Dense Bicoid hubs accentuate binding along the morphogen gradient.

Morphogen gradients direct the spatial patterning of developing embryos; however, the mechanisms by which these gradients are interpreted remain elusive. Here we used lattice light-sheet microscopy to perform in vivo single-molecule imaging in early Drosophila melanogaster embryos of the transcription factor Bicoid that forms a gradient and initiates patterning along the anteroposterior axis. In contrast to canonical models, we observed that Bicoid binds to DNA with a rapid off rate throughout the embryo such that its average occupancy at target loci is on-rate-dependent. We further observed Bicoid forming transient "hubs" of locally high density that facilitate binding as factor levels drop, including in the posterior, where we observed Bicoid binding despite vanishingly low protein levels. We propose that localized modulation of transcription factor on rates via clustering provides a general mechanism to facilitate binding to low-affinity targets and that this may be a prevalent feature of other developmental transcription factors.

Net greenhouse gas balance in U.S. croplands: How can soils be part of the climate solution?

Agricultural soils play a dual role in regulating the Earth's climate by releasing or sequestering carbon dioxide (CO2 ) in soil organic carbon (SOC) and emitting non-CO2 greenhouse gases (GHGs) such as nitrous oxide (N2 O) and methane (CH4 ). To understand how agricultural soils can play a role in climate solutions requires a comprehensive assessment of net soil GHG balance (i.e., sum of SOC-sequestered CO2 and non-CO2 GHG emissions) and the underlying controls. Herein, we used a model-data integration approach to understand and quantify how natural and anthropogenic factors have affected the magnitude and spatiotemporal variations of the net soil GHG balance in U.S. croplands during 1960-2018. Specifically, we used the dynamic land ecosystem model for regional simulations and used field observations of SOC sequestration rates and N2 O and CH4 emissions to calibrate, validate, and corroborate model simulations. Results show that U.S. agricultural soils sequestered 13.2 ± 1.16 $$ 13.2\pm 1.16 $$ Tg CO2 -C year-1 in SOC (at a depth of 3.5 m) during 1960-2018 and emitted 0.39 ± 0.02 $$ 0.39\pm 0.02 $$ Tg N2 O-N year-1 and 0.21 ± 0.01 $$ 0.21\pm 0.01 $$ Tg CH4 -C year-1 , respectively. Based on the GWP100 metric (global warming potential on a 100-year time horizon), the estimated national net GHG emission rate from agricultural soils was 122.3 ± 11.46 $$ 122.3\pm 11.46 $$ Tg CO2 -eq year-1 , with the largest contribution from N2 O emissions. The sequestered SOC offset ~28% of the climate-warming effects resulting from non-CO2 GHG emissions, and this offsetting effect increased over time. Increased nitrogen fertilizer use was the dominant factor contributing to the increase in net GHG emissions during 1960-2018, explaining ~47% of total changes. In contrast, reduced cropland area, the adoption of agricultural conservation practices (e.g., reduced tillage), and rising atmospheric CO2 levels attenuated net GHG emissions from U.S. croplands. Improving management practices to mitigate N2 O emissions represents the biggest opportunity for achieving net-zero emissions in U.S. croplands. Our study highlights the importance of concurrently quantifying SOC-sequestered CO2 and non-CO2 GHG emissions for developing effective agricultural climate change mitigation measures.

Interference-induced generation of a chirp-free short isolated attosecond pulse in the water window region with multicolor laser fields.

Compensating for the intrinsic attosecond chirp (atto-chirp) of wideband high-order harmonics in the water window region is a significant challenge, in order to obtain isolated attosecond pulses (IAPs) with a width of tens of attoseconds (as). Here, we propose to realize the generation of IAP with duration as short as 20 as, central energy of 365 eV, and bandwidth exceeding 150 eV from chirp-free high harmonics generated by a four-color driving laser, without the necessity for atto-chirp compensation with natural materials. Unlike any other gating methods that an IAP arises from only one electron ionization event, we take advantage of the interference between harmonic radiation produced by multiple ionizing events. We further demonstrate that such chirp-free short IAP survives after taking account of macroscopic propagation effects. Given that the synthesized multicolor laser field can also effectively increase the harmonic flux, this work provides a practical way for experiments to generate the broad bandwidth chirp-free IAPs in the water window region.

Associations between insufficient sleep, skipping breakfast and depressive symptoms in children and adolescents: A school-based cross-sectional study in China.

OBJECTIVE: Insufficient sleep and skipping breakfast are increasingly prevalent among children and adolescents. Both behaviors are associated with the onset of depression. This study aims to examine the independent and joint associations of these two behaviors with depressive symptoms, and investigate whether these associations varied by age or sex. METHODS: The Center for Epidemiological Studies Depression Scale (CES-D) was used to evaluate the depressive symptoms. This cross-sectional study including 11,887 students aged 11-19 years using a stratified cluster, multistage sampling method in Ningbo, China. Multiple logistic regressions were conducted to evaluate the independent and joint association between insufficient sleep, skipping breakfast and depressive symptoms. Sensitivity analyses and stratified analyses by age and sex were performed using the same modelling strategies. RESULTS: The overall prevalence of depressive symptoms was 15.27%. Skipping breakfast (Odds Ratio (OR) = 2.557, 95% Confidence Interval (CI) = 2.236-2.925) and insufficient sleep (OR = 1.547, 95%CI = 1.390-1.723) was independently associated with depressive symptoms. Compared to students with "sufficient sleep and breakfast every day", the OR was 4.385 (95%CI = 3.649-5.271) for those with "insufficient sleep and skipping breakfast". Meanwhile, the joint association was moderated by age group, with a more apparent association observed in the 11-15-year-old group compared to the 16-19-year-old group. CONCLUSIONS: These findings indicated that insufficient sleep and skipping breakfast were independently and jointly associated with depressive symptoms. Insufficient sleep and skipping breakfast could be considered as two of the predictors of depression.

A biomarker panel of secondary hypertension is simultaneously quantified by coupling of magnetic solid-phase extraction and liquid chromatography-tandem mass spectrometry.

RATIONALE: Secondary hypertension is often caused by activation of complex multi-organ endocrine systems, while renin activity indicated by angiotensins (Angs), aldosterone (ALD) and cortisol (COR) in such systems are generally accepted as its diagnostic markers. As antibody-based methods cannot offer comparable quantification for these biomarkers, a liquid chromatography (LC)-tandem mass spectrometry (MS/MS)-based approach was developed to quantify them simultaneously and accurately. METHODS: Five different beads for magnetic solid-phase extraction (MSPE) were evaluated towards their enrichment efficiency for these biomarkers. An LC system with optimized elution gradient and a triple-quadrupole MS with tuned parameters were coupled to quantitatively monitor the extracted analytes. The method performance was further examined such as linearity, precision, stability, recovery rate and matrix effect. Based on the developed method, the abundance of Ang II, ALD and COR in plasma was measured and the quantification was compared with that derived from commercial ELISA kits. RESULTS: As compared with other MSPEs, Angs, ALD and COR were highly enriched by the HLB magnetic beads with satisfactory recoveries. These analytes were simultaneously quantified by LC/MS/MS and all the method parameters for quantification were well matched with the requirements of clinical testing. Comparison of the quantitative results derived from ELISA and LC/MS/MS exhibited that the two methods offered basically comparable values with Pearson r values at 0.896, 0.895 and 0.835, respectively. The stability test for plasma Angs at room temperature indicated that the abundance of Ang II was relatively stable within 3 h, whereas that of Ang I and Ang 1-7 was time-dependently changed. CONCLUSIONS: Coupling of HLB beads and LC/MS/MS thus enables simultaneous quantification of a set of biomarkers related to secondary hypertension.

Advanced Glycation End Products (AGEs) Inhibit Macrophage Efferocytosis of Apoptotic ß Cells through Binding to the Receptor for AGEs.

Pancreatic ß cell apoptosis is important in the pathogenesis of type 2 diabetes mellitus (T2DM). Generally, apoptotic ß cells are phagocytosed by macrophages in a process known as "efferocytosis." Efferocytosis is critical to the resolution of inflammation and is impaired in T2DM. Advanced glycation end products (AGEs), which are increased in T2DM, are known to suppress phagocytosis function in macrophages. In this study, we found that AGEs inhibited efferocytosis of apoptotic ß cells by primary peritoneal macrophages in C57BL/6J mice or mouse macrophage cell line Raw264.7. Mechanistically, AGEs inhibit efferocytosis by blocking Ras-related C3 botulinum toxin substrate 1 activity and cytoskeletal rearrangement through receptor for advanced glycation end products/ras homolog family member A/Rho kinase signaling in macrophages. Furthermore, it was observed that AGEs decreased the secretion of anti-inflammatory factors and promoted the proinflammatory ones to modulate the inflammation function of efferocytosis. Taken together, our results indicate that AGEs inhibit efferocytosis through binding to receptor for advanced glycation end products and activating ras homolog family member A/Rho kinase signaling, thereby inhibiting the anti-inflammatory function of efferocytosis.

Notoginsenoside R1 restrains the proliferation and migration of airway smooth muscle cells isolated from rats with chronic obstructive pulmonary disease.

OBJECTIVE: Chronic obstructive pulmonary disease (COPD) is a common disorder that is characterized by systemic and lung inflammation. Notoginsenoside R1 (NGR1) displays anti-inflammatory properties in numerous diseases. We aimed to explore the function and mechanism of NGR1 in COPD. MATERIALS AND METHODS: COPD rats were established through cigarette smoke exposure, lipopolysaccharide injection, and cold stimulation. Rat airway smooth muscle cells (ASMCs) were separated and identified. Then, ASMCs were treated with NGR1 (25 or 50 µM) and cigarette smoke extract (CSE). Thereafter, the vitality, proliferation, and migration of ASMCs were measured. Additionally, cell cycle, inflammation-related factors, α-SMA, and PI3K/AKT pathway-related marker expressions of the ASMCs were also detected. Molecular docking experiments were conducted to explore the interaction of NGR1 to PI3K, TGF-ß, p65, and AKT. Moreover, 740 Y-P (a PI3K/Akt pathway agonist) were used to validate the mechanism of NGR1 on COPD. RESULTS: NGR1 inhibited the proliferation and migration, but caused cell cycle arrest for CSE-triggered ASMCs. Furthermore, NGR1 not only decreased IL-1ß, IL-6, IL-8, and TNF-α contents, but also reduced α-SMA expression in CSE-stimulated ASMCs. Moreover, NGR1restrainedTGF-ß1 expression, PI3K, p65, and AKT phosphorylation in CSE-stimulated ASMCs. Molecular docking experiments showed NGR1 exhibited a strong binding ability to PI3K, TGF-ß1, p65, and AKT. Notably, the effects of NGR1 on the proliferation and migration of CSE-induced ASMCs were reversed by 740 Y-P. CONCLUSIONS: NGR1 can restrain the proliferation and migration of CSE-induced ASMCs, indicating that NGR1 may be a therapeutic candidate for treating COPD.

Nucleos(t)ide analogues altered quasispecies composition of hepatitis B virus (HBV)-resistant mutations in serum HBV DNA and serum HBV RNA.

Serum hepatitis B virus (HBV) RNA is a new serological indicator reflecting viral replication with good clinical application prospects. This study aimed to clarify the dynamic changes of serum HBV RNA levels and the quasispecies of HBV RNA virus-like particles in nucleos(t)ide analogues (NAs)-experienced chronic hepatitis B (CHB) patients harboring NAs-resistant mutations and their identifiable effects on NAs resistance. We included CHB patients who were on long-term NAs treatment and with HBV DNA rebound. The longitudinally dynamics of serum HBV RNA levels were quantitatively detected, and the quasispecies differences between serum HBV DNA and serum HBV RNA were compared by high-throughput sequencing. The effect of NAs concentration pressure on altering the resistance mutations quasispecies proportion of HBV DNA and HBV RNA in cell supernatant was analyzed in vitro. A total of 447 serum samples from 36 CHB patients treated with NAs were collected. The median follow-up period was 47 months (about 4 years), and the longest follow-up period was 117 months (about 10 years). Our results showed that HBV RNA could reflect virological breakthrough in 23 (64%, 23/36) patients, and serum HBV RNA rebound earlier than HBV DNA in 12 (52%, 12/23) patients. However, serum HBV RNA remained at a consistently high level and did not fluctuate significantly with the HBV DNA rebound in 6 of 36 patients. In addition, serum HBV RNA was not consistently detectable in 7 of the 36 patients, and their serum HBV RNA was undetectable even after HBV DNA had rebounded. The proportion of drug-resistant mutations in HBV DNA was higher than that of HBV RNA by high-throughput sequencing. The results of in vitro experiments showed that the viral strains with drug-resistant mutation in HBV DNA in cell supernatants gradually become the dominant strains with the increase of NAs concentrations. Serum HBV RNA levels can reflect virological breakthrough in most NAs- treated CHB patients, but there are certain limitations. NAs alter the quasispecies composition of serum HBV DNA and serum HBV RNA, resulting in a higher detection rate of drug-resistant mutations in serum HBV DNA than in serum HBV RNA.

Controllable waveform terahertz generation using rippled plasma driven by an inhomogeneous electrostatic field.

We theoretically present the waveform controls of terahertz (THz) radiations generated from homogeneous and rippled plasma within inhomogeneous external electrostatic field. The Particle-in-cell (PIC) simulations is implemented to demonstrate generation and controllability of three types of THz pulses: single frequency THz pulse in homogeneous plasma, broadband THz pulse and dual frequency THz pulse in rippled plasma. The single frequency THz pulse can be tuned via shifting the knob of electron density of homogeneous plasma. Waveform of broadband THz pulse can be regulated into an envelope-like shape by varying amplitude of electron density of rippled plasma. The two center frequencies' interval of dual frequency THz pulse can be controlled by wave numbers of density distribution of rippled plasma. This work provides a potential means to generate the dual frequency THz pulses with two harmonic frequencies (ω+Ωω, Ω=2) or incommensurate frequencies (ω+Ωω, Ω=1.7,1.8, 2.2…).

Tandem Addition/Cyclization/Halogenation Reaction of Difluoromethylated N-Acylhydrazones with Allyltrimethylsilanes.

As novel difluoromethyl building blocks, difluoromethylated N-acylhydrazones react with allyltrimethylsilanes and the halogen source via a tandem addition/cyclization/halogenation strategy, which produces various difluoromethylpyrazoline compounds in good yields. The method features mild reaction conditions, broad substrate scopes, and a transition metal-free process with easy operation. It also proves that difluoromethylated N-acylhydrazones are useful difluoromethyl building blocks for the construction of difluoromethylated nitrogen heterocycles.

Optimized leaf storage and photosynthetic nitrogen trade-off promote synergistic increases in photosynthetic rate and photosynthetic nitrogen use efficiency.

A coordinated increase in the photosynthetic rate (A) and photosynthetic nitrogen use efficiency (PNUE) is an effective strategy for improving crop yield and nitrogen (N) utilization efficiency. PNUE tends to decrease with increasing N levels, but there are natural variations. Consequently, leaf functional N partitioning in Brassica napus genotypes under different N rates was measured to explore the optimized N allocation model for synchronously increasing A and PNUE values. The results showed that genotypes whose PNUE increased with increasing N supply (PNUE-I) produced an approximate A value with a relatively low leaf N content, owing to reduced storage N (Nstore ) and close photosynthetic N (Npsn ) content. Partial least squares path modeling showed that A was dominated by the Npsn content, and PNUE was directly influenced by A and Nstore . The A value increased with the Npsn content until the Npsn content exceeded the threshold value. The boundary line of PNUE varied with the Npsn and Nstore proportions, indicating that the optimum Npsn and Nstore proportions were 51.6% and 40.3%, respectively. The Nstore proportion of PNUE-I was closer to the thresholds and benefited from lower increments in Rubisco content and nonprotein form storage N content with improved N supply. Optimized Nstore and Npsn trade-off by regulating increments in Nstore content with increased N supply, thereby promoting coordinated increases in A and PNUE.

The influence of different glucose tolerance on QTc interval: a population-based study.

BACKGROUND: Corrected QT (QTc) interval has been reported to be associated with type 2 diabetes. This study aimed to explore the relationship between different glucose tolerance and QTc intervals among middle-aged and older Chinese individuals. METHODS: We conducted a cross-sectional analysis that included 9898 subjects (3194 men and 6704 women) in a Chinese population. Glucose tolerance was studied during the oral glucose tolerance test (OGTT). Insulin, blood pressure, hemoglobin A1c (HbA1c), serum lipids, hepatic transaminases and waist-to-hip ratio were assessed. The QTc interval was derived from ECG recordings, and the subjects were stratified based on different glucose tolerance. RESULTS: QTc interval levels were increased significantly in the subjects with abnormal glucose metabolism compared with the normal glucose regulation group. Multiple regression analyses showed that the QTc interval was significantly associated with fasting plasma glucose, 2-h OGTT plasma glucose and HbA1c. The odds ratio of prolonged QTc was 1.396 for impaired glucose regulation (IFG)/impaired fasting glucose (IGT) (95% CI 0.126-1.730), and 1.342 for type 2 diabetes (95% CI 0.142-1.577) after all potential confounders were adjusted. CONCLUSIONS: Impaired glucose tolerance (IGR) and diabetes are associated with prolonged QTc intervals among middle-aged and older Chinese individuals. Abnormal glucose regulation can be used to monitor the QTc interval in the population.

Integrative analysis of the 3D genome structure reveals that CTCF maintains the properties of mouse female germline stem cells.

The three-dimensional configuration of the genome ensures cell type-specific gene expression profiles by placing genes and regulatory elements in close spatial proximity. Here, we used in situ high-throughput chromosome conformation (in situ Hi-C), RNA sequencing (RNA-seq) and chromatin immunoprecipitation sequencing (ChIP-seq) to characterize the high-order chromatin structure signature of female germline stem cells (FGSCs) and identify its regulating key factor based on the data-driven of multiple omics data. By comparison with pluripotent stem cells (PSCs), adult stem cells (ASCs), and somatic cells at three major levels of chromatin architecture, A/B compartments, topologically associating domains, and chromatin loops, the chromatin architecture of FGSCs was most similar to that of other ASCs and largely different from that of PSCs and somatic cells. After integrative analysis of the three-dimensional chromatin structure, active compartment-associating loops (aCALs) were identified as a signature of high-order chromatin organization in FGSCs, which revealed that CCCTC-binding factor was a major factor to maintain the properties of FGSCs through regulation of aCALs. We found FGSCs belong to ASCs at chromatin structure level and characterized aCALs as the high-order chromatin structure signature of FGSCs. Furthermore, CTCF was identified to play a key role in regulating aCALS to maintain the biological functions of FGSCs. These data provide a valuable resource for future studies of the features of chromatin organization in mammalian stem cells and further understanding of the fundamental characteristics of FGSCs.

A Lightweight Intelligent Network Intrusion Detection System Using One-Class Autoencoder and Ensemble Learning for IoT.

Network intrusion detection technology is key to cybersecurity regarding the Internet of Things (IoT). The traditional intrusion detection system targeting Binary or Multi-Classification can detect known attacks, but it is difficult to resist unknown attacks (such as zero-day attacks). Unknown attacks require security experts to confirm and retrain the model, but new models do not keep up to date. This paper proposes a Lightweight Intelligent NIDS using a One-Class Bidirectional GRU Autoencoder and Ensemble Learning. It can not only accurately identify normal and abnormal data, but also identify unknown attacks as the type most similar to known attacks. First, a One-Class Classification model based on a Bidirectional GRU Autoencoder is introduced. This model is trained with normal data, and has high prediction accuracy in the case of abnormal data and unknown attack data. Second, a multi-classification recognition method based on ensemble learning is proposed. It uses Soft Voting to evaluate the results of various base classifiers, and identify unknown attacks (novelty data) as the type most similar to known attacks, so that exception classification becomes more accurate. Experiments are conducted on WSN-DS, UNSW-NB15, and KDD CUP99 datasets, and the recognition rates of the proposed models in the three datasets are raised to 97.91%, 98.92%, and 98.23% respectively. The results verify the feasibility, efficiency, and portability of the algorithm proposed in the paper.

Free nitrous acid prediction in ANAMMOX process using hybrid deep neural network model.

Free nitrous acid (FNA) is a critical metric for stabilization of ANAMMOX but can not be directly and immediately measured by sensors or chemical measurement method, which hinders the effective management and operation for ANAMMOX. This study focuses on FNA prediction using hybrid model based on temporal convolutional network (TCN) combined with attention mechanism (AM) optimized by multiobjective tree-structured parzen estimator (MOTPE), called MOTPE-TCNA. A case study in an ANAMMOX reactor is carried out. Results show that nitrogen removal rate (NRR) is highly correlated with FNA concentration, indicating that it can forecast the operational status by predicting FNA. Then, MOTPE successfully optimizes the hyperparameters of TCN, helping TCN achieve a high prediction accuracy, and AM furtherly improves model accuracy. MOTPE-TCNA obtains the highest prediction accuracy, whose R2 value gets 0.992, increasing 1.71-11.80% compared to other models. As a deep neural network model, MOTPE-TCNA has more advantages than traditional machine learning methods in FNA prediction, which is beneficial to maintain the stable operation and easy control for ANAMMOX process.

Mechanochemical Synthesis of PdO2 Nanoparticles Immobilized over Silica Gel for Catalytic Suzuki-Miyaura Cross-Coupling Reactions Leading to the C-3 Modification of 1H-Indazole with Phenylboronic Acids.

The C-3 modification of 1H-indazole has produced active pharmaceuticals for the treatment of cancer and HIV. But, so far, this transformation has seemed less available, due to the lack of efficient C-C bond formation at the less reactive C-3 position. In this work, a series of silica gel-supported PdO2 nanoparticles of 25-66 nm size were prepared by ball milling silica gel with divalent palladium precursors, and then employed as catalysts for the Suzuki-Miyaura cross-coupling of 1H-indazole derivative with phenylboronic acid. All the synthesized catalysts showed much higher cross-coupling yields than their palladium precursors, and could also be reused three times without losing high activity and selectivity in a toluene/water/ethanol mixed solvent. Although the palladium precursors showed an order of activity of PdCl2(dppf, 1,1'-bis(diphenylphosphino)ferrocene) > PdCl2(dtbpf, 1,1'-bis(di-tert-butylphosphino)ferrocene) > Pd(OAc, acetate)2, the synthesized catalysts showed an order of C1 (from Pd(OAc)2) > C3 (from PdCl2(dtbpf)) > C2 (from PdCl2(dppf)), which conformed to the orders of BET (Brunauer-Emmett-Teller) surface areas and acidities of these catalysts. Notably, the most inexpensive Pd(OAc)2 can be used as a palladium precursor for the synthesis of the best catalyst through simple ball milling. This work provides a highly active and inexpensive series of catalysts for C-3 modification of 1H-indazole, which are significant for the large-scale production of 1H-indazole-based pharmaceuticals.

An Adaptive Model Filtering Algorithm Based on Grubbs Test in Federated Learning.

Federated learning has been popular for its ability to train centralized models while protecting clients' data privacy. However, federated learning is highly susceptible to poisoning attacks, which can result in a decrease in model performance or even make it unusable. Most existing defense methods against poisoning attacks cannot achieve a good trade-off between robustness and training efficiency, especially on non-IID data. Therefore, this paper proposes an adaptive model filtering algorithm based on the Grubbs test in federated learning (FedGaf), which can achieve great trade-offs between robustness and efficiency against poisoning attacks. To achieve a trade-off between system robustness and efficiency, multiple child adaptive model filtering algorithms have been designed. Meanwhile, a dynamic decision mechanism based on global model accuracy is proposed to reduce additional computational costs. Finally, a global model weighted aggregation method is incorporated, which improves the convergence speed of the model. Experimental results on both IID and non-IID data show that FedGaf outperforms other Byzantine-robust aggregation rules in defending against various attack methods.

Serum creatinine levels and risk of nonalcohol fatty liver disease in a middle-aged and older Chinese population: A cross-sectional analysis.

BACKGROUND: Non-alcoholic fatty liver disease (NAFLD) is now regarded as the hepatic manifestation of metabolic syndrome (MetS). Recent research has suggested that serum creatinine (SCr) may be an indicator of MetS and its related diseases. We aimed to investigate the association between SCr and NAFLD in Chinese adults. METHODS: A cross-sectional sample of 8862 subjects aged 40 years or older (40-73 years) from China were analysed in this study. The anthropometric measurements, laboratory tests, and hepatic ultrasonography were conducted. NAFLD presence was defined by hepatic ultrasound in the absence of other liver diseases. RESULTS: NAFLD subjects had higher SCr than those without NAFLD (66.8 µmol/L vs. 65.6 µmol/L, p < 0.001). Moreover, SCr levels were correlated with alanine aminotransferase (ß = 0.099, p < 0.001), aspartate aminotransferase (ß = 0.135, p < 0.001), γ-glutamyltransferase (ß = 0.039, p < 0.001), and insulin resistance (ß = 0.027, p = 0.014) after adjusted for potential covariates. In the multivariable-adjusted logistic regression analyses, compared to the first SCr quintile, the odds ratio for NAFLD was 1.35 (95% confidence interval 1.14-1.60, p < 0.001) for the fifth quintile after adjusting multiple measured confounders. CONCLUSION: SCr concentration is independently associated with NAFLD in a middle aged and older Chinese population. Elevated SCr levels, even within normal ranges, were associated with higher risk of NAFLD.

Mechanistic insights into HuR inhibitor MS-444 arresting embryonic development revealed by low-input RNA-seq and STORM.

With improvements in the survival rate of patients with cancer, fertility maintenance has become a major concern in terms of cancer treatment for women of reproductive age. Thus, it is important to examine the impact on fertility of anticancer drugs that are used clinically or are undergoing trials. The HuR small-molecule inhibitor MS-444 has been used in many cancer treatment studies, but its reproductive toxicity in females is unknown. Here, we reported that MS-444 blocked the nucleocytoplasmic transport of Agbl2 mRNA by inhibiting HuR dimerization, resulting in the developmental arrest of 2-cell stage embryos in mouse. Combining analysis of low-input RNA-seq for MS-444-treated 2-cell embryos and mapping binding sites of RNA-binding protein, Agbl2 was predicted to be the target gene of MS-444. For further confirmation, RNAi experiment in wild-type zygotes showed that Agbl2 knockdown reduced the proportion of embryos successfully developed to the blastocyst stage: from 71% in controls to 23%. Furthermore, RNA-FISH and luciferase reporter analyses showed that MS-444 blocked the nucleocytoplasmic transport of Agbl2 mRNA and reduced its stability by inhibiting HuR dimerization. In addition, optimized stochastic optical reconstruction microscopy (STORM) imaging showed that MS-444 significantly reduced the HuR dimerization, and HuR mainly existed in cluster form in 2-cell stage embryos. In conclusion, this study provides clinical guidance for maintaining fertility during the treatment of cancer with MS-444 in women of reproductive age. And also, our research provides guidance for the application of STORM in nanometer scale studies of embryonic cells. HuR inhibitor MS-444 arrested embryonic development at 2-cell stage. Low-input RNA-seq revealed that Agbl2 was the target gene of MS-444. MS-444 blocked the nucleocytoplasmic transport of Agbl2 mRNA by inhibiting HuR dimerization and reduced the stability of Agbl2 mRNA. STORM with our optimized protocol showed that HuR tended to form elliptical and dense clusters in 2-cell stage embryos.

Water quality prediction model using Gaussian process regression based on deep learning for carbon neutrality in papermaking wastewater treatment system.

Wastewater recycling is the measure with enormous potentiality to achieve carbon neutrality in wastewater treatment plants. High-precision online monitoring can improve the stability of wastewater treatment system and help wastewater recycling. A new water quality prediction CSWLSTM-GPR model, which fused the spatial feature of convolutional neural network (CNN), the temporal feature of sharing-weight long short-term memory (SWLSTM) and the probabilistic reliability of Gaussian process regression (GPR), was applied for monitoring papermaking wastewater treatment system with high-precision point prediction and interval prediction. Compared with SWLSTM-GPR and CLSTM-GPR, RMSE of CSWLSTM-GPR reduced by more than 48.9% on effluent chemical oxygen demand (CODeff), MAE reduced by more than 49.3%, R2 increased by more than 25.14%, R increased by more than 7.07%. And for the effluent suspended solids (SSeff), CSWLSTM-GPR had better predictive results than SWLSTM-GPR and CSWLSTM-GPR. Compared with SWLSTM-GPR, RMSE, MAE, R, R2 of CSWLSTM-GPR on effluent suspended solids (SSeff) were improved by 4.8%, 6.1%, 29.01% and 31.15%, respectively. Simulation results showed convincing comprehensive forecasting ability were obtained and the true values frequently stayed within the water quality range obtained by CSWLSTM-GPR model, which provided important insights for online monitoring, wastewater recycling and carbon neutrality of papermaking industry.