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ABSTRACT Lyme disease, caused by spirochetes in the Borrelia burgdorferi sensu lato clade within the Borrelia genus, is transmitted by Ixodes ticks and is currently the most prevalent and rapidly expanding tick-borne disease in Europe and North America. We report complete genome sequences of 47 isolates that encompass all established species in this clade while highlighting the diversity of the widespread human pathogenic species B. burgdorferi. A similar set of plasmids has been maintained throughout Borrelia divergence, indicating that they are a key adaptive feature of this genus. Phylogenetic reconstruction of all sequenced Borrelia genomes revealed the original divergence of Eurasian and North American lineages and subsequent dispersals that introduced B. garinii, B. bavariensis, B. lusitaniae, B. valaisiana, and B. afzelii from East Asia to Europe and B. burgdorferi and B. finlandensis from North America to Europe. Molecular phylogenies of the universally present core replicons (chromosome and cp26 and lp54 plasmids) are highly consistent, revealing a strong clonal structure. Nonetheless, numerous inconsistencies between the genome and gene phylogenies indicate species dispersal, genetic exchanges, and rapid sequence evolution at plasmid-borne loci, including key host-interacting lipoprotein genes. While localized recombination occurs uniformly on the main chromosome at a rate comparable to mutation, lipoprotein-encoding loci are recombination hotspots on the plasmids, suggesting adaptive maintenance of recombinant alleles at loci directly interacting with the host. We conclude that within- and between-species recombination facilitates adaptive sequence evolution of host-interacting lipoprotein loci and contributes to human virulence despite a genome-wide clonal structure of its natural populations.IMPORTANCELyme disease (also called Lyme borreliosis in Europe), a condition caused by spirochete bacteria of the genus Borrelia, transmitted by hard-bodied Ixodes ticks, is currently the most prevalent and rapidly expanding tick-borne disease in the United States and Europe. Borrelia interspecies and intraspecies genome comparisons of Lyme disease-related bacteria are essential to reconstruct their evolutionary origins, track epidemiological spread, identify molecular mechanisms of human pathogenicity, and design molecular and ecological approaches to disease prevention, diagnosis, and treatment. These Lyme disease-associated bacteria harbor complex genomes that encode many genes that do not have homologs in other organisms and are distributed across multiple linear and circular plasmids. The functional significance of most of the plasmid-borne genes and the multipartite genome organization itself remains unknown. Here we sequenced, assembled, and analyzed whole genomes of 47 Borrelia isolates from around the world, including multiple isolates of the human pathogenic species. Our analysis elucidates the evolutionary origins, historical migration, and sources of genomic variability of these clinically important pathogens. We have developed web-based software tools (BorreliaBase.org) to facilitate dissemination and continued comparative analysis of Borrelia genomes to identify determinants of human pathogenicity.

Under the forces of expansive soil and landslides, the construction of the tunnel entrance is more likely to cause engineering disasters, such as surface cracking and landslides. The application of micro piles in the tunnel has advantages over anti slide piles. Based on the homogenization theory and upper limit analysis, this study calculates the stability of expansive soil landslide at the entrance of an expressway tunnel, and evaluates the treatment effect of different combinations of micro pile groups and cutting-unloading. In the calculation, to improve the calculation efficiency, the micro pile groups and soil around the piles are equivalent to the plus solid conforming to the Mohr-Coulomb strength criterion based on the homogenization theory. the results then are verified by monitoring the landslide deformation after the cutting and micro pile group reinforcement treatment in the field. This study indicates that compared with the strength parameters of soil, the internal friction angle of equivalent reinforcement remains constant, and the cohesion increases from 26 kPa to 85.36 kPa. The evaluated landslide stability before and after treatment show that the sliding surface of the landslide extends from the rock-soil interface above the landslide to the front of the tunnel portal without treatment; when only using micro pile group reinforcement, the landslide safety factor is about 1.17, and the sliding surface extends from the rock-soil interface to the tunnel portal; when only using both micro pile group reinforcement and cutting-unloading, the safety factor increases from 1.26 to 1.28, and the upper edge of the sliding surface moves forward from the rock-soil interface. The field deformation monitoring shows that the deformation of surface and deep soil are less than 3 mm, which can keep the landslide stable, and also verifies the effectiveness of the calculation method. This study provides beneficial information for similar projects.

Abstract Estrogens promote binge alcohol drinking and contribute to sex differences in alcohol use disorder. However, the mechanisms are largely unknown. This study aims to test if estrogens act on 5-hydroxytryptamine neurons in the dorsal raphe nucleus (5-HTDRN) to promote binge drinking. We found that female mice drank more alcohol than male mice in chronic drinking in the dark (DID) tests. This sex difference was associated with distinct alterations in mRNA expression of estrogen receptor α (ERα) and 5-HT-related genes in the DRN, suggesting a potential role of estrogen/ERs/5-HT signaling. In supporting this view, 5-HTDRN neurons from naïve male mice had lower baseline firing activity but higher sensitivity to alcohol-induced excitation compared to 5-HTDRN neurons from naïve female mice. Notably, this higher sensitivity was blunted by 17β-estradiol treatment in males, indicating an estrogen-dependent mechanism. We further showed that both ERα and ERβ are expressed in 5-HTDRN neurons, whereas ERα agonist depolarizes and ERβ agonist hyperpolarizes 5-HTDRN neurons. Notably, both treatments blocked the stimulatory effects of alcohol on 5-HTDRN neurons in males, even though they have antagonistic effects on the activity dynamics. These results suggest that ERs’ inhibitory effects on ethanol-induced burst firing of 5-HTDRN neurons may contribute to higher levels of binge drinking in females. Consistently, chemogenetic activation of ERα- or ERβ-expressing neurons in the DRN reduced binge alcohol drinking. These results support a model in which estrogens act on ERα/β to prevent alcohol-induced activation of 5-HTDRN neurons, which in return leads to higher binge alcohol drinking.

Abstract Acute lung injury (ALI) as well as its more severe form, acute respiratory distress syndrome (ARDS), frequently leads to an uncontrolled inflammatory response. N6-methyladenosine (m6A) modification was associated with the progression of several inflammatory diseases. However, the role of methyltransferase-like 14 (METTL14)-mediated m6A methylation in ALI/ARDS remains unclear. Here, we reported an increase in overall expression levels of m6A and METTL14 in circulating monocyte-derived macrophages recruited to the lung following ALI, which is correlated with the severity of lung injury. We further demonstrated the critical function of METTL14 in activating NOD-like receptor pyrin domain-containing protein 3 (NLRP3) inflammasome in vitro and in mouse models of ALI/ARDS, and validated NLRP3 as the downstream target of METTL14 by the m6A RNA immunoprecipitation (MeRIP) and RIP assays. Mechanistically, METTL14-methylated NLRP3 transcripts were subsequently recognized by insulin-like growth factor 2 mRNA-binding protein 2 (IGF2BP2), an m6A reader, which stabilized NLRP3 mRNA. Furthermore, we observed that IGF2BP2 knockdown diminished LPS-induced ALI in mice by downregulating NLRP3 expression. In summation, our study revealed that the molecular mechanism underlying the pathogenesis of ALI/ARDS involves METTL14-mediated activation of NLRP3 inflammasome in an IGF2BP2 dependent manner, thereby demonstrating the potential of METTL14 and IGF2BP2 as promising biomarkers and therapeutic targets for ALI/ARDS treatment.

In order to accurately predict the power consumption data of charging piles, assist related enterprises to accurately predict the benefits of charging piles and further optimize the relationship between households and transformers, this paper proposes an improved Gate Recurrent Unit (IGRU) prediction model based on spline interpolation. This method first extracts relevant data features based on Pearson correlation analysis, and then fuses feature data and performs spline interpolation input prediction network model for charging pile load pre-diction. Finally, based on the power consumption data of 174 charging piles in the jurisdiction of a provincial capital city in southwest China, the prediction accuracy of the model is verified. Through case analysis and experimental comparison, it shows that the improve gate recurrent unit (IGRU) prediction model designed in this paper is superior to the traditional deep learning prediction model in terms of stability, prediction accuracy and generalization ability.

The development of multifunctional materials with optical and electrical properties has become a research hotspot in recent years. In this work, multifunctional 0.935(Bi[Formula: see text]Na[Formula: see text])TiO3–0.065BaTiO3 (BNT–BT)-based ferroelectric ceramics doped with small amounts of CaMAlO4 ([Formula: see text], Ho) were prepared, and the effect of CaMAlO4 on the electrostrain and photoluminescence properties of the ceramics was studied. The results showed that the CaMAlO4 addition weakened the ferroelectric properties of the BNT–BT matrix, and promoted the improvement of the electrostrain performance. For samples doped with 1.5[Formula: see text]mol% CaMAlO4, the unipolar strain [Formula: see text] reached the largest values, which were 0.33% ([Formula: see text]) and 0.38% ([Formula: see text]) under an electric field of 70[Formula: see text]kV/cm, corresponding to a large signal [Formula: see text] ([Formula: see text]) of 471[Formula: see text]pm/V ([Formula: see text]) and 543[Formula: see text]pm/V ([Formula: see text]), respectively. In addition, due to the existing Dy[Formula: see text] and Ho[Formula: see text] luminescent ions, the modified samples exhibited excellent photoluminescence performance, which exhibited bright yellow emission ([Formula: see text]) and green emission [Formula: see text] under the blue excitation. Due to their multifunctional features, these materials have potential applications as “on-off” actuators, optical-electro integration and coupling devices.

Backgroud and objectivesThe implementation of patient-specific quality assurance (PSQA) has become a crucial aspect of the radiation therapy process. Machine learning models have demonstrated their potential as virtual QA tools, accurately predicting the gamma passing rate (GPR) of volumetric modulated arc therapy (VMAT)plans, thereby ensuring safe and efficient treatment for patients. However, there is limited multi-center research dedicated to predicting the GPR. In this study, a dosiomics-based machine learning approach was employed to construct a prediction model for classifying GPR in multiple radiotherapy institutions. Additionally, the model’s performance was compared by evaluating the impact of two distinct feature selection methods.MethodsA retrospective data collection was conducted on 572 VMAT patients across three radiotherapy institutions. Utilizing a three-dimensional dose verification technique grounded in real-time measurements, γ analysis was conducted according to the criteria of 3%/2 mm and 2%/2 mm, employing a dose threshold of 10% along with absolute dose and global normalization mode. Dosiomics features were extracted from the dose files, and distinct subsets of features were selected as inputs for the model using the random forest (RF) and RF combined with SHapley Additive exPlanations (SHAP) methods. The data underwent training using the extreme gradient boosting (XGBoost) algorithm, and the model’s classification performance was assessed through F1-score and area under the curve (AUC) values.ResultsThe model exhibited optimal performance under the 3%/2 mm criteria, utilizing a subset of 20 features and attaining an AUC value of 0.88 and an F1-score of 0.89. Similarly, under the 2%/2 mm criteria, the model demonstrated superior performance with a subset of 10 features, resulting in an AUC value of 0.91 and an F1-score of 0.89. The feature selection methods of RF and RF + SHAP have achieved good model performance by selecting as few features as possible.ConclusionBased on the multi-center PSQA results, it is possible to utilize dosiomics features extracted from dose files to construct a machine learning predictive model. This model demonstrates excellent discriminative abilities, thus promoting the progress of gamma passing rate prognostic models in clinical application and implementation. Furthermore, it holds potential in providing patients with secure and efficient personalized QA management, while also reducing the workload of medical physicists.

Background Combining immune checkpoint inhibitors (ICIs) with chemotherapy has become a standard treatment for patients with non-small cell lung cancer (NSCLC) lacking driver gene mutations. Reliable biomarkers are essential for predicting treatment outcomes. Emerging evidence from various cancers suggests that early assessment of serum metabolites could serve as valuable biomarkers for predicting outcomes. This study aims to identify metabolites linked to treatment outcomes in patients with advanced NSCLC undergoing first-line or second-line therapy with programmed cell death 1 (PD-1) inhibitors plus chemotherapy.Method 200 patients with advanced NSCLC receiving either first-line or second-line PD-1 inhibitor plus chemotherapy, and 50 patients undergoing first-line chemotherapy were enrolled in this study. The 200 patients receiving combination therapy were divided into a Discovery set (n=50) and a Validation set (n=150). These sets were further categorized into respond and non-respond groups based on progression-free survival PFS criteria (PFS≥12 and PFS1 and p

Abstract Background Mitochondrial dysfunction and lung cellular senescence are significant features involved in the pathogenesis of chronic obstructive pulmonary disease (COPD). Cigarette smoke (CS) stands as the primary contributing factor to COPD. This study examined mitochondrial dynamics, mitophagy and lung cellular senescence in COPD patients and investigated the effects of modulation of mitochondrial fusion [mitofusin2 (MFN2) and Optic atrophy 1 (OPA1)] on CS extract (CSE)-induced lung cellular senescence. Methods Senescence-associated secretory phenotype (SASP) component mRNAs (IL-1β, IL-6, CXCL1 and CXCL8), mitochondrial morphology, mitophagy and mitochondria-related proteins (including phosphorylated-DRP1(p-DRP1), DRP1, MFF, MNF2, OPA1, PINK1, PARK2, SQSTM1/p62 and LC3b) and senescence-related proteins (including P16, H2A.X and Klotho) were measured in lung tissues or primary alveolar type II (ATII) cells of non-smokers, smokers and COPD patients. Alveolar epithelial (A549) cells were exposed to CSE with either pharmacologic inducer (leflunomide and BGP15) or genetic induction of MFN2 and OPA1 respectively. Results There were increases in mitochondrial number, and decreases in mitochondrial size and activity in lung tissues from COPD patients. SASP-related mRNAs, DRP1 phosphorylation, DRP1, MFF, PARK2, SQSTM1/p62, LC3B II/LC3B I, P16 and H2A.X protein levels were increased, while MFN2, OPA1, PINK1 and Klotho protein levels were decreased in lung tissues from COPD patients. Some similar results were identified in primary ATII cells of COPD patients. CSE induced increases in oxidative stress, SASP-related mRNAs, mitochondrial damage and dysfunction, mitophagy and cellular senescence in A549 cells, which were ameliorated by both pharmacological inducers and genetic overexpression of MFN2 and OPA1. Conclusions Impaired mitochondrial fusion, enhanced mitophagy and lung cellular senescence are observed in the lung of COPD patients. Up-regulation of MFN2 and OPA1 attenuates oxidative stress, mitophagy and lung cellular senescence, offering potential innovative therapeutic targets for COPD therapy. Graphical Abstract

Highlights Engineering Fe-N4 electronic structure with adjacent Co-N2C2 and Co sub-nanoclusters to optimize the electronic structure of the Fe-N4 active center is first demonstrated. Electrochemical studies reveal that the amorphous carbon corrosion leads to significantly increased charge- and mass-transport resistances. The operando X-ray absorption spectroscopy allows an investigation of the effect of highly oxidative environments on electrochemical behavior.

Small modular reactors (SMRs) are currently advancing towards increased degrees of automation and intelligence, with intelligent control emerging as a prominent trend in SMR development. SMRs exhibit significant variations in design specifications and safety auxiliary system design as compared to conventional commercial nuclear power reactors. Consequently, defect diagnostic techniques that rely on commercial nuclear power plants are not appropriate for SMRs. This study designed a defect detection system for the System-integrated Modular Advanced ReacTor SMR by utilizing the PCTRAN/SMR V1.0 software and a deep learning neural network structure. Through the comparison of several neural network designs, it was discovered that the CNN-BiLSTM model, which utilizes bidirectional data processing, obtained a fault diagnostic accuracy of 97.33%. This result confirms the accuracy and effectiveness of the fault diagnosis system. This strongly supports the eventual implementation of autonomous control for SMRs.

The cumulative deformation properties of subgrade soil under cyclic traffic loads are critical for optimizing pavement structure design and ensuring long-term highway structural performance. This study aims to investigate the coupling effect of freeze-thaw cycles and cyclic loads on the cumulative deformation behaviors and meso-structure of coarse-grained saline soil (CGSS) subgrade filling in high-cold areas. Dynamic triaxial tests and computed tomography (CT) scanning were conducted to analyze the CGSS under different working conditions. The research focused on the dynamic deformation development and damage evolution under varying freeze-thaw cycles and load amplitudes. The research results show that the cumulative deformation behavior of CGSS under cyclic loading is relatively sensitive to the freeze-thaw process. The cumulative dynamic strain increases as the freeze-thaw cycles, with a critical freeze-thaw cycle number of five. The stable cumulative dynamic strain curve exhibits clear three-stage characteristics when plotted in semi-log coordination, with critical loading cycles at 20 and 1,000. After 10–100 loading cycles, the cumulative strain curve quickly shows failure. The CGSS’s low density and pore regions greatly increase after a freeze-thaw cycle. The rise in dynamic stress amplitude notably affects the bonding between soil particles and crystalline salts. The coupling effect of the freeze-thaw cycle and dynamic activity exacerbates the deterioration of soil structure, resulting in variations in CT values within the scanning layer in the final state.

Abstract Objective Responders of the World Trade Center (WTC) disaster suffer from co‐morbidities. A Mediterranean Diet (MedDiet) nutrition intervention with physical activity was implemented among WTC responders with overweight/obesity and post‐traumatic stress disorder (PTSD). Methods WTC Health Program members (N = 62), 45–65 years, males 87%, body mass index (BMI) 27–45 kg/m2 randomized to MedDiet (n = 31) or usual nutrition counseling (n = 31). The 10‐week intervention included online nutrition education, text messages, and group experiential cooking; both groups had three in‐person individual nutrition counseling. Anthropometrics, serum biomarkers, psychosocial factors, MedDiet score, and PTSD symptoms were assessed at baseline, post‐intervention, and 3‐months (follow‐up). The primary outcome was intervention feasibility and secondary outcomes were within‐ and between‐group changes of all measures at post‐intervention and follow‐up. Nonparametric Wilcoxon rank sum tests for between‐group comparisons and Wilcoxon signed rank tests for pre‐post within‐group comparisons. Results A total of 58(94%) and 46(74%) participants completed the post‐intervention and follow‐up measurements, respectively. Both groups experienced significant improvements in anthropometrics, MedDiet score, oxidized low‐density lipoprotein, and PTSD symptoms. Baseline median (range) were weight 100.42 (73.66–135.17) kg, BMI 33.20 (27.50–41.75) kg/m2, and Waist circumference (WC) 109.22 (90.17–150.62) cm. Median % weight loss at post‐intervention was MedDiet: −3% (−11%–7%), p = 0.0002; Control: −1% (−13%–4%), p = 0.008 and at follow‐up MedDiet: −2% (−14%–12%), p = 0.07; Control: −2% (−20%–3%), p = 0.006. The overall BMI was reduced by −0.68 kg/m2 (−4.61–2.09) kg/m2 p

Digital transformation plays an important role in improving the efficiency of production of enterprises and can provide strong support for green and sustainable development. Compared with domestic enterprises, outward foreign direct investment (OFDI) enterprises have greater access to advanced digital technology. This paper aims to analyze the path selection of green and sustainable production for the digital transformation of manufacturing outward foreign direct investment (OFDI) companies, whether gradual or leapfrogging. However, there is a lack of systemic game mechanisms and numerical simulation methods for heterogeneous enterprises. Based on the analysis of reverse technology spillover intensity of outward foreign direct investment (OFDI) and differences in the absorptive capacity of enterprises, we have proposed the evolutionary game model for different path selection of digital transformation of manufacturing enterprises, due to heterogeneous enterprises under different spillover degrees with numerical analysis methods. The research results show that: (i) Under low reverse technology spillover intensity, all enterprises evolve to a gradual transformation path, and enterprises with weaker absorptive capacity converge faster; (ii) There is a certain threshold for reverse technology spillover. When reverse technology spillover intensity exceeds the threshold, enterprises with stronger absorptive capacity converge to a leapfrog transformation path, but enterprises with weak absorptive capacity converge to a gradual transformation path; (iii) With high reverse technology spillover intensity, all enterprises evolve toward a leapfrog transformation path, and faster convergence happens to enterprises with higher absorptive capacity. The evolutionary game path of digital transformation in manufacturing enterprises is illustrated in Fig. 1.

Abstract With the rapid development of computer technology, artificial intelligence and big data technology have undergone a qualitative leap, permeating into various industries. In order to fully harness the role of artificial intelligence in the field of nuclear engineering, we propose to use the LSTM algorithm in deep learning to model the BEAVRS (Benchmark for Evaluation And Validation of Reactor Simulations) core first cycle loading. The BEAVRS core is simulated by DRAGON and DONJON, the training set and the test set are arranged in a sequential fashion according to the evolution of time, and the LSTM model is constructed by changing a number of hyperparameters. In addition to this, the training set and the test set are retained in a chronological order that is different from one another throughout the whole process. Additionally, there is a significant pattern that is followed when subsetting both the training set and the test set. This pattern applies to both sets. The steps in this design are very carefully arranged. The findings of the experiments suggest that the model can be altered by making use of the appropriate hyperparameters in such a way as to bring the maximum error of the effective multiplication factor keff prediction of the core within 2.5 pcm (10–5), and the average error within 0.5266 pcm, which validated the successful application of machine learning to transport equations.

Magnetic nanoparticles (MNPs) have found extensive application in the biomedical domain due to their enhanced biocompatibility, minimal toxicity, and strong magnetic responsiveness. MNPs exhibit great potential as nanomaterials in various biomedical applications, including disease detection and cancer therapy. Typically, MNPs consist of a magnetic core surrounded by surface modification coatings, such as inorganic materials, organic molecules, and polymers, forming a nucleoshell structure that mitigates nanoparticle agglomeration and enhances targeting capabilities. Consequently, MNPs exhibit magnetic responsiveness in vivo for transportation and therapeutic effects, such as enhancing medical imaging resolution and localized heating at the site of injury. MNPs are utilized for specimen purification through targeted binding and magnetic separation in vitro, thereby optimizing efficiency and expediting the process. This review delves into the distinctive functional characteristics of MNPs as well as the diverse bioactive molecules employed in their surface coatings and their corresponding functionalities. Additionally, the advancement of MNPs in various applications is outlined. Additionally, we discuss the advancements of magnetic nanoparticles in medical imaging, disease treatment, and in vitro assays, and we anticipate the future development prospects and obstacles in this field. The objective is to furnish readers with a thorough comprehension of the recent practical utilization of MNPs in biomedical disciplines.

Cement grout is traditionally used for treating water leakage distress in tunnels. However, traditional cement grout has the disadvantages of a poor anti-seepage performance, long setting time, and slow strength gain. To this end, a high-performance cement-based capillary crystalline waterproofing (CCCW) grouting material was synthesized using cement, capillary crystalline material, and several admixtures. The influences of the material proportions on the viscosity, bleeding rate, and setting time of the fresh grout, as well as the permeability coefficient of the grouted aggregate and the unconfined compression strength of the hardened grout material, were systematically studied. The mineralogy and microstructure of the CCCW grouting material were examined using X-ray diffraction, industrial computed tomography, and scanning electron microscopy. The results indicated that the capillary crystalline material PNC803 was not suitable for mixing with bentonite, sodium chloride, and triethanolamine in cementitious slurries, but it can produce excellent synergistic effects with sulfate, calcium chloride, and triisopropanolamine. An analysis of the microstructure of the CCCW grouting material showed that the PNC803 and additives can promote the hydration of cement, which yields more hydration products, sealing water passage and filling micro voids and therefore leading to enhanced waterproofing and strengthening effects. These research results could improve the applicability of CCCW material in tunnel engineering.

Background Heart failure (HF) in patients undergoing maintenance hemodialysis (MHD) increases their hospitalization rates, mortality, and economic burden significantly. We aimed to develop and validate a predictive model utilizing contemporary deep phenotyping for individual risk assessment of all-cause mortality or HF hospitalization in patients on MHD.Materials and Methods A retrospective review was conducted from January 2017 to October 2022, including 348 patients receiving MHD from four centers. The variables were adjusted by Cox regression analysis, and the clinical prediction model was constructed and verified.Results The median follow-up durations were 14 months (interquartile range [IQR] 9–21) for the modeling set and 14 months (9–20) for the validation set. The composite outcome occurred in 72 (29.63%) of 243 patients in the modeling set and 39 (37.14%) of 105 patients in the validation set. The model predictors included age, albumin, history of cerebral hemorrhage, use of angiotensin-converting enzyme inhibitors/angiotensin II receptor blockers/“sacubitril/valsartan”, left ventricular ejection fraction, urea reduction ratio, N-terminal prohormone of brain natriuretic peptide, and right atrial size. The C-index was 0.834 (95% CI 0.784–0.883) for the modeling set and 0.853 (0.798, 0.908) for the validation set. The model exhibited excellent calibration across the complete risk profile, and the decision curve analysis (DCA) suggested its ability to maximize patient benefits.Conclusion The developed prediction model offered an accurate and personalized assessment of HF hospitalization risk and all-cause mortality in patients with MHD. It can be employed to identify high-risk patients and guide treatment and follow-up.

The exploration of novel bio-based functional polymers has high application value and confirms to sustainable development strategies following the increasing shortage of fossil resources. In this research, several different recyclable bio-based dynamic covalent polymer networks (DCPNs) containing dynamic Diels-Alder bonds from vegetable oil and furan were designed and fabricated via a simple preparation process. The reprocessability, shape memory, molecular structures, thermal properties and mechanical properties of the DCPNs were all investigated. 1H nuclear magnetic resonance (1H-NMR) and Fourier transform infrared spectroscopy (FTIR) analysises demonstrated the target reactive products were all successfully synthesized. Variable-temperature FTIR and differential scanning calorimetry revealed the changing rule of dynamic Diels-Alder bond molecular structures with temperature. The DCPNs possess controllable tensile properties including superior ductility and certain rigidity via adjusting fatty chain component, which is in accordance with the result of dynamic mechanical analysis. Thermal gravimetric analysis demonstrated the DCPNs had excellent thermostability, and the main peak decomposition temperatures were all above 460 °C. The nature of the dynamic Diels-Alder bonds could make shattered DCPNs be reprocessed multiple times under relatively mild conditions. The DCPNs displayed certain shape memory properties, and the shape fixation and recovery ratio at the last two cycles were kept above 95.53% and 84.58%, respectively. This work will help with the development on this kind of bio-based polymers containing dynamic Diels-Alder covalent bonds.

Abstract Proteomics provides an opportunity to develop biomarkers for the early detection and monitoring of post-traumatic stress disorder (PTSD). However, research to date has been limited by small sample sizes and a lack of replication. This study performed Olink Proseek Multiplex Platform profiling of 81 proteins involved in neurological processes in 936 responders to the 9/11 disaster (mean age at blood draw = 55.41 years (SD = 7.93), 94.1% white, all men). Bivariate correlations and elastic net regressions were used in a discovery subsample to identify concurrent associations between PTSD symptom severity and the profiled proteins, and to create a multiprotein composite score. In hold-out subsamples, nine bivariate associations between PTSD symptoms and differentially expressed proteins were replicated: SKR3, NCAN, BCAN, MSR1, PVR, TNFRSF21, DRAXIN, CLM6, and SCARB2 (|r| = 0.08–0.17, p

Lactic acid bacteria effectively utilize the nutrients and active compounds in plant-based materials via their powerful metabolic pathways and enzyme systems, achieving a combination of nutrition, functionality, and deliciousness. Currently, the majority of review articles predominantly concentrate on summarizing the fermentation of fruits and vegetables by lactic acid bacteria, devoting comparatively less attention to researching other plant species varieties and plant-based by-products. Furthermore, the summary of the research on the active substances and functional properties lacks sufficient depth. This review provides a comprehensive overview of the status of and technological progress in lactic acid bacteria fermentation of various plant species and plant-based by-products, and the effects of lactic acid bacteria on the active substances and functional properties are emphasized. In addition, this review emphasizes that active substances give products more functionality. The aim of this review is to emphasize the significant contribution of lactic acid bacteria to the active substances and functional properties of plant-based products, which will assist researchers in better comprehending the application value of lactic acid bacteria in the plant-based domain and direct attention towards the interaction mechanisms between active substances and product functionality. Concurrently, this review provides a certain theoretical foundation and reference for the application of fermented functional products in promoting health and preventing diseases.

In order to study the long-term bearing capacity of concrete pile composite foundation in the Salt Lake area, based on the Tehran Isfahan high-speed railway project in Iran, the full (semi) immersion drying test and rapid freeze-thaw test was carried out, and the specimens were scanned by electron microscope. Numerical calculations were used to study the effects of different pile strengths and design parameters on the long-term bearing capacity of the composite foundation. The main conclusions were as follows: The concrete specimens in the adsorption zone deteriorated earlier and faster. In the rapid freeze-thaw tests, the strength attenuation of high-strength (C40, C50) specimens was smaller than that of low-strength specimens (C20). Within 20 years after construction, the additional settlement of low-strength (C20) piles was 12.21 mm, while high-strength concrete was less affected by deterioration. With pile spacing ranging from 1.8 m to 4.5 m, the maximum increase in additional settlement under the C20 condition was about 20 mm. The pile-soil stress ratio under the three conditions increased by 2.42, 6.59, and 8.63. As the pile length and diameter increased, the peak stress of the pile body moved towards the pile end, and the changes in the pile-soil stress ratio under the three conditions were similar.

Backgroundand objectives: Implementation of patient-specific quality assurance (PSQA) is a crucial aspect of precise radiotherapy. Various machine learning-based models have showed potential as virtual quality assurance tools, being capable of accurately predicting the dose verification results of fixed-beam intensity-modulated radiation therapy (IMRT) or volumetric modulated arc therapy (VMAT) plans, thereby ensuring safe and efficient treatment for patients. However, there has been no research yet that simultaneously integrates different IMRT techniques to predict the gamma pass rate (GPR) and explain the model.Methods: Retrospective analysis of the 3D dosimetric verification results based on measurements with gamma pass rate criteria of 3%/2 mm and 10% dose threshold of 409 pelvic IMRT and VMAT plans was carried out. Radiomics features were extracted from the dose files, from which the XGBoost algorithm based on SHapley Additive exPlanations (SHAP) values was used to select the optimal feature subset as the input for the prediction model. The study employed four different machine learning algorithms, namely, random forest (RF), adaptive boosting (AdaBoost), extreme gradient boosting (XGBoost), and light gradient boosting machine (LightGBM), to construct predictive models. Sensitivity, specificity, F1 score, and AUC value were calculated to evaluate the classification performance of these models. The SHAP values were utilized to perform a related interpretive analysis on the best performing model.Results: The sensitivities and specificities of the RF, AdaBoost, XGBoost, and LightGBM models were 0.96, 0.82, 0.93, and 0.89, and 0.38, 0.54, 0.62, and 0.62, respectively. The F1 scores and area under the curve (AUC) values were 0.86, 0.81, 0.88, and 0.86, and 0.81, 0.77, 0.85, and 0.83, respectively. The explanation of the model output based on SHAP values can provide a reference basis for medical physicists when adjusting the plan, thereby improving the efficiency and quality of treatment plans.Conclusion: It is feasible to use a machine learning method based on radiomics to establish a gamma pass rate classification prediction model for IMRT and VMAT plans in the pelvis. The XGBoost model performs better in classification than the other three tree-based ensemble models, and global explanations and single-sample explanations of the model output through SHAP values may offer reference for medical physicists to provide high-quality plans, promoting the clinical application and implementation of GPR prediction models, and providing safe and efficient personalized QA management for patients.

Abstract Greenland rainfall has come into focus as a climate change indicator and from a variety of emerging cryospheric impacts. This study first evaluates rainfall in five state‐of‐the‐art numerical prediction systems (NPSs) (CARRA, ERA5, NHM‐SMAP, RACMO, MAR) using in situ rainfall data from two regions spanning from land onto the ice sheet. The new EU Copernicus Climate Change Service (C3S) Arctic Regional ReAnalysis (CARRA), with a relatively fine (2.5 km) horizontal grid spacing and extensive within‐model‐domain observational initialization, has the lowest average bias and highest explained variance relative to the field data. ERA5 inland wet bias versus CARRA is consistent with the field data and other research and is presumably due to more ERA5 topographic smoothing. A CARRA climatology 1991–2021 has rainfall increasing by more than one‐third for the ice sheet and its peripheral ice masses. CARRA and in situ data illuminate extreme (above 300 mm per day) local rainfall episodes. A detailed examination CARRA data reveals the interplay of mass conservation that splits flow around southern Greenland and condensational buoyancy generation that maintains along‐flow updraft ‘rapids’ 2 km above sea level, which produce rain bands within an atmospheric river interacting with Greenland. CARRA resolves gravity wave oscillations that initiate as a result of buoyancy offshore, which then amplify from terrain‐forced uplift. In a detailed case study, CARRA resolves orographic intensification of rainfall by up to a factor of four, which is consistent with the field data.

Objective: Brown adipose tissue (BAT) plays a crucial role in regulating non-shivering thermogenesis under cold exposure. Proline hydroxylases (PHDs) were found to be involved in adipocyte differentiation and lipid deposition. However, the effects of PHDs on regulatory mechanisms of BAT thermogenesis are not fully understood. Methods: We detected the expression of PHDs in different adipose tissues by using immunoblotting and real-time PCR. Further, immunoblotting, real-time PCR, and immunostaining were performed to determine the correlation between proline hydroxylase 2 (PHD2) and UCP1 expression. Inhibitor of PHDs and PHD2-sgRNA viruses were used to construct the PHD2-deficiency model in vivo and in vitro to investigate the impacts of PHD2 on BAT thermogenesis. Afterward, the interaction between UCP1 and PHD2 and the hydroxylation modification level of UCP1 were verified by Co-IP assays and immunoblotting. Finally, the effect of specific proline hydroxylation on the expression/activity of UCP1 was further confirmed by site-directed mutation of UCP1 and mass spectrometry analysis. Results: PHD2, but not PHD1 and PHD3, was highly enriched in BAT, colocalized, and positively correlated with UCP1. Inhibition or knockdown of PHD2 significantly suppressed BAT thermogenesis under cold exposure and aggravated obesity of mice fed HFD. Mechanistically, mitochondrial PHD2 bound to UCP1 and regulated the hydroxylation level of UCP1, which was enhanced by thermogenic activation and attenuated by PHD2 knockdown. Furthermore, PHD2-dependent hydroxylation of UCP1 promoted the expression and stability of UCP1 protein. Mutation of the specific prolines (Pro-33, 133, and 232) in UCP1 significantly mitigated the PHD2-elevated UCP1 hydroxylation level and reversed the PHD2-increased UCP1 stability. Conclusions: This study suggested an important role for PHD2 in BAT thermogenesis regulation by enhancing the hydroxylation of UCP1.

Background: Chronically re-experiencing the memory of a traumatic event might cause a glial response. This study examined whether glial activation would be associated with PTSD in a study of responders present after the 9/11 World Trade Center attacks without comorbid cerebrovascular disease. Methods: Plasma was retrieved from 1,520 WTC responders and stored for a cross-sectional sample of responders of varying levels of exposure and PTSD. Plasma levels (pg/ml) of glial fibrillary acidic protein (GFAP) were assayed. Because stroke and other cerebrovascular diseases cause distributional shifts in GFAP levels, multivariable-adjusted finite mixture models analyzed GFAP distributions in responders with and without possible cerebrovascular disease. Results: Responders were aged 56.3 years and primarily male; 11.07% (n = 154) had chronic PTSD. Older age was associated with increased GFAP, whereas higher body mass was associated with decreased GFAP. Multivariable-adjusted finite mixture models revealed that severe re-experiencing trauma from 9/11 was associated with lower GFAP (B = −0.558, p = 0.003). Conclusion: This study presents evidence of reduced plasma GFAP levels among WTC responders with PTSD. Results suggest re-experiencing traumatic events might cause glial suppression.

Abstract Background The factors associated with estimated glomerular filtrate rate (eGFR) decline in low risk adults remain relatively unknown. We hypothesized that a polygenic risk score (PRS) will be associated with eGFR decline. Methods We analyzed genetic data from 1,601 adult participants with European ancestry in the World Trade Center Health Program (baseline age 49.68 ± 8.79 years, 93% male, 23% hypertensive, 7% diabetic and 1% with cardiovascular disease) with ≥ three serial measures of serum creatinine. PRSs were calculated from an aggregation of single nucleotide polymorphisms (SNPs) from a recent, large-scale genome-wide association study (GWAS) of rapid eGFR decline. Generalized linear models were used to evaluate the association of PRS with renal outcomes: baseline eGFR and CKD stage, rate of change in eGFR, stable versus declining eGFR over a 3–5-year observation period. eGFR decline was defined in separate analyses as “clinical” (> -1.0 ml/min/1.73 m2/year) or “empirical” (lower most quartile of eGFR slopes). Results The mean baseline eGFR was ~ 86 ml/min/1.73 m2. Subjects with decline in eGFR were more likely to be diabetic. PRS was significantly associated with lower baseline eGFR (B = -0.96, p = 0.002), higher CKD stage (OR = 1.17, p = 0.010), decline in eGFR (OR = 1.14, p = 0.036) relative to stable eGFR, and the lower quartile of eGFR slopes (OR = 1.21, p = 0.008), after adjusting for established risk factors for CKD. Conclusion Common genetic variants are associated with eGFR decline in middle-aged adults with relatively low comorbidity burdens.

Abstract An elevated risk of myeloma precursor disease, monoclonal gammopathy of undetermined significance (MGUS), was identified among Fire Department of the City of New York (FDNY) World Trade Center (WTC)-exposed firefighters. Further investigation was needed to determine if these findings were reproducible in a more heterogeneous WTC-exposed rescue/recovery workers cohort, the Stony Brook University-General Responder Cohort GRC (SBU-GRC). MGUS risk was compared between the cohorts and to published general population estimates from Olmsted County, MN, USA. In this observational seroprevalence study, odds ratios (OR) and age-standardized risk ratios (RR) of MGUS (M-spike and light-chain-MGUS combined), M-spike, and light-chain-MGUS were estimated using logistic regression. Age-standardized prevalences were calculated for white males aged 50–79; RRs were estimated by comparing risk in the WTC-exposed cohort with the Olmsted County screened cohort. SBU-GRC had elevated odds of MGUS compared with FDNY (OR = 1.38; 95%CI = 1.00–1.89). The age-standardized prevalence of MGUS was 9.0/100 persons (95%CI = 7.5–10.6), over two-fold higher than the general population (RR = 2.08; 95%CI = 1.72–2.51); the age-standardized prevalence of light-chain-MGUS was 3.5-fold higher (RR = 3.54; 95%CI = 2.52–4.97). This study adds to mounting evidence supporting an association between WTC/environmental exposures and MGUS among rescue/recovery workers. Access to MGUS screenings for the entire WTC-exposed cohort could allow for treatment interventions that improve survival.

As a Traditional Chinese Medicine prescription, Qingjin Yiqi Granules (QJYQ) provides an effective treatment for patients recovering from COVID-19. However, the pharmacokinetics characteristics of the main components of QJYQ in vivo are still unknown. An efficacious ultra-performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS) was developed and validated for the simultaneous determination of 33 components in rat plasma after oral administration of QJYQ. The plasma samples were precipitated with 400 µL methanol/acetonitrile (1/1, v/v) and analyzed in scheduled multiple reaction monitoring mode. The linear relationship of the 33 components was good (r > 0.9928). The lower limit of quantification for 33 components ranged from 0.4–60.5 ng/mL. The average recoveries and matrix effects of the analytes ranged from 72.9% to 115.0% with RSD of 1.4%–15.0%. All inter-day and intra-day RSDs were within 15.0%. After oral administration (3.15 g/kg), the validated approach was effectively applied to the pharmacokinetics of main components of QJYQ. Finally, fifteen main constituents of QJYQ with large plasma exposure were obtained, including baicalin, wogonoside, wogonin, apigenin-7-O-glucuronide, verbenalin, isoferulic acid, hesperidin, liquiritin, harpagide, protocatechuic acid, p-Coumaric acid, ferulic acid, sinapic acid, liquiritin apioside and glycyrrhizic acid. The present research lays a foundation for clarifying the therapeutic material basis of QJYQ and provides a reference for further scientific research and clinical application of QJYQ.

Type 2 diabetes mellitus (T2DM) has become a worldwide public health problem. Epimedin C is considered one of the most important flavonoids in Epimedium, a famous edible herb in China and Southeast Asia that is traditionally used in herbal medicine to treat diabetes. In the present study, the therapeutic potential of epimedin C against T2DM was ascertained using a mouse model, and the mechanism underlying the hypoglycemic activity of epimedin C was explored using a label-free proteomic technique for the first time. Levels of fasting blood glucose (FBG), homeostasis model assessment of insulin resistance (HOMA-IR), and oral glucose tolerance, as well as contents of malondialdehyde (MDA) and low-density lipoprotein cholesterol (LDL-C) in the 30 mg·kg−1 epimedin C group (EC30 group), were significantly lower than those in the model control group (MC group) (p < 0.05), while the contents of hepatic glycogen, insulin, and high-density lipoprotein cholesterol (HDL-C), as well as activities of superoxide dismutase (SOD) and glutathione peroxidase (GSH-Px) in the EC30 group were notably higher than those in the MC group (p < 0.05). The structures of liver cells and tissues were greatly destroyed in the MC group, whereas the structures of cells and tissues were basically complete in the EC30 group, which were similar to those in the normal control group (NC group). A total of 92 differentially expressed proteins (DEPs) were enriched in the gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. In the EC30 vs. MC groups, the expression level of cytosolic phosphoenolpyruvate carboxykinase (Pck1) was down-regulated, while the expression levels of group XIIB secretory phospholipase A2-like protein (Pla2g12b), apolipoprotein B-100 (Apob), and cytochrome P450 4A14 (Cyp4a14) were up-regulated. According to the KEGG pathway assay, Pck1 participated in the gluconeogenesis and insulin signaling pathways, and Pla2g12b, Apob, and Cyp4a14 were the key proteins in the fat digestion and fatty acid degradation pathways. Pck1, Pla2g12b, Apob, and Cyp4a14 seemed to play important roles in the prevention and treatment of T2DM. In summary, epimedin C inhibited Pck1 expression to maintain FBG at a relatively stable level, promoted Pla2g12b, Apob, and Cyp4a14 expressions to alleviate liver lipotoxicity, and protected liver tissues and cells from oxidant stress possibly by its phenolic hydroxyl groups.

Mammary fat plays a profound role in the postnatal development of mammary glands. However, the specific types (white, brown, or beige) of adipocytes in mammary fat and their potential regulatory effects on modulating mammary gland development remain poorly understood. This study aimed to investigate the role of the browning of mammary fat on pubertal mammary gland development and explore the underlying mechanisms. Thus, the mammary gland development and the serum lipid profile were evaluated in mice treated with CL316243, a β3-adrenoceptor agonist, to induce mammary fat browning. In addition, the proliferation of HC11 cells co-cultured with brown adipocytes or treated with the altered serum lipid metabolite was determined. Our results showed that the browning of mammary fat by injection of CL316243 suppressed the pubertal development of mice mammary glands, accompanied by the significant elevation of serum dioleoylphosphocholine (DOPC). In addition, the proliferation of HC11 was repressed when co-cultured with brown adipocytes or treated with DOPC. Furthermore, DOPC suppressed the activation of the PI3K/Akt pathway, while the DOPC-inhibited HC11 proliferation was reversed by SC79, an Akt activator, suggesting the involvement of the PI3K/Akt pathway in the DOPC-inhibited proliferation of HC11. Together, the browning of mammary fat suppressed the development of the pubertal mammary gland, which was associated with the elevated serum DOPC and the inhibition of the PI3K/Akt pathway.

Abstract Metabolomics has yielded promising insights into the pathophysiology of post-traumatic stress disorder (PTSD). The current study expands understanding of the systems-level effects of metabolites by using global metabolomics and complex lipid profiling in plasma samples from 124 World Trade Center responders (56 PTSD, 68 control) on 1628 metabolites. Differential metabolomics analysis identified hexosylceramide HCER(26:1) associated with PTSD at FDR

The rapid expansion of nuclear technology across various sectors due to global economic growth has led to a substantial rise in the transportation of radioactive materials. The International Atomic Energy Agency (IAEA) estimates that approximately 20 million shipments of radioactive materials occur annually. In this context, ensuring the safety and security of radioactive material transportation is of significant importance. IAEA’s “Security of Radioactive Materials in Transport” (Nuclear Security Series No. 9-G) mandates that an effective transport security system should provide immediate detection of any unauthorized removal of the packages. In the present study, an innovative Adam-optimized BP neural network model is developed for detecting unauthorized movements of radioactive material packages. To analyze the performance of the proposed algorithm, numerous experiments were conducted. The results demonstrate that the proposed method achieves a 99.17% accuracy rate in detecting unauthorized movements of radioactive materials, with a missed alarm rate of 0.72% and a false alarm rate of 0.1%. This method also enables real-time detection of unauthorized removal of radioactive materials and effectively enhances the security of radioactive materials during transport to reduce the risks of theft, loss, diversion, or sabotage.

Background Genetic factors contribute to individual differences in the severity of coronavirus disease 2019 (COVID-19). A portion of genetic predisposition can be captured using polygenic risk scores (PRS). Relatively little is known about the associations between PRS and COVID-19 severity or post-acute COVID-19 in community-dwelling individuals. Methods Participants in this study were 983 World Trade Center responders infected for the first time with SARS-CoV-2 (mean age at infection = 56.06; 93.4% male; 82.7% European ancestry). Seventy-five (7.6%) responders were in the severe COVID-19 category; 306 (31.1%) reported at least one post-acute COVID-19 symptom at 4-week follow-up. Analyses were adjusted for population stratification and demographic covariates. Findings The asthma PRS was associated with severe COVID-19 category (odds ratio [OR] = 1.61, 95% confidence interval: 1.17–2.21) and more severe COVID-19 symptomatology (β = .09, p = .01), independently of respiratory disease diagnosis. Severe COVID-19 category was also associated with the allergic disease PRS (OR = 1.97, [1.26–3.07]) and the PRS for COVID-19 hospitalization (OR = 1.35, [1.01–1.82]). PRS for coronary artery disease and type II diabetes were not associated with COVID-19 severity. Conclusion Recently developed polygenic biomarkers for asthma, allergic disease, and COVID-19 hospitalization capture some of the individual differences in severity and clinical course of COVID-19 illness in a community population.

Abstract Introduction World Trade Center (WTC) responders are experiencing a high risk of mild cognitive impairment (MCI) and dementia, though the etiology remains inadequately characterized. This study investigated whether WTC exposures and chronic post‐traumatic stress disorder (PTSD) were correlated with plasma biomarkers characteristic of Alzheimer's disease (AD) neuropathology. Methods Eligible participants included WTC‐exposed individuals with a baseline cognitive assessment and available plasma sample. We examined levels of the amyloid beta (Aβ)40/42 ratio, phosphorylated tau 181 (p‐tau181), and neurofilament light chain (NfL) and associations with a WTC exposures (duration on site ≥15 weeks, dust cloud), the PTSD Symptom Checklist for Diagnostic and Statistical Manual of Mental Disorders, 4th edition PTSD, and classification of amyloid/tau/neurodegeneration (AT[N]) profiles. Multinomial logistic regressions assessed whether biomarkers predicted increased risk of MCI or dementia. Results Of 1179 eligible responders, 93.0% were male, mean (standard deviation) age 56.6 years (7.8). Aβ40/42, p‐tau181, and NfL intercorrelated and increased with age. In subgroup analyses of responders with available neuroimaging data (n = 75), Aβ40/42 and p‐tau181 were further associated with decreased hippocampal volume (Spearman's ρ = −0.3). Overall, 58.08% of responders with dementia had ≥1 elevated biomarker, and 3.45% had elevations across all biomarkers. In total, 248 (21.05%) had MCI and 70 (5.94%) had dementia. Increased risk of dementia was associated with plasma AT(N) profile T+ or A+N+. Exposure on site ≥15 weeks was independently associated with T+ (adjusted risk ratio [aRR] = 1.03 [1.01−1.05], P = 0.009), and T+N+ profile (aRR = 2.34 [1.12−4.87]). The presence of PTSD was independently associated with risk of A+ (aRR = 1.77 [1.11−2.82]). Discussion WTC exposures and chronic PTSD are associated with plasma biomarkers consistent with neurodegenerative disease.

Accurate and complete diagnosis of nuclear accidents is the primary link to nuclear emergencies. The signed directed graph (SDG), as a common method of fault diagnosis, has good completeness. However, if there are feedforward and negative feedback control loops, compensation response and reverse response will be generated in the process of fault occurrence and propagation, which makes the state of the compensation variable and reverse variable uncertain, thus destroying the compatibility of the fault propagation path, leading to incomplete SDG reverse reasoning. In order to solve this problem, this paper proposes a SDG fault diagnosis method based on information flow. This method first finds out all the directed edges with the compensation variable or inverse variable node as the endpoint. By comparing the goodness of fit between the information flow on these directed edges and their total information flow curves, the path that contained the directed edge represented by sub-information flow with the highest R2 is obtained, and it is used as the fault propagation path with the maximum probability to determine the state of the compensation variable or inverse variable and fault location. At the same time, this paper extends the SDG model from the structure to build an FR-SDG model that can intuitively describe the node steady-state information under the final response and the fault propagation path with the maximum probability, which improves the diagnosis resolution. Finally, this paper carried out the relevant experiments in the subsystem of the nuclear reactor primary loop by using the simulation system PCTran AP1000, which verified the feasibility of this method.

Novel functional dynamic covalent-bonded polymer networks (DCPN) containing dynamic disulfide bonds were prepared from castor oil via a simple process. Firstly, UV-curable castor-oil-based polyurethane acrylate (COPUA) containing disulfide bonds and unsaturated double bonds was synthesized, then added with glycidyl methacrylate (GMA) to reduce viscosity (named COPUA-GMA) and mixed with different proportions of glycidyl esters containing unsaturated double bonds to form a series of UV-cured polymers named COPUA-GMA-EP. FTIR and NMR demonstrated the target pre-polymers and DCPNs were successfully synthesized. The DCPNs possessed controllable mechanical properties. Tensile tests showed the polymers had a range of tunable stiffness and flexibility. The COPUA-GMA-EP-2 copolymerized system containing 50 wt% COPUA-GMA had relatively excellent tensile strength of 11.8 MPa and elongation at break of 72.3%. Thermal analysis showed that DCPNs had excellent thermal stability, and COPUA-GMA-EP-2 had higher crosslinking density. Importantly, COPUA-GMA-EP-2 displayed excellent shape memory properties with Rf of 98.9% and Rr of 79.0%. Meanwhile, this DCPN exhibited certain self-healing properties. The DCPNs will be widely applied with good prospects owing to their excellent UV-curable, eco-friendly and shape memory properties.

The representation of 2-m air temperature and 10-m wind speed in the high-resolution (with a 2.5-km grid spacing) Copernicus Arctic Regional Reanalysis (CARRA) and the coarser resolution (ca. 31-km grid spacing) global European Center for Medium-range Weather Forecasts fifth-generation reanalysis (ERA5) for Svalbard, northern Norway, Sweden and Finland is evaluated against observations. The largest differences between the two reanalyses are found in regions with complex terrain and coastlines, and over the sea ice for temperature in winter. In most aspects, CARRA outperforms ERA5 in its agreement with the observations, but the value added by CARRA varies with region and season. Furthermore, the added value by CARRA is seen for both parameters but is more pronounced for temperature than wind speed. CARRA is in better agreement with observations in terms of general evaluation metrics like bias and standard deviation of the errors, is more similar to the observed spatial and temporal variability and better captures local extremes. A better representation of high-impact weather like polar lows, vessel icing and warm spells during winter is also demonstrated. Finally, it is shown that a substantial part of the difference between reanalyses and observations is due to representativeness issues, that is, sub-grid variability, which cannot be represented in gridded data. This representativeness error is larger in ERA5 than in CARRA, but the fraction of the total error is estimated to be similar in the two analyses for temperature but larger in ERA5 for wind speed.

Abstract Novel cost‐effective fuel cells have become more attractive due to the demands for rare and expensive platinum‐group metal (PGM) catalysts for mitigating the sluggish kinetics of the oxygen reduction reaction (ORR). The high‐cost PGM catalyst in fuel cells can be replaced by Earth‐abundant transition‐metal‐based catalysts, that is, an Fe–N–C catalyst, which is considered one of the most promising alternatives. However, the performance of the Fe–N–C catalyst is hindered by the low catalytic activity and poor stability, which is caused by insufficient active sites and the lack of optimization of the triple‐phase interface for mass transportation. Herein, a novel Fe–N–C catalyst consisting of mono‐dispersed hierarchically mesoporous carbon sphere cores and single Fe atom‐dispersed functional shells are presented. The synergistic effect between highly dispersed Fe‐active sites and well‐organized porous structures yields the combination of high ORR activity and high mass transfer performance. The half‐wave potential of the catalyst in 0.1 M H2SO4 is 0.82 V versus reversible hydrogen electrode, and the peak power density is 812 mW·cm−2 in H2–O2 fuel cells. Furthermore, it shows superior methanol tolerance, which is almost immune to methanol poisoning and generates up to 162 mW·cm−2 power density in direct methanol fuel cells.

Mg-based materials are one of the most promising hydrogen storage candidates due to their high hydrogen storage capacity, environmental benignity, and high Clarke number characteristics. However, the limited thermodynamics and kinetic properties pose major challenges for their engineering applications. Herein, we review the recent progress in improving their thermodynamics and kinetics, with an emphasis on the models and the influence of various parameters in the calculated models. Subsequently, the impact of alloying, composite, and nano-crystallization on both thermodynamics and dynamics are discussed in detail. In particular, the correlation between various modification strategies and the hydrogen capacity, dehydrogenation enthalpy and temperature, hydriding/dehydriding rates are summarized. In addition, the mechanism of hydrogen storage processes of Mg-based materials is discussed from the aspect of classical kinetic theories and microscope hydrogen transferring behavior. This review concludes with an outlook on the remaining challenge issues and prospects.

Study region: Guangdong Province in China. Study focus: Water shortages due to the spatially uneven distribution of water resources have become the main obstacle to the sustainable development of regional society and the economy. To alleviate this problem, this study developed a framework including prediction, optimization, and decision-making models to allocate available water resources among the different sectors of the cities in the region. The framework was advantageous in efficiently predicting future water demand and supply for multiple cities, quantitatively reflecting the level of the spatial equilibrium of water allocation (SEWA) through coupling coordination degree (CCD), and achieving a higher level of SEWA rather than just the equitable water distribution. New hydrological insights for the region: The results indicated that: (i) by 2030, the deficit of water supply and demand of Guangdong Province would be further aggravated, with a water shortage rate of 4.18%; (ii) by optimal water allocation, the water shortage rate of Guangdong Province decreased to 1.56% and the level of SEWA improved significantly from moderate equilibrium to good equilibrium; and (iii) from 2018 to 2030, key water-saving sectors in different cities were identified, while the industrial sector had a higher water-saving intensity than other water use sectors. This study could provide references for integrated water allocation strategies to realize the coordinated development of socioeconomic and environmental systems in other regions of the world.

Diabetes mellitus (DM) is a fast-growing chronic metabolic disorder that leads to significant health, social, and economic problems worldwide. Chronic hyperglycemia caused by DM leads to multiple devastating complications, including macrovascular complications and microvascular complications, such as diabetic cardiovascular disease, diabetic nephropathy, diabetic neuropathy, and diabetic retinopathy. Numerous studies provide growing evidence that aberrant expression of and mutations in RNA-binding proteins (RBPs) genes are linked to the pathogenesis of diabetes and associated complications. RBPs are involved in RNA processing and metabolism by directing a variety of post-transcriptional events, such as alternative splicing, stability, localization, and translation, all of which have a significant impact on RNA fate, altering their function. Here, we purposed to summarize the current progression and underlying regulatory mechanisms of RBPs in the progression of diabetes and its complications. We expected that this review will open the door for RBPs and their RNA networks as novel therapeutic targets for diabetes and its related complications.

Abstract The aim of this meta‐analysis was to review systematically and to identify the relationship between the severity and location of white matter hyperintensities (WMHs) and the degree of cognitive decline in patients with Parkinson’s disease (PD). We searched the PubMed, EMBASE, Web of Science, Ovid, and Cochrane Library databases for clinical trials of the severity and location of WMHs on the degree of cognitive impairment in PD through October 2020. We conducted the survey to compare the association of WMH burden in patients with PD with mild cognitive impairment (PD‐MCI) versus those with normal cognition (PD‐NC) and in patients with PD with dementia (PDD) versus those with PD without dementia (PD‐ND). Nine studies with PD‐MCI versus PD‐NC and 10 studies with PDD versus PD‐ND comparisons were included. The WMH burden in PD‐MCI patients was significantly different compared to that in PD‐NC patients (standard mean difference, SMD = 0.39, 95% CI: 0.12 to 0.66, p = 0.005), while there was no correlation shown in the age‐matched subgroup of the comparison. In addition, PDD patients had a significantly higher burden of WMHs (SMD = 0.8, 95% CI: 0.44 to 1.71, p

Abstract The relationship between circular RNA (circRNA) and cancer stem cells (CSCs) is uncertain. We have investigated the combined influence of CSCs, circRNA (hsa_circ_0003222), and immune checkpoint inhibitors in NSCLC progression and therapy resistance. We constructed lung CSCs (LCSCs; PC9 and A549). The effects of hsa_circ_0003222 in vitro were determined by cell counting, colony and sphere formation, and Transwell assays. A tumor xenograft model of metastasis and orthotopic model were built for in vivo analysis. We found that hsa_circ_0003222 was highly expressed in NSCLC tissues and LCSCs. Higher levels of hsa_circ_0003222 were associated with the stage, metastasis, and survival rate of patients with NSCLC. Reduced levels of hsa_circ_0003222 decreased tumor cell proliferation, migration, invasion, stemness-like properties, and chemoresistance. The silencing of hsa_circ_0003222 was found to downregulate PHF21B expression and its downstream, β-catenin by relieving the sponging effect of miR-527. Moreover, silencing hsa_circ_0003222 alleviated NSCLC resistance to anti-programmed cell death-ligand 1 (PD-L1)-based therapy in vivo. Our data demonstrate the significant role of hsa_circ_0003222 in NSCLC cell stemness-like properties. The manipulation of circRNAs in combination with anti-PD-L1 therapy may alleviate NSCLC stemness and progression.

Purpose: To investigate the impact of different baseline characteristics on the efficacy of immune checkpoint inhibitors (ICIs) for advanced lung cancer.Methods: In order to identify eligible randomized controlled trials (RCTs), a systematic search was conducted in PubMed, Embase, Cochrane Library, Web of Science, and Scopus databases. The primary outcomes were hazard ratios (HRs) and 95% confidence intervals (CIs) for overall survival (OS). To explore the potential interaction during the administration of ICI, patients were stratified by baseline characteristics.Results: The meta-analysis included 24 RCTs. ① Compared with non-ICI therapy, patients with lung cancer benefitted more from immunotherapy (HR, 0.78; p < 0.0001). ② Patients without liver metastases could get more survival benefits than those with liver metastases (HR, 1.20; p = 0.0139). Similar outcomes were also observed in the following subgroups: small-cell lung cancer (HR, 1.20; p = 0.0433), subsequent line (HR, 1.40; p = 0.0147), and ICI monotherapy (HR, 1.40; p = 0.0147). ③ Subgroup analysis showed that tumor type affected the efficacy of immunotherapy in patients with brain metastases (HR, 0.72 vs. 1.41; interaction, p < 0.01). Among patients with smoking history (HR, 0.87 vs. 1.23; interaction, p = 0.05) and brain metastases (HR, 0.69 vs. 1.21; interaction, p = 0.05), the type of therapy (i.e., monotherapy or combination therapy) had potential influences on the efficacy of immunotherapy.Conclusion: Some critical baseline characteristics could indicate the efficacy of ICI therapy. Liver metastasis status could predict the efficacy of ICI therapy for lung cancer. Compared with small-cell lung cancer, patients with brain metastases might have durable OS in non-small-cell lung cancer. The smoking history or brain metastasis status of patients could indicate the potential clinical benefits of monotherapy or combination therapy.

Biomass eugenol derived polyols with two or three functionalities were synthesized and used for the preparation of self-healing polyurethanes PU-2SH and PU-3SH, respectively. The structure of PU-2SH and PU-3SH were characterized by Fourier transition infrared spectroscopy (FTIR). Variable temperature FTIR and swelling test were carried out to analysis the self-healing behavior and determine the self-healing temperature of PU-2SH and PU-3SH. The thermal stability, dynamic mechanical properties, swelling performance and self-healing performance of the prepared PU-2SH and PU-3SH were studied in detail. Compared with PU-2SH, PU-3SH showed higher stability, Tg and storage modulus, and weaker self-healing abilities.

Biallelic variants in ABCA3, the gene encoding the lipid transporter ATP-binding cassette subfamily A member 3 (ABCA3) that is predominantly expressed in alveolar type II cells, may cause interstitial lung diseases in children (chILD) and adults. Currently, there is no proven therapy, but, frequently, hydroxychloroquine (HCQ) is used empirically. We hypothesized that the in vitro responsiveness to HCQ might correlate to patients’ clinical outcomes from receiving HCQ therapy. The clinical data of the subjects with chILD due to ABCA3 deficiency and treated with HCQ were retrieved from the literature and the Kids Lung Register data base. The in vitro experiments were conducted on wild type (WT) and 16 mutant ABCA3-HA-transfected A549 cells. The responses of the functional read out were assessed as the extent of deviation from the untreated WT. With HCQ treatment, 19 patients had improved or unchanged respiratory conditions, and 20 had respiratory deteriorations, 5 of whom transiently improved then deteriorated. The in vitro ABCA3 functional assays identified two variants with complete response, five with partial response, and nine with no response to HCQ. The variant-specific HCQ effects in vivo closely correlated to the in vitro data. An ABCA3+ vesicle volume above 60% of the WT volume was linked to responsiveness to HCQ; the HCQ treatment response was concentration dependent and differed for variants in vitro. We generated evidence for an ABCA3 variant-dependent impact of the HCQ in vitro. This may also apply for HCQ treatment in vivo, as supported by the retrospective and uncontrolled data from the treatment of chILD due to ABCA3 deficiency.

ATP-binding cassette subfamily A member 3 (ABCA3) is a lipid transporter within alveolar type II cells. Patients with bi-allelic variants in ABCA3 may suffer from a variable severity of interstitial lung disease. We characterized and quantified ABCA3 variants’ overall lipid transport function by assessing the in vitro impairment of its intracellular trafficking and pumping activity. We expressed the results relative to the wild type, integrated the quantitative readouts from eight different assays and used newly generated data combined with previous results to correlate the variants’ function and clinical phenotype. We differentiated normal (within 1 normalized standard deviation (nSD) of the wild-type mean), impaired (within 1 to 3 nSD) and defective (beyond 3 nSD) variants. The transport of phosphatidylcholine from the recycling pathway into ABCA3+ vesicles proved sensitive to the variants’ dysfunction. The sum of the quantitated trafficking and pumping predicted a clinical outcome. More than an approximately 50% loss of function was associated with considerable morbidity and mortality. The in vitro quantification of ABCA3 function enables detailed variant characterization, substantially improves the phenotype prediction of genetic variants and possibly supports future treatment decisions.

Nutritional diarrhea and subsequent performance degradation in weaned piglets are major challenges for the pig industry. Bile acids (BA) can be added to the diet as emulsifiers. This experiment was conducted to investigate the effects of chenodeoxycholic acid (CDCA), a major primary BA, on growth performance, serum metabolic profiles and gut health in weaned piglets. A total of 72 healthy weaned piglets were randomly assigned to the control (CON) and the CDCA groups, which were feed a basal diet and the basal diet supplemented with 200 mg/kg CDCA for 30 d, respectively. Our results demonstrated that CDCA significantly increased final BW and average daily gain (ADG), decreased feed-to-gain (F:G) ratio and tended to reduce diarrhea incidence. In addition, CDCA increased the villus height-to-crypt depth (V:C) ratio, elevated goblet cell numbers and the expression of tight junction proteins, suggesting the enhancement of intestinal barrier function. As an emulsifier, CDCA increased jejunal lipase activity and the mRNA expression of pancreatic lipases. CDCA supplementation also altered the serum metabolic profiles, including increasing the levels of indole 3-acetic acid, N′-formylkynurenine and theobromine that were beneficial for gut health. Moreover, the relative abundance of 2 beneficial gut bacteria, Prevotella 9 and Prevotellaceae TCG-001, were increased, whereas the relative abundance of a harmful bacteria, Dorea, was decreased in the gut of weaned piglets supplemented with CDCA. Importantly, the altered serum metabolic profiles showed a strong correlation with the changed gut bacteria. In conclusion, CDCA improved the growth performance of weaned piglets by improving intestinal morphology and barrier function, and enhancing lipid digestion, accompanied by alterations of serum metabolic profiles, and changes in relative abundance of certain gut bacteria.