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Abstract Solid tumours often endure nutrient insufficiency during progression. How tumour cells adapt to temporal and spatial nutrient insufficiency remains unclear. We previously identified STC2 as one of the most upregulated genes in cells exposed to nutrient insufficiency by transcriptome screening, indicating the potential of STC2 in cellular adaptation to nutrient insufficiency. However, the molecular mechanisms underlying STC2 induction by nutrient insufficiency and subsequent adaptation remain elusive. Here, we report that STC2 protein is dramatically increased and secreted into the culture media by Gln-/Glc- deprivation. STC2 promoter contains cis-elements that are activated by ATF4 and p65/RelA, two transcription factors activated by a variety of cellular stress. Biologically, STC2 induction and secretion promote cell survival but attenuate cell proliferation during nutrient insufficiency, thus switching the priority of cancer cells from proliferation to survival. Loss of STC2 impairs tumour growth by inducing both apoptosis and necrosis in mouse xenografts. Mechanistically, under nutrient insufficient conditions, cells have increased levels of reactive oxygen species (ROS), and lack of STC2 further elevates ROS levels that lead to increased apoptosis. RNA-Seq analyses reveal STC2 induction suppresses the expression of monoamine oxidase B (MAOB), a mitochondrial membrane enzyme that produces ROS. Moreover, a negative correlation between STC2 and MAOB levels is also identified in human tumour samples. Importantly, the administration of recombinant STC2 to the culture media effectively suppresses MAOB expression as well as apoptosis, suggesting STC2 functions in an autocrine/paracrine manner. Taken together, our findings indicate that nutrient insufficiency induces STC2 expression, which in turn governs the adaptation of cancer cells to nutrient insufficiency through the maintenance of redox homoeostasis, highlighting the potential of STC2 as a therapeutic target for cancer treatment.

Objective: Solid tumor cells utilize amino acid transporters (AATs) to increase amino acid uptake in response tonutrient-insufficiency. The upregulation of AATs is therefore critical for tumor development and progression. This studyidentifies the upregulated AATs under amino acid deprived conditions, and further determines the clinicopathologicalimportance of these AATs in evaluating the prognosis of patients with cancers.Materials and Methods: In this experimental study, the Gene Expression Omnibus (GEO) datasets (GSE62673,GSE26370, GSE125782 and GSE150874) were downloaded from the NCBI website and utilized for integrateddifferential expression and pathway analysis v0.96, Gene Set Enrichment Analysis (GSEA), and REACTOME analysesto identify the AATs upregulated in response to amino acid deprivation. In addition, The Cancer Genome Atlas (TCGA)datasets with prognostic information were assessed and employed to evaluate the association of identified AATs withpatients’ prognoses using SurvExpress analysis.Results: Using analysis of NCBI GEO data, this study shows that amino acid deprivation leads to the upregulationof six AAT genes; SLC3A2, SLC7A5, SLC7A1, SLC1A4, SLC7A11 and SLC1A5. GSEA and REACTOME analysesidentified altered signaling in cells exposed to amino acid deprivation, such as pathways related to stress responses,the cell cycle and apoptosis. In addition, Principal Component Analysis showed these six AAT genes to be well dividedinto two distinct clusters in relation to TCGA tumor tissues versus normal counterparts. Finally, Log-Rank analysisconfirmed the upregulation of this panel of six AAT genes is correlated with poor prognosis in patients with colorectal,esophageal, kidney and lung cancers.Conclusion: The upregulation of a panel of six AATs is common in several human cancers and may provide a valuablediagnostic tool to evaluate the prognosis of patients with colorectal, esophageal, kidney and lung cancers.

Abstract Background Immunocheckpoint inhibitors (ICIs) have been widely used in the clinical treatment of lung cancer. Although clinical studies and trials have shown that patients can benefit significantly after PD-1/PD-L1 blocking therapy, less than 20% of patients can benefit from ICIs therapy due to tumor heterogeneity and the complexity of immune microenvironment. Several recent studies have explored the immunosuppression of PD-L1 expression and activity by post-translational regulation. Our published articles demonstrate that ISG15 inhibits lung adenocarcinoma progression. Whether ISG15 can enhance the efficacy of ICIs by modulating PD-L1 remains unknown. Methods The relationship between ISG15 and lymphocyte infiltration was identified by IHC. The effects of ISG15 on tumor cells and T lymphocytes were assessed using RT-qPCR and Western Blot and in vivo experiments. The underlying mechanism of PD-L1 post-translational modification by ISG15 was revealed by Western blot, RT-qPCR, flow cytometry, and Co-IP. Finally, we performed validation in C57 mice as well as in lung adenocarcinoma tissues. Results ISG15 promotes the infiltration of CD4+ T lymphocytes. In vivo and in vitro experiments demonstrated that ISG15 induces CD4+ T cell proliferation and invalidity and immune responses against tumors. Mechanistically, we demonstrated that the ubiquitination-like modifying effect of ISG15 on PD-L1 increased the modification of K48-linked ubiquitin chains thus increasing the degradation rate of glycosylated PD-L1 targeting proteasomal pathway. The expression of ISG15 and PD-L1 was negatively correlated in NSCLC tissues. In addition, reduced accumulation of PD-L1 by ISG15 in mice also increased splenic lymphocyte infiltration as well as promoted cytotoxic T cell infiltration in the tumor microenvironment, thereby enhancing anti-tumor immunity. Conclusions The ubiquitination modification of PD-L1 by ISG15 increases K48-linked ubiquitin chain modification, thereby increasing the degradation rate of glycosylated PD-L1-targeted proteasome pathway. More importantly, ISG15 enhanced the sensitivity to immunosuppressive therapy. Our study shows that ISG15, as a post-translational modifier of PD-L1, reduces the stability of PD-L1 and may be a potential therapeutic target for cancer immunotherapy.

Currently, the alteration of external factors during crude oil extraction easily disrupts the thermodynamic equilibrium of asphaltene, resulting in the continuous flocculation and deposition of asphaltene molecules in crude oil. This accumulation within the pores of reservoir rocks obstructs the pore throat, hindering the efficient extraction of oil and gas, and consequently, affecting the recovery of oil and gas resources. Therefore, it is crucial to investigate the principles of asphaltene deposition inhibition and the synthesis of asphaltene inhibitors. In recent years, the development of nanotechnology has garnered significant attention due to its unique surface and volume effects. Nanoparticles possess a large specific surface area, high adsorption capacity, and excellent suspension and catalytic abilities, exhibiting unparalleled advantages compared with traditional organic asphaltene inhibitors, such as sodium dodecyl benzene sulfonate and salicylic acid. At present, there are three primary types of nanoparticle inhibitors: metal oxide nanoparticles, organic nanoparticles, and inorganic nonmetal nanoparticles. This paper reviews the recent advancements and application challenges of nanoparticle asphaltene deposition inhibition technology based on the mechanism of asphaltene deposition and nano-inhibitors. The aim was to provide insights for ongoing research in this field and to identify potential future research directions.

With the development of modern communication technology and the large number of new controllable loads connected to the power grid, the new controllable loads with flexible regulation characteristics can participate in the emergency frequency stability control. However, the communication state differences and spatial distribution characteristics of controllable load will affect the actual effect of frequency control. In this paper, an emergency frequency control method based on deep reinforcement learning is proposed considering the response time of controllable load shedding. The proposed method evaluates response ability for emergency control of controlled loads through load response time, controllable load amount and controllable load buses. Then, the controllable load with smaller response time is cut out preferentially to ensure rapid control, and the Markov Decision Process (MDP) is used to model the emergency frequency control problem. Finally, Rainbow algorithm of Deep Reinforcement Learning (DRL) is used to optimize the emergency frequency stability control strategy involving controllable load resources. The formation of emergency load shedding instruction is directly driven by high-dimensional operation state data after power grid failure, so that, the aim of minimizing the economic cost is achieved under the constraint of system stability. The effectiveness of the proposed method is verified in the IEEE 39-bus system.

How photoexcitations influence superconductivity at the FeSe/SrTiO3 interface remains elusive. Here, the authors report fast optical generation of a metastable superconducting state and its reversal by voltage pulses at the FeSe monolayer/SrTiO3 interface.

Water-in-oil-in-water (W1/O/W2) double emulsions must resist W1–W1, O–O and W1–W2 coalescence to be suitable for applications. This work isolates the stability of the oil droplets in a double emulsion, focusing on the impact of the concentration of the hydrophilic surfactant. The stability against coalescence was measured on droplets ranging in size from millimeters to micrometers, evaluating three different measurement methods. The time between the contact and coalescence of millimeter-sized droplets at a planar interface was compared to the number of coalescence events in a microfluidic emulsion and to the change in the droplet size distributions of micrometer-sized single and double emulsions. For the examined formulations, the same stability trends were found in all three droplet sizes. When the concentration of the hydrophilic surfactant is reduced drastically, lipophilic surfactants can help to increase the oil droplets’ stability against coalescence. This article also provides recommendations as to which purpose each of the model experiments is suited and discusses advantages and limitations compared to previous research carried out directly on double emulsions.

Abstract The incidence of patients diagnosed with either breast cancer (BC) or inflammatory bowel disease (IBD) is increasing each year. IBD has been shown to be strongly associated with the development of a variety of solid tumors, but the relationship with breast cancer is not yet definitive. We explored the causative relationship between IBD and BC using a Mendelian randomization (MR) strategy. MR-Egger regression, weighted median (WM), simple median (SM), maximum likelihood (ML), and inverse variance weighting (IVW) methods were among the analytical techniques used in this work. The examination of heterogeneity was conducted by the use of Cochran's Q test and Rucker's Q test. The sensitivity analysis in this study used the IVW and MR-Egger methodologies. The results of our investigation suggested that IBD had a beneficial impact on estrogen receptor-negative (ER-) breast cancer (odds ratio (OR) = 0.92, P = 0.02). The study did not find a significant association between IBD and the risk of developing overall breast cancer (OR = 0.99, P = 0.60), as well as estrogen receptor-positive (ER+) breast cancer (OR = 1.02, P = 0.60) specifically. In addition, our study findings indicated that there was a detrimental association between ER+ breast cancer and IBD as determined using reverse MR analysis (OR = 1.07, P = 0.04). Furthermore, this analysis failed to observe any significant association between overall breast cancer (OR = 1.07, P = 0.07) or ER- breast cancer (OR = 0.99, P = 0.89) and IBD. Our bidirectional MR study yielded a correlation between IBD and some specific hormone receptor status of BC.

Abstract Background Telomere length (TL), mitochondrial DNA copy number (mtDNAcn), and DNA methylation age (DNAmAge) are common aging biomarkers. However, research on the associations between these three markers at birth and subsequent metabolic status was limited. This study aimed to evaluate the association between TL, mtDNAcn, and DNAmAge in newborns and the variation in metabolic hormones of children at 3 years old. Methods This research involved 895 mother–child pairs from a birth cohort in China, with TL and mtDNAcn measured using quantitative real-time PCR, DNA methylation (DNAm) assessed using Infinium MethylationEPIC Beadchip, and DNAm age (DNAmAge) determined using Horvath’s epigenetic clock. Insulin and leptin levels were measured via electrochemiluminescence assay. Multivariable adjusted linear regression and restricted cubic spline (RCS) analysis were utilized to examine the association between aging markers and metabolic hormones. Results The linear regression analysis indicated the percentage change of metabolism hormones for per doubling of aging biomarkers alterations and found significant associations between DNAmAge and insulin levels (adjusted percent change (95% CI), − 13.22 (− 23.21 to − 1.94)), TL and leptin levels (adjusted percent change (95% CI), 15.32 (1.32 to 31.24)), and mtDNAcn and leptin levels (adjusted percent change (95% CI), − 14.13 (− 21.59 to − 5.95)). The RCS analysis revealed significant non-linear associations between TL (Ln transformed) and insulin (Ln transformed) (P = 0.024 for nonlinearity), as well as DNAmAge (Ln transformed) and leptin (Ln transformed) (P = 0.043 for nonlinearity). Specifically, for TL and insulin, a positive association was observed when TL (Ln transformed) was less than − 0.05, which transitioned to an inverse association when TL (Ln transformed) was greater than − 0.05. Regarding DNAmAge and leptin, there was a sharp decline when DNAmAge (Ln transformed) was less than − 1.35, followed by a plateau between − 1.35 and − 0.67 and then a further decline when DNAmAge (Ln transformed) was greater than − 0.67. Conclusions In this prospective birth cohort study, variation in metabolic hormones of children at 3 years old was associated with TL, mtDNAcn, and DNAmAge at birth. These findings suggested that TL, mtDNAcn, and DNAmAge might play a role in the biological programming of metabolic health from birth.

Abstract Articular cartilage damage and wear can result in cartilage degeneration, ultimately culminating in osteoarthritis. Current surgical interventions offer limited capacity for cartilage tissue regeneration and offer only temporary alleviation of symptoms. Tissue engineering strategies are increasingly recognized as promising modalities for cartilage restoration. Currently, various biological scaffolds utilizing tissue engineering materials are extensively employed in both fundamental and clinical investigations of cartilage repair. In order to optimize the cartilage repair ability of tissue engineering scaffolds, researchers not only optimize the structure and properties of scaffolds from the perspective of materials science and manufacturing technology to enhance their histocompatibility, but also adopt strategies such as loading cells, cytokines, and drugs to promote cartilage formation. This review provides an overview of contemporary tissue engineering strategies employed in cartilage repair, as well as a synthesis of existing preclinical and clinical research. Furthermore, the obstacles faced in the translation of tissue engineering strategies to clinical practice are discussed, offering valuable guidance for researchers seeking to address these challenges.

According to World Health Organization statistics, inappropriate medication has become an important factor affecting the safety of rational medication. In the gray area of medical insurance supervision, such as designated drugstores and medical institutions, there are lots of inappropriate medication phenomena regarding “big prescription for minor ailments.” A traditional clinical decision support system is mostly based on established rules to regulate inappropriate prescriptions, which are not suitable for clinical environments and require intelligent review. In this study, we model the complex relationships between patients, diseases, and drugs based on medical big data to promote appropriate medication use. More specifically, we first construct the medication knowledge graph based on the historical prescription big data of tertiary hospitals and medical text data. Second, based on the medication knowledge graph, we employ a Gaussian mixture model to group patient population representation as physiological features. For diagnostic features, we employ pre-training word vector Bidirectional Encoder Representations from Transformers to enhance the semantic representation between diagnoses. In addition, to reduce adverse drug interactions caused by drug combinations, we employ a graph convolution network to transform drug interaction information into drug interaction features. Finally, we employ the sequence generation model to learn the complex relationships between patients, diseases, and drugs and provide an appropriate medication evaluation for doctor prescriptions in small hospitals from two aspects: drug list and medication course of treatment. In this study, we utilize the MIMIC III dataset alongside data from a tertiary hospital in Fujian Province to validate our model. The results show that our method is more effective than other baseline methods in the accuracy of the medication regimen prediction of rational medication. In addition, it achieved high accuracy in the appropriate medication detection of prescription in small hospitals.

Abstract The role of tumor-resident intracellular microbiota (TRIM) in carcinogenesis has sparked enormous interest. Nevertheless, the impact of TRIM-targeted antibacteria on tumor inhibition and immune regulation in the tumor microenvironment (TME) remains unexplored. Herein, we report long-term relapse-free survival by coordinating antibacteria with antitumor treatment, addressing the aggravated immunosuppression and tumor overgrowth induced by TRIM using breast and prostate cancer models. Combining Ag+ release with a Fenton-like reaction and photothermal conversion, simultaneous bacteria killing and multimodal antitumor therapy are enabled by a single agent. Free of immune-stimulating drugs, the agent restores antitumor immune surveillance and activates immunological responses. Secondary inoculation and distal tumor analysis confirm lasting immunological memory and systemic immune responses. A relapse-free survival of >700 days is achieved. This work unravels the crucial role of TRIM-targeted antibacteria in tumor inhibition and unlocks an unconventional route for immune regulation in TME and a complete cure for cancer.

To evaluate the correlation between the water absorption characteristics of dried chrysanthemums and their structure, water activity (Aw), and storage temperature, two types of powdered chrysanthemums ("Xiaohuangju" and "Gongjuwang") were analyzed through SEM, FTIR, and XPS. The results indicated that the surface of the powdered chrysanthemums was rough and contained a large number of indentations and cavities. In comparison to "Xiaohuangju", "Gongjuwang" powder had smaller particle sizes and more hydrophilic groups on the surface, such as -OH, O-C-O, etc. To examine the water adsorption behavior of two varieties of powdered chrysanthemums, the static gravimetric method was employed at 20, 30, and 40 ℃ and a range of Aw values from 0.112 to 0.976. Model fitting and thermodynamic analysis were conducted to gain insight into the water adsorption mechanism. An increase in water activity (Aw) resulted in a rise in the equilibrium water content (Xe) of powdered chrysanthemums, conversely, the higher the temperature, the lower the Xe values at the equivalent Aw levels. The fitting results demonstrated that the Peleg model was the most suitable model for depicting the water adsorption isotherms. Results from the thermodynamic analysis suggested that the net isosteric heat of adsorption (qst) decreased when the equilibrium water content (Xe) increased, and the qst values of "Xiaohuangju" and "Gongjuwang" powder remained steady in the presence of Xe values greater than 0.14 g/g and 0.24 g/g, respectively. The monolayer water content (Xm) of "Xiaohuangju" at 20, 30, and 40 ℃ were 0.0690, 0.0525, and 0.0505 g/g (d. b), respectively, while those of "Gongjuwang" were 0.0645, 0.0591 and 0.0584 g/g (d. b). When the temperature and water content increased, the effective pore size (rp) of "Xiaohuangju" powder increased, exhibiting mesoporous characteristics when Xe>0.09 g/g (d. b). Conversely, the internal pores of “Gongjuwang” powder shifted from micropore to mesopore only when Xe>0.11 g/g (d. b). The results of the study can be employed as a guide for improving the drying process of chrysanthemums and determining the most suitable storage conditions.

Enhancing photosynthesis is a pivotal strategy for achieving sustainable plant production. Blue and red light facilitate plant growth since these wavelengths are readily absorbed by chlorophyll pigments and power crucial photosynthetic processes. In this investigation, double light conversion films were prepared by incorporating biomass-derived carbon dots into a polyvinyl alcohol matrix (CDs@PVAs). The study conclusively demonstrated that CDs@PVAs can convert ultraviolet and green light from sunlight into blue and red light. Using 2-week-old Athaliana plants as the model organism, the Athaliana plants were covered with CDs@PVAs and then exposed to simulated sunlight (0.57 mW cm−2) for 1 hour. The Fv/Fm value in the presence of the CDs@PVAs was approximately 12% higher than without the film, indicating a significant boost in photosynthesis. Analysis of gene expression showed that the CDs@PVAs cause significant upregulation of genes associated with photosynthesis. These double light conversion films thus emerge as promising contenders for eco-friendly plant cultivation methods that circumvent reliance on electric power. Their potential applications in agriculture are substantial, underscoring their significance in promoting sustainable practices.

Abstract The impairment of sperm maturation is one of the major pathogenic factors in male subfertility, a serious medical and social problem affecting millions of global couples. Regrettably, the existing research on sperm maturation is slow, limited, and fragmented, largely attributable to the lack of a global molecular view. To fill the data gap, we newly established a database, namely the Sperm Maturation Database (SperMD, http://bio-add.org/SperMD ). SperMD integrates heterogeneous multi-omics data (170 transcriptomes, 91 proteomes, and five human metabolomes) to illustrate the transcriptional, translational, and metabolic manifestations during the entire lifespan of sperm maturation. These data involve almost all crucial scenarios related to sperm maturation, including the tissue components of the epididymal microenvironment, cell constituents of tissues, different pathological states, and so on. To the best of our knowledge, SperMD could be one of the limited repositories that provide focused and comprehensive information on sperm maturation. Easy-to-use web services are also implemented to enhance the experience of data retrieval and molecular comparison between humans and mice. Furthermore, the manuscript illustrates an example application demonstrated to systematically characterize novel gene functions in sperm maturation. Nevertheless, SperMD undertakes the endeavor to integrate the islanding omics data, offering a panoramic molecular view of how the spermatozoa gain full reproductive abilities. It will serve as a valuable resource for the systematic exploration of sperm maturation and for prioritizing the biomarkers and targets for precise diagnosis and therapy of male subfertility.

BackgroundPostmenopausal osteoporosis is a prevalent disease that affects the bone health of middle-aged and elderly women. The link between gut microbiota and bone health, known as the gut-bone axis, has garnered widespread attention.MethodsWe employed a two-sample Mendelian randomization approach to assess the associations between gut microbiota with osteoclasts and postmenopausal osteoporosis, respectively. Single nucleotide polymorphisms associated with the composition of gut microbiota were used as instrumental variables. By analyzing large-scale multi-ethnic GWAS data from the international MiBioGen consortium, and combining data from the eQTLGen consortium and the GEFOS consortium, we identified microbiota related to osteoclasts and postmenopausal osteoporosis. Key genes were further identified through MAGMA analysis, and validation was performed using single-cell data GSE147287.ResultsThe outcomes of this study have uncovered significant associations within the gut microbiome community, particularly with the Burkholderiales order, which correlates with both an increase in osteoclasts and a reduced risk of postmenopausal osteoporosis. with an odds ratio (OR) of 0.400, and a P-value of 0.011. Further analysis using single-cell data allowed us to identify two key genes, FMNL2 and SRBD1, that are closely linked to both osteoclasts and osteoporosis.ConclusionThis study utilizing Mendelian randomization and single-cell data analysis, provides new evidence of a causal relationship between gut microbiota and osteoclasts, as well as postmenopausal osteoporosis. It was discovered that the specific microbial group, the Burkholderiales order, significantly impacts both osteoporosis and osteoclasts. Additionally, key genes FMNL2 and SRBD1 were identified, offering new therapeutic strategies for the treatment of postmenopausal osteoporosis.

Objectives This study aimed to investigate the impact of adjuvant chemotherapy (ACT) on survival outcomes in older women with hormone receptor-positive and human epidermal growth factor receptor 2-negative (HR+/HER2−) breast cancer (BC).Design A retrospective cohort study using data from the Surveillance, Epidemiology, and End Results database, which contains publicly available information from US cancer registries.Setting and participants The study included 45 762 older patients with BC aged over 65 years diagnosed between 2010 and 2015.Methods Patients were divided into two groups based on age: 65–79 years and ≥80 years. Propensity score matching (PSM) was employed to balance clinicopathological characteristics between patients who received ACT and those who did not. Data analysis used the χ2 test and Kaplan-Meier method, with a subgroup analysis conducted to identify potential beneficiaries of ACT.Outcome measures Overall survival (OS) and cancer-specific survival (CSS).Results Due to clinicopathological characteristic imbalances between patients with BC aged 65–79 years and those aged ≥80 years, PSM was used to categorise the population into two groups for analysis: the 65–79 years age group (n=38 128) and the ≥80 years age group (n=7634). Among patients aged 65–79 years, Kaplan-Meier analysis post-PSM indicated that ACT was effective in improving OS (p

Abstract Photothermal devices and thermoelectric cells hold great promise for energy generation but integration of the two remains a considerable challenge in real‐life power supply for sensors. Here, a novel photo‐thermo‐electric hydrogel (PTEH‐Interlocking) was constructed by the synthesis of a photothermal layer on a thermoelectric hydrogel with the redox pair Fe(CN)63−/Fe(CN)64−. The smart design of using the oxidation of pyrogallic acid by Fe(CN)63− to construct the photothermal layer for photo‐to‐heat conversion protected the redox couple of the thermogalvanic ion pair from ultraviolet damage, as well as triggered the formation of an interlocking structure at the interface of the photothermal layer and the thermoelectric hydrogel. The as‐prepared PTEH‐Interlocking has shown a high Seebeck coefficient and rapid heat transfer, boosting the photo‐thermo‐electric conversion. As a demonstration of a practical application, the PTEH‐Interlocking cells are successfully used as the energy supply for a mechanical sensor.

Abstract Event camera is a new vision sensor that produces independent asynchronous responses to each pixel's change of illumination intensity. The unique principle of event camera has many advantages over traditional cameras, such as low latency, high temporal resolution, and high dynamic range (HDR). These advantages make event camera ideal for dealing with high speed, HDR visual tasks, especially in automatic driving scenes. In this study, we propose an image generation network named Event‐based attention generative adversarial networks (EAGAN), which simultaneously deals with optical flow and depth estimation of monocular event camera data. In addition to the innovative network architecture and loss function suitable for depth estimation, we are also the first to process incomplete training data to obtain more dense and uniform prediction results. Experiments on the multi‐vehicle stereo event camera dataset show that our EAGAN is competitive on the depth estimation task and achieves the state‐of‐the‐art effect in the optical flow estimation task.

BackgroundAn accurate assessment of current trends in cardiovascular risks could inform public health policy. This study aims to determine 20-year trends in the prevalence of elevated cardiovascular risk and its risk factors' control among US adults.MethodsIn this serial cross-sectional analysis of 23,594 adults, aged 40–79 years, without clinical atherosclerotic cardiovascular disease (ASCVD) in the National Health and Nutrition Examination Survey from 2001 to 2020, we calculated the prevalence of elevated cardiovascular risk (10-year ASCVD risk ≥ 7.5%) for all participants and subgroups with their risk factors controlled for diabetes, hypertension, or dyslipidemia.ResultsThe age- and sex-adjusted prevalence of elevated cardiovascular risk slightly decreased from 41.5% (95% CI, 39.7–43.3%) in 2001–2004 to 38.6% (95% CI, 36.1–41.1%) in 2017–2020 (P for trend = 0.169) while the respective sex-adjusted prevalence significantly increased from 34.4% (95% CI, 32.8–36.0%) to 39.5% (95% CI, 37.0–42.0%; P for trend

Osteoarthritis (OA) is a debilitating joint disorder that affects millions of people worldwide. Despite its prevalence, our understanding of the underlying mechanisms remains incomplete. In recent years, transient receptor potential vanilloid (TRPV) channels have emerged as key players in OA pathogenesis. This review provides an in-depth exploration of the role of the TRPV pathway in OA, encompassing its involvement in pain perception, inflammation, and mechanotransduction. Furthermore, we discuss the latest research findings, potential therapeutic strategies, and future directions in the field, shedding light on the multifaceted nature of TRPV channels in OA.

Tendon-bone insertion (TBI) injuries are common, primarily involving the rotator cuff (RC) and anterior cruciate ligament (ACL). At present, repair surgery and reconstructive surgery are the main treatments, and the main factor determining the curative effect of surgery is postoperative tendon-bone healing, which requires the stable combination of the transplanted tendon and the bone tunnel to ensure the stability of the joint. Fibrocartilage and bone formation are the main physiological processes in the bone marrow tract. Therefore, therapeutic measures conducive to these processes are likely to be applied clinically to promote tendon-bone healing. In recent years, biomaterials and compounds, stem cells, cell factors, platelet-rich plasma, exosomes, physical therapy, and other technologies have been widely used in the study of promoting tendon-bone healing. This review provides a comprehensive summary of strategies used to promote tendon-bone healing and analyses relevant preclinical and clinical studies. The potential application value of these strategies in promoting tendon-bone healing was also discussed.

Abstract Background Winter wheat requires prolonged exposure to low temperature to initiate flowering (vernalization). Shoot apical meristem of the crown is the site of cold perception, which produces leaf primordia during vegetative growth before developing into floral primordia at the initiation of the reproductive phase. Although many essential genes for winter wheat cold acclimation and floral initiation have been revealed, the importance of microRNA (miRNA) meditated post-transcriptional regulation in crowns is not well understood. To understand the potential roles of miRNAs in crown tissues, we performed a temporal expression study of miRNAs in crown tissues at the three-leaf stage, winter dormancy stage, spring green-up stage, and jointing stage of winter wheat grown under natural growth conditions. Results In total, 348 miRNAs belonging to 298 miRNA families, were identified in wheat crown tissues. Among them, 92 differentially expressed miRNAs (DEMs) were found to be significantly regulated from the three-leaf stage to the jointing stage. Most of these DEMs were highly expressed at the three-leaf stage and winter dormancy stage, and then declined in later stages. Six DEMs, including miR156a-5p were markedly induced during the winter dormancy stage. Eleven DEMs, including miR159a.1, miR390a-5p, miR393-5p, miR160a-5p, and miR1436, were highly expressed at the green-up stage. Twelve DEMs, such as miR172a-5p, miR394a, miR319b-3p, and miR9676-5p were highly induced at the jointing stage. Moreover, 14 novel target genes of nine wheat or Pooideae-specific miRNAs were verified using RLM-5′ RACE assay. Notably, six mTERFs and two Rf1 genes, which are associated with mitochondrial gene expression, were confirmed as targets of three wheat-specific miRNAs. Conclusions The present study not only confirmed the known miRNAs associated with phase transition and floral development, but also identified a number of wheat or Pooideae-specific miRNAs critical for winter wheat cold acclimation and floral development. Most importantly, this study provided experimental evidence that miRNA could regulate mitochondrial gene expression by targeting mTERF and Rf1 genes. Our study provides valuable information for further exploration of the mechanism of miRNA mediated post-transcriptional regulation during winter wheat vernalization and inflorescent initiation.

BackgroundAs neoadjuvant chemotherapy is widely used in breast cancer patients, the lymph node ratio has not been fully validated as a prognostic indicator of breast cancer received neoadjuvant chemotherapy. This study was conducted to investigate the prognostic value of lymph node ratio in breast cancer patients received neoadjuvant chemotherapy.MethodsSystematic searches were performed in the PubMed, Embase, and Cochrane Library databases until 15 December 2021 for studies on the association between lymph node ratio and the prognosis of breast cancer after neoadjuvant chemotherapy. Overall survival and disease-free survival were used as outcome events, and hazard ratio was chosen as the parameter to evaluate the correlation. The dose-response relationship was assessed by restricted cubic splines. In the subgroup analyses, which were used to explore potential heterogeneity among the included studies according to study region and sample size. Sensitivity analysis was performed to assess the stability of individual studies, and publication bias was determined with funnel plots, Begg’s test, and Egger's test. All statistical analyses were performed using Stata 15.1.ResultsA total of 12 studies with 4,864 patients were included in this meta-analysis. In this study, high lymph node ratio was significantly associated with decreased overall survival (HR: 4.74; 95%CI: 3.36–6.67; P

The increased vascular inflammation is a key event in the development of atherosclerotic lesions. Antrodia cinnamomea has been shown to promote anticancerogenic activity through decreasing inflammation. However, the potential role of A. cinnamomea in cardiovascular diseases remains unexplored. Herein, using carotid arterial ligation models, we found that ethanol extract from A. cinnamomea (EEAC) significantly inhibited neointimal hyperplasia in a dose-dependent manner, accompanied with the reduced expression of activated p65 and inflammatory cytokines. We also show that EEAC ameliorated TNF-α-induced phosphorylation of p65 and pro-inflammatory cytokine expression in both vascular smooth muscle cells (VSMCs) and macrophages in vitro. Mechanistically, EEAC suppressed expression levels of intercellular adhesion molecule-1 (ICAM-1) and vascular cell adhesion molecule (VCAM-1) in VSMCs, which attenuates the ability of monocytes/macrophages adhesion to VSMCs. Furthermore, the expression level of these adhesion molecules and infiltration of monocytes/macrophages were also decreased in neointimal VSMCs of arteries pretreated with EEAC. Altogether, our results reveal a novel function of A. cinnamomea in suppressing vascular inflammation upon ligation injury during neointimal formation, likely through inhibition of inflammatory cell infiltration via downregulating the adhesion molecules in VSMCs. Thus, A. cinnamomea may offer a pharmacological therapy to slow down disease progression in patients with vascular injury.

Computer-aided diagnosis (CAD) has undergone rapid development with the advent of advanced neuroimaging and machine learning methods. Nevertheless, how to extract discriminative features from the limited and high-dimensional data is not ideal, especially for amnesic mild cognitive impairment (aMCI) data based on resting-state functional magnetic resonance imaging (rs-fMRI). Furthermore, a robust and reliable system for aMCI detection is conducive to timely detecting and screening subjects at a high risk of Alzheimer’s disease (AD). In this scenario, we first develop the mask generation strategy based on within-class and between-class criterion (MGS-WBC), which primarily aims at reducing data redundancy and excavating multiscale features of the brain. Concurrently, vector generation for brain networks based on Laplacian matrix (VGBN-LM) is presented to obtain the global features of the functional network. Finally, all multiscale features are fused to further improve the diagnostic performance of aMCI. Typical classifiers for small data learning, such as naive Bayesian (NB), linear discriminant analysis (LDA), logistic regression (LR), and support vector machines (SVMs), are adopted to evaluate the diagnostic performance of aMCI. This study helps to reveal discriminative neuroimaging features, and outperforms the state-of-the-art methods, providing new insights for the intelligent construction of CAD system of aMCI.

Bacterial fuel cells have generated attention with the prospect of green energy production; current research is focused on optimising the system to improve efficiency. Here, the authors report on the feeding of carbon dots to S. oneidensis MR-1 to enhance metabolic activity and bioelectric generation.

Alzheimer's Disease (AD) is a form of dementia which causes memory, thinking, and behavior disorders in humans. Effective early diagnosis and treatment of AD is of fundamental importance as it can reduce disease progression, allow more effective management of symptoms, facilitate timely patient access to advice and support, and lower associated costs of health care. Given that Alzheimer's typically progresses in stages over an extended period of time, we propose that automated analysis of time sequential data may enhance disease prediction. We present a novel time-series Alzheimer's Disease Prediction Model (ADPM) comprising Random Forest (RF) region of interest (ROI) selection and Gated Recurrent Units (GRU) prediction. Experiments show that our methodology achieves higher classification accuracy in comparison to existing algorithms, and can facilitate prediction of early onset AD. Furthermore, testing demonstrates that random forest ROI selection can identify disease-relative brain regions across different image modalities (MRI, PET, DTI).

Human pose estimation localizes body keypoints to accurately recognizing the postures of individuals given an image. This step is a crucial prerequisite to multiple tasks of computer vision which include human action recognition, human tracking, human-computer interaction, gaming, sign languages, and video surveillance. Therefore, we present this survey article to fill the knowledge gap and shed light on the researches of 2D human pose estimation. A brief introduction is followed by classifying it as a single or multi-person pose estimation based on the number of people needed to be tracked. Then gradually the approaches used in human pose estimation are described before listing some applications and also flaws facing in pose estimation. Following that, a center of attention is given on briefly discussing researches with a significant effect on human pose estimation and examine the novelty, motivation, architecture, the procedures (working principles) of each model together with its practical application and drawbacks, datasets implemented, as well as the evaluation metrics used to evaluate the model. This review is presented as a baseline for newcomers and guides researchers to discover new models by observing the procedure and architecture flaws of existing researches.

Due to the non-invasiveness and high precision of electroencephalography (EEG), the combination of EEG and artificial intelligence (AI) is often used for emotion recognition. However, the internal differences in EEG data have become an obstacle to classification accuracy. To solve this problem, considering labeled data from similar nature but different domains, domain adaptation usually provides an attractive option. Most of the existing researches aggregate the EEG data from different subjects and sessions as a source domain, which ignores the assumption that the source has a certain marginal distribution. Moreover, existing methods often only align the representation distributions extracted from a single structure, and may only contain partial information. Therefore, we propose the multi-source and multi-representation adaptation (MSMRA) for cross-domain EEG emotion recognition, which divides the EEG data from different subjects and sessions into multiple domains and aligns the distribution of multiple representations extracted from a hybrid structure. Two datasets, i.e., SEED and SEED IV, are used to validate the proposed method in cross-session and cross-subject transfer scenarios, experimental results demonstrate the superior performance of our model to state-of-the-art models in most settings.

Convolutional neural networks (CNNs)-based classifiers improve the accuracy of diagnosis and prediction for Alzheimer's disease (AD). However, exploiting specific brain regions with the AD is essential to understand pathological alteration in the AD and monitor its progression. This paper aims to construct novel AD classification models which have a good performance and interpretation on AD diagnosis. We propose the three classifiers including a simple broaden plain CNNs (SBPCNNs), a major slice-assemble CNNs (SACNNs) and a multi-slice CNNs (MSCNNs), which record the slice positions but have fewer parameters. Specifically, we integrate the ranking and the random forest methods to find the discriminative region that is consistent with domain knowledge about the AD. The results of the visualization explanation of pixel and slice level deliver a clearer understanding of the AD to specialists. The experimental results indicate that the proposed models are meaningful for AD classification.

Alzheimer's Disease (AD) is a chronic neurodegenerative disease. Early diagnosis will considerably decrease the risk of further deterioration. Unfortunately, current studies mainly focus on classifying the states of disease in its current stage, instead of predicting the possible development of the disease. Long short-term memory (LSTM) is a special kind of recurrent neural network, which might be able to connect previous information to the present task. Noticing that the temporal data for a patient are potentially meaningful for predicting the development of the disease, we propose a predicting model based on LSTM. Therefore an LSTM network, with fully connected layer and activation layers, is built to encode the temporal relation between features and the next stage of Alzheimer's Disease. The Experiments show that our model outperforms most of the existing models.

Background: The value of cerebrospinal fluid (CSF) biomarkers for assessing idiopathic normal pressure hydrocephalus (iNPH) must be determined. This prospective study aimed to reveal the correlation between CSF biomarkers and clinical symptoms of iNPH and the predictive value of these biomarkers for tap test responsiveness.Methods: Thirty-nine patients with suspected iNPH were recruited, contributed qualified CSF, and underwent a tap test and unified pre- and post-test evaluations of the neurological function.Results: The analysis of biomarkers from the patients’ CSF showed decreased levels of tau and its phosphorylated form, especially in the tap test (+) group. The responsiveness of the tap test was also related to the number of combined symptoms (p < 0.01), and a correlation was found between the end pressure or pressure difference in CSF and tap test responsiveness (p < 0.05). The results of the binary logistic regression analysis showed that P (tap test responsiveness) = 1/1 + e∧ − (−5.505 + 55.314 * ratio of p/T-tau − 1.586 * numbers of combined symptoms). The combined indicators (−5.505 + 0.553 * percentage of p/T-tau − 1.586 * numbers of combined symptoms) resulted in the highest sensitivity and specificity of 94.12% and 72.73%, respectively.Conclusions: CSF biomarkers may be assessed to judge tap test responsiveness, which is beneficial for the feasibility of a clinical application.

Background: The association between exposure to organochlorine pesticides (OCPs) and infant growth has been reported contradictorily in previous studies. Few studies have investigated the effects of prenatal exposure to OCPs on infant growth assessed longitudinally at multiple time points. Objectives: The purpose of the study was to examine the associations between prenatal exposure to OCPs and infant growth at birth, 6, 12 and 24 months of age, and further to explore the potential sex-specific effects. Methods: The study population included 1039 mother-infant pairs who participated in a birth cohort study in Wuhan, China. The weight, length and body mass index (BMI) z-score of infants were measured and calculated at birth, 6, 12 and 24 months of age. The overweight status was defined as BMI z-score ≥ 85th percentile according to the standard of World Health Organization. The concentrations of OCPs were measured in cord serum, including hexachlorocyclohexanes (HCHs, consisted of α-HCH, β-HCH, and γ-HCH), p,p′-dichlorodiphenyltrichloroethane (p,p′-DDT) and its metabolites: p,p′-dichlorodiphenyldichloroethane (p,p′-DDD), and p,p′-dichlorodiphenyldichloroethylene (p,p′-DDE). Generalized linear models were applied to estimate the associations of cord OCPs with infant growth parameters. A group-based semiparametric mixture model was used to estimate growth patterns of infants. Linear-mixed growth curve models were used to examine relationships between predicted growth trajectories and prenatal exposure to OCPs. Weighted quantile sum regression (WQSR) analyses were used to estimate the mixture effects of OCPs on infant growth. Results: Higher cord serum β-HCH concentrations were associated with higher BMI z-score at 12 [β = 0.07, 95%CI: 0.01, 0.13] and 24 months of age [β = 0.08, 95% CI: 0.02, 0.14]. Similar patterns were observed for relationships of γ-HCH [β = 0.04, 95%CI: 0.01, 0.07] and p,p′-DDT [β = 0.03, 95% CI: 0.00, 0.06] with BMI z-score at 6 and 12 months of age, respectively. However, higher cord serum p,p′-DDE concentrations were associated with a reduction of BMI z-score at 6 months of age [β = −0.07, 95% CI: −0.12, −0.01]. Cord serum β-HCH was also positively associated with the risk of overweight at 12 months of age [RR = 1.16, 95% CI (1.02, 1.33), for the medium vs the lowest tertile]. Among girls, the effects of β-HCH on BMI z-score and overweight status were stronger than boys at 12 and 24 months of age. No statistically significant relationships of other OCPs with infant growth were observed. Conclusions: Prenatal exposure to β-HCH was associated with increased BMI z-score and higher risk of overweight status in infants especially at 12 and 24 months of age, which seemed to be stronger in girls.

The surface of a topological crystalline insulator (TCI) carries an even number of Dirac cones protected by crystalline symmetry. We epitaxially grew high-quality Pb1-xSnxTe(111) films and investigated the TCI phase by in situ angle-resolved photoemission spectroscopy. Pb1-xSnxTe(111) films undergo a topological phase transition from a trivial insulator to TCI via increasing the Sn/Pb ratio, accompanied by a crossover from n-type to p-type doping. In addition, a hybridization gap is opened in the surface states when the thickness of the film is reduced to the two-dimensional limit. The work demonstrates an approach to manipulating the topological properties of TCI, which is of importance for future fundamental research and applications based on TCI. [ABSTRACT FROM AUTHOR]

Magnetic Resonance Imaging (MRI) is an indispensable tool in the diagnosis of brain diseases due to painlessness and safety. Nevertheless, Rician noise is inevitably injected during the image acquisition process, which leads to poor observation and interferes with the treatment. Owing to the complexity of Rician noise, using the elimination method of Gaussian to remove it does not perform well. Therefore, the feature fusion and attention network (FFA-DMRI) is proposed to separate noise from observed MRI. Inspired by the attention-guided CNN network (ADNet) and Convolutional block attention module (CBAM), a spatial attention mechanism has been specially designed to obtain the area of interest in MRI. Furthermore, the feature fusion block concatenates local with global information, which makes full use of the multilevel structure and boosts the expressive ability of network. The comprehensive experiments on Alzheimer’s disease neuroimaging initiative dataset (ADNI) have demonstrated high effectiveness of FFA-DMRI with maintaining the crucial brain details. Moreover, in terms of visual inspections, the denoising results are also consistent with human perception.

The subjective cognitive decline (SCD) may last for decades prior to the onset of dementia and has been proposed as a risk population for development to amnestic mild cognitive impairment (aMCI) and Alzheimer disease (AD). Disruptions of functional connectivity and causal connectivity (CC) in the salience network (SN) are generally perceived as prominent hallmarks of the preclinical AD. Nevertheless, the alterations in anterior SN (aSN), and posterior SN (pSN) remain unclear. Here, we hypothesized that both the functional connectivity (FC) and CC of the SN subnetworks, comprising aSN and pSN, were distinct disruptive in the SCD and aMCI. We utilized resting-state functional magnetic resonance imaging to investigate the altered FC and CC of the SN subnetworks in 28 healthy controls, 23 SCD subjects, and 29 aMCI subjects. In terms of altered patterns of FC in SN subnetworks, aSN connected to the whole brain was significantly increased in the left orbital superior frontal gyrus, left insula lobule, right caudate lobule, and left rolandic operculum gyrus (ROG), whereas decreased FC was found in the left cerebellum superior lobule and left middle temporal gyrus when compared with the HC group. Notably, no prominent statistical differences were obtained in pSN. For altered patterns of CC in SN subnetworks, compared to the HC group, the aberrant connections in aMCI group were separately involved in the right cerebellum inferior lobule (CIL), right supplementary motor area (SMA), and left ROG, whereas the SCD group exhibited more regions of aberrant connection, comprising the right superior parietal lobule, right CIL, left inferior parietal lobule, left post-central gyrus (PG), and right angular gyrus. Especially, SCD group showed increased CC in the right CIL and left PG, whereas the aMCI group showed decreased CC in the left pre-cuneus, corpus callosum, and right SMA when compared to the SCD group. Collectively, our results suggest that analyzing the altered FC and CC observed in SN subnetworks, served as impressible neuroimaging biomarkers, may supply novel insights for designing preclinical interventions in the preclinical stages of AD.

Alzheimer’s disease (AD), which most commonly occurs in the elder, is a chronic neurodegenerative disease with no agreed drugs or treatment protocols at present. Amnestic mild cognitive impairment (aMCI), earlier than AD onset and later than subjective cognitive decline (SCD) onset, has a serious probability of converting into AD. The SCD, which can last for decades, subjectively complains of decline impairment in memory. Distinct altered patterns of default mode network (DMN) subnetworks connected to the whole brain are perceived as prominent hallmarks of the early stages of AD. Nevertheless, the aberrant phase position connectivity (PPC) connected to the whole brain in DMN subnetworks remains unknown. Here, we hypothesized that there exist distinct variations of PPC in DMN subnetworks connected to the whole brain for patients with SCD and aMCI, which might be acted as discriminatory neuroimaging biomarkers. We recruited 27 healthy controls (HC), 20 SCD and 28 aMCI subjects, respectively, to explore aberrant patterns of PPC in DMN subnetworks connected to the whole brain. In anterior DMN (aDMN), SCD group exhibited aberrant PPC in the regions of right superior cerebellum lobule (SCL), right superior frontal gyrus of medial part (SFGMP), and left fusiform gyrus (FG) in comparison of HC group, by contrast, no prominent difference was found in aMCI group. It is important to note that aMCI group showed increased PPC in the right SFGMP in comparison with SCD group. For posterior DMN (pDMN), SCD group showed decreased PPC in the left superior parietal lobule (SPL) and right superior frontal gyrus (SFG) compared to HC group. It is noteworthy that aMCI group showed decreased PPC in the left middle frontal gyrus of orbital part (MFGOP) and right SFG compared to HC group, yet increased PPC was found in the left superior temporal gyrus of temporal pole (STGTP). Additionally, aMCI group exhibited decreased PPC in the left MFGOP compared to SCD group. Collectively, our results have shown that the aberrant regions of PPC observed in DMN are related to cognitive function, and it might also be served as impressible neuroimaging biomarkers for timely intervention before AD occurs.

Nitrides MAX have attracted ever-growing interest owing to its unique metallic and ceramic characteristics and properties. Here, we report on the synthesis of highly purified Ti2AlN and Ti4AlN3 powders from Ti, Al and TiN powders by a facile atmosphere sintering method. The obtained nitrides show highly pure phase and excellent layered structure. Except for the composition difference of raw materials, both the nitrides can be sintered and obtained by same sintering temperature and holding time, which thus makes less processing time and less usage of synthesis parameters as compared to previously synthesis methods. To our knowledge, present work is one of the few reports on synthesis of Ti4AlN3 and Ti2AlN using atmosphere sintering method. Furthermore, the lattice changes of the layered structure of Ti2AlX (X=C∕N) were studied by changing the composition of X position from the synthesis of Ti2AlCN and Ti2AlC, and the optimal formulation and synthesis mechanism of Ti4AlN3 were also studied.

Context.--Eosinophilic solid and cystic renal cell carcinoma is now defined in the 5th edition of the 2022 World Health Organization classification of urogenital tumors. Objective.--To perform morphologic, immunohistochemical, and preliminary genetic studies about this new entity in China for the purpose of understanding it better. Design.--The study includes 18 patients from a regional tertiary oncology center in northern China (Tianjin, China). We investigated the clinical and immunohistochemical features of these cases. Results.--The mean age of patients was 49.6 years, and the male to female ratio was 11:7. Macroscopically, 1 case had the classic cystic and solid appearance, whereas the others appeared purely solid. Microscopically, all 18 tumors shared a similar solid and focal macrocystic or microcystic growth pattern, and the cells were characterized by voluminous and eosinophilic cytoplasm, along with coarse ampho-philic stippling. Immunohistochemically, most of the tumors had a predominant cytokeratin (CK) 20-positive feature, ranging from focal cytoplasmic staining to diffuse membranous accentuation. Initially, we separated these cases into different immunohistochemical phenotypes. Group 1 (7 of 18; 38.5%) was characterized by positive phospho-4EBP1 and phospho-S6, which can imply hyperactive mechanistic target of rapamycin complex 1 (mTORC1) signaling. Group 2 (4 of 18; 23%) was negative for NF2, probably implying a germ-line mutation of NF2. Group 3 (7 of 18; 38.5%) consisted of the remaining cases. One case had metastatic spread and exhibited an aggressive clinical course, and we detected cyclin-dependent kinase inhibitor 2A (CDKN2A) mutation in this case; other patients were alive and without disease progression. Conclusions.--Our research proposes that eosinophilic solid and cystic renal cell carcinoma exhibits prototypical pathologic features with CK20 positivity and has aggressive potential. [ABSTRACT FROM AUTHOR]

Herein, we report on a novel two-dimensional (2D) material application, which shows that an accordion-like layered Ti3C2 nanomaterial (MXene) with an excellent adsorption capacity of Cr(VI) from aqueous solution was prepared by etching Al layer from Ti3AlC2 phase in hydrofluoric acid (HF) solution. Ti3C2 nanopowders were well characterized by X-ray diffraction (XRD), scanning electron microscopy (SEM), transmission electron microscopy (TEM), and the physical property of as-obtained samples was studied by UV–Vis diffuse reflectance spectra (DRS). After HF treatment, Ti3AlC2 not only has a phase transition from one crystal to another, but surprisingly, its microstructure is also undergoing an obvious change. Ti3C2 with product of change possesses an accordion-like multilayer structure, and a relatively higher specific surface area (SSA) than untreated Ti3AlC2. Then, accordion-like Ti3C2 with a high SSA provides abundant active sites for pollutant removal and functionalization. Accordion-like Ti3C2 nanomaterial exhibits a stable adsorption capacity, and 1g as-prepared accordion-like Ti3C2 powders can remove about 80mg potassium dichromate. Therefore, the results suggest that 2D MXenes are promising as an effective nanoadsorbent in heavy metal removal from the wastewater.

Maintaining the high visual recognizability of traffic signs for traffic safety is a key matter for road network management. Mobile Laser Scanning (MLS) systems provide efficient way of 3D measurement over large-scale traffic environment. This paper presents a quantitative visual recognizability evaluation method for traffic signs in large-scale traffic environment based on traffic recognition theory and MLS 3D point clouds. We first propose the Visibility Evaluation Model (VEM) to quantitatively describe the visibility of traffic sign from any given viewpoint, then we proposed the concept of visual recognizability field and Traffic Sign Visual Recognizability Evaluation Model (TSVREM) to measure the visual recognizability of a traffic sign. Finally, we present an automatic TSVREM calculation algorithm for MLS 3D point clouds. Experimental results on real MLS 3D point clouds show that the proposed method is feasible and efficient.

The indirect exchange interaction between local magnetic moments via surface electrons has been long predicted to bolster the surface ferromagnetism in magnetic topological insulators (MTIs), which facilitates the quantum anomalous Hall effect. This unconventional effect is critical to determining the operating temperatures of future topotronic devices. However, the experimental confirmation of this mechanism remains elusive, especially in intrinsic MTIs. Here, we combine time-resolved photoemission spectroscopy with time-resolved magneto-optical Kerr effect measurements to elucidate the unique electromagnetism at the surface of an intrinsic MTI MnBi2Te4. Theoretical modeling based on 2D Ruderman-Kittel-Kasuya-Yosida interactions captures the initial quenching of a surface-rooted exchange gap within a factor of two but overestimates the bulk demagnetization by one order of magnitude. This mechanism directly explains the sizable gap in the quasi-2D electronic state and the nonzero residual magnetization in even-layer MnBi2Te4. Furthermore, it leads to efficient light-induced demagnetization comparable to state-of-the-art magnetophotonic crystals, promising an effective manipulation of magnetism and topological orders for future topotronics. [ABSTRACT FROM AUTHOR]

We report the magneotransport studies on the topological crystalline insulator (TCI) Pb1−xSnxTe (111) single crystal thin films grown by molecular beam epitaxy. By decreasing Sn content, an enhanced sheet resistance and decreased hole density are observed in Pb1−xSnxTe (111) thin films. A weak antilocalization likely related to the topological surface states is observed in transport of Pb1−xSnxTe (x > 0.4) thin films, whereas a weak localization is displayed in Pb1−xSnxTe (x < 0.4) thin films. This tunable weak antilocalization to weak localization transition is attributed to the open of Dirac gap because of the topological phase transition in TCI Pb1−xSnxTe. Our research has a potential application in the tunable electronic and spintronic devices and is very significant to the fundamental research based on TCI Pb1−xSnxTe thin film. [ABSTRACT FROM AUTHOR]

Grain boundaries (GBs) are inherent extended defects in chemical vapor deposited (CVD) transition metal dichalcogenide (TMD) films. Characterization of the atomic structure and electronic properties of these GBs is crucial for understanding and controlling the properties of TMDs via defect engineering. Here, we report the atomic and electronic structure of GBs in CVD grown MoS2 on epitaxial graphene/SiC(0001). Using scanning tunneling microscopy/spectroscopy, we find that GBs mostly consist of arrays of dislocation cores, where the presence of mid-gap states shifts both conduction and valence band edges by up to 1 eV. Our findings demonstrate the first charging effect near GBs in CVD grown MoS2, providing insights into the significant impact GBs can have on materials properties. [ABSTRACT FROM AUTHOR]

Inflammatory damage plays an important role in cerebral ischemic pathogenesis and may represent a target for treatment. Toll-like receptor-4 (TLR4), toll-like receptor-2 (TLR2), myeloid differentiation factor 88 (MyD88), and nuclear factor kappa-B (NF-κB) have been linked to inflammatory reactions. Our previous studies have proved that oxymatrine (OMT) protected ischemic brain injury and this effect may be through the decreasing of NF-κB expression. However, little is known regarding the mechanism of OMT in the acute phase of ischemic stroke. We therefore investigated the OMT's potential neuroprotective role and the underlying mechanisms. Male, Sprague-Dawley rats were randomly divided into sham, saline and OMT treatment groups. We used a middle cerebral artery occlusion (MCAO) model and administered OMT intraperitoneally immediately after cerebral ischemia and once daily on the following days. At time points after MCAO, brain water content and infarct size were measured. Immunohistochemistry and RT-PCR were used to analyse the expression of TLR4, TLR2, MyD88, and NF-κB at gene and protein level in ischemic brain tissue. The result indicated that OMT protected the brain from damage caused by MCAO; this effect may be through downregulation of the TLR4, TLR2, MyD88, and NF-κB.