Search

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.

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.

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.

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.

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.

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.

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

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.

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.

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 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.

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.

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.

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.