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Abstract High-grade B-cell lymphoma with 11q aberration (HGBL-11q) is a distinct lymphoma entity according to the 5th edition of the WHO classification of hematolymphoid tumors. It lacks MYC translocation but carries proximal gains and/or telomeric losses of chromosome 11q. This rare type of B-cell lymphoma is less frequently reported in people living with HIV (PLWH), and its exact frequency remains unclear. Our goal was to retrospectively analyze its frequency in a cohort of aggressive B-cell lymphomas in PLWH, including Burkitt lymphoma (BL, n = 35), diffuse large B-cell lymphoma (DLBCL, n = 48), high-grade B-cell lymphoma, not otherwise specified (HGBL-NOS, n = 13), which was diagnosed as AIDS-related lymphoma (ARL) at our institution. In total, 10/96 (10.4%) cases harbored the typical 11q aberration pattern, predominantly those that had been classified as BL (6/35, 17.1%), DLBCL (2/48, 4.2%), and HGBL, NOS (2/13, 15.4%). We also evaluated 7 cases of AIDS-related HGBL-11q (AR-HGBL-11q) reported in the literature. The median age of our cohort was 35 years, and all the patients were male. Most cases (70%) had a history of HIV infection for over 1 year, and all were involved in lymph nodes (100%), frequently involved extranodal sites (60%), and Ann Arbor stage III/IV. In histomorphology, the cases exhibited diverse cytological features, reminiscent of BL (6 cases), DLBCL (2 cases), and HGBL (2 cases). A comparison of the combined cohort of 17 AR-HGBL-11q cases with 11 ARL cases that lacked both MYC rearrangement and 11q aberration at our institution showed that HGBL-11q cases were characterized by strikingly coarse apoptotic debris (P

Abstract Myocardial ischemia-reperfusion injury (MIRI) is a significant complication following reperfusion therapy after myocardial infarction. Mitochondrial oxidative stress is a critical factor in MIRI, and Sirtuin 3 (SIRT3), as a major mitochondrial deacetylase, plays a key protective role, with its activity potentially regulated by O-GlcNAcylation. This study used the H9C2 cell line to establish a simulated ischemia/reperfusion (SI/R) model, we utilized co-immunoprecipitated to validate the relationship between O-GlcNAc transferase (OGT) and SIRT3, demonstrated SIRT3 O-GlcNAcylation sites through LC–MS/MS, and performed site mutations using CRISPR/Cas9 technology. The results were validated using immunoblotting. SIRT3 and superoxide dismutase 2 (SOD2) activities were detected using a fluorometric assay, while mitochondrial reactive oxygen species (MROS) levels and cellular apoptosis were assessed using immunofluorescence. We have identified an interaction between SIRT3 and OGT, where SIRT3 undergoes dynamic O-GlcNAcylation at the S190 site, facilitating SIRT3 deacetylase activity. During SI/R, elevated levels of O-GlcNAcylation activate SOD2 by promoting SIRT3 enzyme activity, thereby inhibiting excessive MROS production. This significantly mitigates the occurrence of malignant autophagy in myocardial cells during reperfusion, promoting their survival. Conversely, blocking SIRT3 O-GlcNAcylation at the S190 site exacerbates SI/R injury. We demonstrate that O-GlcNAcylation is a crucial post-translational modification (PTM) of SIRT3 during SI/R, shedding light on a promising mechanism for future therapeutic approaches.

ABSTRACT: Objectives: Klebsiella aerogenes is a largely understudied opportunistic pathogen that can cause sepsis and lead to high mortality rates. In this study, we reported the occurrence of carbapenem-resistant blaOXA-181-carrying Klebsiella aerogenes from swine in China and elucidate their genomic characteristics. Methods: A total of 126 samples, including 109 swine fecal swabs, 14 environmental samples, and three feed samples were collected from a pig farm in China. The samples were enriched with LB broth culture and then inoculated into MacConkey agar plates for bacterial isolation. After PCR detection of carbapenemases genes, the blaOXA-181-carrying isolates were subjected to antimicrobial susceptibility testing, and whole-genome sequence analysis. Results: Four Klebsiella aerogenes isolates carrying the blaOXA-181 gene were obtained from swine faecal samples. All the 4 strains were belonged to ST438. The blaOXA-181 genes were located in IncX3-ColKP3 hybrid plasmids with the core genetic structure of IS26-ΔIS3000-ΔISEcp1-blaOXA-181-ΔlysR-ΔereA-ΔrepA-ISKpn19-tinR-qnrS1-ΔIS2-IS26, which suggests the potential for horizontal transfer and further dissemination of this resistance gene among Enterobacteriaceae and other sources. Conclusions: This study represents the first instance of OXA-181-producing K. aerogenes being identified from swine faeces in China. It is crucial to maintain continuous monitoring and ongoing attention to the detection of K. aerogenes carrying blaOXA-181 and other resistance genes in pigs.

Abstract Constructing crossmodal in-sensor processing system based on high-performance flexible devices is of great significance for the development of wearable human-machine interfaces. A bio-inspired crossmodal in-sensor computing system can perform real-time energy-efficient processing of multimodal signals, alleviating data conversion and transmission between different modules in conventional chips. Here, we report a bio-inspired crossmodal spiking sensory neuron (CSSN) based on a flexible VO2 memristor, and demonstrate a crossmodal in-sensor encoding and computing system for wearable human-machine interfaces. We demonstrate excellent performance in the VO2 memristor including endurance (>1012), uniformity (0.72% for cycle-to-cycle variations and 3.73% for device-to-device variations), speed (

Clinical use of small-diameter vascular grafts remains a challenging issue in neovessel regeneration in view of thrombosis and intimal hyperplasia. Developing a vascular graft with structure and function similar to those of the native vessels necessitates a major direction of vascular tissue regeneration. Thus, this study sought to design and fabricate a range of tri-phasic scaffolds (0, 2, and 5 wt% gastrodin-polyurethane (PU)) with spatiotemporally defined structure and gastrodin-release for regulating the highly coordinated processes in growth of the intima and media. While the small pores of inner layer guided infiltration of human umbilical vein endothelial cells (HUVECs), the bigger pores of medial layer could offer smooth muscle cell (SMC)-friendly habitat, and external fibers conferred adequate mechanical properties. Correspondingly, spatial distribution and differential regulation of key proteins in HUVECs and SMCs were mediated by hierarchical release of gastrodin, of which rapid release in inner layer elicited enhanced HUVEC proliferation and migration against those of the SMC via activated endothelial nitric oxide synthase (eNOS) and heat shock protein 70 (HSP70) signal. Of note, superior anti-coagulation was reflected in 2 wt% gastrodin-PU ex vivo extracorporeal blood circulation experiment. After in vivo implantation for 12 weeks, there was no formation of obvious thrombosis and intimal hyperplasia in 2 wt% gastrodin-PU. The scaffold maintained high patency and improved vascular remodeling, including the formation of thin endothelialization in lumen and dense extracellular matrix deposition in medial layer. Taken together, the results demonstrate the positive function of hierarchical releasing system that responded to tri-phasic structure, which not only suppressed intimal thickening but also tightly controlled tissue regeneration.

Abstract Convenient and effective biomarkers are essential for the early diagnosis and treatment of Alzheimer’s disease (AD). In the cross-sectional study, 103 patients with AD, 82 patients with aMCI and 508 normal controls (NC) were enrolled. The single‐molecule array (Simoa) technique was used to assess the levels of plasma proteins, including NfL, T-tau, P-tau-181, Aβ40, Aβ42. Montreal Cognitive Assessment (MoCA) was used to assess the overall cognitive function of all subjects. Moreover, Amyloid PET and structural head MRI were also performed in a subset of the population. In the follow-up, the previous 508 normal older adults were followed up for two years, then COX regression analysis was used to investigate the association between baseline plasma proteins and future cognitive outcomes. NfL, T-tau, P-tau-181, Aβ40, Aβ42 and Aβ42/40 were altered in AD dementia, and NfL, Aβ42 and Aβ42/40 significantly outperformed all plasma proteins in differentiating AD dementia from NC, while NfL and Aβ42/40 could effectively distinguish between aMCI and NC. However, only plasma NfL was associated with future cognitive decline, and it was negatively correlated with MoCA (r = − 0.298, p

Abstract Background The association between the triglyceride-glucose (TyG) index and clinical outcomes in patients with both coronary artery disease (CAD) and psoriasis is unclear. This study investigated the association between the TyG index and major adverse cardiovascular events (MACE) in patients with both CAD and psoriasis. Methods This retrospective cohort study included patients diagnosed with both CAD and psoriasis who underwent coronary angiography at the Fuwai Hospital, Beijing, China, between January 2017 and May 2022. The study endpoint was the occurrence of MACE or end of follow-up time. Multivariate Cox proportional analysis and restricted cubic splines (RCS) were used to determine the association between the TyG index and MACE. Receiver operating characteristic (ROC) curves were used to determine the optimal threshold value of the TyG index for predicting MACE. Results This study enrolled 293 patients with both CAD and psoriasis, including 258 (88.1%) males with a mean age of 58.89 ± 9.61 years. Patients were divided into four groups based on the TyG quartiles: Q1 (N = 74), Q2 (N = 73), Q3 (N = 73), and Q4 (N = 73). After adjusting for the potential confounders, the TyG index was independently associated with MACE, both as a continuous variable (HR = 1.53, 95% CI = 1.03–2.28, P = 0.035) and as a categorical variable (Q1: reference; Q2: HR = 1.85, 95% CI = 0.88–3.87, P = 0.105; Q3: HR = 2.39, 95% CI = 1.14-5.00, P = 0.021; Q4: HR = 2.19, 95% CI = 1.001–4.81, P = 0.0497; P for trend = 0.039). RCS analysis showed an linear association between the TyG index and MACE (P-overall = 0.027, P-non-linear = 0.589). ROC curve analysis showed that the TyG index of ≥ 8.73 was the optimal threshold value (area under the ROC curve = 0.60, 95% CI 0.53–0.67). TyG index ≥ 8.73 was significantly associated with MACE (HR = 2.10, 95% CI = 1.32–3.34, P = 0.002). After adjustment for confounders, the TyG index showed independent association with MACE (HR = 2.00, 95% CI = 1.17–3.42, P = 0.011). Conclusions The TyG index showed a positive linear correlation with MACE in patients with both CAD and psoriasis. The TyG index of ≥ 8.73 might be the optimal threshold for predicting MACE. Graphical Abstract

Abstract Objective To investigate the mechanism by which cancer-associated fibroblasts (CAFs) affect the growth and immune evasion of lung cancer cells. Methods Initially, datasets comparing CAFs with normal fibroblasts were downloaded from the GEO dataset GSE48397. Genes with the most significant differential expression were selected and validated using clinical data. Subsequently, CAFs were isolated, and the selected genes were knocked down in CAFs. Co-culture experiments were conducted with H1299 or A549 cells to analyze changes in lung cancer cell growth, migration, and immune evasion in vitro and in vivo. To further elucidate the upstream regulatory mechanism, relevant ChIP-seq data were downloaded from the GEO database, and the regulatory relationships were validated through ChIP-qPCR and luciferase reporter assays. Results OLR1 was significantly overexpressed in CAFs and strongly correlated with adverse prognosis in lung cancer patients. Knockdown of OLR1 markedly inhibited CAFs’ support for the growth and immune evasion of lung cancer cells in vitro and in vivo. ChIP-seq results demonstrated that PRRX1 can promote OLR1 expression by recruiting H3K27ac and H3K4me3, thereby activating CAFs. Knockdown of PRRX1 significantly inhibited CAFs’ function, while further overexpression of OLR1 restored CAFs’ support for lung cancer cell growth, migration, and immune evasion. Conclusion PRRX1 promotes OLR1 expression by recruiting H3K27ac and H3K4me3, activating CAFs, and thereby promoting the growth, migration, and immune evasion of lung cancer cells.

In order to study the effective method of the enrichment and purification of anthocyanin in black wolfberry and mulberry, and identify the structure of anthocyanin, the black wolfberry and mulberry extracts were purified by macroporous resins. The adsorption and desorption abilities of different types of the resins for anthocyanins were compared. LX-20SS was optimized as the resin for the purification of anthocyanins from black wolfberry. The purification conditions were as follows: The mass ratio of resin to crude anthocyanin powder of black wolfberry was at 10:1, and the elution concentration of ethanol was 70%, and the flow rate was 3 mL/min. After the purification, the content of anthocyanin reached 144.18±3.40 mg/g. DM-21 was optimized as the resin for the purification of mulberry anthocyanin. The purification conditions were as follows: The mass ratio of resin to crude anthocyanin powder of mulberry was at 20:3, and the elution concentration of ethanol was 30%, and the flow rate was 1 mL/min. The content of anthocyanin reached 112.44±2.24 mg/g after purification. High performance liquid chromatography tandem mass spectrometry (HPLC-MS/MS) analysis for anthocyanin structures in black wolfberry and mulberry showed that the main anthocyanin in black wolfberry was petunidin-3-O-rutinose (p-coumaroyl)-5-O-glucoside, which accounted for more than 95% of the total anthocyanin. In addition, there are two main types of anthocyanins in mulberry, corresponding to cyanidin-3-glucoside and cyanidin-3-rutinoside, which accounted for 63.58% and 36.42% of the total anthocyanins respectively. The results provided references for the development of black wolfberry and mulberry.

Intelligent recognition technology for underground safety violations in coal mines has become the primary means of safety management and information acquisition. However, the accuracy of intelligent recognition is reduced by factors such as low illumination, point light sources, and high dust in the underground spatial environment. To overcome those problems, this paper proposes a multi-weight fusion image enhancement method, which achieves the fusion enhancement of image brightness and illumination balance. The monitoring image brightness is increased by using the Gamma algorithm. Based on the brightness enhancement, the HSV spatial transformation is carried out to keep the hue component and saturation component unchanged, the illumination component is extracted by using a multi-scale Gaussian function, and then the regions where the illumination component is too strong and too weak are adjusted by using an improved two-dimensional gamma function to achieve an illumination equalization. Combining the three weights of Laplacian contrast, luminance, and saturation and fusing the luminance-enhanced and illuminance-balanced images by Gaussian and Laplacian pyramids, the intelligent surveillance image enhancement is achieved. Through the experimental verification of the intelligent recognition of helmets in mine monitoring, the image enhancement method proposed in this paper and the MSR, MSRCP, MSRCR, and AMSRCR algorithms are evaluated in terms of image evaluation indexes such as standard deviation, peak signal-to-noise ratio, and information entropy, and the peak signal-to-noise ratio is improved by 32.44% on average compared with other algorithms, the standard deviation is improved by 115.38% on average compared with the original image, and the average improvement in standard deviation is 115.38% compared with the original image and 47.30% compared with other algorithms, and the accuracy of helmet recognition reaches 86.7%, an average improvement of 47.52% compared with other algorithms. The results show that the algorithm in this paper can effectively improve the contrast and clarity of mine images, reduce the halo phenomenon, and significantly improve the accuracy of target recognition in intelligent mine monitoring. It can lay a solid foundation for the intelligent identification of safety violations in underground coal mines.

Abstract Background Drug use disorders (DUDs) have emerged as one of the most significant public health crises, exerting a substantial influence on both community health and socio-economic progress. The United States (US) also suffers a heavy burden, it is necessary to figure out the situation from multiple perspectives and take effective measures to deal with it. Therefore, using the data from the Global Burden of Diseases, Injuries, and Risk Factors (GBD) 2021, we evaluated this topic. Methods Annual data on DUDs-related burden were collected from the GBD study 2021. We calculated the indicator of estimated annual percentage change (EAPC) to evaluate the changing trend of burden. The Bayesian model for age-period-cohort was introduced to forecast the burden. Results In 2021, the number and age-standardized rate of prevalence were particularly prominent, with 12,146.95 thousand and 3821.43 per 100,000, respectively. Higher burden was also observed in males, 15–45 years old populations, and opioid use disorders subtype. From 1990 to 2021, the DUDs-related burden increased in the US and all states, especially in West Virginia; and the national death-related burden with the highest increase (EAPC = 7.96). Other significant inverse associations were seen between EAPC, age-standardized rates, and socio-demographic index (SDI). Moreover, in the next 14 years, the projected DUDs burden remains exigent. Conclusions The burden of DUDs in the US is heavy and has been enlarging. This study proposes that greater attention should be paid to the strategies in males, the younger population, opioid use disorders, and low-SDI states implemented by decision-makers to achieve goals such as reducing burden.

Abstract Greenhouse gases (GHGs) are generated during fermentation in silages, especially in barley silage. However, little is known regarding the dynamics of GHG production in silages during fermentation. In the present study, GHG accumulation and reduction were assessed in barley silage. Barley was harvested at the milk stage and ensiled without (CK) or with two commercial lactic acid bacterial (LAB) additives (L1 or L2). Gas and GHG (CO2, N2O, and CH4) production, fermentation quality, fermentation weight loss (FWL), and bacterial communities were analyzed at d 0, 1, 3, 6, 15, 35, and 90 after ensiling. Gas and GHG production rapidly increased in CK during the first 3 days and in L1 and L2 during the first day and then decreased (P

Abstract Background Selenium is essential for livestock and human health. The traditional way of adding selenium to livestock diets has limitations, and there is a growing trend to provide livestock with a safe and efficient source of selenium through selenium-enriched pasture. Therefore, this study was conducted to investigate the effects of selenium enrichment on fermentation characteristics, selenium content, selenium morphology, microbial community and in vitro digestion of silage alfalfa by using unenriched (CK) and selenium-enriched (Se) alfalfa as raw material for silage. Results In this study, selenium enrichment significantly increased crude protein, soluble carbohydrate, total selenium, and organic selenium contents of alfalfa silage fresh and post-silage samples, and it significantly decreased neutral detergent fiber and acid detergent fiber contents (p

Abstract Background Influenza A virus infections can occur in multiple species. Eurasian avian-like swine influenza A (H1N1) viruses (EAS-H1N1) are predominant in swine and occasionally infect humans. A Eurasian avian-like swine influenza A (H1N1) virus was isolated from a boy who was suffering from fever; this strain was designated A/Shandong-binzhou/01/2021 (H1N1). The aims of this study were to investigate the characteristics of this virus and to draw attention to the need for surveillance of influenza virus infection in swine and humans. Methods Throat-swab specimens were collected and subjected to real-time fluorescent quantitative polymerase chain reaction (RT‒PCR). Positive clinical specimens were inoculated onto Madin-Darby canine kidney (MDCK) cells to isolate the virus, which was confirmed by a haemagglutination assay. Then, whole-genome sequencing was carried out using an Illumina MiSeq platform, and phylogenetic analysis was performed with MEGA X software. Results RT‒PCR revealed that the throat-swab specimens were positive for EAS-H1N1, and the virus was subsequently successfully isolated from MDCK cells; this strain was named A/Shandong-binzhou/01/2021 (H1N1). Whole-genome sequencing and phylogenetic analysis revealed that A/Shandong-binzhou/01/2021 (H1N1) is a novel triple-reassortant EAS-H1N1 lineage that contains gene segments from EAS-H1N1 (HA and NA), triple-reassortant swine influenza H1N2 virus (NS) and A(H1N1) pdm09 viruses (PB2, PB1, PA, NP and MP). Conclusions The isolation and analysis of the A/Shandong-binzhou/01/2021 (H1N1) virus provide further evidence that EAS-H1N1 poses a threat to human health, and greater attention should be given to the surveillance of influenza virus infections in swine and humans.

Generative artificial intelligence (GAI) is a technology based on algorithms, models, etc., that creates content such as text, audio, images, videos, and code. GAI is deeply integrated into journalism as tools, platforms and systems. However, GAI’s role in journalism dilutes the power of media professionals, changes traditional news production and poses ethical questions. This study attempts to systematically answer these ethical questions in specific journalistic practices from the perspectives of journalistic professionalism and epistemology. Building on the review of GAI’s development and application, this study identifies the responsibilities of news organizations, journalists and audiences, ensuring that they realize the potential of GAI while adhering to journalism professionalism and universal human values to avoid negative technological effects.

Abstract Light-induced spin currents with the faster response is essential for the more efficient information transmission and processing. Herein, we systematically explore the effect of light illumination energy and direction on the light-induced spin currents in the W/Y3Fe5O12 heterojunction. Light-induced spin currents can be clearly categorized into two types. One is excited by the low light intensity, which mainly involves the photo-generated spin current from spin photovoltaic effect. The other is caused by the high light intensity, which is the light-thermally induced spin current and mainly excited by spin Seebeck effect. Under low light-intensity illumination, light-thermally induced temperature gradient is very small so that spin Seebeck effect can be neglected. Furthermore, the mechanism on spin photovoltaic effect is fully elucidated, where the photo-generated spin current in Y3Fe5O12 mainly originates from the process of spin precession induced by photons. These findings provide some deep insights into the origin of light-induced spin current.

Abstract Dielectric elastomer actuators (DEAs) with large actuation strain and high energy density are highly desirable for actuating soft robots. However, DEAs usually require high driving electric fields (>100 MV m−1) to achieve high performances due to the low dielectric constant and high stiffness of dielectric elastomers (DEs). Here, we introduce polar fluorinated groups and nanodomains aggregated by long alkyl side chains into DE design, simultaneously endowing DE with a high dielectric constant and desirable modulus. Our DE exhibits a maximum area strain of 253% at a low driving electric field of 46 MV m−1. Notably, it achieves an ultrahigh specific energy of 225 J kg−1 at only‍‌ ‌‌40‍‌ MV m−1, around 6 times higher than natural muscle and twice higher than the state-of-the-art DE. Using our DE, soft robots reach an ultrafast running speed of 20.6 BL s−1, 60 times higher than that of commercial VHB 4910, representing the fastest DEA-driven soft robots ever reported.

Abstract Feed shortage has hindered the development of the world’s livestock industry, and the rational use of non-conventional forages can help resolve this issue. To improve the fermentation quality of Caragana korshinskii silage, this study isolated lactic acid bacteria (LAB) from fresh Caragana korshinskii and silage samples, as alternatives to traditional commercial LAB inoculants. Utilizing Single Molecule, Real-Time (SMRT) sequencing technology and metabolomics analysis, the microbial community structure and metabolome were examined after 60 days of fermentation to elucidate the mechanism by which isolated LAB affect the fermentation quality of Caragana korshinskii silage. After 60 days of ensiling, the dominant microbial population in the silage shifted from harmful bacteria such as Erwinia, Pantoea, and Enterobacter to LAB. Compared to commercial LAB, the isolated Lactiplantibacillus plantarum significantly reduced the microbial diversity of Caragana korshinskii silage. The species composition of LAB became simpler with Lentilactobacillus parakefiri dominating and achieving a higher relative abundance. By down-regulating Butanoate metabolism and the Pentose phosphate pathway and up-regulating the Ascorbate and aldarate metabolism pathway, the isolated Lactiplantibacillus plantarum significantly lowered the pH of the silage, increased the content of water-soluble carbohydrates (WSC) and lactic acid (LA), reduced the neutral detergent fiber content (NDF), and improved in vitro neutral detergent fiber digestibility (IVNDFD), thereby enhancing the fermentation quality of Caragana korshinskii silage. On the other hand, the isolated Limosilactobacillus fermentum had the opposite effect, with its ensiling outcome being less effective than that of commercial LAB. The results of the study indicate that the addition of the isolated Lactiplantibacillus plantarum improved the quality of Caragana korshinskii silage by regulating metabolic pathways and the composition of microbes within the ensiled feed. Graphical Abstract

Abstract For the first time, a control strategy based on Fuzzy Sliding Mode Control is implemented in the control of a large amplitude limit cycle of a composite cantilever beam in a multi-dimensional nonlinear form. In the dynamic model establishment of the investigated structure, the higher-order shearing effect is applied, as well as the second-order discretization. Numerical simulation demonstrates that a multi-dimensional nonlinear dynamic system of the investigated structure is demanded for accurate estimation of large amplitude limit cycle responses. Therefore, a control strategy is employed to effectively suppress such responses of the beam in multi-dimensional nonlinear form.

Metal rubber, which has the advantages of low density, strong environmental adaptability, and excellent design flexibility, is widely applied in manufacturing industries such as the aerospace, shipping, and automotive industries. Based on the research object of flexible porous metal rubber (FPMR) structures made of high-temperature elastic alloys, this study established a constitutive model for the quasi-static mechanical properties of FPMR structure under ultra-wide temperature range conditions. Firstly, the forming mechanism and the influencing factors of the static stiffness properties of the FPMR micro-structure were analyzed. Then, the theoretical model of the FPMR micro-element spring was established by applying the cylindrical spiral compression spring stiffness theory, and the theoretical model was corrected based on the large deformation theory and numerical analysis methods. A comparative analysis was carried out through the corrected theoretical model and the test results of different test samples. And the results show that the corrected theoretical model can comprehensively reflect the nonlinear quasi-static stiffness characteristics of the FPMR structure in an ultra-wide temperature range. More importantly, by comparison with the prediction models proposed by other scholars, it is proved that the model proposed in this paper has higher prediction accuracy and the goodness of fit R2 is closer to 1, which provides a theoretical basis for the application of metal rubber in flexible support structures under ultra-high temperature environments.

Dairy farming is a notable source of nitrogen (N) emissions, impacting both atmospheric and aquatic ecosystems, thus necessitating a detailed analysis of nutrient dynamics to curtail nutrient wastage. However, N flow variability and its environmental ramifications differ markedly among dairy farms, and a holistic understanding of these differences is lacking in Inner Mongolia, the biggest dairy production province in China. Utilizing data from 187 dairy farms and employing the NUFER-farm model, this study assessed N flows, N use efficiency (NUE), and N losses across four predominant dairy farming systems in Inner Mongolia. These systems include traditional pastoral dairy farms (PF), smallholder dairy farms with croplands (SF), industrial landless farms (IDF), and coupled dairy cattle and cropland-intensive farms (CDF). Our findings indicate considerable differences in N flows, NUE, and losses among the systems. On average, N deposition and N fertilizer were the primary N sources for PF and SF, respectively, whereas IDF and CDF derived over 90% of their N inputs from purchased feeds. PF and SF recycled all available manure N on-farm, whereas IDF and CDF recycled only approximately 36% of the total available manure N. N losses constituted 39–72% of total N outputs, with ammonia emissions accounting for 68–73% of total N losses across all farm types. In particular, PF had a higher N loss per kilogram of dairy product than other systems. Farm-level NUE ranged from 17 to 35%, with manure management practices showing significant variability, underscoring the potential for enhanced strategies to reduce N losses through improved manure treatment.

The hospital is a workplace full of stressful events for healthcare workers (HCWs) due to unpredictable changes in their daily routines. Perceptions of stressful events (stress mindset) have a significant impact on an individual’s health and well-being. However, few studies have reported the factors and potential counter mechanisms influencing these perceptions. This study aimed to evaluate the relationship between empathy, self-disclosure, social support, and stress mindset of HCWs, and to explore the mechanism of empathy on stress mindset. Five hundred and eight HCWs (35.2% men and 64.8% women) completed the Interpersonal Reactivity Index (IRI), the Distress Disclosure Index (DDI), the Social Support Rating Scale (SSRS), the Stress Mindset Measure (SMM), and demographic questionnaires online in China. The results showed that empathy was positively linked with stress mindset and positively correlated with self-disclosure and social support. In the multiple mediating model, self-disclosure and social support mediated the association between empathy and stress mindset sequentially. The results imply that empathy, self-disclosure, and social support play a significant role in the formation of HCWs’ stress mindset. These findings have substantial ramifications for reducing stress and creating successful government interventions to fortify stress mindset in healthcare.

Liquid nitrogen has emerged as a promising fracturing medium for unconventional natural gas extraction, particularly in the context of coalbed methane extraction, generating significant interest in recent times. In this paper, we analyze the acoustic emission (AE) characteristics of coal samples treated with liquid nitrogen under three-point bending load conditions using indoor experiments and field investigations. We investigate the impact of liquid nitrogen on coal samples by analyzing AE data. The mechanical properties of coal samples with varying initial temperatures were tested under three-point bending load conditions after treatment with liquid nitrogen. The load-displacement curve was analyzed to study the mechanical properties of the coal samples after treatment with liquid nitrogen. Through indoor three-point bending experiments, data analysis, and knowledge of mechanics, we systematically investigated the changes in mechanical properties caused by liquid nitrogen treatment under different conditions. The results demonstrate that the application of liquid nitrogen has significant impacts on the mechanical and AE characteristics of coal samples. The load-displacement curve indicated that the mechanical properties of the coal samples changed after treatment with liquid nitrogen. The AE experiment revealed regular changes in vibration and energy parameters of coal samples after liquid nitrogen treatment under different conditions. We further investigated the changes in mechanical properties and deformation characteristics of coal samples after undergoing liquid nitrogen freezing and thawing in differing environments. Graphs such as load-displacement curves, load-time curves, cumulative vibration count-energy count graphs, and RA-AF density distribution diagrams visually demonstrated the changes in mechanical properties and deformation characteristics. Through an integrated approach of indoor experiments, data analysis, and knowledge of mechanics, our study provides a better understanding of the behavior of coal samples under different conditions. This understanding can contribute to the development of safer and more efficient methods for extracting coalbed methane.

The scarcity of the early Precambrian geological record limits our comprehension of crucial information concerning interactions between the crust and mantle, mechanisms involved in subduction zone arc-continental collisions, as well as patterns of mantle enrichment and crustal growth during this epoch. The Dengfeng terrane in the North China Craton provides significant data on Precambrian crustal evolution, particularly within the Neoarchean magmatic suites. Our study focuses on a variety of basic rocks across several locations in this region. Basic rocks from Huishansi and Sanhuangzhai (2558–2525 Ma) exhibit characteristics such as low SiO2 (45.44–56.54 wt%), K2O (0.77–2.7 wt%), Na2O (1.66–4.51 wt%), and high MgO (4.66–11.22 wt%) and FeOT (8.17–13.77 wt%). Similarly, basic rocks from Shipaihe and Guojiayao (2480 Ma) also display low SiO2 (46.16–52.48 wt%), K2O (0.24–1.28 wt%), and Na2O (1.87–3.75 wt%), with FeOT (1.07–2.31 wt%), but feature higher content of MgO (5.33–8.83 wt%) and Mg# (44–62, averaging 53). Both sets exhibit relatively flat REE patterns and weak negative anomalies in Nb, Ta, and Ti, corresponding to a tholeiitic basalt composition for the protoliths. Analyzing low (Hf/Sm)N, (Nb/La)N, and Th/Yb ratios, coupled with depleted HFSE, suggests potential crustal contamination in the rocks from Huishansi and Sanhuangzhai. Further, based on low V/Sc ratios (5.38–10.27, average 7.02) and depleted zircon ƐHf(t) values, our proposition is that the magma was sourced through partial melting of a depleted and relatively reduced mantle source. These findings offer valuable insights into the tectonic evolution of the Dengfeng terrane, spanning from subduction to post-collisional extension.

Solid polymer electrolytes (SPEs) with wide electrochemically stable window and high lithium-ion transference number (tLi+) are a requirement for high energy density lithium batteries. Here, we construct a copolymer electrolyte (PDA) with ether-ester bifunctional groups that exhibits a low highest occupied molecular orbital (HOMO) energy level by in situ polymerization. Compared to the poly(1,3-dioxolane) (PDOL) pure polyether electrolyte, the weakening of the ion-dipole interaction between lithium salt and polymer in the PDA electrolyte promotes the formation of a “weak solvation” structure. Therefore, the electrolyte achieves high oxidative stability (4.6 V vs. Li+/ Li with a standard leakage current of 10 μA), high Li+ transference number (0.60), and importantly, derives a stable LiF-rich composition on high voltage cathode surface. Which ultimately enables stable cycling of Li||LiNi0.5Co0.2Mn0.3O2 (NCM523) batteries at a range of 3.0–4.3 V. This work provides a fundamental understanding of the design of antioxidant SPEs to achieve high energy density lithium batteries.

Summary: Abnormal epigenetics is the initial factor of the occurrence and development of osteoarthritis (OA), and abnormal mechanical load is a key pathogenic factor of OA. However, how abnormal mechanical load affects chondrocyte epigenetics is unclear. Chondrocytes reportedly respond to mechanics through the extracellular matrix (ECM), which has a role in regulating epigenetics in various diseases, and mitochondria are potential mediators of communication between mechanics and epigenetics. Therefore, it is hypothesized that the matrix mechanics of cartilage regulates their epigenetics through mitochondria and leads to OA. The matrix stiffness of OA cartilage on the stress-concentrated side increases, mitochondrial damage of chondrocyte is severe, and the chondrocyte H3K27me3 is demethylated. Moreover, mitochondrial permeability transition pore (mPTP) opens to increase the translocation of plant homeodomain finger protein 8 (Phf8) into the nucleus to catalyze H3K27me3 demethylation. This provides a new perspective for us to understand the mechanism of OA based on mechanobiology.

The ionic environment of body fluids influences nervous functions for maintaining homeostasis in organisms and ensures normal perceptual abilities and reflex activities. Neural reflex activities, such as limb movements, are closely associated with potassium ions (K+). In this study, we developed artificial synaptic devices based on ion concentration–adjustable gels for emulating various synaptic plasticities under different K+ concentrations in body fluids. In addition to performing essential synaptic functions, potential applications in information processing and associative learning using short- and long-term plasticity realized using ion concentration–adjustable gels are presented. Artificial synaptic devices can be used for constructing an artificial neural pathway that controls artificial muscle reflex activities and can be used for image pattern recognition. All tests show a strong relationship with ion homeostasis. These devices could be applied to neuromorphic robots and human-machine interfaces.

Abstract The odor of alfalfa (Medicago sativa L.), the most extensively cultivated forage, can interfere with livestock feeding. This study used an electronic nose in conjunction with gas chromatography–mass spectrometry (GC–MS) to examine the quality, volatile organic compounds (VOCs), and metabolic pathways of alfalfa at budding (X), early flowering (C), and full flowering (S) stages. Results showed that terpenoids increased first and then decreased with growth and development, heterocyclic substances decreased continuously, and alcohols and ketones increased. The crude protein and ether extract decreased and were positively correlated with terpenoids, heterocycles, and nitrogen and sulfur compounds, while the dry matter content, soluble carbohydrates, and neutral detergent fiber increased and were positively correlated with alcohols and ketones. The VOCs were most accumulated in the early flowering stages, which had more sweet and fruity flavors, and the main substances that differed from the budding stage and the full flowering stage were methyl heptanoate, butyl butyrate, β-ionone, and other esters and terpenoids. The monoterpene, sesquiterpene, and triterpene pathways were up-regulated in the early flowering stage, and the phenyl-propylene synthesis pathway was up-regulated in the full flowering stage. These substances and pathways were key to further improving alfalfa odor, grade and utilization. Graphical Abstract

Objectives Analyzing the lower limb coronal morphological parameters in populations without knee osteoarthritis (KOA) holds significant value in predicting, diagnosing, and formulating surgical strategies for KOA. This study aimed to comprehensively analyze the variability in these parameters among Chinese non‐KOA populations, employing a substantial sample size. Methods A cross‐sectional retrospective analysis was performed on the Chinese non‐KOA populations (n = 407; 49.9% females). The study employed an in‐house developed artificial intelligence software to meticulously assess the coronal morphological parameters of all 814 lower limbs. The parameters evaluated included the hip‐knee‐ankle angle (HKAA), weight‐bearing line ratio (WBLR), joint line convergence angle (JLCA), mechanical lateral‐proximal‐femoral angle (mLPFA), mechanical lateral‐distal‐femoral angle (mLDFA), mechanical medial‐proximal‐tibial angle (mMPTA), and mechanical lateral‐distal‐tibial angle (mLDTA). Differences in these parameters were compared between left and right limbs, different genders, and different age groups (with 50 years as the cut‐off point). Results HKAA and JLCA exhibited left–right differences (left vs. right: 178.2° ± 3.0° vs. 178.6° ± 2.9° for HKAA, p = 0.001; and 1.8° ± 1.5° vs. 1.4° ± 1.6° for JLCA, p

Obtaining precise ground-level fine particulate matter (PM2.5) information is significant for human health. Spatial PM2.5 maps can be obtained by remote sensing technology, but considerable uncertainty exists when suffering from high pollution with complicated aerosol types. To address this issue, we propose using a hierarchical machine learning model to retrieve high-accuracy and daily full-coverage PM2.5 concentrations from 2014 to 2023 in China. Our hierarchical model was validated by the sample-based 10 cross-validation . Results suggest that our model performs better in terms of RMSE of 12.12 µg/m3, MAE of 8.14 µg/m3 and R2 of 0.95 than traditional model with RMSE of 18.18 µg/m3, MAE of 12.21 µg/m3 and R2 of 0.89, showing 27.49–37.41% improvements for RMSE, 21.85–39.26% improvements for MAE and 8.31–15.39% improvements for R2 at three-folds samples. On longer time scales, our model also shows better results than previous studies. Additionally, for high-pollution provinces, our model can capture PM2.5 trends more preciously than the traditional model. Under severe haze, our hierarchical model can also rightly reflect PM2.5 changes. Overall, due to the hierarchical strategy, our ML-based model can obtain daily full-coverage PM2.5 maps in China with high accuracy and can be applied for follow-up studies.

For many applications, raw satellite observations need to be converted to high-level products of various essential environmental variables. While numerous products are available at kilometer spatial resolutions, there are few global products at high spatial resolutions (10–30 m), which are also referred to fine or medium resolutions in the literature. To facilitate the development of more high spatial resolution products, this paper systematically reviews the state-of-the-art progress on inversion algorithms and publicly available regional and global products. We begin with an inventory of available high-resolution satellite data, and then present different algorithms for determining cloud masks, estimating aerosol optical depth, and performing atmospheric correction and topographic correction for land surface reflectance retrieval. The majority of this paper reviews the inversion algorithms and existing regional to global products of 18 variables in four major categories: 1) Land surface radiation, including broadband albedo, land surface temperature, and all-wave net radiation; 2) Terrestrial ecosystem variables, including leaf area index, fraction of absorbed photosynthetically active radiation, fractional vegetation cover, fractional forest cover, tree height, forest above-ground biomass gross primary production, net primary production, and agricultural crop yield; 3) Water cycle and cryosphere, including soil moisture, evapotranspiration, and snow cover; and 4) Land surface types, such as global land cover, impervious surface, inland water, crop type, and fire. Since the existing products over large regions are usually spatially discontinuous due to cloud contamination, different data fusion and data assimilation algorithms and some products for producing spatially seamless and temporally continuous products are presented. In the end, we discuss a variety of challenges in generating global high spatial resolution satellite products.

Nanoscale zerovalent iron (nZVI) has garnered significant attention as an efficient advanced oxidation activator, but its practical application is hindered by aggregation and oxidation. Coating nZVI with carbon can effectively addresses these issues. A simple and scalable production method for carbon-coated nZVI composite is highly desirable. The anti-oxidation and catalytic performance of carbon-coated nZVI composite merit in-depth research. In this study, a highly stable carbon-coated core-shell nZVI composite (Fe0@RF-C) was successfully prepared using a simple method combining phenolic resin embedding and carbothermal reduction. Fe0@RF-C was employed as a heterogeneous persulfate (PS) activator for degrading 2,4-dihydroxybenzophenone (BP-1), an emerging contaminant. Compared to commercial nZVI, Fe0@RF-C exhibited superior PS activation performance and oxidation resistance. Nearly 95% of BP-1 was removed within 10 min in the Fe0@RF-C/PS system. The carbon layer promotes the enrichment of BP-1 and accelerates its degradation through singlet oxygen oxidation and direct electron transfer processes. This study provides a straightforward approach for designing highly stable carbon-coated nZVI composite and elucidates the enhanced catalytic performance mechanism by carbon layers.

CD4+ T cells are central mediators of protective immunity to blood-stage malaria, particularly for their capacity in orchestrating germinal center reaction and generating parasite-specific high-affinity antibodies. T follicular helper (Tfh) cells are predominant CD4+ effector T cell subset implicated in these processes, yet the factors and detailed mechanisms that assist Tfh cell development and function during Plasmodium infection are largely undefined. Here we provide evidence that receptor for activated C kinase 1 (RACK1), an adaptor protein of various intracellular signals, is not only important for CD4+ T cell expansion as previously implied but also plays a prominent role in Tfh cell differentiation and function during blood-stage Plasmodium yoelii 17XNL infection. Consequently, RACK1 in CD4+ T cells contributes significantly to germinal center formation, parasite-specific IgG production, and host resistance to the infection. Mechanistic exploration detects specific interaction of RACK1 with STAT3 in P. yoelii 17XNL-responsive CD4+ T cells, ablation of RACK1 leads to defective STAT3 phosphorylation, accompanied by substantially lower amount of STAT3 protein in CD4+ T cells, whereas retroviral overexpression of RACK1 or STAT3 in RACK1-deficient CD4+ T cells greatly restores STAT3 activity and Bcl-6 expression under the Tfh polarization condition. Further analyses suggest RACK1 positively regulates STAT3 stability by inhibiting the ubiquitin-proteasomal degradation process, thus promoting optimal STAT3 activity and Bcl-6 induction during Tfh cell differentiation. These findings uncover a novel mechanism by which RACK1 participates in posttranslational regulation of STAT3, Tfh cell differentiation, and subsequent development of anti-Plasmodium humoral immunity.

PurposeTo investigate potential differences in pregnancy outcomes among patients with regular menstruation who underwent frozen-thawed embryo transfer using natural cycle (NC) or hormone replacement therapy (HRT).MethodsThis study retrospectively analyzed 2672 patients with regular menstruation who underwent FET from November 2015 to June 2021 at the single reproductive medical center. A one-to-one match was performed applying a 0.02 caliper with propensity score matching. Independent factors influencing the live birth and clinical pregnancy rates were screened and developed in the nomogram by logistic regression analysis. The efficacy of live birth rate and clinical pregnancy rate prediction models was assessed with the area under the ROC curve, and the live birth rate prediction model was internally validated within the bootstrap method.ResultsThe NC protocol outperformed the HRT protocol in terms of clinical pregnancy and live birth rates. The stratified analysis revealed consistently higher live birth and clinical pregnancy rates with the NC protocol across different variable strata compared to the HRT protocol. However, compared to the HRT treatment, perinatal outcomes indicated that the NC protocol was related to a higher probability of gestational diabetes. Multifactorial logistic regression analysis demonstrated independent risk factors for live birth rate and clinical pregnancy rate. To predict the two rates, nomogram prediction models were constructed based on these influencing factors. The receiver operating characteristic curve demonstrated moderate predictive ability with an area under curve (AUC) of 0.646 and 0.656 respectively. The internal validation of the model for live birth rate yielded an average AUC of 0.646 implying the stability of the nomogram model.ConclusionThis study highlighted that NC yielded higher live birth and clinical pregnancy rates in comparison to HRT in women with regular menstruation who achieved successful pregnancies through frozen-thawed embryo transfer. However, it might incur a higher risk of developing gestational diabetes.

Tigecycline serves as a last-resort antimicrobial agent against severe infections caused by multidrug-resistant bacteria. Tet(X) and its numerous variants encoding flavin-dependent monooxygenase can confer resistance to tigecycline, with tet(X4) being the most prevalent variant. This study aims to investigate the prevalence and characterize tigecycline resistance gene tet(X) in E. coli isolates from various origins in Yangzhou, China, to provide insights into tet(X) dissemination in this region. In 2022, we tested the presence of tet(X) in 618 E. coli isolates collected from diverse sources, including patients, pig-related samples, chicken-related samples, and vegetables in Yangzhou, China. The antimicrobial susceptibility of tet(X)-positive E. coli isolates was conducted using the agar dilution method or the broth microdilution method. Whole genome sequencing was performed on tet(X)-positive strains using Illumina and Oxford Nanopore platforms. Four isolates from pig or pork samples carried tet(X4) and exhibited resistance to multiple antimicrobial agents, including tigecycline. They were classified as ST542, ST10, ST761, and ST48, respectively. The tet(X4) gene was located on IncFIA8-IncHI1/ST17 (n=2), IncFIA18-IncFIB(K)-IncX1 (n=1), and IncX1 (n=1) plasmids, respectively. These tet(X4)-carrying plasmids exhibited high similarity to other tet(X4)-bearing plasmids with the same incompatible types found in diverse sources in China. They shared related genetic environments of tet(X4) associated with ISCR2, as observed in the first identified tet(X4)-bearing plasmid p47EC. In conclusion, although a low prevalence (0.65%) of tet(X) in E. coli strains was observed in this study, the horizontal transfer of tet(X4) among E. coli isolates mediated by pandemic plasmids and the mobile element ISCR2 raises great concerns. Thus, heightened surveillance and immediate action are imperative to curb this clinically significant resistance gene and preserve the efficacy of tigecycline.

Theiler’s murine encephalomyelitis virus (TMEV) infected mice have been often used as an animal model for Multiple sclerosis (MS) due to their similar pathology in the central nervous system (CNS). So far, there has been no effective treatment or medicine to cure MS completely. The drugs used in the clinic can only reduce the symptoms of MS, delay its recurrence, and increase the interval between relapses. MS can be caused by many factors, and clinically MS drugs are used to treat MS regardless of what factors are caused rather than MS caused by a specific factor. This can lead to inappropriate medicine, which may be one of the reasons why MS has not been completely cured. Therefore, this review summarized the drugs investigated in the TMEV-induced disease (TMEV-IDD) model of MS, so as to provide medication guidance and theoretical basis for the treatment of virus-induced MS.

IntroductionIntervertebral disc degeneration (IVDD) is a complex disease caused by genetic and environmental factors, but its pathogenesis is still unclear. Although studies of inflammatory cytokines have been used in recent years to unravel the biological mechanisms of a variety of diseases, such analyses have not yet been applied to IVDD. Therefore, we used a Mendelian Randomization approach to explore the potential mechanisms underlying the pathogenesis of IVDD.MethodsWe obtained GWAS data from publicly available databases for inflammatory cytokines and IVDD, respectively, and explored the causal relationship between individual inflammatory cytokines and IVDD using instrumental variable (IV) analysis. We primarily used IVW methods to assess causality, while sensitivity, heterogeneity and multidirectionality analyses were performed for positive results (p

The rate and prognosis of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection in patients with solid cancer tumors actively treated with immune checkpoint inhibitors (ICIs) have not been fully determined. The goal of this meta-analysis was to explore this issue, which can be helpful to clinicians in their decision-making concerning patient treatment. We conducted a thorough search for relevant cohort studies in the databases PubMed, Embase, Cochrane Library, and Web of Science. Mortality and infection rate were the primary endpoints, and the incidence of severe or critical disease was the secondary result. A total of 6,267 cases (individual patients) were represented in 15 studies. Prior exposure to ICIs was not correlated with an elevated risk of SARS-CoV-2 infection (relative risk (RR) 1.04, 95% CI 0.57–1.88, z = 0.12, P = 0.905) or mortality (RR 1.22, 95% CI 0.99–1.50, z = 1.90, P = 0.057). However, the results of the meta-analysis revealed that taking ICIs before SARS-CoV-2 diagnosis increased the chance of developing severe or critical disease (RR 1.51, 95% CI 1.09–2.10, z = 2.46, P = 0.014). No significant inter-study heterogeneity was observed. The infection and mortality rates of SARS-CoV-2 in patients with solid tumors who previously received ICIs or other antitumor therapies did not differ significantly. However, secondary outcomes showed that ICIs treatment before the diagnosis of SARS-CoV-2 infection was significantly associated with the probability of severe or critical illness.Systematic review registrationhttps://www.crd.york.ac.uk/prospero/#recordDetails PROSPERO, identifier CRD42023393511.

Effective extraction of building edge information based on high-resolution remote sensing images is the basis for efficient urban 3D modeling. Existing building extraction methods still have some problems, such as an uncertain segmentation scale, effective feature selection, and sample selection. In this paper, we propose a practical building extraction method based on convolutional network edge-enhanced attention U2-Net (EA U2-Net) to accurately achieve multi-scale extraction of buildings from remote sensing imagery. First, the U2-Net is used as the backbone network for building extraction because each stage of the network is filled by residual U-block (RSU), and the network can better aggregate multi-scale features. Second, the building edge feature map is introduced into the generation network to compensate for the problems of insufficient extracted building edge features and loss of detail. Finally, the convolutional block attention module is used to achieve effective feature extraction of buildings. We performed the experiment on the WHU building dataset, and the experimental results showed that the EA U2-Net model has significantly improved the ability to extract buildings, with an accuracy of 96.30%, a recall rate of 94.91%, f1 of 95.26%, and iou of 91.57%. This proves that EA U 2 - Net can achieve better remote sensing image-building segmentation results. Finally, in view of the problem that the deep learning network relies on training samples, this study examined the influence of the number of building samples, sample purity, and sample resolution on the effect of building extraction. The results confirmed that reasonable sample parameter settings can improve the target extraction accuracy and the optimal sample parameter combination was verified in this experiment.

Cellular senescence and chronic inflammation in response to aging are considered to be indicators of brain aging; they have a great impact on the aging process and are the main risk factors for neurodegeneration. Reviewing the microglial response to aging and neuroinflammation in neurodegenerative diseases will help understand the importance of microglia in neurodegenerative diseases. This review describes the origin and function of microglia and focuses on the role of different states of the microglial response to aging and chronic inflammation on the occurrence and development of neurodegenerative diseases, including Alzheimer’s disease, Huntington’s chorea, and Parkinson’s disease. This review also describes the potential benefits of treating neurodegenerative diseases by modulating changes in microglial states. Therefore, inducing a shift from the neurotoxic to neuroprotective microglial state in neurodegenerative diseases induced by aging and chronic inflammation holds promise for the treatment of neurodegenerative diseases in the future.

Compared with ground-based gravitational wave detection, space-based gravitational wave detection has become a research hotspot because of its abundant wave sources. However, how to reliably transmit the detection data, obtained by the space gravitational wave detector, back to the ground station from a distance of 105 kilometers is a huge challenge. In this paper, the visibility analysis and link budget are carried out for the data transmission of gravitational wave detection in geocentric orbit space, and a high real-time data transmission scheme is provided to support the mHz band gravitational wave detection. In more detail, we firstly establish a theoretical model for visibility analysis and link budget based on spacecraft dynamics model and communication link model. Secondly, through visibility simulation and calculation, we obtained the average communication time per day, and found that the Zhuhai station has a more uniform distribution of communication time compared with other ground stations. Subsequently, the link budget model indicates that link performance is largely determined by various gains and attenuations during the link process, which are related to the link working frequency band and resource allocation. Comparing the differences on gain and attenuation between X-band and Ka-band, we design an X-band communication scheme with the transmission rate of 1Mbps and bit error rate of 10−5. The calculation results also show that the communication scheme has a C/N₀ margin of 4.10 dB, which meets the data transmission requirements of TianQin. Finally, the research shows that compared with the heliocentric orbit of LISA, the geocentric orbit of TianQin has obvious advantages in transmission delay, communication time and real-time performance of data transmission, avoiding the antenna pointing issues and is more conducive to the multi-messenger detection of large astronomical events.

Abstract Background Some studies have assessed the predictive role of the atherogenic index of plasma (AIP) for macrovascular diseases. This prospective investigation aimed to elucidate whether AIP is associated with diabetic kidney disease (DKD) and diabetic retinopathy (DR) incidence. Methods The data were extracted from 4831 participants, of whom 2943 and 3360 participants with type 2 diabetes (T2D) were included in the DKD and DR follow-up analyses, respectively. Cox regression models were performed to test the relationships of AIP value at baseline with the risk of incident DKD and DR. Group-based trajectory modelling was utilized to discern AIP trajectories during the follow-up period. Subsequently, logistic regressions were applied to ascertain the influence of AIP trajectories on the incidence of DKD and DR. Results During the follow-up period, 709 (24.1%) and 193 (5.7%) participants developed DKD and DR, respectively. The median (interquartile range) follow-up time was 24.2 (26.3) months for DKD and 25.7 (27.0) months for DR. According to the multivariate Cox regression models, baseline AIP was positively and linearly related to the occurrence of DKD, with a hazard ratio of 1.75 (95% confidence interval [CI] 1.36–2.26). Three distinct trajectories of AIP were identified throughout the follow-up time: Low (31.4%), Median (50.2%), and High (18.3%). Compared to participants with the Low AIP trajectory, those with High and Median AIP trajectories presented 117% (95% CI: 1.62–2.91) and 84% (95% CI 1.46–2.32) greater odds of developing DKD, respectively. However, neither baseline levels nor trajectories of AIP were shown to be related to DR after adjusting for confounding factors. Conclusions Baseline levels and trajectories of AIP were independently related to elevated DKD risk, indicating that AIP could be used as a predictor for identifying T2D participants at higher risk of DKD. No association between AIP and DR was detected.

We studied the characteristics of coupled-core four-core fibers (CC-4CFs) with different core pitches both theoretically and experimentally. The spatial mode dispersions of different fibers were analyzed, and the result agrees well with theoretical ones. In the experiment, we achieved a spatial mode dispersion as low as 3.72 ps/km1/2 for a 4 km-long CC-4CF with core pitch of 19 μm at a bending radius of 8 cm. The impulse response matrices of four core fibers with different core pitches was investigated using swept-wavelength interferometry over 100 nm bandwidth. The impulse responses were Gaussian-shaped and consistent between different inputs and outputs for CC-4CFs. Our results show that the CC-4CFs with core pitches of 17 and 19 μm exhibit narrower pulse broadening. In addition, the mode-dependent losses of different fibers were analyzed. For the fibers with core pitch of 19 μm, the estimated mode-dependent loss was lower than 3 dB for the entire 100 nm bandwidth. Our results are especially helpful for developing coupled-core multicore fibers for long-haul transmission applications.

Abstract Here we retrieve global daily 1 km gapless PM2.5 concentrations via machine learning and big data, revealing its spatiotemporal variability at an exceptionally detailed level everywhere every day from 2017 to 2022, valuable for air quality monitoring, climate change, and public health studies. We find that 96%, 82%, and 53% of Earth’s populated areas are exposed to unhealthy air for at least one day, one week, and one month in 2022, respectively. Strong disparities in exposure risks and duration are exhibited between developed and developing countries, urban and rural areas, and different parts of cities. Wave-like dramatic changes in air quality are clearly seen around the world before, during, and after the COVID-19 lockdowns, as is the mortality burden linked to fluctuating air pollution events. Encouragingly, only approximately one-third of all countries return to pre-pandemic pollution levels. Many nature-induced air pollution episodes are also revealed, such as biomass burning.

A clear understanding of customer needs is key to the success of new product development and customer-centric product design. Online reviews, particularly initial reviews, are commonly used as effective sources for mining customer requirements. Although customers may post truer and more objective supplementary reviews after a period of product use, such reviews are often overlooked when identifying customer requirements for product design improvement. In this study, we proposed a framework for identifying customer requirements by combining initial and supplementary reviews based on text mining. We categorized the identified customer needs into five product attribute categories using the Kano model. Two case studies were conducted in the laptop and cell phone industries to demonstrate the effectiveness of our method. Thus, dynamic customer requirements and satisfaction can be accurately mined and captured when considering supplementary reviews. In practice, the appropriate use of supplementary reviews may provide valuable guidance for product design and development strategies.

In this paper, four widely used temporal compositing algorithms, i.e. median, maximum NDVI, medoid, and weighted scoring-based algorithms, were evaluated for annual land cover classification using monthly Landsat time series data. Four study areas located in California, Texas, Kansas, and Minnesota, USA were selected for image compositing and land cover classification. Results indicated that images composited using weighted scoring-based algorithms have the best spatial fidelity compared to other three algorithms. In addition, the weighted scoring-based algorithms have superior classification accuracy, followed by median, maximum NDVI, and medoid in descending order. However, the median algorithm has a significant advantage in computational efficiency which was ∼70 times that of weighted scoring-based algorithms, and with overall classification accuracy just slightly lower (∼0.13% on average) than weighted scoring-based algorithms. Therefore, we recommended the weighted scoring-based compositing algorithms for small area land cover mapping, and median compositing algorithm for the land cover mapping of large area considering the balance between computational complexity and classification accuracy. The findings of this study provide insights into the performance difference between various compositing algorithms, and have potential uses for the selection of pixel-based image compositing technique adopted for land cover mapping based on Landsat time series data.