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This is an article in the field of metallurgical engineering. Mangane-zinc spinel ferrite has been widely used in various fields due to its advantages of high permeability， high frequency and low loss. In order to make full use of Fe, Zn, Mn and other elements in electric arc furnace dust (EAFD)， Mn-Zn spinel ferrite was prepared by solid phase sintering method with alkali leaching zinc-containing EAFD as raw materials and MnSO4·H2O added. The effects of temperature， mass ratio (RZ/M) and pretreatment on the synthesis and magnetic properties of Mn-Zn ferrite were investigated by XRD, SEM-EDS and VSM. The results show that with the increase of reaction temperature，the speed of inter-grain merging in the Mn-Zn ferrite increases， the magnetic saturation induction and crystal grain size increase， and the coercivity decreases. When RZ/M changes to 1∶1.0，the magnetic saturation induction， coercivity and grain size increase. After pretreatment，the content of SiO2 in the EAFD decreases，and the magnetic saturation strength of the synthesized manganese-zinc ferrite increases. Therefore, after pretreatment with 2 mol/L alkali solution， the performance of manganzn-spinel ferrite synthesized at the condition of mass ratio 1∶1.0 and calcination temperature 1 100 ℃ is the best. Its saturation magnetic induction intensity (Ms) is 17.902 emu/g, and coercivity (Hc) is 3.21 kA/m.

Waste plastics and rubber have always posed a threat to the environment and a great challenge for disposal. The use of these two waste materials as modifiers for road asphalt provides new road asphalt binders and at the same time provides a new way for waste material resource treatment. Rubber-modified asphalt and plastic-modified asphalt have received widespread attention due to their green and low-carbon characteristics and some performance advantages, but there are still some performance shortcomings that hinder their promotion and application. In order to continue to explore the application of waste materials in the field of road engineering, combined with the performance advantages of both, many scholars began to study the rubber-plastic composite modified asphalt (RPCMA). Therefore, this paper reviewed the different types of waste rubber and plastic, the comprehensive performance of different types of asphalt and its mixture performance, analyzed the modification mechanism of rubber-plastic composite modified asphalt and its performance changes. The results show that rubber-plastic composite modified asphalt is mostly prepared by directly adding modified materials. However, the pretreatment or melt granulation of rubber and plastic will make the performance of rubber-plastic modified asphalt has improved. There is a mutual promotion mechanism between rubber and plastic in asphalt, which makes the performance of rubber-plastic modified asphalt better than that of asphalt obtained by a single modification method (rubber modified asphalt or plastic modified asphalt). In some properties, it can be close to the commercial SBS modified asphalt. The performance of rubber and plastic composite modified asphalt at high temperature has been generally recognized by researchers, but its low-temperature performance is still controversial. Therefore, it is recommended to apply in high-temperature areas. Future work should focus on the development of composite modifiers with stable performance, low cost and ease of use, standardization of modification processes, improvement of low-temperature performance, and monitoring of road performance and environmental impact.

Abstract To investigate the genetic relationship between end stage renal disease (ESRD) and human leukocyte antigen (HLA) alleles in the Guangxi Zhuang population. We performed polymerase chain reaction reversed sequence-specific oligonucleotide (PCR-rSSO) in 325 patients with ESRD and genotyped the HLA-A, HLA-B, HLA-C, HLA-DRB1, and HLA-DQB1 loci. The direct counting method was used to determine the frequencies of HLA alleles, and Arlequin software (version 3.5.2.2) was used for haplotypic frequency analyses to compare the included ESRD patients with 350 healthy donors from the Guangxi Zhuang population. In our study, 120 HLA alleles, 284 HLA-A-B-DRB1 haplotypes, and 332 HLA-A-C-B-DRB1-DQB1 haplotypes were detected. We found that only A*11:01-B*15:02-DRB1*12:02 had a positive association with ESRD (P = 0.001, P c = 0.020, OR = 3.106, 95% CI = 1.497–6.446) after Bonferroni correction; thus, individuals with this haplotype may be susceptible to ESRD. A*11:01-B*15:02-DRB1*12:02 is a potentially valuable haplotype for evaluating the risk of ESRD in the Guangxi Zhuang population.

Abstract The image object recognition and detection technology are widely used in many scenarios. In recent years, big data has become increasingly abundant, and big data-driven artificial intelligence models have attracted more and more attention. Evolutionary computation has also provided a powerful driving force for the optimization and improvement of deep learning models. In this paper, we propose an image object detection method based on self-supervised and data-driven learning. Differ from other methods, our approach stands out due to its innovative use of multispectral data fusion and evolutionary computation for model optimization. Specifically, our method uniquely combines visible light images and infrared images to detect and identify image targets. Firstly, we utilize a self-supervised learning method and the AutoEncoder model to perform high-dimensional feature extraction on the two types of images. Secondly, we fuse the extracted features from the visible light and infrared images to detect and identify objects. Thirdly, we introduce a model parameter optimization method using evolutionary learning algorithms to enhance model performance. Validation on public datasets shows that our method achieves comparable or superior performance to existing methods.

Abstract Background Glioma is the most common brain tumor. IDH mutations occur frequently in glioma, indicating a more favorable prognosis. We aimed to explore energy metabolism-related genes in glioma to promote the research and treatment. Methods Datasets were obtained from TCGA and GEO databases. Candidate genes were screened by differential gene expression analysis, then functional enrichment analysis was conducted on the candidate genes. PPI was also carried out to help determine the target gene. GSEA and DO analysis were conducted in the different expression level groups of the target gene. Survival analysis and immune cell infiltrating analysis were performed as well. Results We screened 34 candidate genes and selected GLUD1 as the target gene. All candidate genes were significantly enriched in 10 KEGG pathways and 330 GO terms. GLUD1 expression was higher in IDH-mutant samples than IDH-wildtype samples, and higher in normal samples than tumor samples. Low GLUD1 expression was related to poor prognosis according to survival analysis. Most types of immune cells were negatively related to GLUD1 expression, but monocytes and activated mast cells exhibited significantly positive correlation with GLUD1 expression. GLUD1 expression was significantly related to 119 drugs and 6 immune checkpoint genes. GLUD1 was able to serve as an independent prognostic indicator of IDH-mutant glioma. Conclusion In this study, we identified an energy metabolism-related gene GLUD1 potentially contributing to favorable clinical outcomes of IDH-mutant glioma. In glioma, GLUD1 related clinical outcomes and immune landscape were clearer, and more valuable information was provided for immunotherapy.

In the realm of solid-state lithium-ion battery (SLIB) research, anode development remains a focal area because the interface between the solid electrolyte and the anode plays a critical role in determining battery performance. Among various anode materials, vertically aligned graphene nanowalls (GNWs) stand out as a promising candidate due to their extensive surface area, sharp exposed edges, and high conductivity. These features give GNWs great potential to enhance the efficiency and capacity of solid-state batteries. However, the plasma generated in microwave plasma chemical vapor deposition (MWPCVD) equipment chamber exhibits uneven distribution, making it challenging to achieve uniform growth of GNWs over a large area. To improve the in-plane uniformity during the growth of GNWs, a drive motor was installed beneath the substrate holder, allowing the substrate to rotate at a constant speed during the film deposition process, thus enhancing the in-plane uniformity of the GNWs. This paper also showed that the charge-discharge properties of SLIBs are improved with substrate rotation. Compared with the previously reported method of producing uniform microwave plasma through rapid rotation and slow pulsation in a resonant field, this modification of the apparatus is simpler. Additionally, the use of a mixed gas can effectively improve the uniformity of the in-plane GNW films, providing a viable reference for the mass production of SLIB anode electrodes.

Abstract Background Pneumothorax is the most frequent complication after CT-guided percutaneous transthoracic lung biopsy (CT-PTLB). Many studies reported that injection of autologous blood patch (ABP) during biopsy needle withdrawal could reduce the pneumothorax and chest tube insertion rate after CT-PTLB, but the result is debatable. The aim of this systematic review and meta-analysis is to synthesize evidence regarding the efficacy of ABP procedure in patients receiving CT-PTLB. Methods Eligible studies were searched in Pubmed, Embase and Web of Science databases. The inclusion criteria were studies that assessed the relationship between ABP and the pneumothorax and/or chest tube insertion rate after CT-PTLB. Subgroup analyses according to study type, emphysema status and ABP technique applied were also conducted. Odds ratio (OR) with 95% confidence interval (CI) were calculated to examine the risk association. Results A total of 10 studies including 3874 patients were qualified for analysis. Our analysis suggested that ABP reduced the pneumothorax (incidence: 20.0% vs. 27.9%, OR = 0.67, 95% CI = 0.48–0.66, P

Pervasive environmental pollutants, specifically particulate matter (PM2.5), possess the potential to disrupt homeostasis of female thyroid hormone (TH). However, the precise mechanism underlying this effect remains unclear. In this study, we established a model of PM2.5-induced thyroid damage in female rats through intratracheal instillation and employed histopathological and molecular biological methods to observe the toxic effects of PM2.5 on the thyroid gland. Transcriptome gene analysis and 16S rRNA sequencing were utilized to investigate the impact of PM2.5 exposure on the female rat thyroid gland. Furthermore, based on the PM2.5-induced toxic model in female rats, we evaluated its effects on intestinal microbiota, TH levels, and indicators of thyroid function. The findings revealed that PM2.5 exposure induced histopathological damage to thyroid tissue by disrupting thyroid hormone levels (total T3 [TT3], (P < 0.05); total T4 [TT4], (P < 0.05); and thyrotropin hormone [TSH], (P < 0.05)) and functional indices (urine iodine [UI], P > 0.05), thus further inducing histopathological injuries. Transcriptome analysis identified differentially expressed genes (DEGs), primarily concentrated in interleukin 17 (IL-17), forkhead box O (FOXO), and other signaling pathways. Furthermore, exposure to PM2.5 altered the composition and abundance of intestinal microbes. Transcriptome and microbiome analyses demonstrated a correlation between the DEGs within these pathways and the flora present in the intestines. Moreover, 16 S rRNA gene sequencing analysis or DEGs combined with thyroid function analysis revealed that exposure to PM2.5 significantly induced thyroid hormone imbalance. We further identified key DEGs involved in thyroid function-relevant pathways, which were validated using molecular biology methods for clinical applications. In conclusion, the homeostasis of the ''gut-thyroid'' axis may serve as the underlying mechanism for PM2.5-induced thyrotoxicity in female rats.

Silicosis is a systemic disease caused by long-term exposure to high concentrations of free silica dust particles in the workplace. It is characterized by a persistent inflammatory response, fibroblast proliferation, and excessive collagen deposition, leading to pulmonary interstitial fibrosis. Epithelial interstitial transformation (EMT) can cause epithelial cells to lose their tight junctions, cell polarity, and epithelial properties, thereby enhancing the properties of interstitial cells, which can lead to the progression of fibrosis and the formation of scar tissue. Integrin 1 (ITGB1) is considered an important factor for promoting EMT and tumor invasion in a variety of tumors and also plays an important role in the progression of fibrotic diseases. Therefore, ITGB1 can be used as a potential target for the treatment of silicosis. In this study, we found that silica exposure induced epithelial-mesenchymal transformation in rats and that the expression of integrin ITGB1 was elevated along with the EMT. We used CRISPR/Cas9 technology to construct integrin ITGB1 knockdown cell lines for in vitro experiments. We compared the expression of the EMT key proteins E-cadherin and vimentin in the ITGB1 knockdown cells and wild-type cells simultaneously stimulated by silica and detected the aggregation point distribution of E-cadherin and vimentin in the cells using laser confocal microscopy. Our results showed that ITGB1 knockout inhibited the ITGB1/ILK/Snail signaling pathway and attenuated the EMT occurrence compared to control cells. These results suggested that ITGB1 is associated with silica-induced EMT and may be a potential target for the treatment of silicosis.

Abstract Background Optimal blood pressure (BP) levels to reduce the long-term risk of cognitive decline remains controversial. We aimed to investigate the association between BP and anti-hypertensive treatment status with cognitive decline in older adults. Methods This study used data from the China Health and Retirement Longitudinal Study. Cognitive function was assessed at year 2011, 2013, 2015, and 2018. Global cognitive Z-score was calculated as the average score of episodic memory and mental intactness. BP were measured at the first and second wave. Pulse pressure (PP) was calculated as systolic BP (SBP) minus diastolic BP. Cumulative BP was calculated as the area under the curve using BP measurements from 2011 to 2013. Linear mixed models were used to assess the longitudinal association between BP-related measurements and cognitive decline. Results We included 11,671 participants (47.3% men and mean age 58.6 years). Individual with BP > 140/90 mm Hg or taking anti-hypertensive medication were independently associated with accelerated cognitive decline (β=-0.014, 95% CI: -0.020 to -0.007). Individuals with anti-hypertensive medication use, but with controlled SBP to less than 120 mm Hg did not have a significantly increased risk of cognitive decline compared with normotension (β=-0.003, 95% CI: -0.021 to 0.014). Individuals on anti-hypertensive treatment with PP of more than 70 mm Hg had a significantly higher risk of cognitive decline (β=-0.033, 95% CI: -0.045 to -0.020). Regardless of anti-hypertensive treatment status, both elevated baseline and cumulative SBP and PP were found to be independently associated with accelerated cognitive decline. Conclusions Cumulatively elevated SBP, PP and uncontrolled BP were associated with subsequent cognitive decline. Effectively controlling BP with anti-hypertensive treatment may be able to preserve cognitive decline in older adults.

The emergence of the digital information age has sparked considerable interest in predictive analytics within the realm of finance. Predicting uncertainty lies at the heart of Financial Engineering, where crafting investment or trading strategies using suitable prediction methods can optimize profits. This paper provides a novel work that approves the application of computer deep learning neural network has ability to predict volatility of the Black-Scholes model and its derivatives. Employing a data-driven methodology, deep learning neural networks are utilized for volatility prediction, investigating their potential to enhance the accuracy of stock volatility forecasts and options pricing. Subsequently, the forecasted outcomes are leveraged for designing and executing hedging strategies, leading to the creation of three delta hedging approaches based on the anticipated stock volatility. The effectiveness of deep learning neural networks in volatility prediction is demonstrated, showcasing their ability to dynamically capture volatility shifts and outperform traditional models in forecasting accuracy.

Background: Benzo(a)pyrene (B[a]P) is the most widely concerned polycyclic aromatic hydrocarbons (PAHs), which metabolizes benzo(a)pyrene-7,8-dihydrodiol-9,10-epoxide (BPDE) in vivo to produce carcinogenic effect on the body. Currently, there is limited research on the role of the variation of metabolic enzymes in this process. Methods: We carried out a study including 752 participants, measured the concentrations of 16 kinds PAHs in both particle and gaseous phases, urinary PAHs metabolites, leukocyte BPDE-DNA adduct and serum BPDE- Albumin (BPDE-Alb) adduct, and calculated daily intake dose (DID) to assess the cumulative exposure of PAHs. We conducted single nucleotide polymorphism sites (SNPs) of metabolic enzymes, explored the exposure–response relationship between the levels of exposure and BPDE adducts using multiple linear regression models. Result: Our results indicated that an interquartile range (IQR) increase in B[a]P, PAHs, BaPeq, 1-hydroxypyrene (1-OHP), 1-hydroxynaphthalene (1-OHNap) and 2-hydroxynaphthalene (2-OHNap) were associated with 26.53 %, 24.24 %, 28.15 %, 39.15 %, 12.85 % and 14.09 % increase in leukocyte BPDE-DNA adduct (all P 0.05). Besides, we also found the polymorphism of CYP1A1(Gly45Asp), CYP2C9 (Ile359Leu), and UGT1A1(downstream) may affect BPDE adducts level. Conclusion: Our results indicated that leukocyte BPDE-DNA adduct could better reflect the exposure to PAHs. Furthermore, the polymorphism of CYP1A1, CYP2C9 and UGT1A1affected the content of BPDE adducts.

The effects of yeast culture (YC) on dairy goat milk yield and potential effects of rumen microbial population changes on rumen fermentation are poorly understood. This study aimed to evaluate the effects of YC on milk yield and rumen fermentation in dairy goats and explore the potential microbial mechanisms. Forty Laoshan dairy goats with a weight of 51.23 ± 2.23 kg and daily milk yield of 1.41 ± 0.26 kg were randomly divided into 4 groups: control (no YC), YC1 (10 g/day per goat), YC2 (25 g/day per goat), and YC3 (40 g/day per goat). The pre-feeding period was 15 days, and the official period was 60 days. Laoshan dairy goats were milked twice daily, and the individual milk yield was recorded. On the last day of the official period, rumen fluid was collected to measure rumen fermentation, perform quantitative polymerase chain reaction (PCR), and detect metabolites. Compared to the control group, the YC group had greater milk yield; higher acetic acid, butyric acid, and total volatile fatty acid contents; and lower ammonia-N (NH3-N) content in the rumen (p

Background: Silicosis, characterized by interstitial lung inflammation and fibrosis, poses a significant health threat. ATII cells play a crucial role in alveolar epithelial repair and structural integrity maintenance. Inhibiting ATII cell senescence has shown promise in silicosis treatment.However, the mechanism behind silica-induced senescence remains elusive. Methods: The study employed male C57BL/6 N mice and A549 human alveolar epithelial cells to investigate silicosis and its potential treatment. Silicosis was induced in mice via intratracheal instillation of crystalline silica particles, with honokiol administered intraperitoneally for 14 days. Silica-induced senescence in A549 cells was confirmed, and SIRT3 knockout and overexpression cell lines were generated. Various analyses were conducted, including immunoblotting, qRT-PCR, histology, and transmission electron microscopy. Statistical significance was determined using one-way ANOVA with Tukey's post-hoc test. Results: This study elucidates how silica induces ATII cell senescence, emphasizing mtDNA damage. Notably, honokiol (HKL) emerges as a promising anti-senescence and anti-fibrosis agent, acting through sirt3. honokiol effectively attenuated senescence in ATII cells, dependent on sirt3 expression, while mitigating mtDNA damage. Sirt3, a class III histone deacetylase, regulates senescence and mitochondrial stress. HKL activates sirt3, protecting against pulmonary fibrosis and mitochondrial damage. Additionally, HKL downregulated cGAS expression in senescent ATII cells induced by silica, suggesting sirt3's role as an upstream regulator of the cGAS/STING signaling pathway. Moreover, honokiol treatment inhibited the activation of the NF-κB signaling pathway, associated with reduced oxidative stress and mtDNA damage. Notably, HKL enhanced the activity of SOD2, crucial for mitochondrial function, through sirt3-mediated deacetylation. Additionally, HKL promoted the deacetylation activity of sirt3, further safeguarding mtDNA integrity. Conclusions: This study uncovers a natural compound, HKL, with significant anti-fibrotic properties through activating sirt3, shedding light on silicosis pathogenesis and treatment avenues.

Abstract Photocatalytic redox reactions are important for synthesizing fine chemicals from olefins, but the limited lifetime of radical cation intermediates severely restricts semiconductor photocatalysis efficiency. Here, we report that Ag3PO4 can efficiently catalyze intramolecular and intermolecular [2 + 2] and Diels-Alder cycloadditions under visible-light irradiation. The approach is additive-free, catalyst-recyclable. Mechanistic studies indicate that visible-light irradiation on Ag3PO4 generates holes with high oxidation power, which oxidize aromatic alkene adsorbates into radical cations. In photoreduced Ag3PO4, the conduction band electron (e CB −) has low reduction power due to the delocalization among the Ag+-lattices, while the particle surfaces have a strong electrostatic interaction with the radical cations, which considerably stabilize the radical cations against recombination with e CB −. The radical cation on the particle’s surfaces has a lifetime of more than 2 ms, 75 times longer than homogeneous systems. Our findings highlight the effectiveness of inorganic semiconductors for challenging radical cation-mediated synthesis driven by sunlight.

Abstract Metabolic reprogramming, which is recognized as a hallmark of cancer, refers to the phenomenon by which cancer cells change their metabolism to support their increased biosynthetic demands. Tumor cells undergo substantial alterations in metabolic pathways, such as glycolysis, oxidative phosphorylation, pentose phosphate pathway, tricarboxylic acid cycle, fatty acid metabolism, and amino acid metabolism. Latest studies have revealed that long non-coding RNAs (lncRNAs), a group of non-coding RNAs over 200 nucleotides long, mediate metabolic reprogramming in tumor cells by regulating the transcription, translation and post-translational modification of metabolic-related signaling pathways and metabolism-related enzymes through transcriptional, translational, and post-translational modifications of genes. In addition, lncRNAs are closely related to the tumor microenvironment, and they directly or indirectly affect the proliferation and migration of tumor cells, drug resistance and other processes. Here, we review the mechanisms of lncRNA-mediated regulation of glucose, lipid, amino acid metabolism and tumor immunity in gastrointestinal tumors, aiming to provide more information on effective therapeutic targets and drug molecules for gastrointestinal tumors. Graphical Abstract

Urethane surfactants (REQ) were synthesized with octadecanol ethoxylate (AEO) and isocyanate methacrylate (IEM). Subsequently, reactive-carbamate-surfactant-modified nanomicrospheres (PER) were prepared via two-phase aqueous dispersion polymerization using acrylamide (AM), 2-acrylamido-2-methylpropanesulfonic acid (AMPS) and ethylene glycol dimethacrylate (EGDMA). The microstructures and properties of the nanomicrospheres were characterized and examined via infrared spectroscopy, nano-laser particle size analysis, scanning electron microscopy, and in-house simulated exfoliation experiments. The results showed that the synthesized PER nanomicrospheres had a uniform particle size distribution, with an average size of 336 nm. The thermal decomposition temperature of the nanomicrospheres was 278 °C, and the nanomicrospheres had good thermal stability. At the same time, the nanomicrospheres maintained good swelling properties at mineralization < 10,000 mg/L and temperature < 90 °C. Under the condition of certain permeability, the blocking rate and drag coefficient gradually increased with increasing polymer microsphere concentration. Furthermore, at certain polymer microsphere concentrations, the blocking rate and drag coefficient gradually decreased with increasing core permeability. The experimental results indicate that nanomicrospheres used in the artificial core simulation drive have a better ability to drive oil recovery. Compared with AM microspheres (without REQ modification), nanomicrospheres exert a more considerable effect on recovery improvement. Compared with the water drive stage, the final recovery rate after the drive increases by 23.53%. This improvement is attributed to the unique structural design of the nanorods, which can form a thin film at the oil–water–rock interface and promote oil emulsification and stripping. In conclusion, PER nanomicrospheres can effectively control the fluid dynamics within the reservoir, reduce the loss of oil and gas resources, and improve the economic benefits of oil and gas fields, giving them a good application prospect.

The extremely-low-frequency (ELF) magnetic fields of submarines serve as key characteristics for target detection, with their formation mechanisms being complex and diverse. Effectively manipulating a submarine to reduce its magnetic signature is crucial for enhancing its magnetic stealth capabilities. However, current research on the impact of various causative factors is insufficient. This study proposes a contribution rate assessment method based on the Analytic Hierarchy Process (AHP) model, aiming to provide a theoretical basis for effective manipulation. Initially, a thorough analysis of the threat causes of a submarine’s ELF magnetic fields is conducted, and a corresponding hierarchical threat structure model is established. Subsequently, magnetic field signal characteristics generated by different causes are obtained through simulation, and threat matrices and characteristic matrices are constructed. Finally, the contribution rates of different causative magnetic fields to the total magnetic field are calculated, and the simulation results validate the effectiveness of the method. At the stern detection line, the contribution rate of the wake magnetic field is the highest, reaching 0.7649. Along the radial detection line, the contribution rate of the shaft frequency magnetic field is the highest and gradually decays, eventually falling below the wake magnetic field at 150 m and remaining at an approximately 0.5 contribution rate. This study calculates the contribution rates under different operational conditions and detection scenarios, laying a technical foundation for research on the comprehensive active control strategies of submarine ELF magnetic fields in different scenarios.

The Fe-skarns from the Greek Island of Serifos in Cyclades has been utilized only for the exploitation of magnetite ores, while significantly vast amounts of red and yellow hematite ores remained unexploited as mining wastes. This study explores the effective utilization of such mining wastes per se, as active mesoporous catalysts for energy applications, taking CO oxidation as a model reaction. The results of our multi-analytical study have illustrated that the physicochemical characteristics of the hematite materials can be positively influenced by the implementation of a simple calcination step, while the characteristics of magnetite remained unaffected. The calcined yellow and red mineral hematite from Serifos Fe-skarns mining wastes per se, act beneficial in the catalytic activity with respect to calcined magnetite catalyst. The calcinated counterparts of hematite, and especially yellow hematite, can efficiently be used as a support for depositing Au nanoparticles, and thus achieving even higher activity for CO oxidation (90% CO conversion), at much lower temperatures (T ∼62.0 °C). The mining wastes per se of Serifos, mainly of mesoporous hematite, are particularly active for CO oxidation, without any complex pretreatments or activation or functionalization in the context of circular economy.

Polymyxin B and polymyxin E (colistin) are presently considered the last line of defense against human infections caused by multidrug-resistant Gram-negative organisms such as carbapenemase-producer Enterobacterales, Acinetobacter baumannii, and Klebsiella pneumoniae. Yet resistance to this last-line drugs is a major public health threat and is rapidly increasing. Polymyxin S2 (S2) is a polymyxin B analogue previously synthesized in our institute with obviously high antibacterial activity and lower toxicity than polymyxin B and colistin. To predict the possible resistant mechanism of S2 for wide clinical application, we experimentally induced bacterial resistant mutants and studied the preliminary resistance mechanisms. Mut-S, a resistant mutant of K. pneumoniae ATCC BAA-2146 (Kpn2146) induced by S2, was analyzed by whole genome sequencing, transcriptomics, mass spectrometry and complementation experiment. Surprisingly, large-scale genomic inversion (LSGI) of approximately 1.1 Mbp in the chromosome caused by IS26 mediated intramolecular transposition was found in Mut-S, which led to mgrB truncation, lipid A modification and hence S2 resistance. The resistance can be complemented by plasmid carrying intact mgrB. The same mechanism was also found in polymyxin B and colistin induced drug-resistant mutants of Kpn2146 (Mut-B and Mut-E, respectively). This is the first report of polymyxin resistance caused by IS26 intramolecular transposition mediated mgrB truncation in chromosome in K. pneumoniae. The findings broaden our scope of knowledge for polymyxin resistance and enriched our understanding of how bacteria can manage to survive in the presence of antibiotics.

A novel fiber sensor for the refractive index sensing of seawater based on a Mach–Zehnder interferometer has been demonstrated. The sensor consisted of a single-mode fiber (SMF)–no-core fiber (NCF)–single-mode fiber structure (shortened to an SNS structure) with a large lateral offset spliced between the two sections of a multimode fiber (MMF). Optimization studies of the multimode fiber length, offset SNS length, and vertical axial offset distance were performed to improve the coupling efficiency of interference light and achieve the best extinction ratio. In the experiment, a large lateral offset sensor was prepared to detect the refractive index of various ratios of saltwater, which were used to simulate seawater environments. The sensor’s sensitivity was up to −13,703.63 nm/RIU and −13,160 nm/RIU in the refractive index range of 1.3370 to 1.3410 based on the shift of the interference spectrum. Moreover, the sensor showed a good linear response and high stability, with an RSD of only 0.0089% for the trough of the interference in air over 1 h.

Dynamic disasters such as coal and gas outburst seriously restrict the safety of mine production. Different types of coal particles reflect the coal structure, mechanical characteristics and energy storage behavior under load, which is of great significance to the study of coal and gas outburst disasters. However, there is little research on the coal particles breakage characteristics at present. In this study, raw coal and tectonic coal particles were selected to carry out confined compression experiments under different particle size distributions and stress conditions. The results show that the loading process is divided into slip stage, breakage stage and consolidation stage in turn. The deformation resistance of tectonic coal is weaker than that of raw coal in slip stage and breakage stage, but its strain hardening tendency is obviously stronger in compression stage than that of raw coal. Although the stress has a great influence on the relative breakage rate of coal particles, it has a weak influence at the consolidation stage. Due to the unstable structure of some coal particles in the middle particle size during loading, obvious particle size loss occurs after loading. At the same time, particle size distribution also affects the coal particle breakage. The relative breakage rate of large-size sample in single-graded sample group is higher and that of mixed-graded sample group is lower than that of single-graded sample group as a whole. Compared with the raw coal, the absolute breakage rate of large and medium size coal particles of tectonic coal is higher, and tends to break into smaller size coal particles during breakage process. The breakage degree of tectonic coal particles is always higher than that of raw coal. In general, strain hardening of tectonic coal particles is obvious, breakage degree is high, and even presents rheological characteristics in the experiment, which is the basic reason for low porosity and low permeability of tectonic coal. Moreover, most of the energy input to tectonic coal particles from outside is dissipated by friction, breakage and plastic deformation of coal particles, so the elastic energy stored in them is low.

Background: Copper chaperone for superoxide dismutase ( CCS ) is an essential component of the oxidation-reduction system. In breast cancer cells, CCS expression is highly up-regulated, which contributes to cellular proliferation and migration. Breast cancer is a multifaceted disease with different tumor prognoses and responses to clinical treatments, which may be associated with multiple molecular subtypes of CCS . Methods: The CCS expression patterns in breast cancer were investigated by TNMplot, cBioPortal, and HPA network database. The correlation of CCS expression with clinicopathological parameters was analyzed using the UALCAN database. The Cancer Genome Atlas (TCGA) data set was used to analyze the Clinical characteristics of CCS in luminal B patients. The bc-GenExMiner database was used to analyze the effects of BReast-CAncer susceptibility gene (BRCA)1/2, TP53 mutation status, estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor (HER) expression on CCS expression. The survival curves and prognostic value of CCS in luminal B breast cancer were performed through Kaplan-Meier curves, univariate and multivariate Cox regression using the PrognoScan, bc-GenExMiner, and Clinical bioinformatics analysis platform. Results: We found that CCS expression was associated with patient age, race, ER, and PR status. We also discovered that BRCA1/2 mutations had an effect on CCS expression. The luminal B subtype had the highest CCS expression, which was linked to poor survival compared with other subtypes. In addition, Kaplan-Meier curve analysis showed that luminal B patients with high CCS mRNA expression showed a poor survival and the CCS gene is an independent predictor of outcome in patients with luminal B breast cancer by univariate and multivariate Cox regression. Conclusions: Our findings emphasize the significant expression of CCS in luminal B breast cancer and its potential as an autonomous prognostic determinant for this specific molecular subtype. These findings suggest that CCS holds promise as a prospective marker for the treatment of luminal B breast cancer.

The construction of a high-precision geomagnetic map is a prerequisite for geomagnetic navigation and magnetic target-detection technology. The Kriging interpolation algorithm makes use of the variogram to perform linear unbiased and optimal estimation of unknown sample points. It has strong spatial autocorrelation and is one of the important methods for geomagnetic map construction. However, in a region with a complex geomagnetic field, the sparse geomagnetic survey lines make the ratio of line-spacing resolution to in-line resolution larger, and the survey line direction differs from the geomagnetic trend, which leads to a serious effect of geometric anisotropy and thus, reduces the interpolation accuracy of the geomagnetic maps. Therefore, this paper focuses on the problem of geometric anisotropy in the process of constructing a geomagnetic map with sparse data, analyzes the influence of sparse data on geometric anisotropy, deduces the formula of geometric anisotropy correction, and proposes a modified interpolation algorithm accounting for geometric anisotropy correction of variogram for sparse geomagnetic data. The results of several sets of simulations and measured data show that the proposed method has higher interpolation accuracy than the conventional spherical variogram model in a region where the geomagnetic anomaly gradient changes sharply, which provides an effective way to build a high-precision magnetic map of the complex geomagnetic field under the condition of sparse survey lines.

Background: Allograft lung ischemia-reperfusion injury (ALIRI) is a major cause of early primary graft dysfunction and poor long-term survival after lung transplantation (LTx); however, its pathogenesis has not been fully elucidated. Cell death is a mechanism underlying ALIRI. Cuproptosis is a recently discovered form of programmed cell death. To date, no studies have been conducted on the mechanisms by which cuproptosis-related genes (CRGs) regulate ALIRI. Therefore, we explored the potential biomarkers related to cuproptosis to provide new insights into the treatment of ALIRI.Materials and methods: Datasets containing pre- and post-LTx lung biopsy samples and CRGs were obtained from the GEO database and previous studies. We identified differentially expressed CRGs (DE-CRGs) and performed functional analyses. Biomarker genes were selected using three machine learning algorithms. The ROC curve and logistic regression model (LRM) of these biomarkers were constructed. CIBERSORT was used to calculate the number of infiltrating immune cells pre- and post-LTx, and the correlation between these biomarkers and immune cells was analyzed. A competing endogenous RNA network was constructed using these biomarkers. Finally, the biomarkers were verified in a validation set and a rat LTx model using qRT-PCR and Western blotting.Results: Fifteen DE-CRGs were identified. GO analysis revealed that DE-CRGs were significantly enriched in the mitochondrial acetyl-CoA biosynthetic process from pyruvate, protein lipoylation, the tricarboxylic acid (TCA) cycle, and copper-transporting ATPase activity. KEGG enrichment analysis showed that the DE-CRGs were mainly enriched in metabolic pathways, carbon metabolism, and the TCA cycle. NFE2L2, NLRP3, LIPT1, and MTF1 were identified as potential biomarker genes. The AUC of the ROC curve for each biomarker was greater than 0.8, and the LRM provided an excellent classifier with an AUC of 0.96. These biomarkers were validated in another dataset and a rat LTx model, which exhibited good performance. In the CIBERSORT analysis, differentially expressed immune cells were identified, and the biomarkers were associated with the immune cells.Conclusion:NFE2L2, NLRP3, LIPT1, and MTF1 may serve as predictors of cuproptosis and play an important role in the pathogenesis of cuproptosis in ALIRI.

Background: Considering the adverse reactions to vaccination against coronavirus disease 2019 (COVID-19), some people, particularly the elderly and those with underlying medical conditions, are hesitant to be vaccinated. This study aimed to explore the prevalence of adverse reactions and provide direct evidence of vaccine safety, mainly for the elderly and people with underlying medical conditions, to receive COVID-19 vaccination. Methods: From 1st March to 30th April 2022, we conducted an online survey of people who had completed three doses of COVID-19 vaccination by convenience sampling. Adverse reaction rates and 95% confidence intervals were calculated. In addition, conditional logistic regression was used to compare the differences in adverse reactions among the elderly and those with underlying medical conditions with the general population. Results: A total of 3339 individuals were included in this study, of which 2335 (69.9%) were female, with an average age of 32.1 ± 11.4 years. The prevalence of adverse reactions after the first dose of inactivated vaccine was 24.6% (23.1–26.2%), 19.2% (17.8–20.7%) for the second dose, and 19.1% (17.7–20.6%) for the booster dose; among individuals using messenger RNA vaccines, the prevalence was 42.7% (32.3–53.6%) for the first dose, 47.2% (36.5–58.1%) for the second dose, and 46.1% (35.4–57.0%) for the booster dose. Compared with the general population, the prevalence of adverse events did not differ in individuals with underlying medical conditions and those aged 60 and above. Conclusions: For individuals with underlying medical conditions and those aged 60 and above, the prevalence of adverse reactions is similar to that of the general population, which provides a scientific basis regarding vaccination safety for these populations.

Improving the detection accuracy of hyperbola in B-scan images has been a considerable challenge for ground penetrating radar (GPR) to detect tree roots. In this paper, a method for data enhancement and target detection, both based on deep learning was proposed to identify hyperbolas in GPR B-scan images. First, the authors used a cyclic consistent adversarial network (CycleGAN) to augment the original data. In this procedure, the hyperbolic features of the images were preserved and created a wider variety of training samples. Then, the authors could apply the enhanced dataset to the YOLOv5 detection model to evaluate the effectiveness of their method. Meanwhile, the detection effects of Yolov3, Yolov5, Faster R-CNN, and CenterNet detection models on the enhanced dataset were compared. The results showed that applying the enhanced dataset to the Yolov5 detection model exhibited better detection accuracy compared to other combinations of datasets and detection models. The authors demonstrate that the proposed method increases data diversity and the number of samples, improving the precision and recall of hyperbolic curves. These results provide a new method for tree root localization with important effects.

Owing to the environmental protection potential and the desirable high performance capabilities, asphalt rubber (AR) and styrene-butadiene-styrene (SBS) modified asphalt have been widely used. However, the poor construction workability and segregation issues of AR, along with the exorbitant cost of SBS modified asphalt, are of the serious problems that plague their application scope. Moreover, SBS/crumb rubber (CR) modified asphalt is gradually becoming widespread and it therefore becomes incumbent to find appropriate ways to mitigate the issues that may limit its use. As a consequence, it becomes crucial to analyze the interaction between CR and SBS modifiers in the composite mixture, as well as evaluate the influence of modifier dosage on the performance of the modified asphalt. This study presents a comprehensive review of the effects of SBS modifier, CR modifier and composite SBS/CR on the performance of modified asphalts. Macro analysis and micro analysis, including analysis on the conventional physical properties, are carried out. It can uncover the interaction between modifier and asphalt, which reveals how the modifiers influence the properties of modified asphalts. This study will serve as a source of invaluable information to researchers, engineers, and designers, informing them the development, potential and challenges of the CR, SBS and SBS/CR modified asphalts, the optimum contents to attain the best performance along with the mechanism involved.

Background: The role of the cellular level in kidney transplant rejection is unclear, and single-cell RNA sequencing (scRNA-seq) can reveal the single-cell landscape behind rejection of human kidney allografts at the single-cell level.Methods: High-quality transcriptomes were generated from scRNA-seq data from five human kidney transplantation biopsy cores. Cluster analysis was performed on the scRNA-seq data by known cell marker genes in order to identify different cell types. In addition, pathways, pseudotime developmental trajectories and transcriptional regulatory networks involved in different cell subpopulations were explored. Next, we systematically analyzed the scoring of gene sets regarding single-cell expression profiles based on biological processes associated with oxidative stress.Results: We obtained 81,139 single cells by scRNA-seq from kidney transplant tissue biopsies of three antibody-mediated rejection (ABMR) patients and two acute kidney injury (AKI) patients with non-rejection causes and identified 11 cell types, including immune cells, renal cells and several stromal cells. Immune cells such as macrophages showed inflammatory activation and antigen presentation and complement signaling, especially in rejection where some subpopulations of cells specifically expressed in rejection showed specific pro-inflammatory responses. In addition, patients with rejection are characterized by an increased number of fibroblasts, and further analysis of subpopulations of fibroblasts revealed their involvement in inflammatory and fibrosis-related pathways leading to increased renal rejection and fibrosis. Notably, the gene set score for response to oxidative stress was higher in patients with rejection.Conclusion: Insight into histological differences in kidney transplant patients with or without rejection was gained by assessing differences in cellular levels at single-cell resolution. In conclusion, we applied scRNA-seq to rejection after renal transplantation to deconstruct its heterogeneity and identify new targets for personalized therapeutic approaches.

The high-precision magnetic anomaly reference map is a prerequisite for magnetic navigation and magnetic target detection. However, it is difficult to reflect the detailed characteristics of magnetic anomaly changes by using conventional data interpolation and reconstruction in the areas where magnetic anomaly gradients vary drastically and the distribution of magnetic survey lines is sparse. To solve the problem, an improved variogram of the Kriging interpolation method is proposed to improve the spatial resolution of magnetic anomaly feature. This method selects the spherical variogram model and uses the third power of the lag distance to fit the trend of magnetic anomalies. Meanwhile, the second power of the lag distance is introduced to solve the problem of under-fitting between the lag distance and the value of the variation function near the origin of the sparse variogram graph of measured data. Hyperparameter λ is introduced to compensate for the unbalance caused by the introduction of quadratic lag in the spherical variogram model. The results of several sets of simulated and measured data show that the interpolation accuracy of the proposed method is improved by 30–50% compared with the traditional Gaussian, spherical, and exponential models in the region where the magnetic anomaly gradient changes drastically, and the proposed model provides an effective way to build a high-precision magnetic anomaly reference map of the complex magnetic background under the condition of sparse survey lines.

Abstract Background Recent studies have suggested that triglyceride-glucose (TyG) index is an independent predictor of cardiovascular disease (CVD). However, the impact of long-term visit-to-visit variability in TyG index on the risk of CVD is not known. We aimed to investigate the longitudinal association between baseline and mean TyG index as well as TyG index variability and incident CVD in a Chinese population. Methods We included 49,579 participants without previous history of CVD in the Kailuan study who underwent three health examinations (2006, 2008, and 2010) and were followed up for clinical events until 2019. TyG index was calculated as Ln [fasting triglyceride (mg/dL) × fasting glucose (mg/dL)/2]. We measured TyG index variability as the SD of the residuals obtained from a linear regression on the three TyG index measurements for each individual. Multivariate-adjusted Cox models were used to estimate the adjusted hazard ratio (aHR) and 95% confidence interval (CI) with incident CVD. Results During a median follow-up time of 9.0 years, 2404 developed CVD. The highest tertile (T3) of baseline and mean TyG index were each associated with higher CVD incidence as compared with the lowest tertile (T1): aHR, 1.25; 95% CI 1.11–1.42; and aHR 1.40; 95% CI 1.24–1.58, respectively. Tertile 3 of TyG index variability was associated with increased CVD incidence compared to T1 group (aHR, 1.12; 95% CI 1.01–1.24). Similar findings were observed in a series of sensitivity analyses. Conclusion Higher TyG index level and greater TyGindex variability were each independently associated with a higher incidence of CVD.

BackgroundCognitive and gait speed decline are common conditions in older adults and are often associated with future adverse consequences. Although an association between cognitive function and gait speed has been demonstrated, its temporal sequence remains unclear, especially in older Chinese adults. Clarifying this could help identify interventions to improve public health in older adults. ObjectiveThis study aims to examine the longitudinal reciprocal association between gait speed and cognitive function and the possible temporal sequence of changes in both factors in a national longitudinal cohort. MethodsData were derived from 2 waves (2011 baseline and 2015 follow-up) of the China Health and Retirement Longitudinal Study (CHARLS). Participants 60 years or older, without dementia or Parkinson disease at baseline, and with completed data on gait speed and cognition at both baseline and follow-up were included. Usual gait speed was measured over two 2.5-m walks. Mental intactness and episodic memory were used to assess global cognitive function. Cross-lagged panel models and linear mixed-effects models were used to examine the association between cognition and gait speed over time. Standardized coefficients were reported. ResultsA total of 3009 participants (mean age 66.4 years, SD 5.4 years; 1422/3009, 47.26%, female participants) were eligible for inclusion in our analyses. Cross-lagged panel analyses revealed that after accounting for baseline gait speed, cognition, and potential confounders, baseline global cognition (β=.117, 95% CI 0.082-0.152; P

Abstract Background Polycyclic aromatic hydrocarbons (PAHs) and its DNA adducts has been suggested to increase the risk of preterm birth (PB). Yet, few studies have been conducted to investigate this association, and the role of dietary nutrients intakes including vitamins, folate, and carotene during pre- and post-conception on this association has not been studied. Methods Building upon a birth cohort in Taiyuan China, we conducted a nested case control study including 83 PB and 82 term births. Benzo[a]pyrene (BaP)-DNA adducts were measured by an improved LC-MC/MC analytic method. Dietary nutrient intakes were estimated from food frequency questionnaire using the Chinese Standard Tables of Food Consumption. Multivariable logistic regression model was used to examine the associations. Results Increased risk of PB was observed as per interquartile increase in maternal BaP-DNA adduct level (OR = 1.27, 95%CI 0.95–1.67). Compared to low level (below mean) of maternal adducts, high level (above mean) of adducts was associated with the risk of PB (OR = 2.05, 95%CI 1.05–4.01). After stratified by dietary nutrients intakes, high adducts levels were associated with approximately 2–fourfold times increases in risk of PB among women with low vitamin A, C, E, folate, and carotene intakes during pre- and/or post-conception. Stronger stratified associations were consistently seen during preconception. Similar patterns were observed after additional adjustment for supplementation. Conclusions Our study supports the hypothesis that high level of maternal PAHs exposure was significantly associated with increased risk of PB, and provides the first evidence that dietary vitamins, carotene, and folate intake levels may modify this association during different pregnancy windows. Our findings are relevant to identify recommendation for environment management and prenatal nutrition regarding pregnant women and newborns. Further investigation in other populations is warranted.

The combination of organic and inorganic materials has been considered an effective solution for achieving ambient thermoelectric energy harvesting and has been developing rapidly. Here, PEDOT:PSS/MWCNT (PPM) composite hydrogels were synthesized using the self-assembled gelation process of poly(3,4-ethylenedioxythiophene)-poly(styrenesulfonate) (PEDOT:PSS) and the interaction between PEDOT:PSS and multi-walled carbon nanotubes (MWCNTs) without the addition of any surfactant. After immersion in dimethyl sulfoxide and freeze-drying, the hydrogel is easily dispersed in water and used as a direct ink writing (DIW) 3D printing ink. At room temperature, the PPM-20 printed film with 20 wt% MWCNT solids achieved a maximum power factor of 7.37 μW m−1 K−2 and maintained stable thermoelectric properties during repeated bending cycles. On this basis, a thermoelectric generator (TEG) consisting of five legs was printed, which could be produced to generate an open circuit voltage of 6.4 mV and a maximum output power of 40.48 nW at a temperature gradient of 50 K, confirming its great potential for application in high-performance flexible organic/inorganic thermoelectric materials.

(1) Objective: To explore the neurobiological effects of terahertz (THz) radiation on zebrafish larvae using calcium (Ca2+) imaging technology. (2) Methods: Zebrafish larvae at 7 days post fertilization (dpf) were exposed to THz radiation for 10 or 20 min; the frequency was 2.52 THz and the amplitude 50 mW/cm2. The behavioral experiments, neural Ca2+ imaging, and quantitative polymerase chain reaction (qPCR) of the dopamine-related genes were conducted following the irradiation. (3) Results: Compared with the control group, the behavioral experiments demonstrated that THz radiation significantly increased the distance travelled and speed of zebrafish larvae. In addition, the maximum acceleration and motion frequency were elevated in the 20 min radiation group. The neural Ca2+ imaging results indicated a substantial increase in zebrafish neuronal activity. qPCR experiments revealed a significant upregulation of dopamine-related genes, such as drd2b, drd4a, slc6a3 and th. (4) Conclusion: THz radiation (2.52 THz, 50 mW/cm2, 20 min) upregulated dopamine-related genes and significantly enhanced neuronal excitability, and the neurobiological effect of THz radiation can be visualized using neural Ca2+ imaging in vivo.

IntroductionAdverse impacts of soil microplastics (MPs, diameter

IntroductionDiabetic erectile dysfunction (DMED) refers to erectile dysfunction secondary to diabetes. Erectile dysfunction is characterized by a persistent inability to achieve and maintain an erection sufficient to permit satisfactory sexual activity.MethodsBased on the Web of Science core collection database, we firstly analyzed the quantity and quality of publications in the field of DMED, secondly profiled the publishing groups in terms of country, institution, author’s publication and cooperation network, and finally sorted out and summarized the hot topics of research.ResultsFrom 2001 to 2022, a total of 1,403 articles relating to this topic were published in 359 journals. They represent the global research status, potential hotspots, and future research directions. The number of DMED-related publications and citations has steadily increased over the few past decades. Academic institutions from Europe and the United States have played a leading role in DMED research. The country, institution, journal, and author with the most publications were the United States (294), INHA University (39), the Journal of Sexual Medicine (156), and Ryu, Ji-Kan (29), respectively. The most common keywords were erectile dysfunction (796), men (256), diabetes (254), diabetes mellitus (239), prevalence (180), corpus cavernosum (171), dysfunction (155), mellitus (154), nitric-oxide synthase (153), and expression (140). The main keyword-based research topics and hotspots in the DMED field were oral sildenafil, smooth muscle relaxation, nitric oxide synthase, gene therapy, metabolic syndrome, cavernous nerve injury, stem cell, and penile prosthesis.DiscussionThe terms oral sildenafil, smooth muscle relaxation, nitric oxide synthase, gene therapy, metabolic syndrome, cavernous nerve injury, stem cell, and penile prosthesis will be at the forefront of DMED-related research.

IntroductionAssisted reproductive technology (ART) is a method that uses various techniques to process sperm or ova. Assisted reproductive technology involves removing ova from a woman's ovaries, combining them with sperm in the laboratory, and returning them to the woman's body or donating them to another woman.MethodsBased on the web of science core collection database, we firstly analyzed the quantity and quality of publications in the field of ART, secondly profiled the publishing groups in terms of country, institution, author's publication and cooperation network, and finally sorted out and summarized the hot topics of research.ResultsIn total, 6,288 articles on ART were published between 2001 and 2022 in 1,013 journals. Most of these published articles represent the global research status, potential hotspots and future research directions. Publications and citations of research on assisted reproductive technology have steadily increased over the past few decades. Academic institutions in Europe and the United States have been leading in assisted reproductive technology research. The countries, institutions, journals, and authors with the most published articles were the United States (1864), Harvard Univ (108), Fertility and Sterility (819), and Stern, Judy E. (64). The most commonly used keywords are Assisted reproductive technology (3303) and in-vitro Fertilization (2139), Ivf (1140), Pregnancy (1140), Women (769), Intracytoplasmic Sperm injection (644), In Fertilization (632), Risk (545), and Outcome (423).ConclusionFrozen embryo transfer, intracytoplasmic sperm injection, and in vitro fertilization are the main research topics and hotspots in the field of assisted reproductive technology.

Abstract Background To evaluate the association of physical activity (PA) intensity with cognitive performance at baseline and during follow-up. Methods A total of 4039 participants aged 45 years or above from the China Health and Retirement Longitudinal Study were enrolled in visit 1 (2011–2012) and followed for cognitive function in visit 2 (2013–2014), visit 3 (2015–2016), and visit 4 (2017–2018). We analyzed the association of PA intensity with global cognition, episodic memory, and mental intactness at baseline using adjusted regression methods and evaluated the long-term effect of PA intensity using multiple measures of cognition scores by mixed effect model. Results In cross-sectional analysis, mild and moderate PA, rather than vigorous PA, was associated with better cognitive performance. The results remained consistent in multiple sensitivity analyses. During the follow-up, participant with mild PA had a 0.56 (95% CI 0.12–0.99) higher global cognition, 0.23 (95% CI 0.01–0.46) higher episodic memory, and 0.33 (95% CI 0.01–0.64) higher mental intactness, while those with moderate PA had a 0.74 (95% CI 0.32–1.17) higher global score, 0.32 (95% CI 0.09–0.54) higher episodic memory, and 0.43 (95% CI 0.12–0.74) higher mental intactness, compared with individuals without PA. Vigorous PA was not beneficial to the long-term cognitive performance. Conclusions Our study indicates that mild and moderate PA could improve cognitive performance, rather than the vigorous activity. The targeted intensity of PA might be more effective to achieve the greatest cognition improvement considering age and depressive status.

Abstract Background The relationship between body mass index (BMI) and low-density lipoprotein cholesterol (LDL-C) has not been clearly elucidated in middle-aged and older adults. This study aimed to evaluate the non-linear dose-response relationship between BMI and LDL-C in males and females. Methods Data was obtained from two nationally representative surveys in China—the China Health and Nutrition Survey (CHNS, 2009) and China Health and Retirement Longitudinal Study (CHARLS, 2011–2012). To evaluate the sex differences in the association between BMI and LDL-C, the generalized additive models with a smooth function for continuous BMI and smooth-factor interaction for sexes with BMI were used. Segmented regressions were fitted to calculate the slopes with different estimated breakpoints among females and males. Results A total of 12,273 participants (47.1% male) aged 45 to 75 years were included. The generalized additive models revealed that a non-linear relationship between BMI and LDL-C level in both sexes after adjustment for age, residence, education levels, marital status, drinking, smoking status, and cohort (CHNS or CHARLS). Slopes of the association between BMI and LDL-C association changed at BMI 20.3 kg/m2 (95% CI: 18.8 to 21.8) in females and 27.1 kg/m2 (95% CI: 25. 8 to 28.4) in males. Below these BMI breakpoints, LDL-C levels increased 1.84 (95% CI: 1.45 to 2.31) in males and 3.49 (95% CI: 1.54 to 5.45) mg/dL per kg/m2 in females. However, LDL-C levels declined − 1.50 (95% CI: − 2.92 to − 0.09) mg/dL per kg/m2 above BMI of 27.1 kg/m2 in males. The non-linear association BMI and LDL-C in males and females was varied by cohort source, age groups, and the number of metabolic syndrome criteria. Conclusions In the Chinese middle aged and older adults, the BMI and LDL-C relationship was inverted U-shaped with a high level of LDL-C at a BMI of 27.1 kg/m2 in males, and an approximately linear association was observed in females.