. This study showed that the combination of the GA-based feature selection method and the RF model has excellent performance and applicability for monitoring the content of multiple minerals using Sentinel-2 imagery in salt lakes on the TP.

BackgroundAdherence to the delirium bundle intervention is sub-optimal in routine practice, and inappropriate use of the instructional design of interventions may result in higher cognitive load among nurses. It remains unclear whether the Clinical Decision Support System (CDSS) Assisted Prevention and Management for Delirium (CDSS-AntiDelirium) results in the improvement of adherence to delirium intervention and the reduction of extraneous cognitive load, as well as improving adherence to delirium intervention, among nurses in the intensive care unit (ICU).MethodsThis study (named the CDSSD-ICU) is a multicentre, prospective, cluster randomized controlled clinical trial. A total of six ICUs in two hospitals will be randomized in a 1:1 ratio to receive either the CDSS-AntiDelirium group or the delirium guidelines group. The CDSS-AntiDelirium consists of four modules: delirium assessment tools, risk factor assessment, a nursing care plan, and a nursing checklist module. Each day, nurses will assess ICU patients with the assistance of the CDSS-AntiDelirium. A total of 78 ICU nurses are needed to ensure statistical power. Outcome assessments will be conducted by investigators who are blinded to group assignments. The primary endpoint will be adherence to delirium intervention, the secondary endpoint will be nurses' cognitive load measured using an instrument to assess different types of cognitive load. Repeated measures analysis of variance will be used to detect group differences. A structural equation model will be used to clarify the mechanism of improvement in adherence.DiscussionAlthough the CDSS has been widely used in hospitals for disease assessment, management, and recording, the applications thereof in the area of delirium are still in infancy. This study could provide scientific evidence regarding the impact of a CDSS on nurses' adherence and cognitive load and promote its further development in future studies.Clinical trial registrationChiCTR1900023711 (Chinese Clinical Trial Registry).

Knowledge about resistance mechanisms can provide ideas for pesticide resistance management. Although several studies have unveiled the positive or negative impacts of gut microbes on host pesticide resistance, minimal research is available regarding the association between gut microbes and host phosphine resistance. To explore the influence of gut bacteria on host phosphine susceptibility and its molecular basis, mortality, fitness, redox responses, and immune responses of adult Tribolium castaneum were determined when it was challenged by phosphine exposure and/or gut bacteria inoculation. Five cultivable gut bacteria were excised from a population of phosphine-resistant T. castaneum. Among them, only Enterococcus sp. inoculation significantly promoted host susceptibility to phosphine, while inoculation of any other gut bacteria had no significant effect on host phosphine susceptibility. Furthermore, when T. castaneum was exposed to phosphine, Enterococcus sp. inoculation decreased the female fecundity, promoted host oxidative stress, and suppressed the expression and activity of host superoxide dismutase, catalase, and peroxidase. In the absence of phosphine, Enterococcus sp. inoculation also elicited overactive immune responses in T. castaneum, including the immune deficiency and Toll signaling pathways and the dual oxidase–reactive oxygen species system. These results indicate that Enterococcus sp. likely promotes host phosphine susceptibility by aggravating oxidative stress and fitness costs.

Abstract In aerial multi-view photogrammetry, whether there is a special positional distribution pattern among candidate homologous pixels of a matching pixel in the multi-view images? If so, can this positional pattern be used to precisely confirm the real homologous pixels? These problems have not been studied at present. Therefore, the study of the positional distribution pattern among candidate homologous pixels based on the adjustment theory in surveying is investigated in this paper. Firstly, the definition and computing method of pixel’s pseudo object-space coordinates are given, which can transform the problem of multi-view matching for confirming real homologous pixels into the problem of surveying adjustment for computing the pseudo object-space coordinates of the matching pixel. Secondly, according to the surveying adjustment theory, the standardized residual of each candidate homologous pixel of the matching pixel is figured out, and the positional distribution pattern among these candidate pixels is theoretically inferred utilizing the quantitative index of standardized residual. Lastly, actual aerial images acquired by different sensors are used to carry out experimental verification of the theoretical inference. Experimental results prove not only that there is a specific positional distribution pattern among candidate homologous pixels, but also that this positional distribution pattern can be used to develop a new object-side multi-view image matching method. The proposed study has an important reference value on resolving the defects of existing image-side multi-view matching methods at the mechanism level.

Chemical communication is widespread among insects and exploited to adjust their behavior, such as food and habitat seeking and preferences, recruitment, defense, and mate attraction. Recently, many studies have revealed that microbial symbionts could regulate host chemical communication by affecting the synthesis and perception of insect semiochemicals. In this paper, we review recent studies of the influence of microbial symbionts on insect chemoreception. Microbial symbionts may influence insect sensitivity to semiochemicals by regulating the synthesis of odorant-binding proteins or chemosensory proteins and olfactory or gustatory receptors and regulating host neurotransmission, thereby adjusting insect behavior. The manipulation of insect chemosensory behavior by microbial symbionts is conducive to their proliferation and dispersal and provides the impetus for insects to change their feeding habits and aggregation and dispersal behavior, which contributes to population differentiation in insects. Future research is necessary to reveal the material and information exchange between both partners to improve our comprehension of the evolution of chemoreception in insects. Manipulating insect chemoreception physiology by inoculating them with microbes could be utilized as a potential approach to managing insect populations.

The symbiotic microbiome is critical in promoting insect resistance against colonization by exogenous microorganisms. The mechanisms by which symbionts contribute to the host’s immune capacity is referred to as colonization resistance. Symbionts can protect insects from exogenous pathogens through a variety of mechanisms, including upregulating the expression of host immune-related genes, producing antimicrobial substances, and competitively excluding pathogens. Concordantly, insects have evolved fine-tuned regulatory mechanisms to avoid overactive immune responses against symbionts or specialized cells to harbor symbionts. Alternatively, some symbionts have evolved special adaptations, such as the formation of biofilms to increase their tolerance to host immune responses. Here, we provide a review of the mechanisms about colonization resistance of symbionts in their insect hosts. Adaptations of symbionts and their insect hosts that may maintain such symbiotic relationships, and the significance of such relationships in the coevolution of symbiotic systems are also discussed to provide insights into the in-depth study of the contribution of symbionts to host physiology and behavior.

Rapid urban development in China has aggravated land subsidence, which poses a potential threat to sustainable urban development. It is imperative to monitor and predict land subsidence over large areas. To address these issues, we chose Henan Province as the study area and applied small baseline subset-interferometric synthetic aperture radar (SBAS-InSAR) technology to obtain land deformation information for monitoring land subsidence from November 2019 to February 2022 with 364 multitrack Sentinel-1A satellite images. The current traditional time-series deep learning models suffer from the problems of (1) poor results in extracting a sequence of information that is too long and (2) the inability to extract the feature information between the influence factor and the land subsidence well. Therefore, a long short-term memory-temporal convolutional network (LSTM-TCN) deep learning model was proposed in order to predict land subsidence and explore the influence of environmental factors, such as the volumetric soil water layer and monthly precipitation, on land subsidence in this study. We used leveling data to verify the effectiveness of SBAS-InSAR in land subsidence monitoring. The results of SBAS-InSAR showed that the land subsidence in Henan Province was obvious and uneven in spatial distribution. The maximum subsidence velocity was −94.54 mm/a, and the uplift velocity was 41.23 mm/a during the monitoring period. Simultaneously, the land subsidence in the study area presented seasonal changes. The rate of land subsidence in spring and summer was greater than that in autumn and winter. The prediction accuracy of the LSTM-TCN model was significantly better than that of the individual LSTM and TCN models because it fully combined their advantages. In addition, the prediction accuracies, with the addition of environmental factors, were improved compared with those using only time-series subsidence information.

Abstract Real-time seizure detection is a resource intensive process as it requires continuous monitoring of patients on stereoelectroencephalography. This study improves real-time seizure detection in drug resistant epilepsy (DRE) patients by developing patient-specific deep learning models that utilize a novel self-supervised dynamic thresholding approach. Deep neural networks were constructed on over 2000 h of high-resolution, multichannel SEEG and video recordings from 14 DRE patients. Consensus labels from a panel of epileptologists were used to evaluate model efficacy. Self-supervised dynamic thresholding exhibited improvements in positive predictive value (PPV; difference: 39.0%; 95% CI 4.5–73.5%; Wilcoxon–Mann–Whitney test; N = 14; p = 0.03) with similar sensitivity (difference: 14.3%; 95% CI − 21.7 to 50.3%; Wilcoxon–Mann–Whitney test; N = 14; p = 0.42) compared to static thresholds. In some models, training on as little as 10 min of SEEG data yielded robust detection. Cross-testing experiments reduced PPV (difference: 56.5%; 95% CI 25.8–87.3%; Wilcoxon–Mann–Whitney test; N = 14; p = 0.002), while multimodal detection significantly improved sensitivity (difference: 25.0%; 95% CI 0.2–49.9%; Wilcoxon–Mann–Whitney test; N = 14; p

Mito-SEPs are small peptides that can modulate oxidative metabolism in mitochondria. Here the authors show that C15ORF48 encodes a mito-SEP, MOCCI, capable of altering mitochondria respiration to suppress inflammation, while C15ORF48 3’ untranslated region also contains a miRNA, miR-147b, that synergizes with MOCCI to modulate host anti-viral responses.

The refined monitoring and identification of fishing operations by fishing vessels is of great significance and value to fishing vessels. In order to solve the problem of inaccurate statistics of current Engraulis japonicus fishing quota and classification, this paper proposes an improved identification algorithm based on YOLOv5. This method introduces the SENet attention mechanism into the YOLOv5 backbone network structure, integrates the target information in different periods of fishing operations, reduces the interference of complex backgrounds, improves the precision of model detection, and ensures real-time detection efficiency. The artificially shot Engraulis japonicus videos are used as the dataset of the study, and the video is converted into a picture format to realize pre-labeling and processing. The 5550 images are divided into the training set, validation set, and test set according to 8:1:1. In order to verify the validity of the data, a set of in the control experiment, the YOLOv5 backbone network was replaced by MobileNetV2 and the SENet attention mechanism was introduced, and four models were implemented for comparison. The experimental results show that the research algorithm can obtain a mean average precision (mAP) of 99.3%, a precision of 98.9%, and a recall of 98.7%, which are improved by 1.4%, 1.7% and 2.5% respectively compared with the original model. The experimental results match the expectations. According to the statistics of some categories, the Kalman filter and the Hungarian matching method are used to count the main categories of fishing baskets, and an accuracy of 96.5% can be obtained. The threshold method for fishing nets and processing vessels can obtain 85.8% and 75% accuracy. These results shows that this target detection research can provide new ideas for job identification of Engraulis japonicus and provide auxiliary means for job statistics.

Small open reading frame-encoded peptides (SEPs), shorter than 100 amino acids, are involved in many cell biological processes. Here the authors identify 16 nuclear-encoded mitochondrial SEPs, including BRAWNIN, an essential regulator of respiratory chain complex III assembly and ATP production.

Reproductive diapause is an overwintering strategy for Bombus terrestris, which is an important pollinator for agricultural production. However, the precise mechanisms underlying reproductive diapause in bumblebees remain largely unclear. Here, a combination analysis of proteomics and phosphoproteomics was used to reveal the mechanisms that occur during and after diapause in three different phases: diapause (D), postdiapause (PD), and founder postdiapause (FPD). In total, 4655 proteins and 10,600 phosphorylation sites of 3339 proteins were identified. Diapause termination and reactivation from D to the PD stage were characterized by the upregulation of proteins associated with ribosome assembly and biogenesis, transcription, and translation regulation in combination with the upregulation of phosphoproteins related to neural signal transmission, hormone biosynthesis and secretion, and energy-related metabolism. Moreover, the reproductive program was fully activated from PD to the FPD stage, as indicated by the upregulation of proteins related to fat digestion and absorption, the biosynthesis of unsaturated fatty acids, fatty acid elongation, protein processing in the endoplasmic reticulum, and the upregulation of energy-related metabolism at the phosphoproteome level. We also predicted a kinase–substrate interaction network and constructed protein–protein networks of proteomic and phosphoproteomic data. These results will help to elucidate the mechanisms underlying the regulation of diapause in B. terrestris for year-round mass breeding.

Dimethylsulfoniopropionate (DMSP) is an abundant and ubiquitous organosulfur molecule in marine environments with important roles in global sulfur and nutrient cycling. Diverse DMSP lyases in some algae, bacteria, and fungi cleave DMSP to yield gaseous dimethyl sulfide (DMS), an infochemical with important roles in atmospheric chemistry. Here, we identified a novel ATP-dependent DMSP lyase, DddX. DddX belongs to the acyl-CoA synthetase superfamily and is distinct from the eight other known DMSP lyases. DddX catalyses the conversion of DMSP to DMS via a two-step reaction: the ligation of DMSP with CoA to form the intermediate DMSP-CoA, which is then cleaved to DMS and acryloyl-CoA. The novel catalytic mechanism was elucidated by structural and biochemical analyses. DddX is found in several Alphaproteobacteria, Gammaproteobacteria, and Firmicutes, suggesting that this new DMSP lyase may play an overlooked role in DMSP/DMS cycles.

BackgroundSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and the associated Coronavirus Disease 2019 (COVID-19) is a public health emergency. Acute kidney injury (AKI) is a common complication in hospitalized patients with COVID-19 although mechanisms underlying AKI are yet unclear. There may be a direct effect of SARS-CoV-2 virus on the kidney; however, there is currently no data linking SARS-CoV-2 viral load (VL) to AKI. We explored the association of SARS-CoV-2 VL at admission to AKI in a large diverse cohort of hospitalized patients with COVID-19.Methods and findingsWe included patients hospitalized between March 13th and May 19th, 2020 with SARS-CoV-2 in a large academic healthcare system in New York City (N = 1,049) with available VL at admission quantified by real-time RT-PCR. We extracted clinical and outcome data from our institutional electronic health records (EHRs). AKI was defined by KDIGO guidelines. We fit a Fine-Gray competing risks model (with death as a competing risk) using demographics, comorbidities, admission severity scores, and log10 transformed VL as covariates and generated adjusted hazard ratios (aHR) and 95% Confidence Intervals (CIs). VL was associated with an increased risk of AKI (aHR = 1.04, 95% CI: 1.01-1.08, p = 0.02) with a 4% increased hazard for each log10 VL change. Patients with a viral load in the top 50th percentile had an increased adjusted hazard of 1.27 (95% CI: 1.02-1.58, p = 0.03) for AKI as compared to those in the bottom 50th percentile.ConclusionsVL is weakly but significantly associated with in-hospital AKI after adjusting for confounders. This may indicate the role of VL in COVID-19 associated AKI. This data may inform future studies to discover the mechanistic basis of COVID-19 associated AKI.

Abstract LiNi0.8Co0.1Mn0.1O2 cathodes suffer from severe bulk structural and interfacial degradation during battery operation. To address these issues, a three in one strategy using ZrB2 as the dopant is proposed for constructing a stable Ni‐rich cathode. In this strategy, Zr and B are doped into the bulk of LiNi0.8Co0.1Mn0.1O2, respectively, which is beneficial to stabilize the crystal structure and mitigate the microcracks. Meanwhile, during the high‐temperature calcination, some of the remaining Zr at the surface combined with the surface lithium source to form lithium zirconium coatings, which physically protect the surface and suppress the interfacial phase transition upon cycling. Thus, the 0.2 mol% ZrB2‐LiNi0.8Co0.1Mn0.1O2 cathode delivers a discharge capacity of 183.1 mAh g−1 after 100 cycles at 50 °C (1C, 3.0–4.3 V), with an outstanding capacity retention of 88.1%. The cycling stability improvement is more obvious when the cut‐off voltage increased to 4.4 V. Density functional theory confirms that the superior structural stability and excellent thermal stability are attributed to the higher exchange energy of Li/Ni exchange and the higher formation energy of oxygen vacancies by ZrB2 doping. The present work offers a three in one strategy to simultaneously stabilize the crystal structure and surface for the Ni‐rich cathode via a facile preparation process.

Abstract Mechanical signals such as pressure and strain reflect important psychological and physiological states of the human body. Body‐integrated sensors, including skin‐mounted and surgically implanted ones, allow personalized health monitoring for the general population as well as patients. However, the development of such measuring devices has been hindered by the strict requirements for human‐biocompatible materials and the need for high performance sensors; most existing devices or sensors do not meet all the desired specifications. Here, a set of flexible, stretchable, wearable, implantable, and degradable mechanical sensors is reported with excellent mechanical robustness and compliance, outstanding biocompatibility, remotely‐triggered degradation, and excellent sensing performance, using a conductive silk fibroin hydrogel (CSFH). They can detect multiple mechanical signals such as pressure, strain, and bending angles. Moreover, combined with a drug‐loaded silk‐based microneedle array, sensor‐equipped devices are shown to be effective for real‐time monitoring and in situ treatment of epilepsy in a rodent model. These sensors offer potential applications in custom health monitoring wearables, and in situ treatment of chronic clinical disorders.

Magnetic Fe3O4 nanoparticles (Fe3O4-NPs) have been widely investigated for their biomedical applications. The main purpose of this study was to evaluate the cytotoxic effects of different sizes of Fe3O4-NPs in chicken macrophage cells (HD11). Experimental groups based on three sizes of Fe3O4-NPs (60, 120 and 250 nm) were created, and the Fe3O4-NPs were added to the cells at different doses according to the experimental group. The cell activity, oxidative index (malondialdehyde (MDA), superoxide dismutase (SOD) and reactive oxygen species (ROS)), apoptosis and pro-inflammatory cytokine secretion level were detected to analyse the cytotoxic effects of Fe3O4-NPs of different sizes in HD11 cells. The results revealed that the cell viability of the 60 nm Fe3O4-NPs group was lower than those of the 120 and 250 nm groups when the same concentration of Fe3O4-NPs was added. No significant difference in MDA was observed among the three Fe3O4-NP groups. The SOD level and ROS production of the 60 nm group were significantly greater than those of the 120 and 250 nm groups. Furthermore, the highest levels of apoptosis and pro-inflammatory cytokine secretion were caused by the 60 nm Fe3O4-NPs. In conclusion, the smaller Fe3O4-NPs produced stronger cytotoxicity in chicken macrophage cells, and the cytotoxic effects may be related to the oxidative stress and apoptosis induced by increased ROS production as well as the increased expression of pro-inflammatory cytokines.

Tissue-engineered skin grafts have long been considered to be the most effective treatment for large skin defects. Especially with the advent of 3D printing technology, the manufacture of artificial skin scaffold with complex shape and structure is becoming more convenient. However, the matrix material used as the bio-ink for 3D printing artificial skin is still a challenge. To address this issue, sodium alginate (SA)/carboxymethyl cellulose (CMC-Na) blend hydrogel was proposed to be the bio-ink for artificial skin fabrication, and SA/CMC-Na (SC) composite hydrogels at different compositions were investigated in terms of morphology, thermal properties, mechanical properties, and biological properties, so as to screen out the optimal composition ratio of SC for 3D printing artificial skin. Moreover, the designed SC composite hydrogel skin membranes were used for rabbit wound defeat repairing to evaluate the repair effect. Results show that SC4:1 blend hydrogel possesses the best mechanical properties, good moisturizing ability, proper degradation rate, and good biocompatibility, which is most suitable for 3D printing artificial skin. This research provides a process guidance for the design and fabrication of SA/CMC-Na composite artificial skin.

Abstract Adipogenesis plays an important role in the regulation of whole-body energy homeostasis and is inextricably related to obesity. Several studies have highlighted the relevance of microRNAs in adipocyte differentiation, but the contributions of long non-coding RNAs (lncRNAs) are still largely uncharacterized. Here, we determined that lncRNA MIR31HG is related to adipocyte lineage commitment. We demonstrated that knockdown of MIR31HG inhibited adipocyte differentiation, whereas overexpression of MIR31HG promoted adipogenesis in vitro and in vivo. Furthermore, inhibition of MIR31HG reduced the enrichment of active histone markers, histone H3 lysine 4 trimethylation (H3K4me3) and acetylation (AcH3), in the promoter of the adipogenic-related gene, fatty acid binding protein 4 (FABP4), leading to suppression of its expression and adipogenesis. These results provide new insights into the molecular mechanisms of MIR31HG in terms of adipogenesis and may have implications for obesity and associated disorders.

Abstract Several recent clinical studies have suggested that the levels of circulating 3-carboxy-4-methyl-5-propyl-2-furanpropanoic acid (CMPF) are significantly higher in patients with gestational diabetes mellitus (GDM), impaired glucose tolerance (IGT), and type 2 diabetes mellitus (T2DM). This study recruited a total of 516 participants. The following patient populations were enrolled: 99 newly diagnosed cases with T2DM, 219 cases with prediabetes [82 with isolated impaired glucose tolerance (I − IGT), 66 with isolated impaired fasting glucose (I − IFG) and 71 with impaired glucose tolerance and impaired fasting glucose (IGT + IFG)], and 198 cases with normal glucose tolerance [NGT, including 99 first-degree relatives of type 2 diabetes patients (FDRs) and 99 non-FDRs]. We investigated the circulating CMPF levels in subjects with different glucose metabolism statuses and examined the potential link between CMPF and β cell function. Our results indicate that the serum CMPF levels were elevated in the prediabetes, T2DM, and FDRs groups compared to the NGT group. Additionally, the serum CMPF concentrations were independently and negatively associated with the triglyceride levels and Stumvoll first-phase insulin secretion index. Cumulatively, our findings suggest that the circulating CMPF levels can predict glycolipid metabolism disorders. Furthermore, elevated serum CMPF concentrations may determine hyperglycemia and β cell dysfunction.