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Abstract The ratio of non-high-density lipoprotein cholesterol (non-HDL-C) to HDL-C (NHHR) is a novel lipid parameter used to assess the risk of cardiovascular disease. Previous studies have demonstrated an association between the NHHR and risk of non-alcoholic fatty liver disease (NAFLD). Owing to the lack of research exploring this relationship in specific populations, this study aimed to determine the potential link between the NHHR and risk of NAFLD among American adults in the United States. Data were retrieved from the National Health and Nutrition Examination Survey (NHANES) spanning 2017–2020. After excluding individuals with other liver diseases, alcohol abuse, and missing lipid data, a total of 6809 eligible adults were included for analysis. The NHHR was calculated as the ratio of (non-HDL-C) to HDL-C, while NAFLD was identified by liver steatosis detected by transient elastography. Multivariable weighted logistic regression models and restricted cubic spline (RCS) models were employed to investigate the relationship between the NHHR and risk of NAFLD. Subgroup and sensitivity analyses were also conducted to test the robustness of the results. As the NHHR increased, the prevalence of NAFLD rose progressively (5.88% vs. 8.75% vs. 12.24% vs. 15.77%, p

Abstract Lung Cancer remains the leading cause of cancer deaths in the USA and worldwide. Non-small cell lung cancer (NSCLC) harbors high transcriptomic intratumor heterogeneity (RNA-ITH) that limits the reproducibility of expression-based prognostic models. In this study, we used multiregional RNA-seq data (880 tumor samples from 350 individuals) from both public (TRACERx) and internal (MDAMPLC) cohorts to investigate the effect of RNA-ITH on prognosis in localized NSCLC at the gene, signature, and tumor microenvironment levels. At the gene level, the maximal expression of hazardous genes (expression negatively associated with survival) but the minimal expression of protective genes (expression positively associated with survival) across different regions within a tumor were more prognostic than the average expression. Following that, we examined whether multiregional expression profiling can improve the performance of prognostic signatures. We investigated 11 gene signatures collected from previous publications and one signature developed in this study. For all of them, the prognostic prediction accuracy can be significantly improved by converting the regional expression of signature genes into sample-specific expression with a simple function—taking the maximal expression of hazardous genes and the minimal expression of protective genes. In the tumor microenvironment, we found a similar rule also seems applicable to immune ITH. We calculated the infiltration levels of major immune cell types in each region of a sample based on expression deconvolution. Prognostic analysis indicated that the region with the lowest infiltration level of protective or highest infiltration level of hazardous immune cells determined the prognosis of NSCLC patients. Our study highlighted the impact of RNA-ITH on the prognostication of NSCLC, which should be taken into consideration to optimize the design and application of expression-based prognostic biomarkers and models. Multiregional assays have the great potential to significantly improve their applications to prognostic stratification.

Abstract High stocking density and suboptimal conditions limit animal behaviors in modern livestock farming. This is particularly evident in captive animals, in which the motivation for foraging behavior is often thwarted. Oral stereotypic behaviors are common in farm animals. Ruminants (e.g., cattle and sheep) show oral stereotypic behaviors such as tongue‐rolling, self‐sucking, and inter‐sucking. Captive pigs exhibit oral stereotypic behaviors such as bar‐biting, sham‐chewing, and ear‐biting. Chickens peck at drinkers, feeders, and pens. Stereotypic behavior in livestock can be reduced by selecting a specific diet composition that prolongs their eating time and increases their satiety. Furthermore, reducing stocking density and enriching the farming environment encourage livestock to explore and reduce stereotypic behavior. It is important to note that stereotypic behavior is also influenced by organismal physiology. Stereotypic behavior was considered an indicator of poor animal welfare. However, recent research has revealed that animals engage in stereotypic behavior as a response to external stimuli, aiming to alleviate the negative impact of these stimuli on their well‐being. Animals that frequently show stereotypic behavior may have higher levels of stress. Certain stress indicators also affect the expression of stereotypic behavior, such as 5‐hydroxytryptamine and dopamine. Consequently, further investigation is necessary to understand how stereotypic behaviors affect the physiological state and metabolic processes of animals. This paper discusses the research progress on the oral stereotypic behaviors of farm animals. The objective is to establish a foundation for enhancing livestock feeding conditions and optimizing feeding practices, ultimately reducing stereotypic behaviors.

Abstract The development of intracerebral hemorrhage (ICH) is a dynamic process and intervention during the acute phase of ICH is critical for subsequent recovery. Therefore, it is crucial to screen potential signature genes and therapeutic target genes in the acute phase of ICH. In this study, based on the results of mRNA sequencing in mouse ICH and mRNA sequencing of human ICH from online databases, top five potential signature genes after ICH, Tyrobp, Itgb2, Tlr2, Ptprc and Itgam, were screened. Quantitative PCR results showed higher mRNA expression of Tyrobp, Itgb2, Tlr2, Ptprc, and Itgam in the 1-, 3- and 5-day mouse ICH groups compared to the sham-operated group. Immune infiltration correlation analysis shows that the top-ranked signature gene, Tyrobp, is negatively correlated with M2 macrophages and plasma cells, and Western blot analysis shows higher expression of the Tyrobp protein in the 1-, 3-, and 5-day mouse ICH groups compared to the sham-operated group. Furthermore, immunohistochemistry revealed that TYROBP protein expression was significantly higher in human ICH tissues than in normal brain tissues. Our results suggest that Tyrobp is a signature gene in the acute phase of ICH and may be a potential target for the treatment of the acute phase of ICH.

To explore the composite process of B–CuO and B–Bi2O3 two-component laminated sticks, obtain the corresponding sticks with good printing effect, and explore the energy release behavior. In this study, boron, copper oxide, and bismuth trioxide powders were dispersed in the dispersed phase (DMF) using F2602 as a binder, and the construction of two-component B–CuO, B–Bi2O3, three-component micro-composite, and three-component macro-composite sticks were realized with the help of double nozzle direct ink writing (DIW) technique respectively. The resulting sticks were ignited by a nichrome wire energized with a direct current, and a high-speed camera system was used to record the combustion behavior of the sticks, mark the flame position, and calculate the rate of ignition. The results showed that the B–CuO stick burning rate (42.11 mm·s−1) was much higher than that of B–Bi2O3 (17.84 mm·s−1). The formulation with the highest CuO content (ωCuO = 58.7%) in the microscale composite of the sticks also had the fastest burning rate of 60.59 mm·s−1, as the CuO content decreased (ωCuO = 43.5%, 29.3%), its burning rate decreased to 34.78 mm·s−1, 37.97 mm·s−1. The stick with the highest copper oxide content (ωCuO = 60%) also possessed the highest burning rate (48.84 mm·s−1) in the macro-composite sticks, and the burning rates of the macro-composite sticks with component spacing of 0.1 mm, 0.2 mm, and 0.5 mm were 43.34 mm·s−1, 48.84 mm·s−1, and 40.76 mm·s−1.

Sleep disordered breathing (SDB) is a common sleep disorder with an increasing prevalence. The current gold standard for diagnosing SDB is polysomnography (PSG), but existing PSG techniques have some limitations, such as long manual interpretation times, a lack of data quality control, and insufficient monitoring of gas metabolism and hemodynamics. Therefore, there is an urgent need in China’s sleep clinical applications to develop a new intelligent PSG system with data quality control, gas metabolism assessment, and hemodynamic monitoring capabilities. The new system, in terms of hardware, detects traditional parameters like nasal airflow, blood oxygen levels, electrocardiography (ECG), electroencephalography (EEG), electromyography (EMG), electrooculogram (EOG), and includes additional modules for gas metabolism assessment via end-tidal CO2 and O2 concentration, and hemodynamic function assessment through impedance cardiography. On the software side, deep learning methods are being employed to develop intelligent data quality control and diagnostic techniques. The goal is to provide detailed sleep quality assessments that effectively assist doctors in evaluating the sleep quality of SDB patients.

Abstract Background Obstructive sleep apnoea (OSA) is commonly associated with insulin resistance (IR) and dyslipidaemia. Apolipoprotein E (APOE) plays important roles in lipid metabolism. The study aimed to disentangle the multifactorial relationships between IR and APOE based on a large-scale population with OSA. Methods A total of 5,591 participants who underwent polysomnography for OSA diagnosis were finally enrolled. We collected anthropometric, fasting biochemical and polysomnographic data for each participant. Linear regression analysis was performed to evaluate the relationships between APOE, IR, and sleep breathing-related parameters. Logistic regression, restricted cubic spline (RCS) and mediation analyses were used to explore relationships between APOE and IR in patients with OSA. Results Increasing OSA severity was associated with greater obesity, more obvious dyslipidaemia, and higher levels of APOE and IR. APOE was positively correlated with the apnoea-hypopnoea index (AHI), oxygen desaturation index (ODI) and microarousal index (MAI) even after adjusting for age, sex, body mass index, and smoking and drinking levels (β = 0.107, β = 0.102, β = 0.075, respectively, all P

Abstract The Taihangshan-Yanshan region (TYR) is an important ecological barrier area for Beijing-Tianjin-Hebei, and the effectiveness of its ecological restoration and protection is of great significance to the ecological security pattern of North China. Based on the FVC data from 2000 to 2021, residual analysis, parametric optimal geodetector technique (OPGD) and multi-scale geographically weighted regression analysis (MGWR) were used to clarify the the multivariate driving mechanism of the evolution of FVC in the TYR. Results show that: (1) FVC changes in the TYR show a slowly fluctuating upward trend, with an average growth rate of 0.02/10a, and a spatial pattern of "high in the northwest and low in the southeast"; more than half of the FVC increased during the 22-year period. (2) The results of residual analysis showed that the effects of temperature and precipitation on FVC were very limited, and a considerable proportion (80.80% and 76.78%) of the improved and degraded areas were influenced by other factors. (3) The results of OPGD showed that the main influencing factors of the spatial differentiation of FVC included evapotranspiration, surface temperature, land use type, nighttime light intensity, soil type, and vegetation type (q > 0.2); The explanatory rates of the two-factor interactions were greater than those of the single factor, which showed either nonlinear enhancement or bifactorial enhancement, among which, the interaction of evapotranspiration with mean air and surface temperature has the strongest effect on the spatial and temporal evolution of FVC (q = 0.75). Surface temperature between 4.98 and 10.4 °C, evapotranspiration between 638 and 762 mm/a, and nighttime light between 1.96 and 7.78 lm/m2 favoured an increase in vegetation cover, and vegetation developed on lysimetric soils was more inclined to be of high cover. (4) The correlation between each variable and FVC showed different performance, GDP, elevation, slope and FVC showed significant positive correlation in most regions, while population size, urban population proportion, GDP proportion of primary and secondary industries, and nighttime light intensity all showed negative correlation with FVC to different degrees. The results can provide data for formulating regional environmental protection and restoration policies.

Abstract Lung oligometastases represent an intermediate state of cancer dissemination between localized and widespread metastases. Stereotactic body radiation therapy (SBRT) has emerged as an effective treatment option, with an efficacy comparable to that of surgical resection. This review aimed to provide a comprehensive summary of the latest advancements and controversial issues regarding SBRT for lung oligometastases. It focuses on four crucial perspectives: efficacy of SBRT, optimal patient selection criteria, technological innovations, and synergistic effects of SBRT combined with systemic therapy. Relevant clinical trials investigating SBRT for lung oligometastases have been conducted, with median 1‐ and 5‐year local control rates of 90% and 79%, respectively. The origin of the primary tumor, size and number of lesions, and biomarker profiles were highlighted as pivotal considerations in patient selection. The precise dose delivery was enhanced using robotic SBRT and optimized dose fractionation schemes. Evidence suggests that dose escalation above 100 Gy biologically effective dose may improve tumor control. Combined immunotherapy and SBRT have demonstrated synergistic effects in prolonging progression‐free survival and overall survival. This review provides valuable insights into the precise treatment of oligometastatic lung diseases using SBRT. Further multicenter randomized trials are warranted to develop definitive patient selection criteria and optimize the integration with systemic therapies.

Abstract The far-from-equilibrium solidification during additive manufacturing often creates large residual stresses that induce solid-state cracking. Here we present a strategy to suppress solid-state cracking in an additively manufactured AlCrFe2Ni2 high-entropy alloy via engineering phase transformation pathway. We investigate the solidification microstructures formed during laser powder-bed fusion and directed energy deposition, encompassing a broad range of cooling rates. At high cooling rates (104−106 K/s), we observe a single-phase BCC/B2 microstructure that is susceptible to solid-state cracking. At low cooling rates (102−104 K/s), FCC phase precipitates out from the BCC/B2 matrix, resulting in enhanced ductility (~10 %) and resistance to solid-state cracking. Site-specific residual stress/strain analysis reveals that the ductile FCC phase can largely accommodate residual stresses, a feature which helps relieve residual strains within the BCC/B2 phase to prevent cracking. Our work underscores the value of exploiting the toolbox of phase transformation pathway engineering for material design during additive manufacturing.

Abstract Background The study aimed to explore the relationship between low-density lipoprotein cholesterol (LDL-C) genetic variants and obstructive sleep apnea (OSA) and its complications, including cardiovascular diseases (CVD), insulin resistance (IR), and metabolic syndrome (MS). Method 4329 individuals with suspected OSA who underwent a comprehensive assessment of anthropometric, biochemical, and polysomnography (PSG) data, along with 30 LDL-C single nucleotide polymorphisms (SNPs) were enrolled. The 10-year Framingham CVD risk score (FRS), IR and MS were evaluated for each subject. Linear regression and logistic regression were utilized to examine the correlations among these variables. Results After the Benjamini-Hochberg correction, linear regression results indicated positive correlations between variants rs3741297 and rs629301 with FRS (β = 0.031, PBH=0.002; β = 0.026, PBH=0.015). Logistic regression revealed that rs3741297 increased MS risk among total subjects [OR = 1.67 (95% CI:1.369–2.038), PBH=1.32 × 10− 5] and increased IR risk in females [OR = 3.475 (95% CI:1.653–7.307), PBH=0.03]. In males, rs2642438 decreased MS risk [OR = 0.81 (95% CI:0.703–0.933), PBH=0.045]. Conclusions The rs3741297 variant correlated with susceptibility to CVD, IR, and MS in the OSA population. OSA, CVD, IR and MS share a potentially common genetic background, which may promote precision medicine. Cinical trial registration The study protocol was registered with the Chinese Clinical Trial Registry (ChiCTR1900025714).

Abstract Ulcerative colitis (UC) is characterized by an abnormal immune response, and the pathogenesis lacks clear understanding. The cGAS-STING pathway is an innate immune signaling pathway that plays a significant role in various pathophysiological processes. However, the role of the cGAS-STING pathway in UC remains largely unclear. In this study, we obtained transcriptome sequencing data from multiple publicly available databases. cGAS-STING related genes were obtained through literature search, and differentially expressed genes (DEGs) were analyzed using R package limma. Hub genes were identified through protein–protein interaction (PPI) network analysis and module construction. The ConsensuClusterPlus package was utilized to identify molecular subtypes based on hub genes. The therapeutic response, immune microenvironment, and biological pathways of subtypes were further investigated. A total of 18 DEGs were found in UC patients. We further identified IFI16, MB21D1 (CGAS), TMEM173 (STING) and TBK1 as the hub genes. These genes are highly expressed in UC. IFI16 exhibited the highest diagnostic value and predictive value for response to anti-TNF therapy. The expression level of IFI16 was higher in non-responders to anti-TNF therapy. Furthermore, a cluster analysis based on genes related to the cGAS-STING pathway revealed that patients with higher gene expression exhibited elevated immune burden and inflammation levels. This study is a pioneering analysis of cGAS-STING pathway-related genes in UC. These findings provide new insights for the diagnosis of UC and the prediction of therapeutic response.

Background: Disorders of glutamate metabolism and excessive release participat in multiple neuronal pathologies including ischemic stroke (IS), Alzheimer's disease (AD), or Parkinson's disease (PD). Recently, herbal medicines have been widely used and have shown satisfactory results in the treatment of neurological disorders. Gastrodin is a traditional Chinese medicine (TCM) used for the treatment of nerve injuries, spinal cord injuries, and some central nervous system diseases as well. This research examines the neuroprotective effects of Gastrodin against glutamate-induced neurotoxicity in neuronal cells. Methods: The HERB database was used to explore the active ingredients and target genes of Gastrodia Elata. The STRING database and Cytoscape software were used to screen and construct the Protein-Protein Interaction (PPI). Furthermore, we used molecular docking to predict the potential targets of Gastrodin. The effects of Gastrodin were revealed by western blot, calcium imaging, membrane clamp, CCK8 and flow cytometry. Neuronal oxidative stress and damage were assessed by measuring malondialdehyde (MDA) levels and superoxide dismutase (SOD) activity. Neuronal morphology was examined using Golgi-Cox staining. Finally, animal behavior was examined using novel object recognition and fear conditioning tests. Results: We have obtained 22 components such as TM10, TM17, TM25 (Gastrodin), and 281 targets such as AKT, EGFR, and CDK1 through network pharmacology. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses revealed these genes were significantly enriched in protein phosphorylation, protein serine/threonine/tyrosine kinase activity, apoptosis and HIF-1 signaling pathways, etc. A higher affinity between Gastrodin and AKT was revealed by PPI analysis and molecular docking. Further, Gastrodin significantly inhibited Ca2+ influxes and excitatory synaptic transmission in cortical neurons. In addition, Gastrodin effectively alleviated neuron apoptosis, oxidative stress and damage. Conclusion: Gastrodin has neuroprotective effects against glutamate-induced neurotoxicity.

Objective: Acute lower gastrointestinal bleeding is a common emergency in gastroenterology. Currently, there is insufficient information to predict adverse outcomes in patients with acute lower gastrointestinal bleeding. Our study aimed to compare the effectiveness of the clinical risk scores currently utilized and their ability to predict significant outcomes in lower gastrointestinal bleeding. Methods: We conducted a prognostic study of patients hospitalized for acute lower gastrointestinal bleeding who underwent colonoscopy or angiography at a single-center hospital between January 2015 and October 2023. Adverse outcomes associated with ALGIB included rebleeding, blood transfusion, hemostatic interventions, and in-hospital death. We calculated three risk scores at admission (Oakland, Birmingham, SALGIB). We measured the accuracy of these scores using the area under the receiver operating characteristic curve (AUC) and compared them with DeLong's test. Results: 222 patients with confirmed lower gastrointestinal bleeding (aged 64 years, 53–75) were finally included. The most common diagnoses were colorectal cancer (28 %) and hemorrhoids (14 %). The Oakland score, Birmingham score, and SALGIB score displayed comparable performance in predicting any adverse outcome (AUC = 0.54, 0.53, 0.55). However, none of the scores were able to sufficiently discriminate rebleeding, blood transfusion, or hemostatic intervention. Using the Youden index, cutoff points for predicting undesired results were identified for the Oakland score at 13, Birmingham score at 3, and SALGIB score at 2. Conclusions: None of the three scores demonstrated satisfactory discrimination for adverse outcomes. Therefore, it is necessary to develop novel risk stratification scores with higher performance to improve risk stratification in acute lower gastrointestinal bleeding.

The prediction of vegetation evolution and the understanding of its relationship with climate factors are essential for environmental protection, land use management, and policy planning. It is crucial to investigate accurate prediction methods for vegetation evolution and explore the impacts of climate factors. In this study, we developed machine learning (ML) based vegetation prediction methods by denoting vegetation status using normalized difference vegetation index (NDVI) and quantified the impacts of climate factors using interpretable methods. For the study region in this paper, i.e. the Anhui province in China, the proportions of areas with improved, stable and degraded vegetation status are 86.03 %, 8.13 % and 5.84 % respectively, and the NDVI evolution for the whole study region exhibits annual growth rate of 0.0031y-1. ML-based NDVI predictors exhibit R2 value exceeding 0.89 and MAE value below 0.1 for all lead times, which indicates the effectiveness of the ML-based prediction approaches. SHapley Additive exPlanation (SHAP) and Permutation Importance (PI) methods were utilized to provide insights into the black-box ML-based predictors. The results reveal that three temperature variables (minimum, maximum, and mean temperature) and precipitation are the key factors influencing vegetation growth. The increase of precipitation corresponds to an increase in vegetation, while higher minimum temperatures lead to a decrease in vegetation. When considering the combined contribution of minimum temperature and precipitation, it is shown that higher minimum temperature and larger amount of precipitation result in vegetation growth. On the contrary, lower minimum temperature and insufficient precipitation have negative impacts on vegetation. This work promotes the development of ML-based NDVI prediction approaches with transparency by taking advantages of interpretable methods. It provides understandings on how climate change influences vegetation growth in the Anhui Province.

Abstract Engineered bacteria‐mediated antitumor approaches have been proposed as promising immunotherapies for cancer. However, the off‐target bacterial toxicity narrows the therapeutic window. Living microbes will benefit from their controllable immunogenicity within tumors for safer antitumor applications. In this study, a genetically encoded microbial activation strategy is reported that uses tunable and dynamic expression of surface extracellular polysaccharides to improve bacterial biocompatibility while retaining therapeutic efficacy. Based on screening of genes associated with Salmonella survival in macrophages, a novel attenuated Salmonella chassis strain AIS (htrA gene‐deficient) highly enriched in tumors after administration and rapidly cleared from normal organs are reported. Subsequently, an engineered bacterial strain, AISI‐H, is constructed based on the AIS strain and an optimized quorum‐sensing regulatory system. The AISI‐H strain can achieve recovery of dynamic tumor‐specific bacterial virulence through a novel HTRA‐RCSA axis‐based and quorum‐sensing synthetic gene circuit‐mediated increase in extracellular polysaccharide content. These strains act “off” in normal organs to avoid unwanted immune activation and “on” in tumors for precise tumor suppression in mice. The AISI‐H strain shows significant tumor inhibition and potent activation of anticancer immunity in a melanoma mouse model. The AISI‐H strain exhibits excellent biocompatibility. This bacterial regulation strategy expands the applications of microbe‐based antitumor therapeutics.

Abstract Backgroud Supernatants from various cytological samples, including body cavity effusion, sputum, bronchoalveolar lavage fluid (BALF), and needle aspiration, have been validated for detecting genetic alterations using cell‐free DNA (cfDNA) in patients with non‐small cell lung cancer (NSCLC). However, the sensitivity of fusion variations detection remains challenging. The protection of cell‐free RNA (cfRNA) is critical for resolving the issue. Methods A protective solution (PS) was applied for preserving cfRNA in cytological supernatant (CS), and the quality of protected cfRNA was assessed by cycle threshold (CT) values from reverse transcription quantitative polymerase chain reaction (RT‐qPCR). Furthermore, we collected an additional set of malignant cytological and matched tumor samples from 84 NSCLC patients, cfDNA & cfRNA extraction and double detection for driver gene mutations was validated using the multi‐gene mutations detection by RT‐qPCR. Results Under the optimal protection system, 91.0% (101/111) of cfRNA were protected effectively. Among the 84 NSCLC patient samples, seven cytological samples failed the tests. In comparison with tumor samples, the overall sensitivity and specificity of detecting driver genes of supernatant cfDNA and cfRNA were 93.8% (74/77) and 100% (77/77), respectively. Notably, when focusing exclusively on patients with fusion gene changes, both sensitivity and specificity reached 100% (11/11) for EML4‐ALK, ROS1, RET fusions, and MET ex14 skipping. Conclusion These findings suggest that cfDNA & cfRNA extraction and double detection strategy recommended in this study improve the accuracy of driver genes mutations test, especially for RNA‐based assay.

ObjectiveExplore the plasticity of the frontal associative areas in children and adolescents induced by exercise and potential moderating variables.MethodsComputer searches of CNKI, WOS, PubMed and EBSCO databases were conducted, and statistical analyses were performed based on SPSS 25.0, Stata 12.0 and Ginger ALE 2.3 software after literature screening, data extraction and quality assessment were performed independently by two researchers.ResultsA total of 13 articles, including 425 participants aged 8.9∼16.8 years, were included. Frequency analysis revealed that exercise induced enhanced activation in frontal, parietal, occipital, limbic system and cerebellum (P < 0.01). Activation Likelihood Estimation (ALE) meta-analysis revealed that exercise altered the activation status of the frontal association (medial frontal gyrus, middle frontal gyrus, inferior frontal gyrus and precentral gyrus), cuneus, lingual gyrus, cingulate gyrus, parahippocampal gyrus, caudate nucleus and cerebellar apex, with the volume of activation in the frontal association accounting for 61.81% of the total activation cluster volume and an enhanced activation effect. Additionally, the study design, age, gender, nationality, cognitive tasks, as well as exercise intensity, intervention time, and type of exercise may be potential moderating variables. Particularly, sustained exercise induced a decrease in activation in the left parahippocampal gyrus, culmen, and lingual gyrus, while variable exercise induced an increase in activation in the left middle frontal gyrus.ConclusionExercise-induced activation increase in the frontal associative areas of children and adolescents is dominant, especially longer periods of moderate-intensity variable exercise can induce more brain region activation. However, some of the included studies are cross-sectional, and the accuracy of the results still requires further verification.Systematic review registrationhttps://www.crd.york.ac.uk/prospero/, identifier PROSPERO, CRD42022348781.

Abstract Objectives Obstructive sleep apnea (OSA) is associated with abnormal glucose and lipid metabolism. However, whether there is an independent association between Sleep Apnea-Specific Hypoxic Burden (SASHB) and glycolipid metabolism disorders in patients with OSA is unknown. Methods We enrolled 2,173 participants with suspected OSA from January 2019 to July 2023 in this study. Polysomnographic variables, biochemical indicators, and physical measurements were collected from each participant. Multiple linear regression analyses were used to evaluate independent associations between SASHB, AHI, CT90 and glucose as well as lipid profile. Furthermore, logistic regressions were used to determine the odds ratios (ORs) for abnormal glucose and lipid metabolism across various SASHB, AHI, CT90 quartiles. Results The SASHB was independently associated with fasting blood glucose (FBG) (β = 0.058, P = 0.016), fasting insulin (FIN) (β = 0.073, P

Stable and low-particle size nanoemulsions were prepared using ultrasound homogenization. The conditions for preparing low-viscosity nanoemulsions were optimized using Response Surface Methodology (RSM) experimental design. The results showed that the addition of composite surfactants at 1%, an ultrasound amplitude of 35%, an ultrasound time of 4 min, and an ultrasound temperature of 20 °C yielded nanoemulsions with the best particle size and stability. The particle distribution was uniform, and the cold and heat stability were good. Compared with traditional emulsions, the low-viscosity nanoemulsion had better environmental stability, storage stability, and exhibited a phenomenon of self-reducing particle size at 40–55 °C, indicating that the emulsion had good performance under complex environmental conditions. The performance test of composite energetic materials using two types of emulsions as bonding systems showed that the low-viscosity nanoemulsion composite energetic material effectively reduced friction sensitivity, increased detonation velocity, and had better thermal stability and smaller propagation size. The results confirmed that the low-viscosity nanoemulsion perfectly met the requirements of bonding agents for composite energetic materials. This study provides a new approach for bonding agent systems of composite energetic materials and can serve as a new method to meet the special requirements of composite energetic materials.

Abstract Planar-chiral cyclophanes have gained considerable concerns for drug discovery due to their unique conformational strain and 3D structure. However, the enantioselective synthesis of planar-chiral cyclophanes is a long-standing challenge for the synthetic community. We herein describe an N-heterocyclic carbene (NHC)-catalyzed asymmetric construction of planar-chiral cyclophanes. This transformation occurs through a dynamic kinetic resolution (DKR) process to convert racemic substrates into planar-chiral macrocycle scaffolds in good to high yields with high to excellent enantioselectivities. The ansa chain length and aromatic ring substituent size is crucial to achieve the DKR approach. Controlled experiments and DFT calculations were performed to clarify the DKR process.

AbstractBackground Angiopoietin-like protein 4 (ANGPTL4) is recognized as a crucial regulator in lipid metabolism. Acetyl-CoA carboxylases (ACACAs) play a role in the β-oxidation of fatty acids. Yet, the functions of ANGPTL4 and ACACA in dyslipidemia of obstructive sleep apnea (OSA) remain unclear.Methods This study included 125 male OSA subjects from the Shanghai Sleep Health Study (SSHS) who were matched for age, body mass index (BMI), and lipid profile. Serum ANGPTL4 levels were measured via ELISA. The ANGPTL4 T266M variants of 4455 subjects along with their anthropometric, fasting biochemical, and standard polysomnographic parameters were collected. Linear regression was used to analyze the associations between quantitative traits and ANGPTL4 T266M. Molecular docking and molecular dynamic simulation were employed to compare the effects of the wild-type ANGPTL4 and its T266M mutation on ACACA.Results Serum ANGPTL4 levels significantly decreased with increasing OSA severity (non-OSA: 59.6 ± 17.4 ng/mL, mild OSA: 50.0 ± 17.5 ng/mL, moderate OSA: 46.3 ± 15.5 ng/mL, severe OSA: 19.9 ± 14.3 ng/mL, respectively, p = 6.02 × 10−16). No associations were found between T266M and clinical characteristics. Molecular docking indicated that mutant ANGTPL4 T266M had stronger binding affinity for the ACACA protein, compared with wild-type ANGPTL4. In terms of protein secondary structure, mutant ANGTPL4 T266M demonstrated greater stability than wild-type ANGPTL4.Conclusions Serum ANGTPL4 levels were significantly decreased in OSA patients, particularly among individuals with severe OSA. Although functional ANGTPL4 T266M variants were not associated with lipid levels in OSA, ANGTPL4 T266M could enhance binding affinity for the ACACA protein, potentially regulating lipid metabolism.

Cordycepin, an adenosine analog, exhibits diverse bioactivities and holds significant potential for applications in healthcare and agriculture. Fungi of the genus Cordyceps, such as Cordyceps militaris, can naturally produce cordycepin. Current sources of cordycepin primarily involve extraction from fruiting bodies or isolation from liquid fermentation using C. militaris, presenting challenges such as low production intensity, complex separation and purification systems, and high production costs, limiting industrial feasibility. Recent advancements have witnessed the utilization of various fungal chassis cells to successfully engineer heterologous biosynthetic platforms for cordycepin, such as Saccharomyces cerevisiae and unconventional yeasts, offering advantages of high yield, short fermentation cycles, and a broad substrate spectrum. This mini review summarizes the biosynthetic pathways of cordycepin and focused on the comparison of the characteristics, advantages, current performance and prospects for the microbial cell factories, analyzing potential targets for metabolic pathway modification and giving strategies in both genetic engineering and process engineering to enhance production intensity. The mini review particularly emphasizes the crucial role of chassis cell stress tolerance to the toxic product in determining cordycepin yield and highlights the urgent need for high-throughput screening methods for high-yield strains.

IntroductionIncreasing global temperatures present a significant challenge to livestock production. The dry period is an important stage in the production cycle of cow, and environmental heat stress (HS) during this period can have adverse effects on the subsequent lactation performance. In this study, we aimed to investigate the effects of HS on endocrine, thermoregulatory, and lactation parameters in heat-tolerant dry cows (HTDC) and heat-sensitive dry cows (HSDC).MethodsWe measured the respiratory rate (RR), body temperature (BT), and temperature-humidity index (THI) in 66 dry cows during HS. The slopes of RR and BT to THI were determined through analysis of measurements and dry cows background information using a mixed-effects model. Subsequently, the heat tolerance or sensitivity of dry cows was assessed using clustering method (HTDC = 19 and HSDC = 47).ResultsCompared with that of HSDC, the RR of HTDC significantly increased after exposure to HS (p < 0.05). The average reduction in milk yield from new lactation to the previous lactation was significantly lower in HTDC compared to HSDC (p < 0.05). Plasma cortisol and non-esterified fatty acid levels were significantly lower in HTDC compared to HSDC (p < 0.05), while plasma triiodothyronine (p = 0.07) and growth hormone (p = 0.08) levels tended to be higher in HTDC relative to HSDC.DiscussionHTDC can more effectively alleviate the impacts of HS through their superior thermoregulation and metabolism, thereby ensuring optimal postpartum lactation performance.

Sleep disorders often accompany neurological injuries, significantly impacting patient recovery and quality of life.The efficacy and adherence of traditional treatment methods have certain limitations. Exercise has been found to be a highly beneficial treatment method, capable of preventing and alleviating neurological injuries and sleep disorders. This article reviews relevant research findings from both domestic and international sources over the past few decades, systematically summarizing and analyzing the application of exercise therapy in sleep disorders,strategy of exercise intervention program and the potential molecular mechanisms by which exercise therapy improves sleep disorders. Shortcomings in current research and suggestions are presented, providing a reference for future in-depth studies on exercise interventions for sleep disorders.

Triggering receptor expressed on myeloid cells 1 (TREM1) is a cell surface receptor expressed on neutrophils, monocytes and some tissue macrophages, where it functions as an immunoregulator that controls myeloid cell responses. The activation of TREM1 is suggested to be an upregulation-based, ligands-induced and structural multimerization-mediated process, in which damage- and pathogen-associated molecular patterns play important roles. Activated TREM1 initiates an array of downstream signaling pathways that ultimately result in the production of pro-inflammatory cytokines and chemokines, whereby it functions as an amplifier of inflammation and is implicated in the pathogenesis of many inflammation-associated diseases. Over the past decade, there has been growing evidence for the involvement of TREM1 overactivation in tumor stroma inflammation and cancer progression. Indeed, it was shown that TREM1 promotes tumor progression, immunosuppression, and resistance to therapy by activating tumor-infiltrating myeloid cells. TREM1-deficiency or blockade provide protection against tumors and reverse the resistance to anti-PD-1/PD-L1 therapy and arginine-deprivation therapy in preclinical models. Here, we first review the structure, activation modes and signaling pathways of TREM1 and emphasize the role of soluble TREM1 as a biomarker of infection and cancer. We then focus on the role of TREM1 in cancer and systematically summarize its expression patterns, upregulation mechanisms and functions in tumor development and progression. Lastly, we discuss the therapeutic prospects of TREM1 inhibition, via effective pharmacological inhibitors, in treating cancer and other diseases.

Abstract Ulcerative colitis (UC) is a chronic inflammatory disease that targets the colon and has seen an increasing prevalence worldwide. In our pursuit of new diagnostic and therapeutic approaches for UC, we undertook a sequencing of colons from UC mouse models. We focused on analyzing their differentially expressed genes (DEGs), enriching pathways, and constructing protein-protein interaction (PPI) and Competing Endogenous RNA (ceRNA) networks. Our analysis highlighted novel DEGs such as Tppp3, Saa3, Cemip, Pappa, and Nr1d1. These DEGs predominantly play roles in pathways like cytokine-mediated signaling, extracellular matrix organization, extracellular structure organization, and external encapsulating structure organization. This suggests that the UC pathogenesis is intricately linked to the interactions between immune and non-immune cells with the extracellular matrix (ECM). To corroborate our findings, we also verified certain DEGs through quantitative real-time PCR. Within the PPI network, nodes like Stat3, Il1b, Mmp3, and Lgals3 emerged as significant and were identified to be involved in the crucial cytokine-mediated signaling pathway, which is central to inflammation. Our ceRNA network analysis further brought to light the role of the Smad7 Long non-coding RNA (lncRNA). Key MicroRNA (miRNAs) in the ceRNA network were pinpointed as mmu-miR-17-5p, mmu-miR-93-5p, mmu-miR-20b-5p, mmu-miR-16-5p, and mmu-miR-106a-5p, while central mRNAs included Egln3, Plagl2, Sema7a, Arrdc3, and Stat3. These insights imply that ceRNA networks are influential in UC progression and could provide further clarity on its pathogenesis. In conclusion, this research deepens our understanding of UC pathogenesis and paves the way for potential new diagnostic and therapeutic methods. Nevertheless, to solidify our findings, additional experiments are essential to confirm the roles and molecular interplay of the identified DEGs in UC.

Abstract Breast carcinoma (BC) ranks as a predominant malignancy and constitutes the second principal cause of mortality among women globally. Epirubicin stands as the drug of choice for BC therapeutics. Nevertheless, the emergence of chemoresistance has significantly curtailed its therapeutic efficacy. The resistance mechanisms to Epirubicin remain not entirely elucidated, yet they are conjectured to stem from diminished tumor vascular perfusion and resultant hypoxia consequent to Epirubicin administration. In our investigation, we meticulously scrutinized the Gene Expression Omnibus database for EPDR1, a gene implicated in hypoxia and Epirubicin resistance in BC. Subsequently, we delineated the impact of EPDR1 on cellular proliferation, motility, invasive capabilities, and interstitial-related proteins in BC cells, employing methodologies such as the CCK-8 assay, Transwell assay, and western blot analysis. Our research further unveiled that hypoxia-induced miR-181a-5p orchestrates the regulation of BC cell duplication, migration, invasion, and interstitial-related protein expression via modulation of EPDR1. In addition, we identified TRPC1, a gene associated with EPDR1 expression in BC, and substantiated that EPDR1 influences BC cellular dynamics through TRPC1-mediated modulation of the PI3K/AKT signaling cascade. Our findings underscore the pivotal role of EPDR1 in the development of BC. EPDR1 was found to be expressed at subdued levels in BC tissues, Epirubicin-resistant BC cells, and hypoxic BC cells. The overexpression of EPDR1 curtailed BC cell proliferation, motility, invasiveness, and the expression of interstitial-related proteins. At a mechanistic level, the overexpression of hypoxia-induced miR-181a-5p was observed to inhibit the EPDR1/TRPC1 axis, thereby activating the PI3K/AKT signaling pathway and diminishing the sensitivity to Epirubicin in BC cells. In summation, our study demonstrates that the augmentation of hypoxia-induced miR-181a-5p diminishes Epirubicin sensitivity in BC cells by attenuating EPDR1/TRPC1 expression, thereby invigorating the PI3K/AKT signaling pathway. This exposition offers a theoretical foundation for the application of Epirubicin in BC therapy, marking a significant contribution to the existing body of oncological literature.

Road extraction from images captured via remote sensing is a pivotal task across multiple domains, encompassing urban planning and intelligent transportation systems. In the realm of high-resolution remote sensing, traditional approaches to road extraction confront obstacles pertaining to reduced accuracy and resilience. This study introduces an innovative methodology for road extraction tailored to high-resolution remote sensing data. The devised algorithm integrates a feature enhancement attention module alongside parallel feature fusion. Specifically, the feature enhancement attention module is introduced to augment the network's capacity in discerning road-related information by analyzing feature maps produced at varying resolutions. Subsequently, during feature map extraction, the parallel feature fusion technique is employed to merge shallow and deep features sharing the same resolution, thus effectively leveraging the strengths of both to enhance the model's precision. Moreover, the network undertakes the computation of correlations among feature maps of differing resolutions as well as the entire feature map, thereby facilitating a holistic grasp of the global structure and semantic information embedded within the image. Experimental evaluations conducted on the CHN6-CUG and Massachusetts datasets substantiate that the proposed approach outperforms prevailing mainstream methods for road extraction in terms of both accuracy and processing speed.

Object detection in unmanned aerial vehicle (UAV) images is an important and challenging task for many applications, which often needs highly efficient detection algorithms to meet the accuracy and real-time requirements of the applications. In this article, we investigate efficient mechanisms for detecting dense and small objects in UAV images. Specifically, 1) kernel K-means is used to obtain optimal anchors for dense and small object detection; 2) a spatial information enhancement module is proposed to improve the detection accuracy of dense objects by extracting object spatial location information; 3) a Coord_C3 module is proposed to improve the receptive field of the network and to reduce the number of network parameters; and 4) a small detection head is added in the Head of the network and skip connections are employed in the Neck of the network to improve the detection accuracy of small objects. Experimental results on the VisDrone-2019, LEVIR-ship, and Stanford Drone datasets show that our method not only has higher detection accuracy but also runs faster compared to state-of-the-art detection methods.

Abstract Live bacteria-mediated antitumor therapies mark a pivotal point in cancer immunotherapy. However, the difficulty in reconciling the safety and efficacy of bacterial therapies has limited their application. Improving bacterial tumor-targeted delivery while maintaining biosafety is a critical hurdle for the clinical translation of live microbial therapy for cancer. Here, we developed “dead” yet “functional” Salmonella-loaded macrophages using liquid nitrogen cold shock of an attenuated Salmonella typhimurium VNP20009-contained macrophage cell line. The obtained “dead” macrophages achieve an average loading of approximately 257 live bacteria per 100 cells. The engineered cells maintain an intact cellular structure but lose their original pathogenicity, while intracellular bacteria retain their original biological activity and are delay freed, followed by proliferation. This “Trojan horse”-like bacterial camouflage strategy avoids bacterial immunogenicity-induced neutrophil recruitment and activation in peripheral blood, reduces the clearance of bacteria by neutrophils and enhances bacterial tumor enrichment efficiently after systemic administration. Furthermore, this strategy also strongly activated the tumor microenvironment, including increasing antitumor effector cells (including M1-like macrophages and CD8+ Teffs) and decreasing protumor effector cells (including M2-like macrophages and CD4+ Tregs), and ultimately improved antitumor efficacy in a subcutaneous H22 tumor-bearing mouse model. The cryo-shocked macrophage-mediated bacterial delivery strategy holds promise for expanding the therapeutic applications of living bacteria for cancer.

Abstract Flocking cohesion is critical for maintaining a group’s aggregation and integrity. Designing a potential function to maintain flocking cohesion unaffected by social distance is challenging due to the uncertainty of real-world conditions and environments that cause changes in agents’ social distance. Previous flocking research based on potential functions has primarily focused on agents’ same social distance and the attraction–repulsion of the potential function, ignoring another property affecting flocking cohesion: well depth, as well as the effect of changes in agents’ social distance on well depth. This paper investigates the effect of potential function well depths and agent’s social distances on the multi-agent flocking cohesion. Through the analysis, proofs, and classification of these potential functions, we have found that the potential function well depth is proportional to the flocking cohesion. Moreover, we observe that the potential function well depth varies with the agents’ social distance changes. Therefore, we design a segmentation potential function and combine it with the flocking control algorithm in this paper. It enhances flocking cohesion significantly and has good robustness to ensure the flocking cohesion is unaffected by variations in the agents’ social distance. Meanwhile, it reduces the time required for flocking formation. Subsequently, the Lyapunov theorem and the LaSalle invariance principle prove the stability and convergence of the proposed control algorithm. Finally, this paper adopts two subgroups with different potential function well depths and social distances to encounter for simulation verification. The corresponding simulation results demonstrate and verify the effectiveness of the flocking control algorithm.

(1) Background: With the increasing aesthetic pursuit of facial features, the clinical use of Botulinum Toxin Type A (BoNT-A) injections for masseter hypertrophy has been on the rise. However, due to variations in masseter muscle structure and differences in clinicians’ injection techniques, blind injections may lack precision, potentially compromising treatment accuracy and increasing the risk of complications. (2) Objectives: The study aims to use ultrasonography to detail the deep inferior tendon (DIT) within the masseter muscle in a young Chinese cohort, refine its classification, analyze muscle belly thickness and variations across groups, and propose a customized ultrasound-guided BoNT-A injection protocol. (3) Methods: Ultrasound imaging was used to observe the bilateral masseter muscles at rest and during clenching. The features of the DIT were classified from these images, and the thickness of the masseter’s distinct bellies associated with the DIT types was measured in both states. (4) Results: The study cohort included 103 participants (27 male, 76 female), with 30 muscles in the normal masseter group and 176 muscles in the hypertrophy group. The DIT was categorized as Type A, B (subtypes B1, B2), and C. The distribution of these types was consistent across normal, hypertrophic, and gender groups, all following the same trend (B > A > C). In hypertrophy, Type B1 showed uniform thickness across masseter bellies, B2 presented with a thinner intermediate belly, and Type C had mainly superficial muscle enlargement. Changes in muscle thickness during clenching were noted but not statistically significant among different bellies. (5) Conclusions: The study evidences individual variation in the DIT, highlighting the importance of precise DIT classification for effective BoNT-A injections. A tailored ultrasound-guided BoNT-A injection strategy based on this classification may enhance safety and efficacy of the therapy.

BackgroundThe population is constantly aging, and most older adults will experience many potential physiological changes as they age, leading to functional decline. Urinary and bowel dysfunction is the most common obstacle in older people. At present, the analysis of pelvic floor histological changes related to aging has not been fully elucidated, and the mechanism of improving intestinal control ability in older people is still unclear. ObjectiveThe purpose of this study is to describe how the finite element method will be used to understand the mechanical characteristics of and physiological changes in the pelvic cavity during the rehabilitation process, providing theoretical support for the mechanism for improving urination and defecation dysfunction in older individuals. MethodsWe will collect magnetic resonance imaging (MRI) and computed tomography (CT) data of the pelvic cavity of one male and one female volunteer older than 60 years and use the finite element method to construct a 3D computer simulation model of the pelvic cavity. By simulating different physiological states, such as the Valsalva maneuver and bowel movement, we will verify the accuracy of the constructed model, investigate the effects of different neuromuscular functional changes, and quantify the impact proportions of the pelvic floor muscle group, core muscle group, and sacral nerve. ResultsAt present, we have registered the study in the Chinese Clinical Trial Registry and collected MRI and CT data for an older male and an older female patient. Next, the construction and analysis of the finite element model will be accomplished according to the study plan. We expect to complete the construction and analysis of the finite element model by July 2024 and publish the research results by October 2025. ConclusionsOur study will build finite element models of the pelvic floor of older men and older women, and we shall elucidate the relationship between the muscles of the pelvic floor, back, abdomen, and hips and the ability of older adults to control bowel movements. The results of this study will provide theoretical support for elucidating the mechanism for improving urination and defecation dysfunction through rehabilitation. Trial RegistrationChinese Clinical Trial Registry ChiCTR2400080749; https://www.chictr.org.cn/showproj.html?proj=193428 International Registered Report Identifier (IRRID)DERR1-10.2196/56333

IntroductionStereotypic behaviours, especially oral stereotypic behaviours, are frequently expressed in farm animals. Tongue-rolling is the most common oral stereotypic behaviour in dairy cows (Bos taurus). If animals frequently display stereotypic behaviours, this is an indication of poor welfare. It has been suggested that animals express stereotypic behaviours as a way of coping with stress. As a result, animals with stereotypic behaviours may have lower levels of stress hormones than animals without stereotypic behaviours.MethodsIn this study, 916 Holstein cows in the first lactation were subjected to scan sampling behavioural observations 200 times for 10 days. All cows were assigned to either a stereotypic behaviours group (SB) or a control group (CON). The SB group was further subdivided into a tongue-rolling group (TR) and an other-stereotypic behaviours group (OS). The TR group was also split into an only tongue-rolling group (OTR) and a mixed tongue-rolling and other stereotypic behaviours group (TROS). Some cows in the TR group belonged to an extreme tongue-rolling group (ETR). Hair and saliva samples were collected from 601 cows to test cortisol concentrations and dairy herd improvement (DHI) data were collected from a total of 762 cows.ResultsThere were no differences in hair or saliva cortisol concentrations between the groups (p>0.05), and the frequencies of tongue-rolling were not associated with cortisol concentrations (p>0.05). For DHI in cows, the milk protein percentage (p = 0.028), milk true protein percentage (p = 0.021) and milk crude protein percentage (p = 0.023) of cows in the ETR group were significantly lower than those in the CON group. For cows in ETR group, as the frequencies of tongue-rolling increased, the milk protein percentage (p = 0.034, r = 0.365), milk true protein percentage (p = 0.022, r = 0.393) and milk crude protein percentage (p = 0.035, r = 0.363) increased.DiscussionWe investigated the relationship between stereotypic behaviours and stress by using a non-invasive sampling method to minimise harm to the cows. We suggest that tongue-rolling may not be a way for cows to cope with stress, at least in terms of cortisol concentrations.

ObjectiveTo explore the expression characteristics and regulatory patterns of RBPs in different immune cell types of AS, and to clarify the potential key role of RBPs in the occurrence and development of AS disease.MethodsPBMC sample data from scRNA-seq (HC*29, AS*10) and bulk RNA-seq (NC*3, AS*5) were selected for correlation analysis.Results(1) Compared with the HC group, the numbers of B, DC (dendritic cells), CD14+ Mono and CD8+ T cells were increased in AS group, while the numbers of platelet (platelets), CD8+ NKT, CD16+ Mono (non-classical monocytes), Native CD4+ T and NK were decreased. (2) Through the analysis of RBP genes in B cells, some RBPs were found to play an important role in B cell differentiation and function, such as DDX3X, SFPQ, SRRM1, UPF2. (3) It may be related to B-cell receptor, IgA immunity, NOD-like receptor and other signaling pathways; Through the analysis of RBP genes in CD8+ T cells, some RBPs that play an important role in the immune regulation of CD8+ T were found, such as EIF2S3, EIF4B, HSPA5, MSL3, PABPC1 and SRSF7; It may be related to T cell receptor, TNF, IL17 and other signaling pathways. (4) Based on bulk RNA-seq, it was found that compared with HC and AS patients, differentially expressed variable splicing genes (RASGs) may play an important role in the occurrence and development of AS by participating in transcriptional regulation, protein phosphorylation and ubiquitination, DNA replication, angiogenesis, intracellular signal transduction and other related pathways.ConclusionRBPs has specific expression characteristics in different immune cell types of AS patients, and has important regulatory functions. Its abnormal expression and regulation may be closely related to the occurrence and development of AS.

The recent remarkable success of mesoporous silica nanoparticle (MSN) technology has stimulated intensive efforts to expand nanoparticle strategies to treat various diseases. However, as an anti-tumor drug delivery system, traditional MSN is prone to clearance by the host immune system, resulting in suboptimal pharmacokinetics and inadequate drug concentrations in tumors. The emergence of biomimetic drug delivery systems has effectively addressed these challenges. In this study, we aimed to develop a biomimetic drug delivery system based on MSN to achieve both immune evasion and tumor targeting. To this end, we coated folic acid-modified mesoporous silica (FMSN) cores with lipid-hybridized macrophage membranes (HEs) through co-extrusion, yielding FMSN@HEs. Initially, we demonstrated effective retention of key proteins Integrin α4 and Integrin β1 in the HEs, leading to significantly reduced clearance of FMSN@HEs by phagocytes in vitro. CCK-8 experiments validated the ability of CUR-FMSN@HEs to effectively inhibit the proliferation of tumor cells. In tumor-bearing mice, FMSN@HEs exhibited stronger tumor targeting and penetration abilities compared to MSN without HEs. The immune escape and tumor-targeting properties of the FMSN@HEs suggest that they could be used as novel bionic drug carriers, potentially providing more options for antitumor therapy.

Mapping the small venous vasculature of the hippocampus in vivo is crucial for understanding how functional changes of hippocampus evolve with age. Oxygen utilization in the hippocampus could serve as a sensitive biomarker for early degenerative changes, surpassing hippocampal tissue atrophy as the main source of information regarding tissue degeneration. Using an ultrahigh field (7T) susceptibility-weighted imaging (SWI) sequence, it is possible to capture oxygen-level dependent contrast of submillimeter-sized vessels. Moreover, the quantitative susceptibility mapping (QSM) results derived from SWI data allow for the simultaneous estimation of venous oxygenation levels, thereby enhancing the understanding of hippocampal function. In this study, we proposed two potential imaging markers in a cohort of 19 healthy volunteers aged between 20 and 74 years. These markers were: 1) hippocampal venous density on SWI images and 2) venous susceptibility (Δχvein) in the hippocampus-associated draining veins (the inferior ventricular veins (IVV) and the basal veins of Rosenthal (BVR) using QSM images). They were chosen specifically to help characterize the oxygen utilization of the human hippocampus and medial temporal lobe (MTL). As part of the analysis, we demonstrated the feasibility of measuring hippocampal venous density and Δχvein in the IVV and BVR at 7T with high spatial resolution (0.25 × 0.25 × 1 mm3). Our results demonstrated the in vivo reconstruction of the hippocampal venous system, providing initial evidence regarding the presence of the venous arch structure within the hippocampus. Furthermore, we evaluated the age effect of the two quantitative estimates and observed a significant increase in Δχvein for the IVV with age (p = 0.006, r2 = 0.369). This may suggest the potential application of Δχvein in IVV as a marker for assessing changes in atrophy-related hippocampal oxygen utilization in normal aging and neurodegenerative diseases such as AD and dementia.

IntroductionDrip irrigation under mulch film promotes a non-uniform salinity distribution in salt fields. The effect of different N application methods on the growth and yield of cotton under drip irrigation under mulch film conditions in eastern coastal saline-alkaline soils in China remain remained unclear.MethodsA randomized complete block design was used in the experiment. Three N application methods were assigned: N applied under mulch film (low-salinity area; UM), N applied between mulch films (high-salinity area; BM), and half N applied under mulch film and half between mulch films (HUHB).ResultsPlant height, photosynthesis, Chl content, boll load, biomass, boll weight and boll density under UM were all significantly higher than those under the other two treatments. The N absorption of UM was higher than in the other two treatments, which might be attributed to the expression of GHNRT1.5 and GHNRT2.1. The net NO3- influx in the roots in UM increased significantly compared with that in BM. The yield and FNRE of UM were 3.9% and 9.1%, respectively, and were 26.52% and 90.36% higher than under HUHB and BM treatments.DiscussionUM not only improved cotton yield but also alleviated the pollution of N residue on drip irrigation under mulch film conditions in salt areas.

BackgroundThe mechanism of pulmonary arterial hypertension (PAH) after surgery/intervention for isolated venticlular septal defect (VSD) in children is unknown. Reliable prognostic indicators for predicting postoperative PAH are urgently needed. Prognostic nutration index (PNI) is widely used to predict postoperative complications and survival in adults, but it is unclear whether it can be used as an indicator of prognosis in children.MethodsA total of 251 children underwent VSD repair surgery or interventional closure in Hunan Children's Hospital from 2020 to 2023 were collected. A 1:1 propensity score matching (PSM) analysis was performed using the nearest neighbor method with a caliper size of 0.2 Logistics regression analysis is used to examine factors associated with the development of PAH.ResultsThe cut-off value for PNI was determined as 58.0. After 1:1 PSM analysis, 49 patients in the low PNI group were matched with high PNI group. Children in the low PNI group had higher risk of postoperative PAH (P = 0.002) than those in the high PNI group. Multivariate logistics regression analysis showed that PNI (RR: 0.903, 95% CI: 0.816–0.999, P = 0.049) and tricuspid regurgitation velocity (RR: 4.743, 95% CI: 1.131–19.897, P = 0.033) were independent prognostic factors for the development of PAH.ConclusionPNI can be used as a prognostic indicator for PAH development after surgery/intervention in children with isolated VSD.

Abstract To improve the economy of offshore oil production platform shore‐based power transmission mode, the reactive power capacity allocation technology of offshore oil production platform shore‐based power supply system based on different network topology reliability measures was proposed. The optimization model of power supply system network topology and the structure model of voltage source converter high voltage direct current transmission system were established, the start and stop control scheme of flexible direct current (DC) transmission system was designed, and the operation parameters of converter station and DC line were monitored in real time. The topological structure of offshore oil production platform shore‐based power supply system is constructed, the mathematical model of flexible DC transmission system is established when the alternating current side voltage is balanced, the reactive power capacity configuration of offshore oil production platform shore‐based power supply system is optimized, and the life cycle cost results are calculated. The experimental results show that the algorithm proposed in this paper can obtain the optimal solution only after 26 calculations, with high optimization efficiency and good convergence effect. Reactive capacity configuration of shore‐based power supply system for offshore production platform can reduce failure rate and life cycle cost.

Using thermal analysis techniques to explore the relation between temperature and physical and chemical changes in materials is crucial for studying the reaction processes of energetic materials. Herein, thermogravimetry–mass spectrometry was used to study the reaction process of B/KNO3/polyvinylidene fluoride (PVDF) composites. The effects of different PVDF and B contents on the decomposition process, pressure release properties and heat of combustion of the composites were investigated. Furthermore, the thermodynamic and kinetic responses of the composites in a linear integrated state after stimulation at different temperatures were studied. The results show that the addition of PVDF lowered the temperature at which KNO3 decomposed and released [O], enabling the composite to react at a lower temperature. Although the initial reaction temperature increased with increasing PVDF content, excessive PVDF hindered the heat and mass transfer between particles, thereby deteriorating the pressure release characteristics and heat of combustion of the composite. In addition, the B/KNO3/PVDF composites were chemically stabilized by heating at 60 °C for 90 d or at 150 °C for 2 h. This treatment ensured stable combustion and pressure release of the composites. These results provide a reference for studying the reactivity and functional applications of B/KNO3 composites.

Abstract Borehole strain monitoring plays a critical role in earthquake precursor research. With the accumulation of observation data, traditional data processing methods struggle to handle the challenges of big data. This study proposes a segmented variational mode decomposition method and a GRU-LUBE deep learning network based on machine learning theory. The algorithm enhances data correlation during decomposition and effectively predicts borehole strain data changes. We extract pre-earthquake anomalies from four-component borehole strain data of the Guza station for two major earthquakes in Sichuan (Wenchuan and Lushan earthquakes), obtaining more comprehensive anomalies than previous studies. Statistical analysis reveals similar abnormal phenomena in the Guza station’s borehole strain data before both earthquakes, suggesting shared crustal stress accumulation and release patterns. These findings highlight the need for further research to improve earthquake prediction and preparedness through understanding underlying mechanisms.

Abstract The coexistence of ulcerative colitis (UC) and nonalcoholic steatohepatitis (NASH) involves a intricate interplay, though the precise pathophysiological mechanisms remain elusive. To shed light on this, our study endeavors to unravel the shared gene signatures and molecular mechanisms by employing quantitative bioinformatics analysis on a publicly available RNA-sequencing database. Gene expression profiles of UC (GSE87466) and NASH (GSE89632) were retrieved from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) were analyzed using R software. After identifying common DEGs, functional enrichment analysis, protein–protein interaction (PPI) network analysis and module construction were performed to obtain candidate hub genes. GSE47908 for UC and GSE159676 for NASH were selected to validate the obtained candidate genes. A total of 119 common DEGs were found in NASH and UC patients. Functional and pathway analyses emphasized that viral infection, inflammation and immune response were enriched in these two diseases. After module construction and validation, CD2, CD8A, GNLY, IFI44, NKG7 and OAS2 were identified as hub genes. 6 hub genes and their combined prediction scores were found with an impressive accuracy and sensitivity. Functional estimation, gene set enrichment analysis and immune infiltration signature identification showed notable associations of the six hub genes with T cells, natural killer cells and type I interferon levels. In addition, we constructed UC combined with NASH mice model successfully with significantly higher expression of hub genes in both liver and colonic tissues than those in control group. Our study elucidates 6 hub genes of UC and NASH, which may participate in immune, inflammatory and antiviral effects. These findings provide some potential biochemical markers for further exploration of UC coexistence with NASH.

In smart transportation, assisted driving relies on data integration from various sensors, notably LiDAR and cameras. However, their optical performance can degrade under adverse weather conditions, potentially compromising vehicle safety. Millimeter-wave radar, which can overcome these issues more economically, has been re-evaluated. Despite this, developing an accurate detection model is challenging due to significant noise interference and limited semantic information. To address these practical challenges, this paper presents the TC–Radar model, a novel approach that synergistically integrates the strengths of transformer and the convolutional neural network (CNN) to optimize the sensing potential of millimeter-wave radar in smart transportation systems. The rationale for this integration lies in the complementary nature of CNNs, which are adept at capturing local spatial features, and transformers, which excel at modeling long-range dependencies and global context within data. This hybrid approach allows for a more robust and accurate representation of radar signals, leading to enhanced detection performance. A key innovation of our approach is the introduction of the Cross-Attention (CA) module, which facilitates efficient and dynamic information exchange between the encoder and decoder stages of the network. This CA mechanism ensures that critical features are accurately captured and transferred, thereby significantly improving the overall network performance. In addition, the model contains the dense information fusion block (DIFB) to further enrich the feature representation by integrating different high-frequency local features. This integration process ensures thorough incorporation of key data points. Extensive tests conducted on the CRUW and CARRADA datasets validate the strengths of this method, with the model achieving an average precision (AP) of 83.99% and a mean intersection over union (mIoU) of 45.2%, demonstrating robust radar sensing capabilities.

Measurement-device-independent quantum key distribution (MDI-QKD) closes all the security loopholes in the detection system and is a promising solution for secret key sharing. Polarization encoding is the most common QKD encoding scheme, as it is straightforward to prepare and measure. However, implementing polarization encoding in MDI QKD imposes extra challenges, as polarization alignment must be maintained over both mutually unbiased bases and be maintained for both paths (Alice-Charlie and Bob-Charlie). Polarization alignment is usually done by interrupting the QKD process (reducing overall key generation rates) or using additional classical laser sources multiplexed with quantum channels for polarization alignment. Since low key rates and cost are the two most pressing challenges preventing wide adoption of QKD systems, using additional resources or reducing key rates runs contrary to making QKD commercially viable. Therefore, we propose and implement a novel polarization compensation scheme in the MDI-QKD system that avoids the aforementioned drawbacks by recycling part of discarded detection events. Our scheme evaluates the polarization drift in real-time based on single measurements corresponding to decoy intensities. Our fully automated experimental demonstration maintains the average polarization drift below 0.13 rad over 40 km of spooled fibre (without an insulating jacket) for at least four hours. The average quantum bit error rate is 3.8$\%$, and we achieved an average key rate of $7.45\times 10^{-6}$ bits per pulse.

In this paper, Au and Cu nanoparticles were successfully loaded onto porous g-C3N4 material through a hydrothermal synthesis method. By adjusting the proportion of Cu, Au-5%Cu/C3N4, Au-10%Cu/C3N4, and Au-15%Cu/C3N4, catalysts were prepared and used for the catalytic reduction of CO2 to methanol. Characterization analysis using high-resolution XPS spectra showed that with an increase in the doping amount of Cu, the electron cloud density on the Cu surface initially increased and then decreased. Electrons from Au atoms transferred to Cu atoms, leading to the accumulation of a more negative charge on the Cu surface, promoting the adsorption of partially positively charged C in CO2, which is more beneficial for catalyzing CO2. Among them, Au-10%Cu/C3N4 exhibited good reducibility and strong basic sites, as demonstrated by H2-TPR and CO2-TPD, with the conversion rates for CO2, methanol yield, and methanol selectivity being 11.58%, 41.29 g·kg−1·h−1 (0.39 μmol·g−1s−1), and 59.77%, respectively.

In the development of ultra-deep wells, extremely high temperatures can lead to inefficiency of additives in drilling fluids. Hence, there is a need to prepare additives with a simple preparation process and good effects at ultra-high temperatures to ensure stable drilling fluid performance. In this study, a high temperature resistant filtration loss polymer (LY-2) was prepared using γ-methacryloyloxypropyltrimethoxysilane (KH570), N,N-dimethylallyl ammonium chloride (DMDAAC), sodium p-styrenesulfonate (SSS), and β-cyclodextrin (β-CD). The impact of the different monomer ratios on particle size, rheology, and filtration performance was systematically investigated. Infrared spectroscopy afforded the structural features. Thermogravimetric Analysis detected the temperature stability, and scanning electron microscopy characterized the polymer micromorphology. LY-2 was completely decomposed at a temperature above 600 °C. Experiments showed FLAPI of the drilling fluid containing 3% LY-2 aged at 260 °C/16 h was only 5.1 mL, which is 85.4% lower compared to the base fluid. This is attributed to the synergistic effect of the polymer adsorption through chemical action at high temperatures and the blocking effect of carbon nanoparticles on the filter cake released by cyclodextrin carbonization at high temperatures. Comparing LY-2 with commercial filter loss reducers shows that LY-2 has excellent temperature resistance, which exhibited five times higher filtration performance and relatively low cost, making it possible to be applied to ultra-high temperature drilling operations in an industrial scale-up.